R version 2.9.0 (2009-04-17)
Copyright (C) 2009 The R Foundation for Statistical Computing
ISBN 3-900051-07-0
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Type 'q()' to quit R.
> x <- array(list(235.1
+ ,0
+ ,280.7
+ ,0
+ ,264.6
+ ,0
+ ,240.7
+ ,0
+ ,201.4
+ ,0
+ ,240.8
+ ,0
+ ,241.1
+ ,0
+ ,223.8
+ ,0
+ ,206.1
+ ,0
+ ,174.7
+ ,0
+ ,203.3
+ ,0
+ ,220.5
+ ,0
+ ,299.5
+ ,0
+ ,347.4
+ ,0
+ ,338.3
+ ,0
+ ,327.7
+ ,0
+ ,351.6
+ ,0
+ ,396.6
+ ,0
+ ,438.8
+ ,0
+ ,395.6
+ ,0
+ ,363.5
+ ,0
+ ,378.8
+ ,0
+ ,357
+ ,0
+ ,369
+ ,0
+ ,464.8
+ ,0
+ ,479.1
+ ,0
+ ,431.3
+ ,0
+ ,366.5
+ ,0
+ ,326.3
+ ,0
+ ,355.1
+ ,0
+ ,331.6
+ ,0
+ ,261.3
+ ,0
+ ,249
+ ,0
+ ,205.5
+ ,0
+ ,235.6
+ ,0
+ ,240.9
+ ,0
+ ,264.9
+ ,0
+ ,253.8
+ ,0
+ ,232.3
+ ,0
+ ,193.8
+ ,0
+ ,177
+ ,0
+ ,213.2
+ ,0
+ ,207.2
+ ,0
+ ,180.6
+ ,0
+ ,188.6
+ ,0
+ ,175.4
+ ,0
+ ,199
+ ,0
+ ,179.6
+ ,0
+ ,225.8
+ ,0
+ ,234
+ ,0
+ ,200.2
+ ,0
+ ,183.6
+ ,0
+ ,178.2
+ ,0
+ ,203.2
+ ,0
+ ,208.5
+ ,0
+ ,191.8
+ ,0
+ ,172.8
+ ,0
+ ,148
+ ,0
+ ,159.4
+ ,0
+ ,154.5
+ ,0
+ ,213.2
+ ,0
+ ,196.4
+ ,0
+ ,182.8
+ ,0
+ ,176.4
+ ,0
+ ,153.6
+ ,0
+ ,173.2
+ ,0
+ ,171
+ ,0
+ ,151.2
+ ,0
+ ,161.9
+ ,0
+ ,157.2
+ ,0
+ ,201.7
+ ,0
+ ,236.4
+ ,0
+ ,356.1
+ ,0
+ ,398.3
+ ,0
+ ,403.7
+ ,0
+ ,384.6
+ ,0
+ ,365.8
+ ,0
+ ,368.1
+ ,0
+ ,367.9
+ ,0
+ ,347
+ ,0
+ ,343.3
+ ,0
+ ,292.9
+ ,0
+ ,311.5
+ ,0
+ ,300.9
+ ,0
+ ,366.9
+ ,0
+ ,356.9
+ ,0
+ ,329.7
+ ,0
+ ,316.2
+ ,0
+ ,269
+ ,0
+ ,289.3
+ ,0
+ ,266.2
+ ,0
+ ,253.6
+ ,0
+ ,233.8
+ ,0
+ ,228.4
+ ,0
+ ,253.6
+ ,0
+ ,260.1
+ ,0
+ ,306.6
+ ,0
+ ,309.2
+ ,0
+ ,309.5
+ ,0
+ ,271
+ ,0
+ ,279.9
+ ,0
+ ,317.9
+ ,0
+ ,298.4
+ ,0
+ ,246.7
+ ,0
+ ,227.3
+ ,0
+ ,209.1
+ ,0
+ ,259.9
+ ,0
+ ,266
+ ,0
+ ,320.6
+ ,0
+ ,308.5
+ ,0
+ ,282.2
+ ,0
+ ,262.7
+ ,0
+ ,263.5
+ ,0
+ ,313.1
+ ,0
+ ,284.3
+ ,0
+ ,252.6
+ ,0
+ ,250.3
+ ,0
+ ,246.5
+ ,0
+ ,312.7
+ ,0
+ ,333.2
+ ,0
+ ,446.4
+ ,0
+ ,511.6
+ ,0
+ ,515.5
+ ,0
+ ,506.4
+ ,0
+ ,483.2
+ ,0
+ ,522.3
+ ,0
+ ,509.8
+ ,0
+ ,460.7
+ ,0
+ ,405.8
+ ,0
+ ,375
+ ,0
+ ,378.5
+ ,0
+ ,406.8
+ ,0
+ ,467.8
+ ,0
+ ,469.8
+ ,0
+ ,429.8
+ ,0
+ ,355.8
+ ,0
+ ,332.7
+ ,0
+ ,378
+ ,0
+ ,360.5
+ ,0
+ ,334.7
+ ,0
+ ,319.5
+ ,0
+ ,323.1
+ ,0
+ ,363.6
+ ,0
+ ,352.1
+ ,0
+ ,411.9
+ ,0
+ ,388.6
+ ,0
+ ,416.4
+ ,0
+ ,360.7
+ ,0
+ ,338
+ ,0
+ ,417.2
+ ,0
+ ,388.4
+ ,0
+ ,371.1
+ ,0
+ ,331.5
+ ,0
+ ,353.7
+ ,0
+ ,396.7
+ ,0
+ ,447
+ ,0
+ ,533.5
+ ,0
+ ,565.4
+ ,0
+ ,542.3
+ ,0
+ ,488.7
+ ,0
+ ,467.1
+ ,0
+ ,531.3
+ ,0
+ ,496.1
+ ,0
+ ,444
+ ,0
+ ,403.4
+ ,0
+ ,386.3
+ ,0
+ ,394.1
+ ,0
+ ,404.1
+ ,0
+ ,462.1
+ ,0
+ ,448.1
+ ,0
+ ,432.3
+ ,0
+ ,386.3
+ ,0
+ ,395.2
+ ,0
+ ,421.9
+ ,0
+ ,382.9
+ ,0
+ ,384.2
+ ,0
+ ,345.5
+ ,0
+ ,323.4
+ ,0
+ ,372.6
+ ,0
+ ,376
+ ,0
+ ,462.7
+ ,0
+ ,487
+ ,0
+ ,444.2
+ ,0
+ ,399.3
+ ,0
+ ,394.9
+ ,0
+ ,455.4
+ ,0
+ ,414
+ ,0
+ ,375.5
+ ,0
+ ,347
+ ,0
+ ,339.4
+ ,0
+ ,385.8
+ ,0
+ ,378.8
+ ,0
+ ,451.8
+ ,0
+ ,446.1
+ ,0
+ ,422.5
+ ,0
+ ,383.1
+ ,0
+ ,352.8
+ ,0
+ ,445.3
+ ,0
+ ,367.5
+ ,0
+ ,355.1
+ ,0
+ ,326.2
+ ,0
+ ,319.8
+ ,0
+ ,331.8
+ ,0
+ ,340.9
+ ,0
+ ,394.1
+ ,0
+ ,417.2
+ ,0
+ ,369.9
+ ,0
+ ,349.2
+ ,0
+ ,321.4
+ ,0
+ ,405.7
+ ,0
+ ,342.9
+ ,0
+ ,316.5
+ ,0
+ ,284.2
+ ,0
+ ,270.9
+ ,0
+ ,288.8
+ ,0
+ ,278.8
+ ,0
+ ,324.4
+ ,0
+ ,310.9
+ ,0
+ ,299
+ ,0
+ ,273
+ ,0
+ ,279.3
+ ,0
+ ,359.2
+ ,0
+ ,305
+ ,0
+ ,282.1
+ ,0
+ ,250.3
+ ,0
+ ,246.5
+ ,0
+ ,257.9
+ ,0
+ ,266.5
+ ,0
+ ,315.9
+ ,0
+ ,318.4
+ ,0
+ ,295.4
+ ,0
+ ,266.4
+ ,0
+ ,245.8
+ ,0
+ ,362.8
+ ,0
+ ,324.9
+ ,0
+ ,294.2
+ ,0
+ ,289.5
+ ,0
+ ,295.2
+ ,0
+ ,290.3
+ ,0
+ ,272
+ ,0
+ ,307.4
+ ,0
+ ,328.7
+ ,0
+ ,292.9
+ ,0
+ ,249.1
+ ,0
+ ,230.4
+ ,0
+ ,361.5
+ ,0
+ ,321.7
+ ,0
+ ,277.2
+ ,0
+ ,260.7
+ ,0
+ ,251
+ ,0
+ ,257.6
+ ,0
+ ,241.8
+ ,0
+ ,287.5
+ ,0
+ ,292.3
+ ,0
+ ,274.7
+ ,0
+ ,254.2
+ ,0
+ ,230
+ ,0
+ ,339
+ ,0
+ ,318.2
+ ,0
+ ,287
+ ,0
+ ,295.8
+ ,0
+ ,284
+ ,0
+ ,271
+ ,0
+ ,262.7
+ ,0
+ ,340.6
+ ,0
+ ,379.4
+ ,0
+ ,373.3
+ ,0
+ ,355.2
+ ,0
+ ,338.4
+ ,0
+ ,466.9
+ ,0
+ ,451
+ ,0
+ ,422
+ ,0
+ ,429.2
+ ,0
+ ,425.9
+ ,0
+ ,460.7
+ ,0
+ ,463.6
+ ,0
+ ,541.4
+ ,0
+ ,544.2
+ ,0
+ ,517.5
+ ,0
+ ,469.4
+ ,0
+ ,439.4
+ ,0
+ ,549
+ ,0
+ ,533
+ ,0
+ ,506.1
+ ,0
+ ,484
+ ,0
+ ,457
+ ,0
+ ,481.5
+ ,0
+ ,469.5
+ ,0
+ ,544.7
+ ,0
+ ,541.2
+ ,0
+ ,521.5
+ ,0
+ ,469.7
+ ,0
+ ,434.4
+ ,0
+ ,542.6
+ ,0
+ ,517.3
+ ,0
+ ,485.7
+ ,0
+ ,465.8
+ ,0
+ ,447
+ ,0
+ ,426.6
+ ,0
+ ,411.6
+ ,0
+ ,467.5
+ ,0
+ ,484.5
+ ,0
+ ,451.2
+ ,0
+ ,417.4
+ ,0
+ ,379.9
+ ,0
+ ,484.7
+ ,0
+ ,455
+ ,0
+ ,420.8
+ ,0
+ ,416.5
+ ,0
+ ,376.3
+ ,0
+ ,405.6
+ ,0
+ ,405.8
+ ,0
+ ,500.8
+ ,1
+ ,514
+ ,1
+ ,475.5
+ ,1
+ ,430.1
+ ,1
+ ,414.4
+ ,1
+ ,538
+ ,1
+ ,526
+ ,1
+ ,488.5
+ ,1
+ ,520.2
+ ,1
+ ,504.4
+ ,1
+ ,568.5
+ ,1
+ ,610.6
+ ,1
+ ,818
+ ,1
+ ,830.9
+ ,1
+ ,835.9
+ ,1
+ ,782
+ ,1
+ ,762.3
+ ,1
+ ,856.9
+ ,1
+ ,820.9
+ ,1
+ ,769.6
+ ,1
+ ,752.2
+ ,1
+ ,724.4
+ ,1
+ ,723.1
+ ,1
+ ,719.5
+ ,1
+ ,817.4
+ ,1
+ ,803.3
+ ,1
+ ,752.5
+ ,1
+ ,689
+ ,1
+ ,630.4
+ ,1
+ ,765.5
+ ,1
+ ,757.7
+ ,1
+ ,732.2
+ ,1
+ ,702.6
+ ,1
+ ,683.3
+ ,1
+ ,709.5
+ ,1
+ ,702.2
+ ,1
+ ,784.8
+ ,1
+ ,810.9
+ ,1
+ ,755.6
+ ,1
+ ,656.8
+ ,1
+ ,615.1
+ ,1
+ ,745.3
+ ,1
+ ,694.1
+ ,1
+ ,675.7
+ ,1
+ ,643.7
+ ,1
+ ,622.1
+ ,1
+ ,634.6
+ ,1
+ ,588
+ ,1
+ ,689.7
+ ,1
+ ,673.9
+ ,1
+ ,647.9
+ ,1
+ ,568.8
+ ,1
+ ,545.7
+ ,1
+ ,632.6
+ ,1
+ ,643.8
+ ,1
+ ,593.1
+ ,1
+ ,579.7
+ ,1
+ ,546
+ ,1
+ ,562.9
+ ,1
+ ,572.5
+ ,1)
+ ,dim=c(2
+ ,372)
+ ,dimnames=list(c('Maandelijkse_werkloosheid'
+ ,'Dummy')
+ ,1:372))
> y <- array(NA,dim=c(2,372),dimnames=list(c('Maandelijkse_werkloosheid','Dummy'),1:372))
> for (i in 1:dim(x)[1])
+ {
+ for (j in 1:dim(x)[2])
+ {
+ y[i,j] <- as.numeric(x[i,j])
+ }
+ }
> par3 = 'Linear Trend'
> par2 = 'Include Monthly Dummies'
> par1 = '1'
> #'GNU S' R Code compiled by R2WASP v. 1.0.44 ()
> #Author: Prof. Dr. P. Wessa
> #To cite this work: AUTHOR(S), (YEAR), YOUR SOFTWARE TITLE (vNUMBER) in Free Statistics Software (v$_version), Office for Research Development and Education, URL http://www.wessa.net/rwasp_YOURPAGE.wasp/
> #Source of accompanying publication: Office for Research, Development, and Education
> #Technical description: Write here your technical program description (don't use hard returns!)
> library(lattice)
> library(lmtest)
Loading required package: zoo
Attaching package: 'zoo'
The following object(s) are masked from package:base :
as.Date.numeric
> n25 <- 25 #minimum number of obs. for Goldfeld-Quandt test
> par1 <- as.numeric(par1)
> x <- t(y)
> k <- length(x[1,])
> n <- length(x[,1])
> x1 <- cbind(x[,par1], x[,1:k!=par1])
> mycolnames <- c(colnames(x)[par1], colnames(x)[1:k!=par1])
> colnames(x1) <- mycolnames #colnames(x)[par1]
> x <- x1
> if (par3 == 'First Differences'){
+ x2 <- array(0, dim=c(n-1,k), dimnames=list(1:(n-1), paste('(1-B)',colnames(x),sep='')))
+ for (i in 1:n-1) {
+ for (j in 1:k) {
+ x2[i,j] <- x[i+1,j] - x[i,j]
+ }
+ }
+ x <- x2
+ }
> if (par2 == 'Include Monthly Dummies'){
+ x2 <- array(0, dim=c(n,11), dimnames=list(1:n, paste('M', seq(1:11), sep ='')))
+ for (i in 1:11){
+ x2[seq(i,n,12),i] <- 1
+ }
+ x <- cbind(x, x2)
+ }
> if (par2 == 'Include Quarterly Dummies'){
+ x2 <- array(0, dim=c(n,3), dimnames=list(1:n, paste('Q', seq(1:3), sep ='')))
+ for (i in 1:3){
+ x2[seq(i,n,4),i] <- 1
+ }
+ x <- cbind(x, x2)
+ }
> k <- length(x[1,])
> if (par3 == 'Linear Trend'){
+ x <- cbind(x, c(1:n))
+ colnames(x)[k+1] <- 't'
+ }
> x
Maandelijkse_werkloosheid Dummy M1 M2 M3 M4 M5 M6 M7 M8 M9 M10 M11 t
1 235.1 0 1 0 0 0 0 0 0 0 0 0 0 1
2 280.7 0 0 1 0 0 0 0 0 0 0 0 0 2
3 264.6 0 0 0 1 0 0 0 0 0 0 0 0 3
4 240.7 0 0 0 0 1 0 0 0 0 0 0 0 4
5 201.4 0 0 0 0 0 1 0 0 0 0 0 0 5
6 240.8 0 0 0 0 0 0 1 0 0 0 0 0 6
7 241.1 0 0 0 0 0 0 0 1 0 0 0 0 7
8 223.8 0 0 0 0 0 0 0 0 1 0 0 0 8
9 206.1 0 0 0 0 0 0 0 0 0 1 0 0 9
10 174.7 0 0 0 0 0 0 0 0 0 0 1 0 10
11 203.3 0 0 0 0 0 0 0 0 0 0 0 1 11
12 220.5 0 0 0 0 0 0 0 0 0 0 0 0 12
13 299.5 0 1 0 0 0 0 0 0 0 0 0 0 13
14 347.4 0 0 1 0 0 0 0 0 0 0 0 0 14
15 338.3 0 0 0 1 0 0 0 0 0 0 0 0 15
16 327.7 0 0 0 0 1 0 0 0 0 0 0 0 16
17 351.6 0 0 0 0 0 1 0 0 0 0 0 0 17
18 396.6 0 0 0 0 0 0 1 0 0 0 0 0 18
19 438.8 0 0 0 0 0 0 0 1 0 0 0 0 19
20 395.6 0 0 0 0 0 0 0 0 1 0 0 0 20
21 363.5 0 0 0 0 0 0 0 0 0 1 0 0 21
22 378.8 0 0 0 0 0 0 0 0 0 0 1 0 22
23 357.0 0 0 0 0 0 0 0 0 0 0 0 1 23
24 369.0 0 0 0 0 0 0 0 0 0 0 0 0 24
25 464.8 0 1 0 0 0 0 0 0 0 0 0 0 25
26 479.1 0 0 1 0 0 0 0 0 0 0 0 0 26
27 431.3 0 0 0 1 0 0 0 0 0 0 0 0 27
28 366.5 0 0 0 0 1 0 0 0 0 0 0 0 28
29 326.3 0 0 0 0 0 1 0 0 0 0 0 0 29
30 355.1 0 0 0 0 0 0 1 0 0 0 0 0 30
31 331.6 0 0 0 0 0 0 0 1 0 0 0 0 31
32 261.3 0 0 0 0 0 0 0 0 1 0 0 0 32
33 249.0 0 0 0 0 0 0 0 0 0 1 0 0 33
34 205.5 0 0 0 0 0 0 0 0 0 0 1 0 34
35 235.6 0 0 0 0 0 0 0 0 0 0 0 1 35
36 240.9 0 0 0 0 0 0 0 0 0 0 0 0 36
37 264.9 0 1 0 0 0 0 0 0 0 0 0 0 37
38 253.8 0 0 1 0 0 0 0 0 0 0 0 0 38
39 232.3 0 0 0 1 0 0 0 0 0 0 0 0 39
40 193.8 0 0 0 0 1 0 0 0 0 0 0 0 40
41 177.0 0 0 0 0 0 1 0 0 0 0 0 0 41
42 213.2 0 0 0 0 0 0 1 0 0 0 0 0 42
43 207.2 0 0 0 0 0 0 0 1 0 0 0 0 43
44 180.6 0 0 0 0 0 0 0 0 1 0 0 0 44
45 188.6 0 0 0 0 0 0 0 0 0 1 0 0 45
46 175.4 0 0 0 0 0 0 0 0 0 0 1 0 46
47 199.0 0 0 0 0 0 0 0 0 0 0 0 1 47
48 179.6 0 0 0 0 0 0 0 0 0 0 0 0 48
49 225.8 0 1 0 0 0 0 0 0 0 0 0 0 49
50 234.0 0 0 1 0 0 0 0 0 0 0 0 0 50
51 200.2 0 0 0 1 0 0 0 0 0 0 0 0 51
52 183.6 0 0 0 0 1 0 0 0 0 0 0 0 52
53 178.2 0 0 0 0 0 1 0 0 0 0 0 0 53
54 203.2 0 0 0 0 0 0 1 0 0 0 0 0 54
55 208.5 0 0 0 0 0 0 0 1 0 0 0 0 55
56 191.8 0 0 0 0 0 0 0 0 1 0 0 0 56
57 172.8 0 0 0 0 0 0 0 0 0 1 0 0 57
58 148.0 0 0 0 0 0 0 0 0 0 0 1 0 58
59 159.4 0 0 0 0 0 0 0 0 0 0 0 1 59
60 154.5 0 0 0 0 0 0 0 0 0 0 0 0 60
61 213.2 0 1 0 0 0 0 0 0 0 0 0 0 61
62 196.4 0 0 1 0 0 0 0 0 0 0 0 0 62
63 182.8 0 0 0 1 0 0 0 0 0 0 0 0 63
64 176.4 0 0 0 0 1 0 0 0 0 0 0 0 64
65 153.6 0 0 0 0 0 1 0 0 0 0 0 0 65
66 173.2 0 0 0 0 0 0 1 0 0 0 0 0 66
67 171.0 0 0 0 0 0 0 0 1 0 0 0 0 67
68 151.2 0 0 0 0 0 0 0 0 1 0 0 0 68
69 161.9 0 0 0 0 0 0 0 0 0 1 0 0 69
70 157.2 0 0 0 0 0 0 0 0 0 0 1 0 70
71 201.7 0 0 0 0 0 0 0 0 0 0 0 1 71
72 236.4 0 0 0 0 0 0 0 0 0 0 0 0 72
73 356.1 0 1 0 0 0 0 0 0 0 0 0 0 73
74 398.3 0 0 1 0 0 0 0 0 0 0 0 0 74
75 403.7 0 0 0 1 0 0 0 0 0 0 0 0 75
76 384.6 0 0 0 0 1 0 0 0 0 0 0 0 76
77 365.8 0 0 0 0 0 1 0 0 0 0 0 0 77
78 368.1 0 0 0 0 0 0 1 0 0 0 0 0 78
79 367.9 0 0 0 0 0 0 0 1 0 0 0 0 79
80 347.0 0 0 0 0 0 0 0 0 1 0 0 0 80
81 343.3 0 0 0 0 0 0 0 0 0 1 0 0 81
82 292.9 0 0 0 0 0 0 0 0 0 0 1 0 82
83 311.5 0 0 0 0 0 0 0 0 0 0 0 1 83
84 300.9 0 0 0 0 0 0 0 0 0 0 0 0 84
85 366.9 0 1 0 0 0 0 0 0 0 0 0 0 85
86 356.9 0 0 1 0 0 0 0 0 0 0 0 0 86
87 329.7 0 0 0 1 0 0 0 0 0 0 0 0 87
88 316.2 0 0 0 0 1 0 0 0 0 0 0 0 88
89 269.0 0 0 0 0 0 1 0 0 0 0 0 0 89
90 289.3 0 0 0 0 0 0 1 0 0 0 0 0 90
91 266.2 0 0 0 0 0 0 0 1 0 0 0 0 91
92 253.6 0 0 0 0 0 0 0 0 1 0 0 0 92
93 233.8 0 0 0 0 0 0 0 0 0 1 0 0 93
94 228.4 0 0 0 0 0 0 0 0 0 0 1 0 94
95 253.6 0 0 0 0 0 0 0 0 0 0 0 1 95
96 260.1 0 0 0 0 0 0 0 0 0 0 0 0 96
97 306.6 0 1 0 0 0 0 0 0 0 0 0 0 97
98 309.2 0 0 1 0 0 0 0 0 0 0 0 0 98
99 309.5 0 0 0 1 0 0 0 0 0 0 0 0 99
100 271.0 0 0 0 0 1 0 0 0 0 0 0 0 100
101 279.9 0 0 0 0 0 1 0 0 0 0 0 0 101
102 317.9 0 0 0 0 0 0 1 0 0 0 0 0 102
103 298.4 0 0 0 0 0 0 0 1 0 0 0 0 103
104 246.7 0 0 0 0 0 0 0 0 1 0 0 0 104
105 227.3 0 0 0 0 0 0 0 0 0 1 0 0 105
106 209.1 0 0 0 0 0 0 0 0 0 0 1 0 106
107 259.9 0 0 0 0 0 0 0 0 0 0 0 1 107
108 266.0 0 0 0 0 0 0 0 0 0 0 0 0 108
109 320.6 0 1 0 0 0 0 0 0 0 0 0 0 109
110 308.5 0 0 1 0 0 0 0 0 0 0 0 0 110
111 282.2 0 0 0 1 0 0 0 0 0 0 0 0 111
112 262.7 0 0 0 0 1 0 0 0 0 0 0 0 112
113 263.5 0 0 0 0 0 1 0 0 0 0 0 0 113
114 313.1 0 0 0 0 0 0 1 0 0 0 0 0 114
115 284.3 0 0 0 0 0 0 0 1 0 0 0 0 115
116 252.6 0 0 0 0 0 0 0 0 1 0 0 0 116
117 250.3 0 0 0 0 0 0 0 0 0 1 0 0 117
118 246.5 0 0 0 0 0 0 0 0 0 0 1 0 118
119 312.7 0 0 0 0 0 0 0 0 0 0 0 1 119
120 333.2 0 0 0 0 0 0 0 0 0 0 0 0 120
121 446.4 0 1 0 0 0 0 0 0 0 0 0 0 121
122 511.6 0 0 1 0 0 0 0 0 0 0 0 0 122
123 515.5 0 0 0 1 0 0 0 0 0 0 0 0 123
124 506.4 0 0 0 0 1 0 0 0 0 0 0 0 124
125 483.2 0 0 0 0 0 1 0 0 0 0 0 0 125
126 522.3 0 0 0 0 0 0 1 0 0 0 0 0 126
127 509.8 0 0 0 0 0 0 0 1 0 0 0 0 127
128 460.7 0 0 0 0 0 0 0 0 1 0 0 0 128
129 405.8 0 0 0 0 0 0 0 0 0 1 0 0 129
130 375.0 0 0 0 0 0 0 0 0 0 0 1 0 130
131 378.5 0 0 0 0 0 0 0 0 0 0 0 1 131
132 406.8 0 0 0 0 0 0 0 0 0 0 0 0 132
133 467.8 0 1 0 0 0 0 0 0 0 0 0 0 133
134 469.8 0 0 1 0 0 0 0 0 0 0 0 0 134
135 429.8 0 0 0 1 0 0 0 0 0 0 0 0 135
136 355.8 0 0 0 0 1 0 0 0 0 0 0 0 136
137 332.7 0 0 0 0 0 1 0 0 0 0 0 0 137
138 378.0 0 0 0 0 0 0 1 0 0 0 0 0 138
139 360.5 0 0 0 0 0 0 0 1 0 0 0 0 139
140 334.7 0 0 0 0 0 0 0 0 1 0 0 0 140
141 319.5 0 0 0 0 0 0 0 0 0 1 0 0 141
142 323.1 0 0 0 0 0 0 0 0 0 0 1 0 142
143 363.6 0 0 0 0 0 0 0 0 0 0 0 1 143
144 352.1 0 0 0 0 0 0 0 0 0 0 0 0 144
145 411.9 0 1 0 0 0 0 0 0 0 0 0 0 145
146 388.6 0 0 1 0 0 0 0 0 0 0 0 0 146
147 416.4 0 0 0 1 0 0 0 0 0 0 0 0 147
148 360.7 0 0 0 0 1 0 0 0 0 0 0 0 148
149 338.0 0 0 0 0 0 1 0 0 0 0 0 0 149
150 417.2 0 0 0 0 0 0 1 0 0 0 0 0 150
151 388.4 0 0 0 0 0 0 0 1 0 0 0 0 151
152 371.1 0 0 0 0 0 0 0 0 1 0 0 0 152
153 331.5 0 0 0 0 0 0 0 0 0 1 0 0 153
154 353.7 0 0 0 0 0 0 0 0 0 0 1 0 154
155 396.7 0 0 0 0 0 0 0 0 0 0 0 1 155
156 447.0 0 0 0 0 0 0 0 0 0 0 0 0 156
157 533.5 0 1 0 0 0 0 0 0 0 0 0 0 157
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164 444.0 0 0 0 0 0 0 0 0 1 0 0 0 164
165 403.4 0 0 0 0 0 0 0 0 0 1 0 0 165
166 386.3 0 0 0 0 0 0 0 0 0 0 1 0 166
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204 340.9 0 0 0 0 0 0 0 0 0 0 0 0 204
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211 342.9 0 0 0 0 0 0 0 1 0 0 0 0 211
212 316.5 0 0 0 0 0 0 0 0 1 0 0 0 212
213 284.2 0 0 0 0 0 0 0 0 0 1 0 0 213
214 270.9 0 0 0 0 0 0 0 0 0 0 1 0 214
215 288.8 0 0 0 0 0 0 0 0 0 0 0 1 215
216 278.8 0 0 0 0 0 0 0 0 0 0 0 0 216
217 324.4 0 1 0 0 0 0 0 0 0 0 0 0 217
218 310.9 0 0 1 0 0 0 0 0 0 0 0 0 218
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220 273.0 0 0 0 0 1 0 0 0 0 0 0 0 220
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226 246.5 0 0 0 0 0 0 0 0 0 0 1 0 226
227 257.9 0 0 0 0 0 0 0 0 0 0 0 1 227
228 266.5 0 0 0 0 0 0 0 0 0 0 0 0 228
229 315.9 0 1 0 0 0 0 0 0 0 0 0 0 229
230 318.4 0 0 1 0 0 0 0 0 0 0 0 0 230
231 295.4 0 0 0 1 0 0 0 0 0 0 0 0 231
232 266.4 0 0 0 0 1 0 0 0 0 0 0 0 232
233 245.8 0 0 0 0 0 1 0 0 0 0 0 0 233
234 362.8 0 0 0 0 0 0 1 0 0 0 0 0 234
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240 272.0 0 0 0 0 0 0 0 0 0 0 0 0 240
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242 328.7 0 0 1 0 0 0 0 0 0 0 0 0 242
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244 249.1 0 0 0 0 1 0 0 0 0 0 0 0 244
245 230.4 0 0 0 0 0 1 0 0 0 0 0 0 245
246 361.5 0 0 0 0 0 0 1 0 0 0 0 0 246
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248 277.2 0 0 0 0 0 0 0 0 1 0 0 0 248
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250 251.0 0 0 0 0 0 0 0 0 0 0 1 0 250
251 257.6 0 0 0 0 0 0 0 0 0 0 0 1 251
252 241.8 0 0 0 0 0 0 0 0 0 0 0 0 252
253 287.5 0 1 0 0 0 0 0 0 0 0 0 0 253
254 292.3 0 0 1 0 0 0 0 0 0 0 0 0 254
255 274.7 0 0 0 1 0 0 0 0 0 0 0 0 255
256 254.2 0 0 0 0 1 0 0 0 0 0 0 0 256
257 230.0 0 0 0 0 0 1 0 0 0 0 0 0 257
258 339.0 0 0 0 0 0 0 1 0 0 0 0 0 258
259 318.2 0 0 0 0 0 0 0 1 0 0 0 0 259
260 287.0 0 0 0 0 0 0 0 0 1 0 0 0 260
261 295.8 0 0 0 0 0 0 0 0 0 1 0 0 261
262 284.0 0 0 0 0 0 0 0 0 0 0 1 0 262
263 271.0 0 0 0 0 0 0 0 0 0 0 0 1 263
264 262.7 0 0 0 0 0 0 0 0 0 0 0 0 264
265 340.6 0 1 0 0 0 0 0 0 0 0 0 0 265
266 379.4 0 0 1 0 0 0 0 0 0 0 0 0 266
267 373.3 0 0 0 1 0 0 0 0 0 0 0 0 267
268 355.2 0 0 0 0 1 0 0 0 0 0 0 0 268
269 338.4 0 0 0 0 0 1 0 0 0 0 0 0 269
270 466.9 0 0 0 0 0 0 1 0 0 0 0 0 270
271 451.0 0 0 0 0 0 0 0 1 0 0 0 0 271
272 422.0 0 0 0 0 0 0 0 0 1 0 0 0 272
273 429.2 0 0 0 0 0 0 0 0 0 1 0 0 273
274 425.9 0 0 0 0 0 0 0 0 0 0 1 0 274
275 460.7 0 0 0 0 0 0 0 0 0 0 0 1 275
276 463.6 0 0 0 0 0 0 0 0 0 0 0 0 276
277 541.4 0 1 0 0 0 0 0 0 0 0 0 0 277
278 544.2 0 0 1 0 0 0 0 0 0 0 0 0 278
279 517.5 0 0 0 1 0 0 0 0 0 0 0 0 279
280 469.4 0 0 0 0 1 0 0 0 0 0 0 0 280
281 439.4 0 0 0 0 0 1 0 0 0 0 0 0 281
282 549.0 0 0 0 0 0 0 1 0 0 0 0 0 282
283 533.0 0 0 0 0 0 0 0 1 0 0 0 0 283
284 506.1 0 0 0 0 0 0 0 0 1 0 0 0 284
285 484.0 0 0 0 0 0 0 0 0 0 1 0 0 285
286 457.0 0 0 0 0 0 0 0 0 0 0 1 0 286
287 481.5 0 0 0 0 0 0 0 0 0 0 0 1 287
288 469.5 0 0 0 0 0 0 0 0 0 0 0 0 288
289 544.7 0 1 0 0 0 0 0 0 0 0 0 0 289
290 541.2 0 0 1 0 0 0 0 0 0 0 0 0 290
291 521.5 0 0 0 1 0 0 0 0 0 0 0 0 291
292 469.7 0 0 0 0 1 0 0 0 0 0 0 0 292
293 434.4 0 0 0 0 0 1 0 0 0 0 0 0 293
294 542.6 0 0 0 0 0 0 1 0 0 0 0 0 294
295 517.3 0 0 0 0 0 0 0 1 0 0 0 0 295
296 485.7 0 0 0 0 0 0 0 0 1 0 0 0 296
297 465.8 0 0 0 0 0 0 0 0 0 1 0 0 297
298 447.0 0 0 0 0 0 0 0 0 0 0 1 0 298
299 426.6 0 0 0 0 0 0 0 0 0 0 0 1 299
300 411.6 0 0 0 0 0 0 0 0 0 0 0 0 300
301 467.5 0 1 0 0 0 0 0 0 0 0 0 0 301
302 484.5 0 0 1 0 0 0 0 0 0 0 0 0 302
303 451.2 0 0 0 1 0 0 0 0 0 0 0 0 303
304 417.4 0 0 0 0 1 0 0 0 0 0 0 0 304
305 379.9 0 0 0 0 0 1 0 0 0 0 0 0 305
306 484.7 0 0 0 0 0 0 1 0 0 0 0 0 306
307 455.0 0 0 0 0 0 0 0 1 0 0 0 0 307
308 420.8 0 0 0 0 0 0 0 0 1 0 0 0 308
309 416.5 0 0 0 0 0 0 0 0 0 1 0 0 309
310 376.3 0 0 0 0 0 0 0 0 0 0 1 0 310
311 405.6 0 0 0 0 0 0 0 0 0 0 0 1 311
312 405.8 0 0 0 0 0 0 0 0 0 0 0 0 312
313 500.8 1 1 0 0 0 0 0 0 0 0 0 0 313
314 514.0 1 0 1 0 0 0 0 0 0 0 0 0 314
315 475.5 1 0 0 1 0 0 0 0 0 0 0 0 315
316 430.1 1 0 0 0 1 0 0 0 0 0 0 0 316
317 414.4 1 0 0 0 0 1 0 0 0 0 0 0 317
318 538.0 1 0 0 0 0 0 1 0 0 0 0 0 318
319 526.0 1 0 0 0 0 0 0 1 0 0 0 0 319
320 488.5 1 0 0 0 0 0 0 0 1 0 0 0 320
321 520.2 1 0 0 0 0 0 0 0 0 1 0 0 321
322 504.4 1 0 0 0 0 0 0 0 0 0 1 0 322
323 568.5 1 0 0 0 0 0 0 0 0 0 0 1 323
324 610.6 1 0 0 0 0 0 0 0 0 0 0 0 324
325 818.0 1 1 0 0 0 0 0 0 0 0 0 0 325
326 830.9 1 0 1 0 0 0 0 0 0 0 0 0 326
327 835.9 1 0 0 1 0 0 0 0 0 0 0 0 327
328 782.0 1 0 0 0 1 0 0 0 0 0 0 0 328
329 762.3 1 0 0 0 0 1 0 0 0 0 0 0 329
330 856.9 1 0 0 0 0 0 1 0 0 0 0 0 330
331 820.9 1 0 0 0 0 0 0 1 0 0 0 0 331
332 769.6 1 0 0 0 0 0 0 0 1 0 0 0 332
333 752.2 1 0 0 0 0 0 0 0 0 1 0 0 333
334 724.4 1 0 0 0 0 0 0 0 0 0 1 0 334
335 723.1 1 0 0 0 0 0 0 0 0 0 0 1 335
336 719.5 1 0 0 0 0 0 0 0 0 0 0 0 336
337 817.4 1 1 0 0 0 0 0 0 0 0 0 0 337
338 803.3 1 0 1 0 0 0 0 0 0 0 0 0 338
339 752.5 1 0 0 1 0 0 0 0 0 0 0 0 339
340 689.0 1 0 0 0 1 0 0 0 0 0 0 0 340
341 630.4 1 0 0 0 0 1 0 0 0 0 0 0 341
342 765.5 1 0 0 0 0 0 1 0 0 0 0 0 342
343 757.7 1 0 0 0 0 0 0 1 0 0 0 0 343
344 732.2 1 0 0 0 0 0 0 0 1 0 0 0 344
345 702.6 1 0 0 0 0 0 0 0 0 1 0 0 345
346 683.3 1 0 0 0 0 0 0 0 0 0 1 0 346
347 709.5 1 0 0 0 0 0 0 0 0 0 0 1 347
348 702.2 1 0 0 0 0 0 0 0 0 0 0 0 348
349 784.8 1 1 0 0 0 0 0 0 0 0 0 0 349
350 810.9 1 0 1 0 0 0 0 0 0 0 0 0 350
351 755.6 1 0 0 1 0 0 0 0 0 0 0 0 351
352 656.8 1 0 0 0 1 0 0 0 0 0 0 0 352
353 615.1 1 0 0 0 0 1 0 0 0 0 0 0 353
354 745.3 1 0 0 0 0 0 1 0 0 0 0 0 354
355 694.1 1 0 0 0 0 0 0 1 0 0 0 0 355
356 675.7 1 0 0 0 0 0 0 0 1 0 0 0 356
357 643.7 1 0 0 0 0 0 0 0 0 1 0 0 357
358 622.1 1 0 0 0 0 0 0 0 0 0 1 0 358
359 634.6 1 0 0 0 0 0 0 0 0 0 0 1 359
360 588.0 1 0 0 0 0 0 0 0 0 0 0 0 360
361 689.7 1 1 0 0 0 0 0 0 0 0 0 0 361
362 673.9 1 0 1 0 0 0 0 0 0 0 0 0 362
363 647.9 1 0 0 1 0 0 0 0 0 0 0 0 363
364 568.8 1 0 0 0 1 0 0 0 0 0 0 0 364
365 545.7 1 0 0 0 0 1 0 0 0 0 0 0 365
366 632.6 1 0 0 0 0 0 1 0 0 0 0 0 366
367 643.8 1 0 0 0 0 0 0 1 0 0 0 0 367
368 593.1 1 0 0 0 0 0 0 0 1 0 0 0 368
369 579.7 1 0 0 0 0 0 0 0 0 1 0 0 369
370 546.0 1 0 0 0 0 0 0 0 0 0 1 0 370
371 562.9 1 0 0 0 0 0 0 0 0 0 0 1 371
372 572.5 1 0 0 0 0 0 0 0 0 0 0 0 372
> k <- length(x[1,])
> df <- as.data.frame(x)
> (mylm <- lm(df))
Call:
lm(formula = df)
Coefficients:
(Intercept) Dummy M1 M2 M3 M4
233.3034 220.7212 66.9386 76.2985 53.4938 14.0343
M5 M6 M7 M8 M9 M10
-7.0414 65.1475 41.8396 10.1575 -7.4859 -23.4648
M11 t
-1.9308 0.5369
> (mysum <- summary(mylm))
Call:
lm(formula = df)
Residuals:
Min 1Q Median 3Q Max
-207.633 -66.837 0.889 67.453 192.481
Coefficients:
Estimate Std. Error t value Pr(>|t|)
(Intercept) 233.3034 17.8153 13.096 < 2e-16 ***
Dummy 220.7212 15.7009 14.058 < 2e-16 ***
M1 66.9386 21.8073 3.070 0.002307 **
M2 76.2985 21.8059 3.499 0.000526 ***
M3 53.4938 21.8047 2.453 0.014631 *
M4 14.0343 21.8036 0.644 0.520203
M5 -7.0414 21.8026 -0.323 0.746913
M6 65.1475 21.8017 2.988 0.003000 **
M7 41.8396 21.8010 1.919 0.055759 .
M8 10.1575 21.8004 0.466 0.641549
M9 -7.4859 21.7999 -0.343 0.731504
M10 -23.4648 21.7996 -1.076 0.282478
M11 -1.9308 21.7994 -0.089 0.929472
t 0.5369 0.0538 9.980 < 2e-16 ***
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
Residual standard error: 85.82 on 358 degrees of freedom
Multiple R-squared: 0.7043, Adjusted R-squared: 0.6936
F-statistic: 65.61 on 13 and 358 DF, p-value: < 2.2e-16
> if (n > n25) {
+ kp3 <- k + 3
+ nmkm3 <- n - k - 3
+ gqarr <- array(NA, dim=c(nmkm3-kp3+1,3))
+ numgqtests <- 0
+ numsignificant1 <- 0
+ numsignificant5 <- 0
+ numsignificant10 <- 0
+ for (mypoint in kp3:nmkm3) {
+ j <- 0
+ numgqtests <- numgqtests + 1
+ for (myalt in c('greater', 'two.sided', 'less')) {
+ j <- j + 1
+ gqarr[mypoint-kp3+1,j] <- gqtest(mylm, point=mypoint, alternative=myalt)$p.value
+ }
+ if (gqarr[mypoint-kp3+1,2] < 0.01) numsignificant1 <- numsignificant1 + 1
+ if (gqarr[mypoint-kp3+1,2] < 0.05) numsignificant5 <- numsignificant5 + 1
+ if (gqarr[mypoint-kp3+1,2] < 0.10) numsignificant10 <- numsignificant10 + 1
+ }
+ gqarr
+ }
[,1] [,2] [,3]
[1,] 0.0464826590 9.296532e-02 9.535173e-01
[2,] 0.0350947806 7.018956e-02 9.649052e-01
[3,] 0.0488802980 9.776060e-02 9.511197e-01
[4,] 0.0304648235 6.092965e-02 9.695352e-01
[5,] 0.0151727827 3.034557e-02 9.848272e-01
[6,] 0.0138799756 2.775995e-02 9.861200e-01
[7,] 0.0063946690 1.278934e-02 9.936053e-01
[8,] 0.0027784968 5.556994e-03 9.972215e-01
[9,] 0.0011624522 2.324904e-03 9.988375e-01
[10,] 0.0006274904 1.254981e-03 9.993725e-01
[11,] 0.0006083021 1.216604e-03 9.993917e-01
[12,] 0.0015672672 3.134534e-03 9.984327e-01
[13,] 0.0048581359 9.716272e-03 9.951419e-01
[14,] 0.0104076781 2.081536e-02 9.895923e-01
[15,] 0.0313730161 6.274603e-02 9.686270e-01
[16,] 0.0921643280 1.843287e-01 9.078357e-01
[17,] 0.1440019216 2.880038e-01 8.559981e-01
[18,] 0.2394871326 4.789743e-01 7.605129e-01
[19,] 0.2797138188 5.594276e-01 7.202862e-01
[20,] 0.3190864066 6.381728e-01 6.809136e-01
[21,] 0.4148126041 8.296252e-01 5.851874e-01
[22,] 0.5601704245 8.796592e-01 4.398296e-01
[23,] 0.6485772649 7.028455e-01 3.514227e-01
[24,] 0.7102131157 5.795738e-01 2.897869e-01
[25,] 0.7462418060 5.075164e-01 2.537582e-01
[26,] 0.7720408974 4.559182e-01 2.279591e-01
[27,] 0.7959565913 4.080868e-01 2.040434e-01
[28,] 0.7987435147 4.025130e-01 2.012565e-01
[29,] 0.7800679161 4.398642e-01 2.199321e-01
[30,] 0.7555940659 4.888119e-01 2.444059e-01
[31,] 0.7241235305 5.517529e-01 2.758765e-01
[32,] 0.7059934953 5.880130e-01 2.940065e-01
[33,] 0.6825545190 6.348910e-01 3.174455e-01
[34,] 0.6649123018 6.701754e-01 3.350877e-01
[35,] 0.6520959883 6.958080e-01 3.479040e-01
[36,] 0.6241662743 7.516675e-01 3.758337e-01
[37,] 0.5879342247 8.241316e-01 4.120658e-01
[38,] 0.5631661027 8.736678e-01 4.368339e-01
[39,] 0.5316280028 9.367440e-01 4.683720e-01
[40,] 0.4916070241 9.832140e-01 5.083930e-01
[41,] 0.4532477168 9.064954e-01 5.467523e-01
[42,] 0.4184958957 8.369918e-01 5.815041e-01
[43,] 0.3874203676 7.748407e-01 6.125796e-01
[44,] 0.3611074651 7.222149e-01 6.388925e-01
[45,] 0.3327248010 6.654496e-01 6.672752e-01
[46,] 0.3207565678 6.415131e-01 6.792434e-01
[47,] 0.3032032467 6.064065e-01 6.967968e-01
[48,] 0.2757632908 5.515266e-01 7.242367e-01
[49,] 0.2510359970 5.020720e-01 7.489640e-01
[50,] 0.2433003660 4.866007e-01 7.566996e-01
[51,] 0.2318942469 4.637885e-01 7.681058e-01
[52,] 0.2164845273 4.329691e-01 7.835155e-01
[53,] 0.1963750403 3.927501e-01 8.036250e-01
[54,] 0.1777811887 3.555624e-01 8.222188e-01
[55,] 0.1643147751 3.286296e-01 8.356852e-01
[56,] 0.1602549776 3.205100e-01 8.397450e-01
[57,] 0.2117291112 4.234582e-01 7.882709e-01
[58,] 0.2926461922 5.852924e-01 7.073538e-01
[59,] 0.4119211895 8.238424e-01 5.880788e-01
[60,] 0.5321458195 9.357084e-01 4.678542e-01
[61,] 0.6290882046 7.418236e-01 3.709118e-01
[62,] 0.6693010111 6.613980e-01 3.306990e-01
[63,] 0.6987168411 6.025663e-01 3.012832e-01
[64,] 0.7312276546 5.375447e-01 2.687723e-01
[65,] 0.7627624970 4.744750e-01 2.372375e-01
[66,] 0.7650962250 4.698075e-01 2.349038e-01
[67,] 0.7646764968 4.706470e-01 2.353235e-01
[68,] 0.7537389879 4.925220e-01 2.462610e-01
[69,] 0.7449932158 5.100136e-01 2.550068e-01
[70,] 0.7239157666 5.521685e-01 2.760842e-01
[71,] 0.6994078803 6.011842e-01 3.005921e-01
[72,] 0.6765000553 6.469999e-01 3.234999e-01
[73,] 0.6454743146 7.090514e-01 3.545257e-01
[74,] 0.6208888656 7.582223e-01 3.791111e-01
[75,] 0.5939926875 8.120146e-01 4.060073e-01
[76,] 0.5638692768 8.722614e-01 4.361307e-01
[77,] 0.5333850257 9.332299e-01 4.666150e-01
[78,] 0.5025878162 9.948244e-01 4.974122e-01
[79,] 0.4723732804 9.447466e-01 5.276267e-01
[80,] 0.4420544086 8.841088e-01 5.579456e-01
[81,] 0.4144385062 8.288770e-01 5.855615e-01
[82,] 0.3884457550 7.768915e-01 6.115542e-01
[83,] 0.3601847017 7.203694e-01 6.398153e-01
[84,] 0.3312692413 6.625385e-01 6.687308e-01
[85,] 0.3036290081 6.072580e-01 6.963710e-01
[86,] 0.2852060130 5.704120e-01 7.147940e-01
[87,] 0.2624934415 5.249869e-01 7.375066e-01
[88,] 0.2429413751 4.858828e-01 7.570586e-01
[89,] 0.2248675766 4.497352e-01 7.751324e-01
[90,] 0.2086538083 4.173076e-01 7.913462e-01
[91,] 0.1902390699 3.804781e-01 8.097609e-01
[92,] 0.1725840594 3.451681e-01 8.274159e-01
[93,] 0.1575466656 3.150933e-01 8.424533e-01
[94,] 0.1460400856 2.920802e-01 8.539599e-01
[95,] 0.1361994552 2.723989e-01 8.638005e-01
[96,] 0.1234974941 2.469950e-01 8.765025e-01
[97,] 0.1096755817 2.193512e-01 8.903244e-01
[98,] 0.1027201468 2.054403e-01 8.972799e-01
[99,] 0.0947996590 1.895993e-01 9.052003e-01
[100,] 0.0876955120 1.753910e-01 9.123045e-01
[101,] 0.0796512690 1.593025e-01 9.203487e-01
[102,] 0.0722550850 1.445102e-01 9.277449e-01
[103,] 0.0674951020 1.349902e-01 9.325049e-01
[104,] 0.0646855819 1.293712e-01 9.353144e-01
[105,] 0.0749772057 1.499544e-01 9.250228e-01
[106,] 0.1126013715 2.252027e-01 8.873986e-01
[107,] 0.1781697876 3.563396e-01 8.218302e-01
[108,] 0.2822484237 5.644968e-01 7.177516e-01
[109,] 0.3898623467 7.797247e-01 6.101377e-01
[110,] 0.4879254993 9.758510e-01 5.120745e-01
[111,] 0.5767708776 8.464582e-01 4.232291e-01
[112,] 0.6344895315 7.310209e-01 3.655105e-01
[113,] 0.6474125492 7.051749e-01 3.525875e-01
[114,] 0.6488180683 7.023639e-01 3.511819e-01
[115,] 0.6363518013 7.272964e-01 3.636482e-01
[116,] 0.6365423283 7.269153e-01 3.634577e-01
[117,] 0.6322588383 7.354823e-01 3.677412e-01
[118,] 0.6207405391 7.585189e-01 3.792595e-01
[119,] 0.5993075311 8.013849e-01 4.006925e-01
[120,] 0.5685181850 8.629636e-01 4.314818e-01
[121,] 0.5374081653 9.251837e-01 4.625918e-01
[122,] 0.5079353097 9.841294e-01 4.920647e-01
[123,] 0.4769895050 9.539790e-01 5.230105e-01
[124,] 0.4459890117 8.919780e-01 5.540110e-01
[125,] 0.4151924733 8.303849e-01 5.848075e-01
[126,] 0.3862424330 7.724849e-01 6.137576e-01
[127,] 0.3609818315 7.219637e-01 6.390182e-01
[128,] 0.3329308341 6.658617e-01 6.670692e-01
[129,] 0.3051483948 6.102968e-01 6.948516e-01
[130,] 0.2802537238 5.605074e-01 7.197463e-01
[131,] 0.2562633821 5.125268e-01 7.437366e-01
[132,] 0.2320328447 4.640657e-01 7.679672e-01
[133,] 0.2093574067 4.187148e-01 7.906426e-01
[134,] 0.1895484340 3.790969e-01 8.104516e-01
[135,] 0.1692718578 3.385437e-01 8.307281e-01
[136,] 0.1515728436 3.031457e-01 8.484272e-01
[137,] 0.1339281042 2.678562e-01 8.660719e-01
[138,] 0.1207473832 2.414948e-01 8.792526e-01
[139,] 0.1120437176 2.240874e-01 8.879563e-01
[140,] 0.1184625973 2.369252e-01 8.815374e-01
[141,] 0.1350208392 2.700417e-01 8.649792e-01
[142,] 0.1676343801 3.352688e-01 8.323656e-01
[143,] 0.2033944754 4.067890e-01 7.966055e-01
[144,] 0.2308843121 4.617686e-01 7.691157e-01
[145,] 0.2608620465 5.217241e-01 7.391380e-01
[146,] 0.2895959557 5.791919e-01 7.104040e-01
[147,] 0.3076947595 6.153895e-01 6.923052e-01
[148,] 0.3114964023 6.229928e-01 6.885036e-01
[149,] 0.3025217363 6.050435e-01 6.974783e-01
[150,] 0.2935820625 5.871641e-01 7.064179e-01
[151,] 0.2801681834 5.603364e-01 7.198318e-01
[152,] 0.2717728525 5.435457e-01 7.282271e-01
[153,] 0.2602212257 5.204425e-01 7.397788e-01
[154,] 0.2446420004 4.892840e-01 7.553580e-01
[155,] 0.2328352304 4.656705e-01 7.671648e-01
[156,] 0.2228852417 4.457705e-01 7.771148e-01
[157,] 0.2219515729 4.439031e-01 7.780484e-01
[158,] 0.2034996652 4.069993e-01 7.965003e-01
[159,] 0.1881238260 3.762477e-01 8.118762e-01
[160,] 0.1756244346 3.512489e-01 8.243756e-01
[161,] 0.1614543292 3.229087e-01 8.385457e-01
[162,] 0.1481643349 2.963287e-01 8.518357e-01
[163,] 0.1388880344 2.777761e-01 8.611120e-01
[164,] 0.1322060589 2.644121e-01 8.677939e-01
[165,] 0.1290353453 2.580707e-01 8.709647e-01
[166,] 0.1310873529 2.621747e-01 8.689126e-01
[167,] 0.1302597342 2.605195e-01 8.697403e-01
[168,] 0.1309421878 2.618844e-01 8.690578e-01
[169,] 0.1385193394 2.770387e-01 8.614807e-01
[170,] 0.1336479438 2.672959e-01 8.663521e-01
[171,] 0.1279558144 2.559116e-01 8.720442e-01
[172,] 0.1220851993 2.441704e-01 8.779148e-01
[173,] 0.1149353880 2.298708e-01 8.850646e-01
[174,] 0.1093350955 2.186702e-01 8.906649e-01
[175,] 0.1103540144 2.207080e-01 8.896460e-01
[176,] 0.1124798111 2.249596e-01 8.875202e-01
[177,] 0.1151848290 2.303697e-01 8.848152e-01
[178,] 0.1165349641 2.330699e-01 8.834650e-01
[179,] 0.1204163255 2.408327e-01 8.795837e-01
[180,] 0.1278444349 2.556889e-01 8.721556e-01
[181,] 0.1376617472 2.753235e-01 8.623383e-01
[182,] 0.1382201309 2.764403e-01 8.617799e-01
[183,] 0.1345986192 2.691972e-01 8.654014e-01
[184,] 0.1325660754 2.651322e-01 8.674339e-01
[185,] 0.1287652881 2.575306e-01 8.712347e-01
[186,] 0.1265861206 2.531722e-01 8.734139e-01
[187,] 0.1268888938 2.537778e-01 8.731111e-01
[188,] 0.1314500148 2.629000e-01 8.685500e-01
[189,] 0.1329456990 2.658914e-01 8.670543e-01
[190,] 0.1366894977 2.733790e-01 8.633105e-01
[191,] 0.1416173371 2.832347e-01 8.583827e-01
[192,] 0.1516314069 3.032628e-01 8.483686e-01
[193,] 0.1651985992 3.303972e-01 8.348014e-01
[194,] 0.1626583750 3.253167e-01 8.373416e-01
[195,] 0.1605846679 3.211693e-01 8.394153e-01
[196,] 0.1590034665 3.180069e-01 8.409965e-01
[197,] 0.1565048241 3.130096e-01 8.434952e-01
[198,] 0.1542521192 3.085042e-01 8.457479e-01
[199,] 0.1550741088 3.101482e-01 8.449259e-01
[200,] 0.1602153201 3.204306e-01 8.397847e-01
[201,] 0.1675417533 3.350835e-01 8.324582e-01
[202,] 0.1836534218 3.673068e-01 8.163466e-01
[203,] 0.1955618994 3.911238e-01 8.044381e-01
[204,] 0.2052075852 4.104152e-01 7.947924e-01
[205,] 0.2121080919 4.242162e-01 7.878919e-01
[206,] 0.2019461116 4.038922e-01 7.980539e-01
[207,] 0.1982625163 3.965250e-01 8.017375e-01
[208,] 0.1925499873 3.851000e-01 8.074500e-01
[209,] 0.1887610062 3.775220e-01 8.112390e-01
[210,] 0.1818081179 3.636162e-01 8.181919e-01
[211,] 0.1787427938 3.574856e-01 8.212572e-01
[212,] 0.1755998364 3.511997e-01 8.244002e-01
[213,] 0.1758255338 3.516511e-01 8.241745e-01
[214,] 0.1781502164 3.563004e-01 8.218498e-01
[215,] 0.1805046686 3.610093e-01 8.194953e-01
[216,] 0.1801997540 3.603995e-01 8.198002e-01
[217,] 0.1807622479 3.615245e-01 8.192378e-01
[218,] 0.1654172638 3.308345e-01 8.345827e-01
[219,] 0.1527425050 3.054850e-01 8.472575e-01
[220,] 0.1407507343 2.815015e-01 8.592493e-01
[221,] 0.1271642568 2.543285e-01 8.728357e-01
[222,] 0.1141597510 2.283195e-01 8.858402e-01
[223,] 0.1036894031 2.073788e-01 8.963106e-01
[224,] 0.0966989070 1.933978e-01 9.033011e-01
[225,] 0.0976468136 1.952936e-01 9.023532e-01
[226,] 0.0950859038 1.901718e-01 9.049141e-01
[227,] 0.0960098721 1.920197e-01 9.039901e-01
[228,] 0.0978245713 1.956491e-01 9.021754e-01
[229,] 0.0986679118 1.973358e-01 9.013321e-01
[230,] 0.0878824125 1.757648e-01 9.121176e-01
[231,] 0.0804478698 1.608957e-01 9.195521e-01
[232,] 0.0758266300 1.516533e-01 9.241734e-01
[233,] 0.0719177340 1.438355e-01 9.280823e-01
[234,] 0.0668428556 1.336857e-01 9.331571e-01
[235,] 0.0647481391 1.294963e-01 9.352519e-01
[236,] 0.0666245254 1.332491e-01 9.333755e-01
[237,] 0.0810369498 1.620739e-01 9.189631e-01
[238,] 0.1010990014 2.021980e-01 8.989010e-01
[239,] 0.1217111061 2.434222e-01 8.782889e-01
[240,] 0.1314525901 2.629052e-01 8.685474e-01
[241,] 0.1419330867 2.838662e-01 8.580669e-01
[242,] 0.1471884029 2.943768e-01 8.528116e-01
[243,] 0.1540579405 3.081159e-01 8.459421e-01
[244,] 0.1620539933 3.241080e-01 8.379460e-01
[245,] 0.1618226447 3.236453e-01 8.381774e-01
[246,] 0.1590537931 3.181076e-01 8.409462e-01
[247,] 0.1756447376 3.512895e-01 8.243553e-01
[248,] 0.2019039685 4.038079e-01 7.980960e-01
[249,] 0.2393619872 4.787240e-01 7.606380e-01
[250,] 0.2565730962 5.131462e-01 7.434269e-01
[251,] 0.2610919272 5.221839e-01 7.389081e-01
[252,] 0.2474863633 4.949727e-01 7.525136e-01
[253,] 0.2298038954 4.596078e-01 7.701961e-01
[254,] 0.2132119791 4.264240e-01 7.867880e-01
[255,] 0.1974780229 3.949560e-01 8.025220e-01
[256,] 0.1817145520 3.634291e-01 8.182854e-01
[257,] 0.1680693231 3.361386e-01 8.319307e-01
[258,] 0.1555630374 3.111261e-01 8.444370e-01
[259,] 0.1459494320 2.918989e-01 8.540506e-01
[260,] 0.1366876875 2.733754e-01 8.633123e-01
[261,] 0.1295042166 2.590084e-01 8.704958e-01
[262,] 0.1207209432 2.414419e-01 8.792791e-01
[263,] 0.1113863634 2.227727e-01 8.886136e-01
[264,] 0.1016804884 2.033610e-01 8.983195e-01
[265,] 0.0917034700 1.834069e-01 9.082965e-01
[266,] 0.0869963825 1.739928e-01 9.130036e-01
[267,] 0.0837441927 1.674884e-01 9.162558e-01
[268,] 0.0818716292 1.637433e-01 9.181284e-01
[269,] 0.0783414979 1.566830e-01 9.216585e-01
[270,] 0.0732312346 1.464625e-01 9.267688e-01
[271,] 0.0692070940 1.384142e-01 9.307929e-01
[272,] 0.0632425341 1.264851e-01 9.367575e-01
[273,] 0.0574063195 1.148126e-01 9.425937e-01
[274,] 0.0505402513 1.010805e-01 9.494597e-01
[275,] 0.0450575854 9.011517e-02 9.549424e-01
[276,] 0.0401210757 8.024215e-02 9.598789e-01
[277,] 0.0351106809 7.022136e-02 9.648893e-01
[278,] 0.0317911964 6.358239e-02 9.682088e-01
[279,] 0.0284971075 5.699422e-02 9.715029e-01
[280,] 0.0257816144 5.156323e-02 9.742184e-01
[281,] 0.0229065878 4.581318e-02 9.770934e-01
[282,] 0.0206382484 4.127650e-02 9.793618e-01
[283,] 0.0166384099 3.327682e-02 9.833616e-01
[284,] 0.0130780387 2.615608e-02 9.869220e-01
[285,] 0.0102428518 2.048570e-02 9.897571e-01
[286,] 0.0078958995 1.579180e-02 9.921041e-01
[287,] 0.0060207331 1.204147e-02 9.939793e-01
[288,] 0.0045610769 9.122154e-03 9.954389e-01
[289,] 0.0034188288 6.837658e-03 9.965812e-01
[290,] 0.0025329454 5.065891e-03 9.974671e-01
[291,] 0.0018495379 3.699076e-03 9.981505e-01
[292,] 0.0013342687 2.668537e-03 9.986657e-01
[293,] 0.0009591962 1.918392e-03 9.990408e-01
[294,] 0.0006758950 1.351790e-03 9.993241e-01
[295,] 0.0004706901 9.413803e-04 9.995293e-01
[296,] 0.0003237508 6.475016e-04 9.996762e-01
[297,] 0.0011417145 2.283429e-03 9.988583e-01
[298,] 0.0039480447 7.896089e-03 9.960520e-01
[299,] 0.0163116121 3.262322e-02 9.836884e-01
[300,] 0.0514235184 1.028470e-01 9.485765e-01
[301,] 0.1353553367 2.707107e-01 8.646447e-01
[302,] 0.3131888107 6.263776e-01 6.868112e-01
[303,] 0.6045383893 7.909232e-01 3.954616e-01
[304,] 0.9071633167 1.856734e-01 9.283668e-02
[305,] 0.9890880912 2.182382e-02 1.091191e-02
[306,] 0.9998823591 2.352817e-04 1.176409e-04
[307,] 0.9999998980 2.040957e-07 1.020478e-07
[308,] 1.0000000000 6.767502e-12 3.383751e-12
[309,] 1.0000000000 1.387793e-12 6.938964e-13
[310,] 1.0000000000 5.710319e-13 2.855160e-13
[311,] 1.0000000000 1.420972e-12 7.104858e-13
[312,] 1.0000000000 2.879773e-12 1.439886e-12
[313,] 1.0000000000 1.996379e-12 9.981897e-13
[314,] 1.0000000000 3.786885e-12 1.893442e-12
[315,] 1.0000000000 1.201861e-11 6.009307e-12
[316,] 1.0000000000 3.688055e-11 1.844027e-11
[317,] 0.9999999999 1.253157e-10 6.265785e-11
[318,] 0.9999999998 4.173305e-10 2.086653e-10
[319,] 0.9999999996 7.931007e-10 3.965504e-10
[320,] 0.9999999990 2.042188e-09 1.021094e-09
[321,] 0.9999999967 6.671870e-09 3.335935e-09
[322,] 0.9999999935 1.290970e-08 6.454848e-09
[323,] 0.9999999933 1.347304e-08 6.736522e-09
[324,] 0.9999999814 3.726277e-08 1.863138e-08
[325,] 0.9999999890 2.190908e-08 1.095454e-08
[326,] 0.9999999772 4.569210e-08 2.284605e-08
[327,] 0.9999999302 1.395425e-07 6.977124e-08
[328,] 0.9999997429 5.142548e-07 2.571274e-07
[329,] 0.9999992717 1.456689e-06 7.283444e-07
[330,] 0.9999975728 4.854355e-06 2.427178e-06
[331,] 0.9999904882 1.902355e-05 9.511775e-06
[332,] 0.9999617310 7.653809e-05 3.826904e-05
[333,] 0.9998654620 2.690759e-04 1.345380e-04
[334,] 0.9998971499 2.057003e-04 1.028501e-04
[335,] 0.9997733630 4.532741e-04 2.266370e-04
[336,] 0.9991589806 1.682039e-03 8.410194e-04
[337,] 0.9963897746 7.220451e-03 3.610225e-03
[338,] 0.9953037555 9.392489e-03 4.696245e-03
[339,] 0.9787022526 4.259549e-02 2.129775e-02
> postscript(file="/var/www/html/rcomp/tmp/1vwe31291066291.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> plot(x[,1], type='l', main='Actuals and Interpolation', ylab='value of Actuals and Interpolation (dots)', xlab='time or index')
> points(x[,1]-mysum$resid)
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/2vwe31291066291.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> plot(mysum$resid, type='b', pch=19, main='Residuals', ylab='value of Residuals', xlab='time or index')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/3oodo1291066291.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> hist(mysum$resid, main='Residual Histogram', xlab='values of Residuals')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/4oodo1291066291.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> densityplot(~mysum$resid,col='black',main='Residual Density Plot', xlab='values of Residuals')
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/5oodo1291066291.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> qqnorm(mysum$resid, main='Residual Normal Q-Q Plot')
> qqline(mysum$resid)
> grid()
> dev.off()
null device
1
> (myerror <- as.ts(mysum$resid))
Time Series:
Start = 1
End = 372
Frequency = 1
1 2 3 4 5
-65.67900831 -29.97578251 -23.80804057 -8.78545993 -27.54675025
6 7 8 9 10
-60.87255670 -37.80158896 -23.95642767 -24.54997606 -40.50804057
11 12 13 14 15
-33.97900831 -19.24675025 -7.72233033 30.28089548 43.44863741
16 17 18 19 20
71.77121806 116.20992773 88.48412128 153.45508903 141.40025032
21 22 23 24 25
126.40670193 157.14863741 113.27766967 122.80992773 151.13434766
26 27 28 29 30
155.53757346 130.00531540 104.12789604 84.46660572 40.54079927
31 32 33 34 35
39.81176701 0.65692830 5.46337991 -22.59468460 -14.56565234
36 37 38 39 40
-11.73339428 -55.20897436 -76.20574855 -75.43800662 -75.01542597
41 42 43 44 45
-71.27671629 -107.80252275 -91.03155500 -86.48639371 -61.37994210
46 47 48 49 50
-59.13800662 -57.60897436 -79.47671629 -100.75229637 -102.44907057
51 52 53 54 55
-113.98132863 -91.65874799 -76.52003831 -124.24584476 -96.17487702
56 57 58 59 60
-81.72971573 -83.62326412 -92.98132863 -103.65229637 -111.02003831
61 62 63 64 65
-119.79561839 -146.49239258 -137.82465065 -105.30207000 -107.56336032
66 67 68 69 70
-160.68916678 -140.11819903 -128.77303774 -100.96658613 -90.22465065
71 72 73 74 75
-67.79561839 -35.56336032 16.66105960 48.96428540 76.63202734
76 77 78 79 80
96.45460798 98.19331766 27.76751121 50.33847895 60.58364024
81 82 83 84 85
73.99009185 39.03202734 35.56105960 22.49331766 21.01773758
86 87 88 89 90
1.12096339 -3.81129468 21.61128597 -5.05000435 -57.47581080
91 92 93 94 95
-57.80484306 -39.25968177 -41.95323016 -31.91129468 -28.78226242
96 97 98 99 100
-24.75000435 -45.72558443 -53.02235863 -30.45461669 -30.03203605
101 102 103 104 105
-0.59332637 -35.31913282 -32.04816508 -52.60300379 -54.89655217
106 107 108 109 110
-57.65461669 -28.92558443 -25.29332637 -38.16890645 -60.16568064
111 112 113 114 115
-64.19793871 -44.77535806 -23.43664838 -46.56245483 -52.59148709
116 117 118 119 120
-53.14632580 -38.33987419 -26.69793871 17.43109355 35.46335162
121 122 123 124 125
81.18777154 136.49099734 162.65873928 192.48131993 189.82002960
126 127 128 129 130
156.19422315 166.46519089 148.51035218 110.71680380 95.35873928
131 132 133 134 135
76.78777154 102.62002960 96.14444952 88.24767533 70.51541727
136 137 138 139 140
35.43799791 32.87670759 5.45090114 10.72186888 16.06703017
141 142 143 144 145
17.97348178 37.01541727 55.44444952 41.47670759 33.80112751
146 147 148 149 150
0.60435332 50.67209525 33.89467590 31.73338557 38.20757912
151 152 153 154 155
32.17854686 46.02370815 23.53015977 61.17209525 82.10112751
156 157 158 159 160
129.93338557 148.95780549 170.96103130 170.12877324 155.45135388
161 162 163 164 165
154.39006356 145.86425711 133.43522485 112.48038614 88.98683775
166 167 168 169 170
87.32877324 73.05780549 80.59006356 71.11448348 47.21770929
171 172 173 174 175
53.68545122 46.60803187 76.04674154 30.02093509 13.79190283
176 177 178 179 180
46.23706412 24.64351574 17.98545122 45.11448348 46.04674154
181 182 183 184 185
65.27116146 79.67438727 59.14212921 53.16470985 69.30341953
186 187 188 189 190
57.07761308 38.44858082 31.09374211 19.70019372 27.54212921
191 192 193 194 195
51.87116146 42.40341953 47.92783945 32.33106526 30.99880719
196 197 198 199 200
30.52138784 20.76009751 40.53429106 -14.49474120 4.25042009
201 202 203 204 205
-7.54312829 1.49880719 -8.57216055 -1.93990249 -16.21548256
206 207 208 209 210
-3.01225676 -28.04451482 -9.82193418 -17.08322450 -5.50903095
211 212 213 214 215
-45.53806321 -40.79290192 -55.98645031 -53.84451482 -58.01548256
216 217 218 219 220
-70.48322450 -92.35880458 -115.75557877 -105.38783684 -92.46525619
221 222 223 224 225
-65.62654652 -58.45235297 -89.88138522 -81.63622393 -96.32977232
226 227 228 229 230
-84.68783684 -95.35880458 -89.22654652 -107.30212659 -114.69890079
231 232 233 234 235
-115.43115885 -105.50857821 -105.56986853 -61.29567498 -76.42470724
236 237 238 239 240
-75.97954595 -63.57309434 -42.43115885 -69.40212659 -90.16986853
241 242 243 244 245
-122.24544861 -110.84222280 -124.37448087 -129.25190022 -127.41319054
246 247 248 249 250
-69.03899700 -86.06802925 -99.42286796 -98.81641635 -93.07448087
251 252 253 254 255
-108.54544861 -126.81319054 -148.58877062 -153.68554482 -149.01780288
256 257 258 259 260
-130.59522224 -134.25651256 -97.98231901 -96.01135127 -96.06618998
261 262 263 264 265
-70.15973837 -66.51780288 -101.58877062 -112.35651256 -101.93209264
266 267 268 269 270
-73.02886683 -56.86112490 -36.03854425 -32.29983457 23.47435897
271 272 273 274 275
30.34532672 32.49048801 56.79693962 68.93887510 81.66790736
276 277 278 279 280
82.10016543 92.42458535 85.32781115 80.89555309 71.71813373
281 282 283 284 285
62.25684341 99.13103696 105.90200470 110.14716599 105.15361760
286 287 288 289 290
93.59555309 96.02458535 81.55684341 89.28126333 75.88448914
291 292 293 294 295
78.45223107 65.57481172 50.81352140 86.28771494 83.75868269
296 297 298 299 300
83.30384398 80.51029559 77.15223107 34.68126333 17.21352140
301 302 303 304 305
5.63794132 12.74116712 1.70890906 6.83148970 -10.12980062
306 307 308 309 310
21.94439293 15.01536067 11.96052196 24.76697358 0.00890906
311 312 313 314 315
7.23794132 4.97019938 -188.22658178 -184.92335597 -201.15561404
316 317 318 319 320
-207.63303339 -202.79432371 -151.92013016 -141.14916242 -147.50400113
321 322 323 324 325
-98.69754952 -99.05561404 -57.02658178 -17.39432371 122.53009621
326 327 328 329 330
125.53332201 152.80106395 137.82364460 138.66235427 160.53654782
331 332 333 334 335
147.30751556 127.15267685 126.85912847 114.50106395 91.13009621
336 337 338 339 340
85.06235427 115.48677419 91.49000000 62.95774194 38.38032258
341 342 343 344 345
0.31903226 62.69322581 77.66419355 83.30935484 70.81580645
346 347 348 349 350
66.95774194 71.08677419 61.31903226 76.44345218 92.64667799
351 352 353 354 355
59.61441992 -0.26299943 -21.42428976 36.04990379 7.62087153
356 357 358 359 360
20.36603282 5.47248444 -0.68558008 -10.25654782 -59.32428976
361 362 363 364 365
-25.09986984 -50.79664403 -54.52890209 -94.70632145 -97.26761177
366 367 368 369 370
-83.09341822 -49.12245048 -68.67728919 -64.97083758 -83.22890209
371 372
-88.39986984 -81.26761177
> postscript(file="/var/www/html/rcomp/tmp/6m0kx1291066291.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> dum <- cbind(lag(myerror,k=1),myerror)
> dum
Time Series:
Start = 0
End = 372
Frequency = 1
lag(myerror, k = 1) myerror
0 -65.67900831 NA
1 -29.97578251 -65.67900831
2 -23.80804057 -29.97578251
3 -8.78545993 -23.80804057
4 -27.54675025 -8.78545993
5 -60.87255670 -27.54675025
6 -37.80158896 -60.87255670
7 -23.95642767 -37.80158896
8 -24.54997606 -23.95642767
9 -40.50804057 -24.54997606
10 -33.97900831 -40.50804057
11 -19.24675025 -33.97900831
12 -7.72233033 -19.24675025
13 30.28089548 -7.72233033
14 43.44863741 30.28089548
15 71.77121806 43.44863741
16 116.20992773 71.77121806
17 88.48412128 116.20992773
18 153.45508903 88.48412128
19 141.40025032 153.45508903
20 126.40670193 141.40025032
21 157.14863741 126.40670193
22 113.27766967 157.14863741
23 122.80992773 113.27766967
24 151.13434766 122.80992773
25 155.53757346 151.13434766
26 130.00531540 155.53757346
27 104.12789604 130.00531540
28 84.46660572 104.12789604
29 40.54079927 84.46660572
30 39.81176701 40.54079927
31 0.65692830 39.81176701
32 5.46337991 0.65692830
33 -22.59468460 5.46337991
34 -14.56565234 -22.59468460
35 -11.73339428 -14.56565234
36 -55.20897436 -11.73339428
37 -76.20574855 -55.20897436
38 -75.43800662 -76.20574855
39 -75.01542597 -75.43800662
40 -71.27671629 -75.01542597
41 -107.80252275 -71.27671629
42 -91.03155500 -107.80252275
43 -86.48639371 -91.03155500
44 -61.37994210 -86.48639371
45 -59.13800662 -61.37994210
46 -57.60897436 -59.13800662
47 -79.47671629 -57.60897436
48 -100.75229637 -79.47671629
49 -102.44907057 -100.75229637
50 -113.98132863 -102.44907057
51 -91.65874799 -113.98132863
52 -76.52003831 -91.65874799
53 -124.24584476 -76.52003831
54 -96.17487702 -124.24584476
55 -81.72971573 -96.17487702
56 -83.62326412 -81.72971573
57 -92.98132863 -83.62326412
58 -103.65229637 -92.98132863
59 -111.02003831 -103.65229637
60 -119.79561839 -111.02003831
61 -146.49239258 -119.79561839
62 -137.82465065 -146.49239258
63 -105.30207000 -137.82465065
64 -107.56336032 -105.30207000
65 -160.68916678 -107.56336032
66 -140.11819903 -160.68916678
67 -128.77303774 -140.11819903
68 -100.96658613 -128.77303774
69 -90.22465065 -100.96658613
70 -67.79561839 -90.22465065
71 -35.56336032 -67.79561839
72 16.66105960 -35.56336032
73 48.96428540 16.66105960
74 76.63202734 48.96428540
75 96.45460798 76.63202734
76 98.19331766 96.45460798
77 27.76751121 98.19331766
78 50.33847895 27.76751121
79 60.58364024 50.33847895
80 73.99009185 60.58364024
81 39.03202734 73.99009185
82 35.56105960 39.03202734
83 22.49331766 35.56105960
84 21.01773758 22.49331766
85 1.12096339 21.01773758
86 -3.81129468 1.12096339
87 21.61128597 -3.81129468
88 -5.05000435 21.61128597
89 -57.47581080 -5.05000435
90 -57.80484306 -57.47581080
91 -39.25968177 -57.80484306
92 -41.95323016 -39.25968177
93 -31.91129468 -41.95323016
94 -28.78226242 -31.91129468
95 -24.75000435 -28.78226242
96 -45.72558443 -24.75000435
97 -53.02235863 -45.72558443
98 -30.45461669 -53.02235863
99 -30.03203605 -30.45461669
100 -0.59332637 -30.03203605
101 -35.31913282 -0.59332637
102 -32.04816508 -35.31913282
103 -52.60300379 -32.04816508
104 -54.89655217 -52.60300379
105 -57.65461669 -54.89655217
106 -28.92558443 -57.65461669
107 -25.29332637 -28.92558443
108 -38.16890645 -25.29332637
109 -60.16568064 -38.16890645
110 -64.19793871 -60.16568064
111 -44.77535806 -64.19793871
112 -23.43664838 -44.77535806
113 -46.56245483 -23.43664838
114 -52.59148709 -46.56245483
115 -53.14632580 -52.59148709
116 -38.33987419 -53.14632580
117 -26.69793871 -38.33987419
118 17.43109355 -26.69793871
119 35.46335162 17.43109355
120 81.18777154 35.46335162
121 136.49099734 81.18777154
122 162.65873928 136.49099734
123 192.48131993 162.65873928
124 189.82002960 192.48131993
125 156.19422315 189.82002960
126 166.46519089 156.19422315
127 148.51035218 166.46519089
128 110.71680380 148.51035218
129 95.35873928 110.71680380
130 76.78777154 95.35873928
131 102.62002960 76.78777154
132 96.14444952 102.62002960
133 88.24767533 96.14444952
134 70.51541727 88.24767533
135 35.43799791 70.51541727
136 32.87670759 35.43799791
137 5.45090114 32.87670759
138 10.72186888 5.45090114
139 16.06703017 10.72186888
140 17.97348178 16.06703017
141 37.01541727 17.97348178
142 55.44444952 37.01541727
143 41.47670759 55.44444952
144 33.80112751 41.47670759
145 0.60435332 33.80112751
146 50.67209525 0.60435332
147 33.89467590 50.67209525
148 31.73338557 33.89467590
149 38.20757912 31.73338557
150 32.17854686 38.20757912
151 46.02370815 32.17854686
152 23.53015977 46.02370815
153 61.17209525 23.53015977
154 82.10112751 61.17209525
155 129.93338557 82.10112751
156 148.95780549 129.93338557
157 170.96103130 148.95780549
158 170.12877324 170.96103130
159 155.45135388 170.12877324
160 154.39006356 155.45135388
161 145.86425711 154.39006356
162 133.43522485 145.86425711
163 112.48038614 133.43522485
164 88.98683775 112.48038614
165 87.32877324 88.98683775
166 73.05780549 87.32877324
167 80.59006356 73.05780549
168 71.11448348 80.59006356
169 47.21770929 71.11448348
170 53.68545122 47.21770929
171 46.60803187 53.68545122
172 76.04674154 46.60803187
173 30.02093509 76.04674154
174 13.79190283 30.02093509
175 46.23706412 13.79190283
176 24.64351574 46.23706412
177 17.98545122 24.64351574
178 45.11448348 17.98545122
179 46.04674154 45.11448348
180 65.27116146 46.04674154
181 79.67438727 65.27116146
182 59.14212921 79.67438727
183 53.16470985 59.14212921
184 69.30341953 53.16470985
185 57.07761308 69.30341953
186 38.44858082 57.07761308
187 31.09374211 38.44858082
188 19.70019372 31.09374211
189 27.54212921 19.70019372
190 51.87116146 27.54212921
191 42.40341953 51.87116146
192 47.92783945 42.40341953
193 32.33106526 47.92783945
194 30.99880719 32.33106526
195 30.52138784 30.99880719
196 20.76009751 30.52138784
197 40.53429106 20.76009751
198 -14.49474120 40.53429106
199 4.25042009 -14.49474120
200 -7.54312829 4.25042009
201 1.49880719 -7.54312829
202 -8.57216055 1.49880719
203 -1.93990249 -8.57216055
204 -16.21548256 -1.93990249
205 -3.01225676 -16.21548256
206 -28.04451482 -3.01225676
207 -9.82193418 -28.04451482
208 -17.08322450 -9.82193418
209 -5.50903095 -17.08322450
210 -45.53806321 -5.50903095
211 -40.79290192 -45.53806321
212 -55.98645031 -40.79290192
213 -53.84451482 -55.98645031
214 -58.01548256 -53.84451482
215 -70.48322450 -58.01548256
216 -92.35880458 -70.48322450
217 -115.75557877 -92.35880458
218 -105.38783684 -115.75557877
219 -92.46525619 -105.38783684
220 -65.62654652 -92.46525619
221 -58.45235297 -65.62654652
222 -89.88138522 -58.45235297
223 -81.63622393 -89.88138522
224 -96.32977232 -81.63622393
225 -84.68783684 -96.32977232
226 -95.35880458 -84.68783684
227 -89.22654652 -95.35880458
228 -107.30212659 -89.22654652
229 -114.69890079 -107.30212659
230 -115.43115885 -114.69890079
231 -105.50857821 -115.43115885
232 -105.56986853 -105.50857821
233 -61.29567498 -105.56986853
234 -76.42470724 -61.29567498
235 -75.97954595 -76.42470724
236 -63.57309434 -75.97954595
237 -42.43115885 -63.57309434
238 -69.40212659 -42.43115885
239 -90.16986853 -69.40212659
240 -122.24544861 -90.16986853
241 -110.84222280 -122.24544861
242 -124.37448087 -110.84222280
243 -129.25190022 -124.37448087
244 -127.41319054 -129.25190022
245 -69.03899700 -127.41319054
246 -86.06802925 -69.03899700
247 -99.42286796 -86.06802925
248 -98.81641635 -99.42286796
249 -93.07448087 -98.81641635
250 -108.54544861 -93.07448087
251 -126.81319054 -108.54544861
252 -148.58877062 -126.81319054
253 -153.68554482 -148.58877062
254 -149.01780288 -153.68554482
255 -130.59522224 -149.01780288
256 -134.25651256 -130.59522224
257 -97.98231901 -134.25651256
258 -96.01135127 -97.98231901
259 -96.06618998 -96.01135127
260 -70.15973837 -96.06618998
261 -66.51780288 -70.15973837
262 -101.58877062 -66.51780288
263 -112.35651256 -101.58877062
264 -101.93209264 -112.35651256
265 -73.02886683 -101.93209264
266 -56.86112490 -73.02886683
267 -36.03854425 -56.86112490
268 -32.29983457 -36.03854425
269 23.47435897 -32.29983457
270 30.34532672 23.47435897
271 32.49048801 30.34532672
272 56.79693962 32.49048801
273 68.93887510 56.79693962
274 81.66790736 68.93887510
275 82.10016543 81.66790736
276 92.42458535 82.10016543
277 85.32781115 92.42458535
278 80.89555309 85.32781115
279 71.71813373 80.89555309
280 62.25684341 71.71813373
281 99.13103696 62.25684341
282 105.90200470 99.13103696
283 110.14716599 105.90200470
284 105.15361760 110.14716599
285 93.59555309 105.15361760
286 96.02458535 93.59555309
287 81.55684341 96.02458535
288 89.28126333 81.55684341
289 75.88448914 89.28126333
290 78.45223107 75.88448914
291 65.57481172 78.45223107
292 50.81352140 65.57481172
293 86.28771494 50.81352140
294 83.75868269 86.28771494
295 83.30384398 83.75868269
296 80.51029559 83.30384398
297 77.15223107 80.51029559
298 34.68126333 77.15223107
299 17.21352140 34.68126333
300 5.63794132 17.21352140
301 12.74116712 5.63794132
302 1.70890906 12.74116712
303 6.83148970 1.70890906
304 -10.12980062 6.83148970
305 21.94439293 -10.12980062
306 15.01536067 21.94439293
307 11.96052196 15.01536067
308 24.76697358 11.96052196
309 0.00890906 24.76697358
310 7.23794132 0.00890906
311 4.97019938 7.23794132
312 -188.22658178 4.97019938
313 -184.92335597 -188.22658178
314 -201.15561404 -184.92335597
315 -207.63303339 -201.15561404
316 -202.79432371 -207.63303339
317 -151.92013016 -202.79432371
318 -141.14916242 -151.92013016
319 -147.50400113 -141.14916242
320 -98.69754952 -147.50400113
321 -99.05561404 -98.69754952
322 -57.02658178 -99.05561404
323 -17.39432371 -57.02658178
324 122.53009621 -17.39432371
325 125.53332201 122.53009621
326 152.80106395 125.53332201
327 137.82364460 152.80106395
328 138.66235427 137.82364460
329 160.53654782 138.66235427
330 147.30751556 160.53654782
331 127.15267685 147.30751556
332 126.85912847 127.15267685
333 114.50106395 126.85912847
334 91.13009621 114.50106395
335 85.06235427 91.13009621
336 115.48677419 85.06235427
337 91.49000000 115.48677419
338 62.95774194 91.49000000
339 38.38032258 62.95774194
340 0.31903226 38.38032258
341 62.69322581 0.31903226
342 77.66419355 62.69322581
343 83.30935484 77.66419355
344 70.81580645 83.30935484
345 66.95774194 70.81580645
346 71.08677419 66.95774194
347 61.31903226 71.08677419
348 76.44345218 61.31903226
349 92.64667799 76.44345218
350 59.61441992 92.64667799
351 -0.26299943 59.61441992
352 -21.42428976 -0.26299943
353 36.04990379 -21.42428976
354 7.62087153 36.04990379
355 20.36603282 7.62087153
356 5.47248444 20.36603282
357 -0.68558008 5.47248444
358 -10.25654782 -0.68558008
359 -59.32428976 -10.25654782
360 -25.09986984 -59.32428976
361 -50.79664403 -25.09986984
362 -54.52890209 -50.79664403
363 -94.70632145 -54.52890209
364 -97.26761177 -94.70632145
365 -83.09341822 -97.26761177
366 -49.12245048 -83.09341822
367 -68.67728919 -49.12245048
368 -64.97083758 -68.67728919
369 -83.22890209 -64.97083758
370 -88.39986984 -83.22890209
371 -81.26761177 -88.39986984
372 NA -81.26761177
> dum1 <- dum[2:length(myerror),]
> dum1
lag(myerror, k = 1) myerror
[1,] -29.97578251 -65.67900831
[2,] -23.80804057 -29.97578251
[3,] -8.78545993 -23.80804057
[4,] -27.54675025 -8.78545993
[5,] -60.87255670 -27.54675025
[6,] -37.80158896 -60.87255670
[7,] -23.95642767 -37.80158896
[8,] -24.54997606 -23.95642767
[9,] -40.50804057 -24.54997606
[10,] -33.97900831 -40.50804057
[11,] -19.24675025 -33.97900831
[12,] -7.72233033 -19.24675025
[13,] 30.28089548 -7.72233033
[14,] 43.44863741 30.28089548
[15,] 71.77121806 43.44863741
[16,] 116.20992773 71.77121806
[17,] 88.48412128 116.20992773
[18,] 153.45508903 88.48412128
[19,] 141.40025032 153.45508903
[20,] 126.40670193 141.40025032
[21,] 157.14863741 126.40670193
[22,] 113.27766967 157.14863741
[23,] 122.80992773 113.27766967
[24,] 151.13434766 122.80992773
[25,] 155.53757346 151.13434766
[26,] 130.00531540 155.53757346
[27,] 104.12789604 130.00531540
[28,] 84.46660572 104.12789604
[29,] 40.54079927 84.46660572
[30,] 39.81176701 40.54079927
[31,] 0.65692830 39.81176701
[32,] 5.46337991 0.65692830
[33,] -22.59468460 5.46337991
[34,] -14.56565234 -22.59468460
[35,] -11.73339428 -14.56565234
[36,] -55.20897436 -11.73339428
[37,] -76.20574855 -55.20897436
[38,] -75.43800662 -76.20574855
[39,] -75.01542597 -75.43800662
[40,] -71.27671629 -75.01542597
[41,] -107.80252275 -71.27671629
[42,] -91.03155500 -107.80252275
[43,] -86.48639371 -91.03155500
[44,] -61.37994210 -86.48639371
[45,] -59.13800662 -61.37994210
[46,] -57.60897436 -59.13800662
[47,] -79.47671629 -57.60897436
[48,] -100.75229637 -79.47671629
[49,] -102.44907057 -100.75229637
[50,] -113.98132863 -102.44907057
[51,] -91.65874799 -113.98132863
[52,] -76.52003831 -91.65874799
[53,] -124.24584476 -76.52003831
[54,] -96.17487702 -124.24584476
[55,] -81.72971573 -96.17487702
[56,] -83.62326412 -81.72971573
[57,] -92.98132863 -83.62326412
[58,] -103.65229637 -92.98132863
[59,] -111.02003831 -103.65229637
[60,] -119.79561839 -111.02003831
[61,] -146.49239258 -119.79561839
[62,] -137.82465065 -146.49239258
[63,] -105.30207000 -137.82465065
[64,] -107.56336032 -105.30207000
[65,] -160.68916678 -107.56336032
[66,] -140.11819903 -160.68916678
[67,] -128.77303774 -140.11819903
[68,] -100.96658613 -128.77303774
[69,] -90.22465065 -100.96658613
[70,] -67.79561839 -90.22465065
[71,] -35.56336032 -67.79561839
[72,] 16.66105960 -35.56336032
[73,] 48.96428540 16.66105960
[74,] 76.63202734 48.96428540
[75,] 96.45460798 76.63202734
[76,] 98.19331766 96.45460798
[77,] 27.76751121 98.19331766
[78,] 50.33847895 27.76751121
[79,] 60.58364024 50.33847895
[80,] 73.99009185 60.58364024
[81,] 39.03202734 73.99009185
[82,] 35.56105960 39.03202734
[83,] 22.49331766 35.56105960
[84,] 21.01773758 22.49331766
[85,] 1.12096339 21.01773758
[86,] -3.81129468 1.12096339
[87,] 21.61128597 -3.81129468
[88,] -5.05000435 21.61128597
[89,] -57.47581080 -5.05000435
[90,] -57.80484306 -57.47581080
[91,] -39.25968177 -57.80484306
[92,] -41.95323016 -39.25968177
[93,] -31.91129468 -41.95323016
[94,] -28.78226242 -31.91129468
[95,] -24.75000435 -28.78226242
[96,] -45.72558443 -24.75000435
[97,] -53.02235863 -45.72558443
[98,] -30.45461669 -53.02235863
[99,] -30.03203605 -30.45461669
[100,] -0.59332637 -30.03203605
[101,] -35.31913282 -0.59332637
[102,] -32.04816508 -35.31913282
[103,] -52.60300379 -32.04816508
[104,] -54.89655217 -52.60300379
[105,] -57.65461669 -54.89655217
[106,] -28.92558443 -57.65461669
[107,] -25.29332637 -28.92558443
[108,] -38.16890645 -25.29332637
[109,] -60.16568064 -38.16890645
[110,] -64.19793871 -60.16568064
[111,] -44.77535806 -64.19793871
[112,] -23.43664838 -44.77535806
[113,] -46.56245483 -23.43664838
[114,] -52.59148709 -46.56245483
[115,] -53.14632580 -52.59148709
[116,] -38.33987419 -53.14632580
[117,] -26.69793871 -38.33987419
[118,] 17.43109355 -26.69793871
[119,] 35.46335162 17.43109355
[120,] 81.18777154 35.46335162
[121,] 136.49099734 81.18777154
[122,] 162.65873928 136.49099734
[123,] 192.48131993 162.65873928
[124,] 189.82002960 192.48131993
[125,] 156.19422315 189.82002960
[126,] 166.46519089 156.19422315
[127,] 148.51035218 166.46519089
[128,] 110.71680380 148.51035218
[129,] 95.35873928 110.71680380
[130,] 76.78777154 95.35873928
[131,] 102.62002960 76.78777154
[132,] 96.14444952 102.62002960
[133,] 88.24767533 96.14444952
[134,] 70.51541727 88.24767533
[135,] 35.43799791 70.51541727
[136,] 32.87670759 35.43799791
[137,] 5.45090114 32.87670759
[138,] 10.72186888 5.45090114
[139,] 16.06703017 10.72186888
[140,] 17.97348178 16.06703017
[141,] 37.01541727 17.97348178
[142,] 55.44444952 37.01541727
[143,] 41.47670759 55.44444952
[144,] 33.80112751 41.47670759
[145,] 0.60435332 33.80112751
[146,] 50.67209525 0.60435332
[147,] 33.89467590 50.67209525
[148,] 31.73338557 33.89467590
[149,] 38.20757912 31.73338557
[150,] 32.17854686 38.20757912
[151,] 46.02370815 32.17854686
[152,] 23.53015977 46.02370815
[153,] 61.17209525 23.53015977
[154,] 82.10112751 61.17209525
[155,] 129.93338557 82.10112751
[156,] 148.95780549 129.93338557
[157,] 170.96103130 148.95780549
[158,] 170.12877324 170.96103130
[159,] 155.45135388 170.12877324
[160,] 154.39006356 155.45135388
[161,] 145.86425711 154.39006356
[162,] 133.43522485 145.86425711
[163,] 112.48038614 133.43522485
[164,] 88.98683775 112.48038614
[165,] 87.32877324 88.98683775
[166,] 73.05780549 87.32877324
[167,] 80.59006356 73.05780549
[168,] 71.11448348 80.59006356
[169,] 47.21770929 71.11448348
[170,] 53.68545122 47.21770929
[171,] 46.60803187 53.68545122
[172,] 76.04674154 46.60803187
[173,] 30.02093509 76.04674154
[174,] 13.79190283 30.02093509
[175,] 46.23706412 13.79190283
[176,] 24.64351574 46.23706412
[177,] 17.98545122 24.64351574
[178,] 45.11448348 17.98545122
[179,] 46.04674154 45.11448348
[180,] 65.27116146 46.04674154
[181,] 79.67438727 65.27116146
[182,] 59.14212921 79.67438727
[183,] 53.16470985 59.14212921
[184,] 69.30341953 53.16470985
[185,] 57.07761308 69.30341953
[186,] 38.44858082 57.07761308
[187,] 31.09374211 38.44858082
[188,] 19.70019372 31.09374211
[189,] 27.54212921 19.70019372
[190,] 51.87116146 27.54212921
[191,] 42.40341953 51.87116146
[192,] 47.92783945 42.40341953
[193,] 32.33106526 47.92783945
[194,] 30.99880719 32.33106526
[195,] 30.52138784 30.99880719
[196,] 20.76009751 30.52138784
[197,] 40.53429106 20.76009751
[198,] -14.49474120 40.53429106
[199,] 4.25042009 -14.49474120
[200,] -7.54312829 4.25042009
[201,] 1.49880719 -7.54312829
[202,] -8.57216055 1.49880719
[203,] -1.93990249 -8.57216055
[204,] -16.21548256 -1.93990249
[205,] -3.01225676 -16.21548256
[206,] -28.04451482 -3.01225676
[207,] -9.82193418 -28.04451482
[208,] -17.08322450 -9.82193418
[209,] -5.50903095 -17.08322450
[210,] -45.53806321 -5.50903095
[211,] -40.79290192 -45.53806321
[212,] -55.98645031 -40.79290192
[213,] -53.84451482 -55.98645031
[214,] -58.01548256 -53.84451482
[215,] -70.48322450 -58.01548256
[216,] -92.35880458 -70.48322450
[217,] -115.75557877 -92.35880458
[218,] -105.38783684 -115.75557877
[219,] -92.46525619 -105.38783684
[220,] -65.62654652 -92.46525619
[221,] -58.45235297 -65.62654652
[222,] -89.88138522 -58.45235297
[223,] -81.63622393 -89.88138522
[224,] -96.32977232 -81.63622393
[225,] -84.68783684 -96.32977232
[226,] -95.35880458 -84.68783684
[227,] -89.22654652 -95.35880458
[228,] -107.30212659 -89.22654652
[229,] -114.69890079 -107.30212659
[230,] -115.43115885 -114.69890079
[231,] -105.50857821 -115.43115885
[232,] -105.56986853 -105.50857821
[233,] -61.29567498 -105.56986853
[234,] -76.42470724 -61.29567498
[235,] -75.97954595 -76.42470724
[236,] -63.57309434 -75.97954595
[237,] -42.43115885 -63.57309434
[238,] -69.40212659 -42.43115885
[239,] -90.16986853 -69.40212659
[240,] -122.24544861 -90.16986853
[241,] -110.84222280 -122.24544861
[242,] -124.37448087 -110.84222280
[243,] -129.25190022 -124.37448087
[244,] -127.41319054 -129.25190022
[245,] -69.03899700 -127.41319054
[246,] -86.06802925 -69.03899700
[247,] -99.42286796 -86.06802925
[248,] -98.81641635 -99.42286796
[249,] -93.07448087 -98.81641635
[250,] -108.54544861 -93.07448087
[251,] -126.81319054 -108.54544861
[252,] -148.58877062 -126.81319054
[253,] -153.68554482 -148.58877062
[254,] -149.01780288 -153.68554482
[255,] -130.59522224 -149.01780288
[256,] -134.25651256 -130.59522224
[257,] -97.98231901 -134.25651256
[258,] -96.01135127 -97.98231901
[259,] -96.06618998 -96.01135127
[260,] -70.15973837 -96.06618998
[261,] -66.51780288 -70.15973837
[262,] -101.58877062 -66.51780288
[263,] -112.35651256 -101.58877062
[264,] -101.93209264 -112.35651256
[265,] -73.02886683 -101.93209264
[266,] -56.86112490 -73.02886683
[267,] -36.03854425 -56.86112490
[268,] -32.29983457 -36.03854425
[269,] 23.47435897 -32.29983457
[270,] 30.34532672 23.47435897
[271,] 32.49048801 30.34532672
[272,] 56.79693962 32.49048801
[273,] 68.93887510 56.79693962
[274,] 81.66790736 68.93887510
[275,] 82.10016543 81.66790736
[276,] 92.42458535 82.10016543
[277,] 85.32781115 92.42458535
[278,] 80.89555309 85.32781115
[279,] 71.71813373 80.89555309
[280,] 62.25684341 71.71813373
[281,] 99.13103696 62.25684341
[282,] 105.90200470 99.13103696
[283,] 110.14716599 105.90200470
[284,] 105.15361760 110.14716599
[285,] 93.59555309 105.15361760
[286,] 96.02458535 93.59555309
[287,] 81.55684341 96.02458535
[288,] 89.28126333 81.55684341
[289,] 75.88448914 89.28126333
[290,] 78.45223107 75.88448914
[291,] 65.57481172 78.45223107
[292,] 50.81352140 65.57481172
[293,] 86.28771494 50.81352140
[294,] 83.75868269 86.28771494
[295,] 83.30384398 83.75868269
[296,] 80.51029559 83.30384398
[297,] 77.15223107 80.51029559
[298,] 34.68126333 77.15223107
[299,] 17.21352140 34.68126333
[300,] 5.63794132 17.21352140
[301,] 12.74116712 5.63794132
[302,] 1.70890906 12.74116712
[303,] 6.83148970 1.70890906
[304,] -10.12980062 6.83148970
[305,] 21.94439293 -10.12980062
[306,] 15.01536067 21.94439293
[307,] 11.96052196 15.01536067
[308,] 24.76697358 11.96052196
[309,] 0.00890906 24.76697358
[310,] 7.23794132 0.00890906
[311,] 4.97019938 7.23794132
[312,] -188.22658178 4.97019938
[313,] -184.92335597 -188.22658178
[314,] -201.15561404 -184.92335597
[315,] -207.63303339 -201.15561404
[316,] -202.79432371 -207.63303339
[317,] -151.92013016 -202.79432371
[318,] -141.14916242 -151.92013016
[319,] -147.50400113 -141.14916242
[320,] -98.69754952 -147.50400113
[321,] -99.05561404 -98.69754952
[322,] -57.02658178 -99.05561404
[323,] -17.39432371 -57.02658178
[324,] 122.53009621 -17.39432371
[325,] 125.53332201 122.53009621
[326,] 152.80106395 125.53332201
[327,] 137.82364460 152.80106395
[328,] 138.66235427 137.82364460
[329,] 160.53654782 138.66235427
[330,] 147.30751556 160.53654782
[331,] 127.15267685 147.30751556
[332,] 126.85912847 127.15267685
[333,] 114.50106395 126.85912847
[334,] 91.13009621 114.50106395
[335,] 85.06235427 91.13009621
[336,] 115.48677419 85.06235427
[337,] 91.49000000 115.48677419
[338,] 62.95774194 91.49000000
[339,] 38.38032258 62.95774194
[340,] 0.31903226 38.38032258
[341,] 62.69322581 0.31903226
[342,] 77.66419355 62.69322581
[343,] 83.30935484 77.66419355
[344,] 70.81580645 83.30935484
[345,] 66.95774194 70.81580645
[346,] 71.08677419 66.95774194
[347,] 61.31903226 71.08677419
[348,] 76.44345218 61.31903226
[349,] 92.64667799 76.44345218
[350,] 59.61441992 92.64667799
[351,] -0.26299943 59.61441992
[352,] -21.42428976 -0.26299943
[353,] 36.04990379 -21.42428976
[354,] 7.62087153 36.04990379
[355,] 20.36603282 7.62087153
[356,] 5.47248444 20.36603282
[357,] -0.68558008 5.47248444
[358,] -10.25654782 -0.68558008
[359,] -59.32428976 -10.25654782
[360,] -25.09986984 -59.32428976
[361,] -50.79664403 -25.09986984
[362,] -54.52890209 -50.79664403
[363,] -94.70632145 -54.52890209
[364,] -97.26761177 -94.70632145
[365,] -83.09341822 -97.26761177
[366,] -49.12245048 -83.09341822
[367,] -68.67728919 -49.12245048
[368,] -64.97083758 -68.67728919
[369,] -83.22890209 -64.97083758
[370,] -88.39986984 -83.22890209
[371,] -81.26761177 -88.39986984
> z <- as.data.frame(dum1)
> z
lag(myerror, k = 1) myerror
1 -29.97578251 -65.67900831
2 -23.80804057 -29.97578251
3 -8.78545993 -23.80804057
4 -27.54675025 -8.78545993
5 -60.87255670 -27.54675025
6 -37.80158896 -60.87255670
7 -23.95642767 -37.80158896
8 -24.54997606 -23.95642767
9 -40.50804057 -24.54997606
10 -33.97900831 -40.50804057
11 -19.24675025 -33.97900831
12 -7.72233033 -19.24675025
13 30.28089548 -7.72233033
14 43.44863741 30.28089548
15 71.77121806 43.44863741
16 116.20992773 71.77121806
17 88.48412128 116.20992773
18 153.45508903 88.48412128
19 141.40025032 153.45508903
20 126.40670193 141.40025032
21 157.14863741 126.40670193
22 113.27766967 157.14863741
23 122.80992773 113.27766967
24 151.13434766 122.80992773
25 155.53757346 151.13434766
26 130.00531540 155.53757346
27 104.12789604 130.00531540
28 84.46660572 104.12789604
29 40.54079927 84.46660572
30 39.81176701 40.54079927
31 0.65692830 39.81176701
32 5.46337991 0.65692830
33 -22.59468460 5.46337991
34 -14.56565234 -22.59468460
35 -11.73339428 -14.56565234
36 -55.20897436 -11.73339428
37 -76.20574855 -55.20897436
38 -75.43800662 -76.20574855
39 -75.01542597 -75.43800662
40 -71.27671629 -75.01542597
41 -107.80252275 -71.27671629
42 -91.03155500 -107.80252275
43 -86.48639371 -91.03155500
44 -61.37994210 -86.48639371
45 -59.13800662 -61.37994210
46 -57.60897436 -59.13800662
47 -79.47671629 -57.60897436
48 -100.75229637 -79.47671629
49 -102.44907057 -100.75229637
50 -113.98132863 -102.44907057
51 -91.65874799 -113.98132863
52 -76.52003831 -91.65874799
53 -124.24584476 -76.52003831
54 -96.17487702 -124.24584476
55 -81.72971573 -96.17487702
56 -83.62326412 -81.72971573
57 -92.98132863 -83.62326412
58 -103.65229637 -92.98132863
59 -111.02003831 -103.65229637
60 -119.79561839 -111.02003831
61 -146.49239258 -119.79561839
62 -137.82465065 -146.49239258
63 -105.30207000 -137.82465065
64 -107.56336032 -105.30207000
65 -160.68916678 -107.56336032
66 -140.11819903 -160.68916678
67 -128.77303774 -140.11819903
68 -100.96658613 -128.77303774
69 -90.22465065 -100.96658613
70 -67.79561839 -90.22465065
71 -35.56336032 -67.79561839
72 16.66105960 -35.56336032
73 48.96428540 16.66105960
74 76.63202734 48.96428540
75 96.45460798 76.63202734
76 98.19331766 96.45460798
77 27.76751121 98.19331766
78 50.33847895 27.76751121
79 60.58364024 50.33847895
80 73.99009185 60.58364024
81 39.03202734 73.99009185
82 35.56105960 39.03202734
83 22.49331766 35.56105960
84 21.01773758 22.49331766
85 1.12096339 21.01773758
86 -3.81129468 1.12096339
87 21.61128597 -3.81129468
88 -5.05000435 21.61128597
89 -57.47581080 -5.05000435
90 -57.80484306 -57.47581080
91 -39.25968177 -57.80484306
92 -41.95323016 -39.25968177
93 -31.91129468 -41.95323016
94 -28.78226242 -31.91129468
95 -24.75000435 -28.78226242
96 -45.72558443 -24.75000435
97 -53.02235863 -45.72558443
98 -30.45461669 -53.02235863
99 -30.03203605 -30.45461669
100 -0.59332637 -30.03203605
101 -35.31913282 -0.59332637
102 -32.04816508 -35.31913282
103 -52.60300379 -32.04816508
104 -54.89655217 -52.60300379
105 -57.65461669 -54.89655217
106 -28.92558443 -57.65461669
107 -25.29332637 -28.92558443
108 -38.16890645 -25.29332637
109 -60.16568064 -38.16890645
110 -64.19793871 -60.16568064
111 -44.77535806 -64.19793871
112 -23.43664838 -44.77535806
113 -46.56245483 -23.43664838
114 -52.59148709 -46.56245483
115 -53.14632580 -52.59148709
116 -38.33987419 -53.14632580
117 -26.69793871 -38.33987419
118 17.43109355 -26.69793871
119 35.46335162 17.43109355
120 81.18777154 35.46335162
121 136.49099734 81.18777154
122 162.65873928 136.49099734
123 192.48131993 162.65873928
124 189.82002960 192.48131993
125 156.19422315 189.82002960
126 166.46519089 156.19422315
127 148.51035218 166.46519089
128 110.71680380 148.51035218
129 95.35873928 110.71680380
130 76.78777154 95.35873928
131 102.62002960 76.78777154
132 96.14444952 102.62002960
133 88.24767533 96.14444952
134 70.51541727 88.24767533
135 35.43799791 70.51541727
136 32.87670759 35.43799791
137 5.45090114 32.87670759
138 10.72186888 5.45090114
139 16.06703017 10.72186888
140 17.97348178 16.06703017
141 37.01541727 17.97348178
142 55.44444952 37.01541727
143 41.47670759 55.44444952
144 33.80112751 41.47670759
145 0.60435332 33.80112751
146 50.67209525 0.60435332
147 33.89467590 50.67209525
148 31.73338557 33.89467590
149 38.20757912 31.73338557
150 32.17854686 38.20757912
151 46.02370815 32.17854686
152 23.53015977 46.02370815
153 61.17209525 23.53015977
154 82.10112751 61.17209525
155 129.93338557 82.10112751
156 148.95780549 129.93338557
157 170.96103130 148.95780549
158 170.12877324 170.96103130
159 155.45135388 170.12877324
160 154.39006356 155.45135388
161 145.86425711 154.39006356
162 133.43522485 145.86425711
163 112.48038614 133.43522485
164 88.98683775 112.48038614
165 87.32877324 88.98683775
166 73.05780549 87.32877324
167 80.59006356 73.05780549
168 71.11448348 80.59006356
169 47.21770929 71.11448348
170 53.68545122 47.21770929
171 46.60803187 53.68545122
172 76.04674154 46.60803187
173 30.02093509 76.04674154
174 13.79190283 30.02093509
175 46.23706412 13.79190283
176 24.64351574 46.23706412
177 17.98545122 24.64351574
178 45.11448348 17.98545122
179 46.04674154 45.11448348
180 65.27116146 46.04674154
181 79.67438727 65.27116146
182 59.14212921 79.67438727
183 53.16470985 59.14212921
184 69.30341953 53.16470985
185 57.07761308 69.30341953
186 38.44858082 57.07761308
187 31.09374211 38.44858082
188 19.70019372 31.09374211
189 27.54212921 19.70019372
190 51.87116146 27.54212921
191 42.40341953 51.87116146
192 47.92783945 42.40341953
193 32.33106526 47.92783945
194 30.99880719 32.33106526
195 30.52138784 30.99880719
196 20.76009751 30.52138784
197 40.53429106 20.76009751
198 -14.49474120 40.53429106
199 4.25042009 -14.49474120
200 -7.54312829 4.25042009
201 1.49880719 -7.54312829
202 -8.57216055 1.49880719
203 -1.93990249 -8.57216055
204 -16.21548256 -1.93990249
205 -3.01225676 -16.21548256
206 -28.04451482 -3.01225676
207 -9.82193418 -28.04451482
208 -17.08322450 -9.82193418
209 -5.50903095 -17.08322450
210 -45.53806321 -5.50903095
211 -40.79290192 -45.53806321
212 -55.98645031 -40.79290192
213 -53.84451482 -55.98645031
214 -58.01548256 -53.84451482
215 -70.48322450 -58.01548256
216 -92.35880458 -70.48322450
217 -115.75557877 -92.35880458
218 -105.38783684 -115.75557877
219 -92.46525619 -105.38783684
220 -65.62654652 -92.46525619
221 -58.45235297 -65.62654652
222 -89.88138522 -58.45235297
223 -81.63622393 -89.88138522
224 -96.32977232 -81.63622393
225 -84.68783684 -96.32977232
226 -95.35880458 -84.68783684
227 -89.22654652 -95.35880458
228 -107.30212659 -89.22654652
229 -114.69890079 -107.30212659
230 -115.43115885 -114.69890079
231 -105.50857821 -115.43115885
232 -105.56986853 -105.50857821
233 -61.29567498 -105.56986853
234 -76.42470724 -61.29567498
235 -75.97954595 -76.42470724
236 -63.57309434 -75.97954595
237 -42.43115885 -63.57309434
238 -69.40212659 -42.43115885
239 -90.16986853 -69.40212659
240 -122.24544861 -90.16986853
241 -110.84222280 -122.24544861
242 -124.37448087 -110.84222280
243 -129.25190022 -124.37448087
244 -127.41319054 -129.25190022
245 -69.03899700 -127.41319054
246 -86.06802925 -69.03899700
247 -99.42286796 -86.06802925
248 -98.81641635 -99.42286796
249 -93.07448087 -98.81641635
250 -108.54544861 -93.07448087
251 -126.81319054 -108.54544861
252 -148.58877062 -126.81319054
253 -153.68554482 -148.58877062
254 -149.01780288 -153.68554482
255 -130.59522224 -149.01780288
256 -134.25651256 -130.59522224
257 -97.98231901 -134.25651256
258 -96.01135127 -97.98231901
259 -96.06618998 -96.01135127
260 -70.15973837 -96.06618998
261 -66.51780288 -70.15973837
262 -101.58877062 -66.51780288
263 -112.35651256 -101.58877062
264 -101.93209264 -112.35651256
265 -73.02886683 -101.93209264
266 -56.86112490 -73.02886683
267 -36.03854425 -56.86112490
268 -32.29983457 -36.03854425
269 23.47435897 -32.29983457
270 30.34532672 23.47435897
271 32.49048801 30.34532672
272 56.79693962 32.49048801
273 68.93887510 56.79693962
274 81.66790736 68.93887510
275 82.10016543 81.66790736
276 92.42458535 82.10016543
277 85.32781115 92.42458535
278 80.89555309 85.32781115
279 71.71813373 80.89555309
280 62.25684341 71.71813373
281 99.13103696 62.25684341
282 105.90200470 99.13103696
283 110.14716599 105.90200470
284 105.15361760 110.14716599
285 93.59555309 105.15361760
286 96.02458535 93.59555309
287 81.55684341 96.02458535
288 89.28126333 81.55684341
289 75.88448914 89.28126333
290 78.45223107 75.88448914
291 65.57481172 78.45223107
292 50.81352140 65.57481172
293 86.28771494 50.81352140
294 83.75868269 86.28771494
295 83.30384398 83.75868269
296 80.51029559 83.30384398
297 77.15223107 80.51029559
298 34.68126333 77.15223107
299 17.21352140 34.68126333
300 5.63794132 17.21352140
301 12.74116712 5.63794132
302 1.70890906 12.74116712
303 6.83148970 1.70890906
304 -10.12980062 6.83148970
305 21.94439293 -10.12980062
306 15.01536067 21.94439293
307 11.96052196 15.01536067
308 24.76697358 11.96052196
309 0.00890906 24.76697358
310 7.23794132 0.00890906
311 4.97019938 7.23794132
312 -188.22658178 4.97019938
313 -184.92335597 -188.22658178
314 -201.15561404 -184.92335597
315 -207.63303339 -201.15561404
316 -202.79432371 -207.63303339
317 -151.92013016 -202.79432371
318 -141.14916242 -151.92013016
319 -147.50400113 -141.14916242
320 -98.69754952 -147.50400113
321 -99.05561404 -98.69754952
322 -57.02658178 -99.05561404
323 -17.39432371 -57.02658178
324 122.53009621 -17.39432371
325 125.53332201 122.53009621
326 152.80106395 125.53332201
327 137.82364460 152.80106395
328 138.66235427 137.82364460
329 160.53654782 138.66235427
330 147.30751556 160.53654782
331 127.15267685 147.30751556
332 126.85912847 127.15267685
333 114.50106395 126.85912847
334 91.13009621 114.50106395
335 85.06235427 91.13009621
336 115.48677419 85.06235427
337 91.49000000 115.48677419
338 62.95774194 91.49000000
339 38.38032258 62.95774194
340 0.31903226 38.38032258
341 62.69322581 0.31903226
342 77.66419355 62.69322581
343 83.30935484 77.66419355
344 70.81580645 83.30935484
345 66.95774194 70.81580645
346 71.08677419 66.95774194
347 61.31903226 71.08677419
348 76.44345218 61.31903226
349 92.64667799 76.44345218
350 59.61441992 92.64667799
351 -0.26299943 59.61441992
352 -21.42428976 -0.26299943
353 36.04990379 -21.42428976
354 7.62087153 36.04990379
355 20.36603282 7.62087153
356 5.47248444 20.36603282
357 -0.68558008 5.47248444
358 -10.25654782 -0.68558008
359 -59.32428976 -10.25654782
360 -25.09986984 -59.32428976
361 -50.79664403 -25.09986984
362 -54.52890209 -50.79664403
363 -94.70632145 -54.52890209
364 -97.26761177 -94.70632145
365 -83.09341822 -97.26761177
366 -49.12245048 -83.09341822
367 -68.67728919 -49.12245048
368 -64.97083758 -68.67728919
369 -83.22890209 -64.97083758
370 -88.39986984 -83.22890209
371 -81.26761177 -88.39986984
> plot(z,main=paste('Residual Lag plot, lowess, and regression line'), ylab='values of Residuals', xlab='lagged values of Residuals')
> lines(lowess(z))
> abline(lm(z))
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/79ouu1291066291.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> acf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/89ouu1291066291.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> pacf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Partial Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/99ouu1291066291.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> opar <- par(mfrow = c(2,2), oma = c(0, 0, 1.1, 0))
> plot(mylm, las = 1, sub='Residual Diagnostics')
> par(opar)
> dev.off()
null device
1
> if (n > n25) {
+ postscript(file="/var/www/html/rcomp/tmp/102xtf1291066291.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
+ plot(kp3:nmkm3,gqarr[,2], main='Goldfeld-Quandt test',ylab='2-sided p-value',xlab='breakpoint')
+ grid()
+ dev.off()
+ }
null device
1
>
> #Note: the /var/www/html/rcomp/createtable file can be downloaded at http://www.wessa.net/cretab
> load(file="/var/www/html/rcomp/createtable")
>
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a, 'Multiple Linear Regression - Estimated Regression Equation', 1, TRUE)
> a<-table.row.end(a)
> myeq <- colnames(x)[1]
> myeq <- paste(myeq, '[t] = ', sep='')
> for (i in 1:k){
+ if (mysum$coefficients[i,1] > 0) myeq <- paste(myeq, '+', '')
+ myeq <- paste(myeq, mysum$coefficients[i,1], sep=' ')
+ if (rownames(mysum$coefficients)[i] != '(Intercept)') {
+ myeq <- paste(myeq, rownames(mysum$coefficients)[i], sep='')
+ if (rownames(mysum$coefficients)[i] != 't') myeq <- paste(myeq, '[t]', sep='')
+ }
+ }
> myeq <- paste(myeq, ' + e[t]')
> a<-table.row.start(a)
> a<-table.element(a, myeq)
> a<-table.row.end(a)
> a<-table.end(a)
> table.save(a,file="/var/www/html/rcomp/tmp/11ngrk1291066291.tab")
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a,hyperlink('http://www.xycoon.com/ols1.htm','Multiple Linear Regression - Ordinary Least Squares',''), 6, TRUE)
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a,'Variable',header=TRUE)
> a<-table.element(a,'Parameter',header=TRUE)
> a<-table.element(a,'S.D.',header=TRUE)
> a<-table.element(a,'T-STAT
H0: parameter = 0',header=TRUE)
> a<-table.element(a,'2-tail p-value',header=TRUE)
> a<-table.element(a,'1-tail p-value',header=TRUE)
> a<-table.row.end(a)
> for (i in 1:k){
+ a<-table.row.start(a)
+ a<-table.element(a,rownames(mysum$coefficients)[i],header=TRUE)
+ a<-table.element(a,mysum$coefficients[i,1])
+ a<-table.element(a, round(mysum$coefficients[i,2],6))
+ a<-table.element(a, round(mysum$coefficients[i,3],4))
+ a<-table.element(a, round(mysum$coefficients[i,4],6))
+ a<-table.element(a, round(mysum$coefficients[i,4]/2,6))
+ a<-table.row.end(a)
+ }
> a<-table.end(a)
> table.save(a,file="/var/www/html/rcomp/tmp/129h891291066291.tab")
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a, 'Multiple Linear Regression - Regression Statistics', 2, TRUE)
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a, 'Multiple R',1,TRUE)
> a<-table.element(a, sqrt(mysum$r.squared))
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a, 'R-squared',1,TRUE)
> a<-table.element(a, mysum$r.squared)
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a, 'Adjusted R-squared',1,TRUE)
> a<-table.element(a, mysum$adj.r.squared)
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a, 'F-TEST (value)',1,TRUE)
> a<-table.element(a, mysum$fstatistic[1])
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a, 'F-TEST (DF numerator)',1,TRUE)
> a<-table.element(a, mysum$fstatistic[2])
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a, 'F-TEST (DF denominator)',1,TRUE)
> a<-table.element(a, mysum$fstatistic[3])
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a, 'p-value',1,TRUE)
> a<-table.element(a, 1-pf(mysum$fstatistic[1],mysum$fstatistic[2],mysum$fstatistic[3]))
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a, 'Multiple Linear Regression - Residual Statistics', 2, TRUE)
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a, 'Residual Standard Deviation',1,TRUE)
> a<-table.element(a, mysum$sigma)
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a, 'Sum Squared Residuals',1,TRUE)
> a<-table.element(a, sum(myerror*myerror))
> a<-table.row.end(a)
> a<-table.end(a)
> table.save(a,file="/var/www/html/rcomp/tmp/13n86z1291066291.tab")
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a, 'Multiple Linear Regression - Actuals, Interpolation, and Residuals', 4, TRUE)
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a, 'Time or Index', 1, TRUE)
> a<-table.element(a, 'Actuals', 1, TRUE)
> a<-table.element(a, 'Interpolation
Forecast', 1, TRUE)
> a<-table.element(a, 'Residuals
Prediction Error', 1, TRUE)
> a<-table.row.end(a)
> for (i in 1:n) {
+ a<-table.row.start(a)
+ a<-table.element(a,i, 1, TRUE)
+ a<-table.element(a,x[i])
+ a<-table.element(a,x[i]-mysum$resid[i])
+ a<-table.element(a,mysum$resid[i])
+ a<-table.row.end(a)
+ }
> a<-table.end(a)
> table.save(a,file="/var/www/html/rcomp/tmp/14qrmn1291066291.tab")
> if (n > n25) {
+ a<-table.start()
+ a<-table.row.start(a)
+ a<-table.element(a,'Goldfeld-Quandt test for Heteroskedasticity',4,TRUE)
+ a<-table.row.end(a)
+ a<-table.row.start(a)
+ a<-table.element(a,'p-values',header=TRUE)
+ a<-table.element(a,'Alternative Hypothesis',3,header=TRUE)
+ a<-table.row.end(a)
+ a<-table.row.start(a)
+ a<-table.element(a,'breakpoint index',header=TRUE)
+ a<-table.element(a,'greater',header=TRUE)
+ a<-table.element(a,'2-sided',header=TRUE)
+ a<-table.element(a,'less',header=TRUE)
+ a<-table.row.end(a)
+ for (mypoint in kp3:nmkm3) {
+ a<-table.row.start(a)
+ a<-table.element(a,mypoint,header=TRUE)
+ a<-table.element(a,gqarr[mypoint-kp3+1,1])
+ a<-table.element(a,gqarr[mypoint-kp3+1,2])
+ a<-table.element(a,gqarr[mypoint-kp3+1,3])
+ a<-table.row.end(a)
+ }
+ a<-table.end(a)
+ table.save(a,file="/var/www/html/rcomp/tmp/15urlb1291066291.tab")
+ a<-table.start()
+ a<-table.row.start(a)
+ a<-table.element(a,'Meta Analysis of Goldfeld-Quandt test for Heteroskedasticity',4,TRUE)
+ a<-table.row.end(a)
+ a<-table.row.start(a)
+ a<-table.element(a,'Description',header=TRUE)
+ a<-table.element(a,'# significant tests',header=TRUE)
+ a<-table.element(a,'% significant tests',header=TRUE)
+ a<-table.element(a,'OK/NOK',header=TRUE)
+ a<-table.row.end(a)
+ a<-table.row.start(a)
+ a<-table.element(a,'1% type I error level',header=TRUE)
+ a<-table.element(a,numsignificant1)
+ a<-table.element(a,numsignificant1/numgqtests)
+ if (numsignificant1/numgqtests < 0.01) dum <- 'OK' else dum <- 'NOK'
+ a<-table.element(a,dum)
+ a<-table.row.end(a)
+ a<-table.row.start(a)
+ a<-table.element(a,'5% type I error level',header=TRUE)
+ a<-table.element(a,numsignificant5)
+ a<-table.element(a,numsignificant5/numgqtests)
+ if (numsignificant5/numgqtests < 0.05) dum <- 'OK' else dum <- 'NOK'
+ a<-table.element(a,dum)
+ a<-table.row.end(a)
+ a<-table.row.start(a)
+ a<-table.element(a,'10% type I error level',header=TRUE)
+ a<-table.element(a,numsignificant10)
+ a<-table.element(a,numsignificant10/numgqtests)
+ if (numsignificant10/numgqtests < 0.1) dum <- 'OK' else dum <- 'NOK'
+ a<-table.element(a,dum)
+ a<-table.row.end(a)
+ a<-table.end(a)
+ table.save(a,file="/var/www/html/rcomp/tmp/16xajh1291066291.tab")
+ }
>
> try(system("convert tmp/1vwe31291066291.ps tmp/1vwe31291066291.png",intern=TRUE))
character(0)
> try(system("convert tmp/2vwe31291066291.ps tmp/2vwe31291066291.png",intern=TRUE))
character(0)
> try(system("convert tmp/3oodo1291066291.ps tmp/3oodo1291066291.png",intern=TRUE))
character(0)
> try(system("convert tmp/4oodo1291066291.ps tmp/4oodo1291066291.png",intern=TRUE))
character(0)
> try(system("convert tmp/5oodo1291066291.ps tmp/5oodo1291066291.png",intern=TRUE))
character(0)
> try(system("convert tmp/6m0kx1291066291.ps tmp/6m0kx1291066291.png",intern=TRUE))
character(0)
> try(system("convert tmp/79ouu1291066291.ps tmp/79ouu1291066291.png",intern=TRUE))
character(0)
> try(system("convert tmp/89ouu1291066291.ps tmp/89ouu1291066291.png",intern=TRUE))
character(0)
> try(system("convert tmp/99ouu1291066291.ps tmp/99ouu1291066291.png",intern=TRUE))
character(0)
> try(system("convert tmp/102xtf1291066291.ps tmp/102xtf1291066291.png",intern=TRUE))
character(0)
>
>
> proc.time()
user system elapsed
10.241 2.048 21.535