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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> x <- array(list(280.7
+ ,235.1
+ ,264.6
+ ,280.7
+ ,240.7
+ ,264.6
+ ,201.4
+ ,240.7
+ ,240.8
+ ,201.4
+ ,241.1
+ ,240.8
+ ,223.8
+ ,241.1
+ ,206.1
+ ,223.8
+ ,174.7
+ ,206.1
+ ,203.3
+ ,174.7
+ ,220.5
+ ,203.3
+ ,299.5
+ ,220.5
+ ,347.4
+ ,299.5
+ ,338.3
+ ,347.4
+ ,327.7
+ ,338.3
+ ,351.6
+ ,327.7
+ ,396.6
+ ,351.6
+ ,438.8
+ ,396.6
+ ,395.6
+ ,438.8
+ ,363.5
+ ,395.6
+ ,378.8
+ ,363.5
+ ,357
+ ,378.8
+ ,369
+ ,357
+ ,464.8
+ ,369
+ ,479.1
+ ,464.8
+ ,431.3
+ ,479.1
+ ,366.5
+ ,431.3
+ ,326.3
+ ,366.5
+ ,355.1
+ ,326.3
+ ,331.6
+ ,355.1
+ ,261.3
+ ,331.6
+ ,249
+ ,261.3
+ ,205.5
+ ,249
+ ,235.6
+ ,205.5
+ ,240.9
+ ,235.6
+ ,264.9
+ ,240.9
+ ,253.8
+ ,264.9
+ ,232.3
+ ,253.8
+ ,193.8
+ ,232.3
+ ,177
+ ,193.8
+ ,213.2
+ ,177
+ ,207.2
+ ,213.2
+ ,180.6
+ ,207.2
+ ,188.6
+ ,180.6
+ ,175.4
+ ,188.6
+ ,199
+ ,175.4
+ ,179.6
+ ,199
+ ,225.8
+ ,179.6
+ ,234
+ ,225.8
+ ,200.2
+ ,234
+ ,183.6
+ ,200.2
+ ,178.2
+ ,183.6
+ ,203.2
+ ,178.2
+ ,208.5
+ ,203.2
+ ,191.8
+ ,208.5
+ ,172.8
+ ,191.8
+ ,148
+ ,172.8
+ ,159.4
+ ,148
+ ,154.5
+ ,159.4
+ ,213.2
+ ,154.5
+ ,196.4
+ ,213.2
+ ,182.8
+ ,196.4
+ ,176.4
+ ,182.8
+ ,153.6
+ ,176.4
+ ,173.2
+ ,153.6
+ ,171
+ ,173.2
+ ,151.2
+ ,171
+ ,161.9
+ ,151.2
+ ,157.2
+ ,161.9
+ ,201.7
+ ,157.2
+ ,236.4
+ ,201.7
+ ,356.1
+ ,236.4
+ ,398.3
+ ,356.1
+ ,403.7
+ ,398.3
+ ,384.6
+ ,403.7
+ ,365.8
+ ,384.6
+ ,368.1
+ ,365.8
+ ,367.9
+ ,368.1
+ ,347
+ ,367.9
+ ,343.3
+ ,347
+ ,292.9
+ ,343.3
+ ,311.5
+ ,292.9
+ ,300.9
+ ,311.5
+ ,366.9
+ ,300.9
+ ,356.9
+ ,366.9
+ ,329.7
+ ,356.9
+ ,316.2
+ ,329.7
+ ,269
+ ,316.2
+ ,289.3
+ ,269
+ ,266.2
+ ,289.3
+ ,253.6
+ ,266.2
+ ,233.8
+ ,253.6
+ ,228.4
+ ,233.8
+ ,253.6
+ ,228.4
+ ,260.1
+ ,253.6
+ ,306.6
+ ,260.1
+ ,309.2
+ ,306.6
+ ,309.5
+ ,309.2
+ ,271
+ ,309.5
+ ,279.9
+ ,271
+ ,317.9
+ ,279.9
+ ,298.4
+ ,317.9
+ ,246.7
+ ,298.4
+ ,227.3
+ ,246.7
+ ,209.1
+ ,227.3
+ ,259.9
+ ,209.1
+ ,266
+ ,259.9
+ ,320.6
+ ,266
+ ,308.5
+ ,320.6
+ ,282.2
+ ,308.5
+ ,262.7
+ ,282.2
+ ,263.5
+ ,262.7
+ ,313.1
+ ,263.5
+ ,284.3
+ ,313.1
+ ,252.6
+ ,284.3
+ ,250.3
+ ,252.6
+ ,246.5
+ ,250.3
+ ,312.7
+ ,246.5
+ ,333.2
+ ,312.7
+ ,446.4
+ ,333.2
+ ,511.6
+ ,446.4
+ ,515.5
+ ,511.6
+ ,506.4
+ ,515.5
+ ,483.2
+ ,506.4
+ ,522.3
+ ,483.2
+ ,509.8
+ ,522.3
+ ,460.7
+ ,509.8
+ ,405.8
+ ,460.7
+ ,375
+ ,405.8
+ ,378.5
+ ,375
+ ,406.8
+ ,378.5
+ ,467.8
+ ,406.8
+ ,469.8
+ ,467.8
+ ,429.8
+ ,469.8
+ ,355.8
+ ,429.8
+ ,332.7
+ ,355.8
+ ,378
+ ,332.7
+ ,360.5
+ ,378
+ ,334.7
+ ,360.5
+ ,319.5
+ ,334.7
+ ,323.1
+ ,319.5
+ ,363.6
+ ,323.1
+ ,352.1
+ ,363.6
+ ,411.9
+ ,352.1
+ ,388.6
+ ,411.9
+ ,416.4
+ ,388.6
+ ,360.7
+ ,416.4
+ ,338
+ ,360.7
+ ,417.2
+ ,338
+ ,388.4
+ ,417.2
+ ,371.1
+ ,388.4
+ ,331.5
+ ,371.1
+ ,353.7
+ ,331.5
+ ,396.7
+ ,353.7
+ ,447
+ ,396.7
+ ,533.5
+ ,447
+ ,565.4
+ ,533.5
+ ,542.3
+ ,565.4
+ ,488.7
+ ,542.3
+ ,467.1
+ ,488.7
+ ,531.3
+ ,467.1
+ ,496.1
+ ,531.3
+ ,444
+ ,496.1
+ ,403.4
+ ,444
+ ,386.3
+ ,403.4
+ ,394.1
+ ,386.3
+ ,404.1
+ ,394.1
+ ,462.1
+ ,404.1
+ ,448.1
+ ,462.1
+ ,432.3
+ ,448.1
+ ,386.3
+ ,432.3
+ ,395.2
+ ,386.3
+ ,421.9
+ ,395.2
+ ,382.9
+ ,421.9
+ ,384.2
+ ,382.9
+ ,345.5
+ ,384.2
+ ,323.4
+ ,345.5
+ ,372.6
+ ,323.4
+ ,376
+ ,372.6
+ ,462.7
+ ,376
+ ,487
+ ,462.7
+ ,444.2
+ ,487
+ ,399.3
+ ,444.2
+ ,394.9
+ ,399.3
+ ,455.4
+ ,394.9
+ ,414
+ ,455.4
+ ,375.5
+ ,414
+ ,347
+ ,375.5
+ ,339.4
+ ,347
+ ,385.8
+ ,339.4
+ ,378.8
+ ,385.8
+ ,451.8
+ ,378.8
+ ,446.1
+ ,451.8
+ ,422.5
+ ,446.1
+ ,383.1
+ ,422.5
+ ,352.8
+ ,383.1
+ ,445.3
+ ,352.8
+ ,367.5
+ ,445.3
+ ,355.1
+ ,367.5
+ ,326.2
+ ,355.1
+ ,319.8
+ ,326.2
+ ,331.8
+ ,319.8
+ ,340.9
+ ,331.8
+ ,394.1
+ ,340.9
+ ,417.2
+ ,394.1
+ ,369.9
+ ,417.2
+ ,349.2
+ ,369.9
+ ,321.4
+ ,349.2
+ ,405.7
+ ,321.4
+ ,342.9
+ ,405.7
+ ,316.5
+ ,342.9
+ ,284.2
+ ,316.5
+ ,270.9
+ ,284.2
+ ,288.8
+ ,270.9
+ ,278.8
+ ,288.8
+ ,324.4
+ ,278.8
+ ,310.9
+ ,324.4
+ ,299
+ ,310.9
+ ,273
+ ,299
+ ,279.3
+ ,273
+ ,359.2
+ ,279.3
+ ,305
+ ,359.2
+ ,282.1
+ ,305
+ ,250.3
+ ,282.1
+ ,246.5
+ ,250.3
+ ,257.9
+ ,246.5
+ ,266.5
+ ,257.9
+ ,315.9
+ ,266.5
+ ,318.4
+ ,315.9
+ ,295.4
+ ,318.4
+ ,266.4
+ ,295.4
+ ,245.8
+ ,266.4
+ ,362.8
+ ,245.8
+ ,324.9
+ ,362.8
+ ,294.2
+ ,324.9
+ ,289.5
+ ,294.2
+ ,295.2
+ ,289.5
+ ,290.3
+ ,295.2
+ ,272
+ ,290.3
+ ,307.4
+ ,272
+ ,328.7
+ ,307.4
+ ,292.9
+ ,328.7
+ ,249.1
+ ,292.9
+ ,230.4
+ ,249.1
+ ,361.5
+ ,230.4
+ ,321.7
+ ,361.5
+ ,277.2
+ ,321.7
+ ,260.7
+ ,277.2
+ ,251
+ ,260.7
+ ,257.6
+ ,251
+ ,241.8
+ ,257.6
+ ,287.5
+ ,241.8
+ ,292.3
+ ,287.5
+ ,274.7
+ ,292.3
+ ,254.2
+ ,274.7
+ ,230
+ ,254.2
+ ,339
+ ,230
+ ,318.2
+ ,339
+ ,287
+ ,318.2
+ ,295.8
+ ,287
+ ,284
+ ,295.8
+ ,271
+ ,284
+ ,262.7
+ ,271
+ ,340.6
+ ,262.7
+ ,379.4
+ ,340.6
+ ,373.3
+ ,379.4
+ ,355.2
+ ,373.3
+ ,338.4
+ ,355.2
+ ,466.9
+ ,338.4
+ ,451
+ ,466.9
+ ,422
+ ,451
+ ,429.2
+ ,422
+ ,425.9
+ ,429.2
+ ,460.7
+ ,425.9
+ ,463.6
+ ,460.7
+ ,541.4
+ ,463.6
+ ,544.2
+ ,541.4
+ ,517.5
+ ,544.2
+ ,469.4
+ ,517.5
+ ,439.4
+ ,469.4
+ ,549
+ ,439.4
+ ,533
+ ,549
+ ,506.1
+ ,533
+ ,484
+ ,506.1
+ ,457
+ ,484
+ ,481.5
+ ,457
+ ,469.5
+ ,481.5
+ ,544.7
+ ,469.5
+ ,541.2
+ ,544.7
+ ,521.5
+ ,541.2
+ ,469.7
+ ,521.5
+ ,434.4
+ ,469.7
+ ,542.6
+ ,434.4
+ ,517.3
+ ,542.6
+ ,485.7
+ ,517.3
+ ,465.8
+ ,485.7
+ ,447
+ ,465.8
+ ,426.6
+ ,447
+ ,411.6
+ ,426.6
+ ,467.5
+ ,411.6
+ ,484.5
+ ,467.5
+ ,451.2
+ ,484.5
+ ,417.4
+ ,451.2
+ ,379.9
+ ,417.4
+ ,484.7
+ ,379.9
+ ,455
+ ,484.7
+ ,420.8
+ ,455
+ ,416.5
+ ,420.8
+ ,376.3
+ ,416.5
+ ,405.6
+ ,376.3
+ ,405.8
+ ,405.6
+ ,500.8
+ ,405.8
+ ,514
+ ,500.8
+ ,475.5
+ ,514
+ ,430.1
+ ,475.5
+ ,414.4
+ ,430.1
+ ,538
+ ,414.4
+ ,526
+ ,538
+ ,488.5
+ ,526
+ ,520.2
+ ,488.5
+ ,504.4
+ ,520.2
+ ,568.5
+ ,504.4
+ ,610.6
+ ,568.5
+ ,818
+ ,610.6
+ ,830.9
+ ,818
+ ,835.9
+ ,830.9
+ ,782
+ ,835.9
+ ,762.3
+ ,782
+ ,856.9
+ ,762.3
+ ,820.9
+ ,856.9
+ ,769.6
+ ,820.9
+ ,752.2
+ ,769.6
+ ,724.4
+ ,752.2
+ ,723.1
+ ,724.4
+ ,719.5
+ ,723.1
+ ,817.4
+ ,719.5
+ ,803.3
+ ,817.4
+ ,752.5
+ ,803.3
+ ,689
+ ,752.5
+ ,630.4
+ ,689
+ ,765.5
+ ,630.4
+ ,757.7
+ ,765.5
+ ,732.2
+ ,757.7
+ ,702.6
+ ,732.2
+ ,683.3
+ ,702.6
+ ,709.5
+ ,683.3
+ ,702.2
+ ,709.5
+ ,784.8
+ ,702.2
+ ,810.9
+ ,784.8
+ ,755.6
+ ,810.9
+ ,656.8
+ ,755.6
+ ,615.1
+ ,656.8
+ ,745.3
+ ,615.1
+ ,694.1
+ ,745.3
+ ,675.7
+ ,694.1
+ ,643.7
+ ,675.7
+ ,622.1
+ ,643.7
+ ,634.6
+ ,622.1
+ ,588
+ ,634.6
+ ,689.7
+ ,588
+ ,673.9
+ ,689.7
+ ,647.9
+ ,673.9
+ ,568.8
+ ,647.9
+ ,545.7
+ ,568.8
+ ,632.6
+ ,545.7
+ ,643.8
+ ,632.6
+ ,593.1
+ ,643.8
+ ,579.7
+ ,593.1
+ ,546
+ ,579.7
+ ,562.9
+ ,546
+ ,572.5
+ ,562.9)
+ ,dim=c(2
+ ,371)
+ ,dimnames=list(c('MW1'
+ ,'MW2')
+ ,1:371))
> y <- array(NA,dim=c(2,371),dimnames=list(c('MW1','MW2'),1:371))
> 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
MW1 MW2 M1 M2 M3 M4 M5 M6 M7 M8 M9 M10 M11 t
1 280.7 235.1 1 0 0 0 0 0 0 0 0 0 0 1
2 264.6 280.7 0 1 0 0 0 0 0 0 0 0 0 2
3 240.7 264.6 0 0 1 0 0 0 0 0 0 0 0 3
4 201.4 240.7 0 0 0 1 0 0 0 0 0 0 0 4
5 240.8 201.4 0 0 0 0 1 0 0 0 0 0 0 5
6 241.1 240.8 0 0 0 0 0 1 0 0 0 0 0 6
7 223.8 241.1 0 0 0 0 0 0 1 0 0 0 0 7
8 206.1 223.8 0 0 0 0 0 0 0 1 0 0 0 8
9 174.7 206.1 0 0 0 0 0 0 0 0 1 0 0 9
10 203.3 174.7 0 0 0 0 0 0 0 0 0 1 0 10
11 220.5 203.3 0 0 0 0 0 0 0 0 0 0 1 11
12 299.5 220.5 0 0 0 0 0 0 0 0 0 0 0 12
13 347.4 299.5 1 0 0 0 0 0 0 0 0 0 0 13
14 338.3 347.4 0 1 0 0 0 0 0 0 0 0 0 14
15 327.7 338.3 0 0 1 0 0 0 0 0 0 0 0 15
16 351.6 327.7 0 0 0 1 0 0 0 0 0 0 0 16
17 396.6 351.6 0 0 0 0 1 0 0 0 0 0 0 17
18 438.8 396.6 0 0 0 0 0 1 0 0 0 0 0 18
19 395.6 438.8 0 0 0 0 0 0 1 0 0 0 0 19
20 363.5 395.6 0 0 0 0 0 0 0 1 0 0 0 20
21 378.8 363.5 0 0 0 0 0 0 0 0 1 0 0 21
22 357.0 378.8 0 0 0 0 0 0 0 0 0 1 0 22
23 369.0 357.0 0 0 0 0 0 0 0 0 0 0 1 23
24 464.8 369.0 0 0 0 0 0 0 0 0 0 0 0 24
25 479.1 464.8 1 0 0 0 0 0 0 0 0 0 0 25
26 431.3 479.1 0 1 0 0 0 0 0 0 0 0 0 26
27 366.5 431.3 0 0 1 0 0 0 0 0 0 0 0 27
28 326.3 366.5 0 0 0 1 0 0 0 0 0 0 0 28
29 355.1 326.3 0 0 0 0 1 0 0 0 0 0 0 29
30 331.6 355.1 0 0 0 0 0 1 0 0 0 0 0 30
31 261.3 331.6 0 0 0 0 0 0 1 0 0 0 0 31
32 249.0 261.3 0 0 0 0 0 0 0 1 0 0 0 32
33 205.5 249.0 0 0 0 0 0 0 0 0 1 0 0 33
34 235.6 205.5 0 0 0 0 0 0 0 0 0 1 0 34
35 240.9 235.6 0 0 0 0 0 0 0 0 0 0 1 35
36 264.9 240.9 0 0 0 0 0 0 0 0 0 0 0 36
37 253.8 264.9 1 0 0 0 0 0 0 0 0 0 0 37
38 232.3 253.8 0 1 0 0 0 0 0 0 0 0 0 38
39 193.8 232.3 0 0 1 0 0 0 0 0 0 0 0 39
40 177.0 193.8 0 0 0 1 0 0 0 0 0 0 0 40
41 213.2 177.0 0 0 0 0 1 0 0 0 0 0 0 41
42 207.2 213.2 0 0 0 0 0 1 0 0 0 0 0 42
43 180.6 207.2 0 0 0 0 0 0 1 0 0 0 0 43
44 188.6 180.6 0 0 0 0 0 0 0 1 0 0 0 44
45 175.4 188.6 0 0 0 0 0 0 0 0 1 0 0 45
46 199.0 175.4 0 0 0 0 0 0 0 0 0 1 0 46
47 179.6 199.0 0 0 0 0 0 0 0 0 0 0 1 47
48 225.8 179.6 0 0 0 0 0 0 0 0 0 0 0 48
49 234.0 225.8 1 0 0 0 0 0 0 0 0 0 0 49
50 200.2 234.0 0 1 0 0 0 0 0 0 0 0 0 50
51 183.6 200.2 0 0 1 0 0 0 0 0 0 0 0 51
52 178.2 183.6 0 0 0 1 0 0 0 0 0 0 0 52
53 203.2 178.2 0 0 0 0 1 0 0 0 0 0 0 53
54 208.5 203.2 0 0 0 0 0 1 0 0 0 0 0 54
55 191.8 208.5 0 0 0 0 0 0 1 0 0 0 0 55
56 172.8 191.8 0 0 0 0 0 0 0 1 0 0 0 56
57 148.0 172.8 0 0 0 0 0 0 0 0 1 0 0 57
58 159.4 148.0 0 0 0 0 0 0 0 0 0 1 0 58
59 154.5 159.4 0 0 0 0 0 0 0 0 0 0 1 59
60 213.2 154.5 0 0 0 0 0 0 0 0 0 0 0 60
61 196.4 213.2 1 0 0 0 0 0 0 0 0 0 0 61
62 182.8 196.4 0 1 0 0 0 0 0 0 0 0 0 62
63 176.4 182.8 0 0 1 0 0 0 0 0 0 0 0 63
64 153.6 176.4 0 0 0 1 0 0 0 0 0 0 0 64
65 173.2 153.6 0 0 0 0 1 0 0 0 0 0 0 65
66 171.0 173.2 0 0 0 0 0 1 0 0 0 0 0 66
67 151.2 171.0 0 0 0 0 0 0 1 0 0 0 0 67
68 161.9 151.2 0 0 0 0 0 0 0 1 0 0 0 68
69 157.2 161.9 0 0 0 0 0 0 0 0 1 0 0 69
70 201.7 157.2 0 0 0 0 0 0 0 0 0 1 0 70
71 236.4 201.7 0 0 0 0 0 0 0 0 0 0 1 71
72 356.1 236.4 0 0 0 0 0 0 0 0 0 0 0 72
73 398.3 356.1 1 0 0 0 0 0 0 0 0 0 0 73
74 403.7 398.3 0 1 0 0 0 0 0 0 0 0 0 74
75 384.6 403.7 0 0 1 0 0 0 0 0 0 0 0 75
76 365.8 384.6 0 0 0 1 0 0 0 0 0 0 0 76
77 368.1 365.8 0 0 0 0 1 0 0 0 0 0 0 77
78 367.9 368.1 0 0 0 0 0 1 0 0 0 0 0 78
79 347.0 367.9 0 0 0 0 0 0 1 0 0 0 0 79
80 343.3 347.0 0 0 0 0 0 0 0 1 0 0 0 80
81 292.9 343.3 0 0 0 0 0 0 0 0 1 0 0 81
82 311.5 292.9 0 0 0 0 0 0 0 0 0 1 0 82
83 300.9 311.5 0 0 0 0 0 0 0 0 0 0 1 83
84 366.9 300.9 0 0 0 0 0 0 0 0 0 0 0 84
85 356.9 366.9 1 0 0 0 0 0 0 0 0 0 0 85
86 329.7 356.9 0 1 0 0 0 0 0 0 0 0 0 86
87 316.2 329.7 0 0 1 0 0 0 0 0 0 0 0 87
88 269.0 316.2 0 0 0 1 0 0 0 0 0 0 0 88
89 289.3 269.0 0 0 0 0 1 0 0 0 0 0 0 89
90 266.2 289.3 0 0 0 0 0 1 0 0 0 0 0 90
91 253.6 266.2 0 0 0 0 0 0 1 0 0 0 0 91
92 233.8 253.6 0 0 0 0 0 0 0 1 0 0 0 92
93 228.4 233.8 0 0 0 0 0 0 0 0 1 0 0 93
94 253.6 228.4 0 0 0 0 0 0 0 0 0 1 0 94
95 260.1 253.6 0 0 0 0 0 0 0 0 0 0 1 95
96 306.6 260.1 0 0 0 0 0 0 0 0 0 0 0 96
97 309.2 306.6 1 0 0 0 0 0 0 0 0 0 0 97
98 309.5 309.2 0 1 0 0 0 0 0 0 0 0 0 98
99 271.0 309.5 0 0 1 0 0 0 0 0 0 0 0 99
100 279.9 271.0 0 0 0 1 0 0 0 0 0 0 0 100
101 317.9 279.9 0 0 0 0 1 0 0 0 0 0 0 101
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103 246.7 298.4 0 0 0 0 0 0 1 0 0 0 0 103
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105 209.1 227.3 0 0 0 0 0 0 0 0 1 0 0 105
106 259.9 209.1 0 0 0 0 0 0 0 0 0 1 0 106
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109 308.5 320.6 1 0 0 0 0 0 0 0 0 0 0 109
110 282.2 308.5 0 1 0 0 0 0 0 0 0 0 0 110
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112 263.5 262.7 0 0 0 1 0 0 0 0 0 0 0 112
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122 515.5 511.6 0 1 0 0 0 0 0 0 0 0 0 122
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159 488.7 542.3 0 0 1 0 0 0 0 0 0 0 0 159
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162 496.1 531.3 0 0 0 0 0 1 0 0 0 0 0 162
163 444.0 496.1 0 0 0 0 0 0 1 0 0 0 0 163
164 403.4 444.0 0 0 0 0 0 0 0 1 0 0 0 164
165 386.3 403.4 0 0 0 0 0 0 0 0 1 0 0 165
166 394.1 386.3 0 0 0 0 0 0 0 0 0 1 0 166
167 404.1 394.1 0 0 0 0 0 0 0 0 0 0 1 167
168 462.1 404.1 0 0 0 0 0 0 0 0 0 0 0 168
169 448.1 462.1 1 0 0 0 0 0 0 0 0 0 0 169
170 432.3 448.1 0 1 0 0 0 0 0 0 0 0 0 170
171 386.3 432.3 0 0 1 0 0 0 0 0 0 0 0 171
172 395.2 386.3 0 0 0 1 0 0 0 0 0 0 0 172
173 421.9 395.2 0 0 0 0 1 0 0 0 0 0 0 173
174 382.9 421.9 0 0 0 0 0 1 0 0 0 0 0 174
175 384.2 382.9 0 0 0 0 0 0 1 0 0 0 0 175
176 345.5 384.2 0 0 0 0 0 0 0 1 0 0 0 176
177 323.4 345.5 0 0 0 0 0 0 0 0 1 0 0 177
178 372.6 323.4 0 0 0 0 0 0 0 0 0 1 0 178
179 376.0 372.6 0 0 0 0 0 0 0 0 0 0 1 179
180 462.7 376.0 0 0 0 0 0 0 0 0 0 0 0 180
181 487.0 462.7 1 0 0 0 0 0 0 0 0 0 0 181
182 444.2 487.0 0 1 0 0 0 0 0 0 0 0 0 182
183 399.3 444.2 0 0 1 0 0 0 0 0 0 0 0 183
184 394.9 399.3 0 0 0 1 0 0 0 0 0 0 0 184
185 455.4 394.9 0 0 0 0 1 0 0 0 0 0 0 185
186 414.0 455.4 0 0 0 0 0 1 0 0 0 0 0 186
187 375.5 414.0 0 0 0 0 0 0 1 0 0 0 0 187
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189 339.4 347.0 0 0 0 0 0 0 0 0 1 0 0 189
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193 446.1 451.8 1 0 0 0 0 0 0 0 0 0 0 193
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205 417.2 394.1 1 0 0 0 0 0 0 0 0 0 0 205
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207 349.2 369.9 0 0 1 0 0 0 0 0 0 0 0 207
208 321.4 349.2 0 0 0 1 0 0 0 0 0 0 0 208
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210 342.9 405.7 0 0 0 0 0 1 0 0 0 0 0 210
211 316.5 342.9 0 0 0 0 0 0 1 0 0 0 0 211
212 284.2 316.5 0 0 0 0 0 0 0 1 0 0 0 212
213 270.9 284.2 0 0 0 0 0 0 0 0 1 0 0 213
214 288.8 270.9 0 0 0 0 0 0 0 0 0 1 0 214
215 278.8 288.8 0 0 0 0 0 0 0 0 0 0 1 215
216 324.4 278.8 0 0 0 0 0 0 0 0 0 0 0 216
217 310.9 324.4 1 0 0 0 0 0 0 0 0 0 0 217
218 299.0 310.9 0 1 0 0 0 0 0 0 0 0 0 218
219 273.0 299.0 0 0 1 0 0 0 0 0 0 0 0 219
220 279.3 273.0 0 0 0 1 0 0 0 0 0 0 0 220
221 359.2 279.3 0 0 0 0 1 0 0 0 0 0 0 221
222 305.0 359.2 0 0 0 0 0 1 0 0 0 0 0 222
223 282.1 305.0 0 0 0 0 0 0 1 0 0 0 0 223
224 250.3 282.1 0 0 0 0 0 0 0 1 0 0 0 224
225 246.5 250.3 0 0 0 0 0 0 0 0 1 0 0 225
226 257.9 246.5 0 0 0 0 0 0 0 0 0 1 0 226
227 266.5 257.9 0 0 0 0 0 0 0 0 0 0 1 227
228 315.9 266.5 0 0 0 0 0 0 0 0 0 0 0 228
229 318.4 315.9 1 0 0 0 0 0 0 0 0 0 0 229
230 295.4 318.4 0 1 0 0 0 0 0 0 0 0 0 230
231 266.4 295.4 0 0 1 0 0 0 0 0 0 0 0 231
232 245.8 266.4 0 0 0 1 0 0 0 0 0 0 0 232
233 362.8 245.8 0 0 0 0 1 0 0 0 0 0 0 233
234 324.9 362.8 0 0 0 0 0 1 0 0 0 0 0 234
235 294.2 324.9 0 0 0 0 0 0 1 0 0 0 0 235
236 289.5 294.2 0 0 0 0 0 0 0 1 0 0 0 236
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241 328.7 307.4 1 0 0 0 0 0 0 0 0 0 0 241
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243 249.1 292.9 0 0 1 0 0 0 0 0 0 0 0 243
244 230.4 249.1 0 0 0 1 0 0 0 0 0 0 0 244
245 361.5 230.4 0 0 0 0 1 0 0 0 0 0 0 245
246 321.7 361.5 0 0 0 0 0 1 0 0 0 0 0 246
247 277.2 321.7 0 0 0 0 0 0 1 0 0 0 0 247
248 260.7 277.2 0 0 0 0 0 0 0 1 0 0 0 248
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250 257.6 251.0 0 0 0 0 0 0 0 0 0 1 0 250
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255 254.2 274.7 0 0 1 0 0 0 0 0 0 0 0 255
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257 339.0 230.0 0 0 0 0 1 0 0 0 0 0 0 257
258 318.2 339.0 0 0 0 0 0 1 0 0 0 0 0 258
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260 295.8 287.0 0 0 0 0 0 0 0 1 0 0 0 260
261 284.0 295.8 0 0 0 0 0 0 0 0 1 0 0 261
262 271.0 284.0 0 0 0 0 0 0 0 0 0 1 0 262
263 262.7 271.0 0 0 0 0 0 0 0 0 0 0 1 263
264 340.6 262.7 0 0 0 0 0 0 0 0 0 0 0 264
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266 373.3 379.4 0 1 0 0 0 0 0 0 0 0 0 266
267 355.2 373.3 0 0 1 0 0 0 0 0 0 0 0 267
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269 466.9 338.4 0 0 0 0 1 0 0 0 0 0 0 269
270 451.0 466.9 0 0 0 0 0 1 0 0 0 0 0 270
271 422.0 451.0 0 0 0 0 0 0 1 0 0 0 0 271
272 429.2 422.0 0 0 0 0 0 0 0 1 0 0 0 272
273 425.9 429.2 0 0 0 0 0 0 0 0 1 0 0 273
274 460.7 425.9 0 0 0 0 0 0 0 0 0 1 0 274
275 463.6 460.7 0 0 0 0 0 0 0 0 0 0 1 275
276 541.4 463.6 0 0 0 0 0 0 0 0 0 0 0 276
277 544.2 541.4 1 0 0 0 0 0 0 0 0 0 0 277
278 517.5 544.2 0 1 0 0 0 0 0 0 0 0 0 278
279 469.4 517.5 0 0 1 0 0 0 0 0 0 0 0 279
280 439.4 469.4 0 0 0 1 0 0 0 0 0 0 0 280
281 549.0 439.4 0 0 0 0 1 0 0 0 0 0 0 281
282 533.0 549.0 0 0 0 0 0 1 0 0 0 0 0 282
283 506.1 533.0 0 0 0 0 0 0 1 0 0 0 0 283
284 484.0 506.1 0 0 0 0 0 0 0 1 0 0 0 284
285 457.0 484.0 0 0 0 0 0 0 0 0 1 0 0 285
286 481.5 457.0 0 0 0 0 0 0 0 0 0 1 0 286
287 469.5 481.5 0 0 0 0 0 0 0 0 0 0 1 287
288 544.7 469.5 0 0 0 0 0 0 0 0 0 0 0 288
289 541.2 544.7 1 0 0 0 0 0 0 0 0 0 0 289
290 521.5 541.2 0 1 0 0 0 0 0 0 0 0 0 290
291 469.7 521.5 0 0 1 0 0 0 0 0 0 0 0 291
292 434.4 469.7 0 0 0 1 0 0 0 0 0 0 0 292
293 542.6 434.4 0 0 0 0 1 0 0 0 0 0 0 293
294 517.3 542.6 0 0 0 0 0 1 0 0 0 0 0 294
295 485.7 517.3 0 0 0 0 0 0 1 0 0 0 0 295
296 465.8 485.7 0 0 0 0 0 0 0 1 0 0 0 296
297 447.0 465.8 0 0 0 0 0 0 0 0 1 0 0 297
298 426.6 447.0 0 0 0 0 0 0 0 0 0 1 0 298
299 411.6 426.6 0 0 0 0 0 0 0 0 0 0 1 299
300 467.5 411.6 0 0 0 0 0 0 0 0 0 0 0 300
301 484.5 467.5 1 0 0 0 0 0 0 0 0 0 0 301
302 451.2 484.5 0 1 0 0 0 0 0 0 0 0 0 302
303 417.4 451.2 0 0 1 0 0 0 0 0 0 0 0 303
304 379.9 417.4 0 0 0 1 0 0 0 0 0 0 0 304
305 484.7 379.9 0 0 0 0 1 0 0 0 0 0 0 305
306 455.0 484.7 0 0 0 0 0 1 0 0 0 0 0 306
307 420.8 455.0 0 0 0 0 0 0 1 0 0 0 0 307
308 416.5 420.8 0 0 0 0 0 0 0 1 0 0 0 308
309 376.3 416.5 0 0 0 0 0 0 0 0 1 0 0 309
310 405.6 376.3 0 0 0 0 0 0 0 0 0 1 0 310
311 405.8 405.6 0 0 0 0 0 0 0 0 0 0 1 311
312 500.8 405.8 0 0 0 0 0 0 0 0 0 0 0 312
313 514.0 500.8 1 0 0 0 0 0 0 0 0 0 0 313
314 475.5 514.0 0 1 0 0 0 0 0 0 0 0 0 314
315 430.1 475.5 0 0 1 0 0 0 0 0 0 0 0 315
316 414.4 430.1 0 0 0 1 0 0 0 0 0 0 0 316
317 538.0 414.4 0 0 0 0 1 0 0 0 0 0 0 317
318 526.0 538.0 0 0 0 0 0 1 0 0 0 0 0 318
319 488.5 526.0 0 0 0 0 0 0 1 0 0 0 0 319
320 520.2 488.5 0 0 0 0 0 0 0 1 0 0 0 320
321 504.4 520.2 0 0 0 0 0 0 0 0 1 0 0 321
322 568.5 504.4 0 0 0 0 0 0 0 0 0 1 0 322
323 610.6 568.5 0 0 0 0 0 0 0 0 0 0 1 323
324 818.0 610.6 0 0 0 0 0 0 0 0 0 0 0 324
325 830.9 818.0 1 0 0 0 0 0 0 0 0 0 0 325
326 835.9 830.9 0 1 0 0 0 0 0 0 0 0 0 326
327 782.0 835.9 0 0 1 0 0 0 0 0 0 0 0 327
328 762.3 782.0 0 0 0 1 0 0 0 0 0 0 0 328
329 856.9 762.3 0 0 0 0 1 0 0 0 0 0 0 329
330 820.9 856.9 0 0 0 0 0 1 0 0 0 0 0 330
331 769.6 820.9 0 0 0 0 0 0 1 0 0 0 0 331
332 752.2 769.6 0 0 0 0 0 0 0 1 0 0 0 332
333 724.4 752.2 0 0 0 0 0 0 0 0 1 0 0 333
334 723.1 724.4 0 0 0 0 0 0 0 0 0 1 0 334
335 719.5 723.1 0 0 0 0 0 0 0 0 0 0 1 335
336 817.4 719.5 0 0 0 0 0 0 0 0 0 0 0 336
337 803.3 817.4 1 0 0 0 0 0 0 0 0 0 0 337
338 752.5 803.3 0 1 0 0 0 0 0 0 0 0 0 338
339 689.0 752.5 0 0 1 0 0 0 0 0 0 0 0 339
340 630.4 689.0 0 0 0 1 0 0 0 0 0 0 0 340
341 765.5 630.4 0 0 0 0 1 0 0 0 0 0 0 341
342 757.7 765.5 0 0 0 0 0 1 0 0 0 0 0 342
343 732.2 757.7 0 0 0 0 0 0 1 0 0 0 0 343
344 702.6 732.2 0 0 0 0 0 0 0 1 0 0 0 344
345 683.3 702.6 0 0 0 0 0 0 0 0 1 0 0 345
346 709.5 683.3 0 0 0 0 0 0 0 0 0 1 0 346
347 702.2 709.5 0 0 0 0 0 0 0 0 0 0 1 347
348 784.8 702.2 0 0 0 0 0 0 0 0 0 0 0 348
349 810.9 784.8 1 0 0 0 0 0 0 0 0 0 0 349
350 755.6 810.9 0 1 0 0 0 0 0 0 0 0 0 350
351 656.8 755.6 0 0 1 0 0 0 0 0 0 0 0 351
352 615.1 656.8 0 0 0 1 0 0 0 0 0 0 0 352
353 745.3 615.1 0 0 0 0 1 0 0 0 0 0 0 353
354 694.1 745.3 0 0 0 0 0 1 0 0 0 0 0 354
355 675.7 694.1 0 0 0 0 0 0 1 0 0 0 0 355
356 643.7 675.7 0 0 0 0 0 0 0 1 0 0 0 356
357 622.1 643.7 0 0 0 0 0 0 0 0 1 0 0 357
358 634.6 622.1 0 0 0 0 0 0 0 0 0 1 0 358
359 588.0 634.6 0 0 0 0 0 0 0 0 0 0 1 359
360 689.7 588.0 0 0 0 0 0 0 0 0 0 0 0 360
361 673.9 689.7 1 0 0 0 0 0 0 0 0 0 0 361
362 647.9 673.9 0 1 0 0 0 0 0 0 0 0 0 362
363 568.8 647.9 0 0 1 0 0 0 0 0 0 0 0 363
364 545.7 568.8 0 0 0 1 0 0 0 0 0 0 0 364
365 632.6 545.7 0 0 0 0 1 0 0 0 0 0 0 365
366 643.8 632.6 0 0 0 0 0 1 0 0 0 0 0 366
367 593.1 643.8 0 0 0 0 0 0 1 0 0 0 0 367
368 579.7 593.1 0 0 0 0 0 0 0 1 0 0 0 368
369 546.0 579.7 0 0 0 0 0 0 0 0 1 0 0 369
370 562.9 546.0 0 0 0 0 0 0 0 0 0 1 0 370
371 572.5 562.9 0 0 0 0 0 0 0 0 0 0 1 371
> k <- length(x[1,])
> df <- as.data.frame(x)
> (mylm <- lm(df))
Call:
lm(formula = df)
Coefficients:
(Intercept) MW2 M1 M2 M3 M4
78.60596 0.97548 -62.63069 -94.57761 -111.80356 -94.39919
M5 M6 M7 M8 M9 M10
-1.66339 -95.40193 -104.35957 -91.10966 -89.88969 -52.78052
M11 t
-71.86763 0.02508
> (mysum <- summary(mylm))
Call:
lm(formula = df)
Residuals:
Min 1Q Median 3Q Max
-67.604 -14.950 -0.886 13.238 135.640
Coefficients:
Estimate Std. Error t value Pr(>|t|)
(Intercept) 78.60596 5.21898 15.062 <2e-16 ***
MW2 0.97548 0.01165 83.725 <2e-16 ***
M1 -62.63069 6.09587 -10.274 <2e-16 ***
M2 -94.57761 6.11103 -15.477 <2e-16 ***
M3 -111.80356 6.07462 -18.405 <2e-16 ***
M4 -94.39919 6.04017 -15.629 <2e-16 ***
M5 -1.66339 6.03641 -0.276 0.783
M6 -95.40193 6.08899 -15.668 <2e-16 ***
M7 -104.35957 6.05885 -17.224 <2e-16 ***
M8 -91.10966 6.03814 -15.089 <2e-16 ***
M9 -89.88969 6.03673 -14.890 <2e-16 ***
M10 -52.78052 6.04187 -8.736 <2e-16 ***
M11 -71.86763 6.03657 -11.905 <2e-16 ***
t 0.02508 0.01647 1.522 0.129
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
Residual standard error: 23.57 on 357 degrees of freedom
Multiple R-squared: 0.9777, Adjusted R-squared: 0.9769
F-statistic: 1204 on 13 and 357 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,] 0.49338035 0.98676071 0.50661965
[2,] 0.38760306 0.77520612 0.61239694
[3,] 0.48009016 0.96018033 0.51990984
[4,] 0.38755481 0.77510962 0.61244519
[5,] 0.45266208 0.90532417 0.54733792
[6,] 0.55365648 0.89268703 0.44634352
[7,] 0.45800652 0.91601304 0.54199348
[8,] 0.38054510 0.76109019 0.61945490
[9,] 0.49168861 0.98337722 0.50831139
[10,] 0.60024416 0.79951168 0.39975584
[11,] 0.73028015 0.53943971 0.26971985
[12,] 0.70970007 0.58059986 0.29029993
[13,] 0.65153973 0.69692054 0.34846027
[14,] 0.63733820 0.72532360 0.36266180
[15,] 0.58824911 0.82350179 0.41175089
[16,] 0.62861800 0.74276399 0.37138200
[17,] 0.58430471 0.83139058 0.41569529
[18,] 0.65540941 0.68918117 0.34459059
[19,] 0.59486275 0.81027450 0.40513725
[20,] 0.69921243 0.60157514 0.30078757
[21,] 0.67129903 0.65740194 0.32870097
[22,] 0.67710013 0.64579973 0.32289987
[23,] 0.64072960 0.71854079 0.35927040
[24,] 0.61306838 0.77386324 0.38693162
[25,] 0.58486354 0.83027292 0.41513646
[26,] 0.53233491 0.93533018 0.46766509
[27,] 0.53671195 0.92657610 0.46328805
[28,] 0.58384393 0.83231215 0.41615607
[29,] 0.54480188 0.91039625 0.45519812
[30,] 0.51404951 0.97190098 0.48595049
[31,] 0.50066638 0.99866723 0.49933362
[32,] 0.46746443 0.93492885 0.53253557
[33,] 0.41805076 0.83610151 0.58194924
[34,] 0.37054099 0.74108199 0.62945901
[35,] 0.37530589 0.75061178 0.62469411
[36,] 0.35854775 0.71709550 0.64145225
[37,] 0.34077151 0.68154302 0.65922849
[38,] 0.31055595 0.62111191 0.68944405
[39,] 0.32006834 0.64013669 0.67993166
[40,] 0.27857103 0.55714206 0.72142897
[41,] 0.24094936 0.48189873 0.75905064
[42,] 0.20717780 0.41435559 0.79282220
[43,] 0.17611178 0.35222357 0.82388822
[44,] 0.15022857 0.30045714 0.84977143
[45,] 0.16236997 0.32473994 0.83763003
[46,] 0.15060379 0.30120757 0.84939621
[47,] 0.16954689 0.33909378 0.83045311
[48,] 0.14273876 0.28547751 0.85726124
[49,] 0.14586292 0.29172584 0.85413708
[50,] 0.12482836 0.24965671 0.87517164
[51,] 0.11718797 0.23437595 0.88281203
[52,] 0.13073613 0.26147227 0.86926387
[53,] 0.12307002 0.24614004 0.87692998
[54,] 0.14694007 0.29388015 0.85305993
[55,] 0.18602758 0.37205517 0.81397242
[56,] 0.36996669 0.73993339 0.63003331
[57,] 0.40463039 0.80926078 0.59536961
[58,] 0.43047165 0.86094329 0.56952835
[59,] 0.40401798 0.80803596 0.59598202
[60,] 0.36648005 0.73296010 0.63351995
[61,] 0.45155363 0.90310727 0.54844637
[62,] 0.42631715 0.85263431 0.57368285
[63,] 0.39987998 0.79975996 0.60012002
[64,] 0.37063672 0.74127344 0.62936328
[65,] 0.39907310 0.79814620 0.60092690
[66,] 0.36226512 0.72453024 0.63773488
[67,] 0.33969489 0.67938979 0.66030511
[68,] 0.30604646 0.61209292 0.69395354
[69,] 0.30642478 0.61284956 0.69357522
[70,] 0.27474031 0.54948062 0.72525969
[71,] 0.26597805 0.53195610 0.73402195
[72,] 0.27431539 0.54863079 0.72568461
[73,] 0.30106913 0.60213826 0.69893087
[74,] 0.29241539 0.58483079 0.70758461
[75,] 0.28511747 0.57023494 0.71488253
[76,] 0.25694379 0.51388758 0.74305621
[77,] 0.24372145 0.48744290 0.75627855
[78,] 0.21874939 0.43749879 0.78125061
[79,] 0.19360851 0.38721701 0.80639149
[80,] 0.19396927 0.38793854 0.80603073
[81,] 0.17335316 0.34670632 0.82664684
[82,] 0.17468358 0.34936717 0.82531642
[83,] 0.15689062 0.31378125 0.84310938
[84,] 0.17835354 0.35670707 0.82164646
[85,] 0.19035202 0.38070405 0.80964798
[86,] 0.17670721 0.35341442 0.82329279
[87,] 0.17268680 0.34537359 0.82731320
[88,] 0.15225183 0.30450365 0.84774817
[89,] 0.13300618 0.26601235 0.86699382
[90,] 0.15202798 0.30405596 0.84797202
[91,] 0.13286381 0.26572762 0.86713619
[92,] 0.12215275 0.24430549 0.87784725
[93,] 0.12250307 0.24500613 0.87749693
[94,] 0.10664029 0.21328058 0.89335971
[95,] 0.09763451 0.19526902 0.90236549
[96,] 0.09606971 0.19213943 0.90393029
[97,] 0.10802915 0.21605830 0.89197085
[98,] 0.10476730 0.20953460 0.89523270
[99,] 0.09011997 0.18023995 0.90988003
[100,] 0.08136432 0.16272864 0.91863568
[101,] 0.07544979 0.15089957 0.92455021
[102,] 0.12079441 0.24158882 0.87920559
[103,] 0.11613818 0.23227636 0.88386182
[104,] 0.18137775 0.36275551 0.81862225
[105,] 0.32707978 0.65415956 0.67292022
[106,] 0.34028285 0.68056570 0.65971715
[107,] 0.35777362 0.71554724 0.64222638
[108,] 0.33210544 0.66421088 0.66789456
[109,] 0.34885202 0.69770404 0.65114798
[110,] 0.33472721 0.66945443 0.66527279
[111,] 0.32176347 0.64352694 0.67823653
[112,] 0.38672566 0.77345131 0.61327434
[113,] 0.36447582 0.72895165 0.63552418
[114,] 0.35796488 0.71592976 0.64203512
[115,] 0.37148247 0.74296494 0.62851753
[116,] 0.34639140 0.69278280 0.65360860
[117,] 0.32315122 0.64630244 0.67684878
[118,] 0.31470346 0.62940693 0.68529654
[119,] 0.38941837 0.77883675 0.61058163
[120,] 0.36039264 0.72078528 0.63960736
[121,] 0.39392552 0.78785103 0.60607448
[122,] 0.37341962 0.74683923 0.62658038
[123,] 0.34677588 0.69355177 0.65322412
[124,] 0.31838994 0.63677988 0.68161006
[125,] 0.31869952 0.63739903 0.68130048
[126,] 0.31199500 0.62398999 0.68800500
[127,] 0.29807912 0.59615825 0.70192088
[128,] 0.27840402 0.55680803 0.72159598
[129,] 0.31673493 0.63346985 0.68326507
[130,] 0.44431272 0.88862545 0.55568728
[131,] 0.44148584 0.88297169 0.55851416
[132,] 0.41180393 0.82360785 0.58819607
[133,] 0.47240594 0.94481187 0.52759406
[134,] 0.45746642 0.91493285 0.54253358
[135,] 0.44245376 0.88490753 0.55754624
[136,] 0.44114606 0.88229212 0.55885394
[137,] 0.51148491 0.97703019 0.48851509
[138,] 0.51349833 0.97300334 0.48650167
[139,] 0.64234577 0.71530846 0.35765423
[140,] 0.63287268 0.73425464 0.36712732
[141,] 0.64760505 0.70478990 0.35239495
[142,] 0.62489627 0.75020747 0.37510373
[143,] 0.61076208 0.77847583 0.38923792
[144,] 0.58449779 0.83100442 0.41550221
[145,] 0.60441021 0.79117957 0.39558979
[146,] 0.59518643 0.80962713 0.40481357
[147,] 0.58260088 0.83479823 0.41739912
[148,] 0.57715274 0.84569453 0.42284726
[149,] 0.54769477 0.90461046 0.45230523
[150,] 0.52972216 0.94055567 0.47027784
[151,] 0.51053324 0.97893352 0.48946676
[152,] 0.48978358 0.97956716 0.51021642
[153,] 0.49088103 0.98176205 0.50911897
[154,] 0.46891301 0.93782603 0.53108699
[155,] 0.44557161 0.89114322 0.55442839
[156,] 0.48361752 0.96723504 0.51638248
[157,] 0.61294625 0.77410751 0.38705375
[158,] 0.60888725 0.78222551 0.39111275
[159,] 0.65427616 0.69144767 0.34572384
[160,] 0.64888285 0.70223430 0.35111715
[161,] 0.62210647 0.75578706 0.37789353
[162,] 0.64873923 0.70252154 0.35126077
[163,] 0.62673497 0.74653006 0.37326503
[164,] 0.61320857 0.77358285 0.38679143
[165,] 0.60653598 0.78692805 0.39346402
[166,] 0.60012723 0.79974554 0.39987277
[167,] 0.57627112 0.84745776 0.42372888
[168,] 0.57783789 0.84432421 0.42216211
[169,] 0.61740502 0.76518997 0.38259498
[170,] 0.61230577 0.77538847 0.38769423
[171,] 0.58480964 0.83038073 0.41519036
[172,] 0.56030273 0.87939454 0.43969727
[173,] 0.53757169 0.92485662 0.46242831
[174,] 0.56472614 0.87054772 0.43527386
[175,] 0.54360968 0.91278065 0.45639032
[176,] 0.51340371 0.97319258 0.48659629
[177,] 0.49445364 0.98890729 0.50554636
[178,] 0.46893629 0.93787258 0.53106371
[179,] 0.44532511 0.89065023 0.55467489
[180,] 0.42291451 0.84582903 0.57708549
[181,] 0.47982903 0.95965807 0.52017097
[182,] 0.62794587 0.74410826 0.37205413
[183,] 0.62629579 0.74740842 0.37370421
[184,] 0.60392070 0.79215860 0.39607930
[185,] 0.58307191 0.83385618 0.41692809
[186,] 0.56202040 0.87595920 0.43797960
[187,] 0.54473591 0.91052819 0.45526409
[188,] 0.54099843 0.91800314 0.45900157
[189,] 0.52792144 0.94415713 0.47207856
[190,] 0.53249232 0.93501536 0.46750768
[191,] 0.53909629 0.92180742 0.46090371
[192,] 0.51354545 0.97290910 0.48645455
[193,] 0.54641998 0.90716004 0.45358002
[194,] 0.61013057 0.77973887 0.38986943
[195,] 0.58315658 0.83368683 0.41684342
[196,] 0.57042056 0.85915887 0.42957944
[197,] 0.54092818 0.91814365 0.45907182
[198,] 0.51477702 0.97044597 0.48522298
[199,] 0.49530722 0.99061443 0.50469278
[200,] 0.53232630 0.93534739 0.46767370
[201,] 0.54010513 0.91978974 0.45989487
[202,] 0.51743376 0.96513247 0.48256624
[203,] 0.50573817 0.98852365 0.49426183
[204,] 0.53391877 0.93216246 0.46608123
[205,] 0.57519864 0.84960271 0.42480136
[206,] 0.61092917 0.77814166 0.38907083
[207,] 0.58519098 0.82961804 0.41480902
[208,] 0.57945843 0.84108313 0.42054157
[209,] 0.55713325 0.88573350 0.44286675
[210,] 0.53435450 0.93129099 0.46564550
[211,] 0.51015510 0.97968981 0.48984490
[212,] 0.54814637 0.90370725 0.45185363
[213,] 0.52245847 0.95508305 0.47754153
[214,] 0.49175016 0.98350031 0.50824984
[215,] 0.47540530 0.95081060 0.52459470
[216,] 0.44686185 0.89372371 0.55313815
[217,] 0.52860383 0.94279233 0.47139617
[218,] 0.51512048 0.96975904 0.48487952
[219,] 0.48353615 0.96707230 0.51646385
[220,] 0.45826473 0.91652946 0.54173527
[221,] 0.45992198 0.91984395 0.54007802
[222,] 0.47138018 0.94276036 0.52861982
[223,] 0.46537389 0.93074778 0.53462611
[224,] 0.60437118 0.79125764 0.39562882
[225,] 0.57808780 0.84382441 0.42191220
[226,] 0.56044447 0.87911105 0.43955553
[227,] 0.53222444 0.93555113 0.46777556
[228,] 0.50257683 0.99484634 0.49742317
[229,] 0.61146342 0.77707316 0.38853658
[230,] 0.60797278 0.78405444 0.39202722
[231,] 0.59114747 0.81770506 0.40885253
[232,] 0.56563883 0.86872235 0.43436117
[233,] 0.53530930 0.92938140 0.46469070
[234,] 0.52098286 0.95803427 0.47901714
[235,] 0.51280149 0.97439703 0.48719851
[236,] 0.63478864 0.73042271 0.36521136
[237,] 0.61072733 0.77854533 0.38927267
[238,] 0.57842384 0.84315231 0.42157616
[239,] 0.57892366 0.84215268 0.42107634
[240,] 0.54765883 0.90468235 0.45234117
[241,] 0.57607838 0.84784325 0.42392162
[242,] 0.54573008 0.90853984 0.45426992
[243,] 0.51321220 0.97357560 0.48678780
[244,] 0.50262748 0.99474504 0.49737252
[245,] 0.46959363 0.93918727 0.53040637
[246,] 0.53983740 0.92032520 0.46016260
[247,] 0.51864853 0.96270295 0.48135147
[248,] 0.53153276 0.93693447 0.46846724
[249,] 0.53872644 0.92254712 0.46127356
[250,] 0.52027807 0.95944387 0.47972193
[251,] 0.54621757 0.90756485 0.45378243
[252,] 0.51668458 0.96663084 0.48331542
[253,] 0.58270103 0.83459793 0.41729897
[254,] 0.54995627 0.90008747 0.45004373
[255,] 0.51514829 0.96970343 0.48485171
[256,] 0.50800703 0.98398594 0.49199297
[257,] 0.49287218 0.98574436 0.50712782
[258,] 0.47044770 0.94089539 0.52955230
[259,] 0.43639782 0.87279563 0.56360218
[260,] 0.43849646 0.87699291 0.56150354
[261,] 0.40483798 0.80967597 0.59516202
[262,] 0.37056308 0.74112616 0.62943692
[263,] 0.34404722 0.68809444 0.65595278
[264,] 0.31286381 0.62572762 0.68713619
[265,] 0.32244859 0.64489718 0.67755141
[266,] 0.29243364 0.58486728 0.70756636
[267,] 0.26402671 0.52805342 0.73597329
[268,] 0.24002634 0.48005268 0.75997366
[269,] 0.21426789 0.42853578 0.78573211
[270,] 0.18887748 0.37775495 0.81112252
[271,] 0.17053178 0.34106356 0.82946822
[272,] 0.18553671 0.37107342 0.81446329
[273,] 0.16908695 0.33817390 0.83091305
[274,] 0.14847043 0.29694085 0.85152957
[275,] 0.13078083 0.26156166 0.86921917
[276,] 0.11456014 0.22912029 0.88543986
[277,] 0.11568110 0.23136220 0.88431890
[278,] 0.09977674 0.19955348 0.90022326
[279,] 0.08386019 0.16772038 0.91613981
[280,] 0.07333027 0.14666055 0.92666973
[281,] 0.06077952 0.12155905 0.93922048
[282,] 0.10510031 0.21020063 0.89489969
[283,] 0.10152802 0.20305605 0.89847198
[284,] 0.23880979 0.47761958 0.76119021
[285,] 0.20895592 0.41791184 0.79104408
[286,] 0.18865191 0.37730381 0.81134809
[287,] 0.17808973 0.35617947 0.82191027
[288,] 0.16612329 0.33224659 0.83387671
[289,] 0.17290161 0.34580322 0.82709839
[290,] 0.16960932 0.33921864 0.83039068
[291,] 0.15079886 0.30159771 0.84920114
[292,] 0.13166139 0.26332278 0.86833861
[293,] 0.15314779 0.30629558 0.84685221
[294,] 0.13765677 0.27531354 0.86234323
[295,] 0.12959346 0.25918691 0.87040654
[296,] 0.21042940 0.42085881 0.78957060
[297,] 0.19637235 0.39274470 0.80362765
[298,] 0.24348161 0.48696321 0.75651839
[299,] 0.21559854 0.43119708 0.78440146
[300,] 0.19979654 0.39959308 0.80020346
[301,] 0.23999900 0.47999800 0.76000100
[302,] 0.28448318 0.56896636 0.71551682
[303,] 0.47559478 0.95118956 0.52440522
[304,] 0.47330324 0.94660649 0.52669676
[305,] 0.72590906 0.54818188 0.27409094
[306,] 0.82544021 0.34911959 0.17455979
[307,] 0.92587505 0.14824990 0.07412495
[308,] 0.97336130 0.05327740 0.02663870
[309,] 0.96697920 0.06604161 0.03302080
[310,] 0.97141697 0.05716606 0.02858303
[311,] 0.97393257 0.05213486 0.02606743
[312,] 0.98138602 0.03722795 0.01861398
[313,] 0.97419211 0.05161578 0.02580789
[314,] 0.96517767 0.06964467 0.03482233
[315,] 0.95912480 0.08175040 0.04087520
[316,] 0.94344604 0.11310793 0.05655396
[317,] 0.92393588 0.15212824 0.07606412
[318,] 0.92541417 0.14917166 0.07458583
[319,] 0.89931060 0.20137881 0.10068940
[320,] 0.86874425 0.26251149 0.13125575
[321,] 0.86786127 0.26427746 0.13213873
[322,] 0.87309602 0.25380797 0.12690398
[323,] 0.83392763 0.33214473 0.16607237
[324,] 0.89641731 0.20716537 0.10358269
[325,] 0.87257149 0.25485703 0.12742851
[326,] 0.83093372 0.33813257 0.16906628
[327,] 0.77613771 0.44772458 0.22386229
[328,] 0.73617936 0.52764127 0.26382064
[329,] 0.66920272 0.66159456 0.33079728
[330,] 0.58501675 0.82996651 0.41498325
[331,] 0.49892943 0.99785887 0.50107057
[332,] 0.40851418 0.81702836 0.59148582
[333,] 0.62035999 0.75928002 0.37964001
[334,] 0.63856363 0.72287274 0.36143637
[335,] 0.63172930 0.73654140 0.36827070
[336,] 0.51073137 0.97853725 0.48926863
[337,] 0.67319227 0.65361547 0.32680773
[338,] 0.52594331 0.94811338 0.47405669
> postscript(file="/var/www/html/rcomp/tmp/12ovj1291067944.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$resid)
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/2dydm1291067944.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> plot(mysum$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/3dydm1291067944.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> hist(mysum$resid, main='Residual Histogram', xlab='values of Residuals')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/45pu71291067944.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> densityplot(~mysum$resid,col='black',main='Residual Density Plot', xlab='values of Residuals')
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/55pu71291067944.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 = 371
Frequency = 1
1 2 3 4 5 6
35.36455085 6.70454787 15.71062614 -17.70487525 -32.72943808 22.85015206
7 8 9 10 11 12
14.19007016 0.09085850 -15.28821207 6.80757607 15.17090066 5.49995306
13 14 15 16 17 18
38.94272339 15.03911885 30.51684453 47.32747322 -23.74735870 68.26954937
19 20 21 22 23 24
-7.16310017 -10.39740726 34.97041893 -38.88865949 13.43880375 25.64034664
25 26 27 28 29 30
9.09507076 -20.73244136 -21.70368064 -16.12209333 -40.86872511 1.25094181
31 32 33 34 35 36
-37.19274129 5.80843094 -26.93822591 8.46085742 3.46096360 -49.60178460
37 38 39 40 41 42
-21.50767250 -0.25801950 -0.58435494 2.74213621 -37.43070280 14.97041996
43 44 45 46 47 48
3.15585539 23.82859788 1.57971852 0.92178992 -22.43749078 -29.20590913
49 50 51 52 53 54
-3.46742952 -13.34452009 20.22753544 13.59103779 -48.90226116 25.72422574
55 56 57 58 59 60
12.78674913 -3.19774990 -10.70869784 -12.25107071 -9.20950833 -17.62237133
61 62 63 64 65 66
-29.07737849 5.63250448 29.69988539 -4.28649747 -55.20646283 17.18761035
67 68 69 70 71 72
8.46622580 25.20571149 8.82303899 20.77353940 31.12674882 45.08491974
73 74 75 76 77 78
33.12569716 29.28232259 22.11560362 4.51780331 -67.60407781 23.66578105
79 80 81 82 83 84
11.89343862 15.30595114 -32.72982460 -2.09993657 -11.78182257 -7.33445560
85 86 87 88 89 90
-19.11045903 -4.63383287 25.60006165 -25.86042073 -52.27869992 -1.46746200
91 92 93 94 95 96
17.39866333 -3.38529936 9.28413585 2.61747151 3.59742450 -28.13589843
97 98 99 100 101 102
-8.29006250 21.39552900 -0.19624737 28.83024379 -34.61240401 2.53285665
103 104 105 106 107 108
-21.21274221 -3.45547830 -3.97623466 27.44323145 3.05092354 -20.19220781
109 110 111 112 113 114
-22.94775131 -5.52261937 17.83334410 20.22573538 -23.71553300 -7.18582806
115 116 117 118 119 120
-1.85947277 13.48821232 10.68676606 43.45933542 18.44465181 39.75462370
121 122 123 124 125 126
57.13601424 29.35662401 33.65312346 1.90053374 -29.12924005 13.94299377
127 128 129 130 131 132
-14.03095768 -34.30993901 -12.80119295 -16.39069218 27.55715384 -10.94161001
133 134 135 136 137 138
-5.84021874 -15.86933987 -33.64931490 -1.99332132 -26.92064300 5.10362138
139 140 141 142 143 144
5.30706464 1.99942397 19.18165606 19.03568125 -12.90919356 -13.78389555
145 146 147 148 149 150
-32.81192954 49.63856654 -15.97888072 -1.77415177 6.80833498 -5.53613675
151 152 153 154 155 156
14.19021855 -21.80899312 37.77492513 21.98504201 49.40146985 14.94216928
157 158 159 160 161 162
25.06884756 2.77290608 -11.09266306 2.16356011 -5.32697998 -9.43926759
163 164 165 166 167 168
-18.26984707 -21.32239158 -0.06299438 -12.71655510 8.73673146 -14.91076776
169 170 171 172 173 174
-22.88293966 6.89560227 -6.49096314 29.85162007 -44.89102773 -16.22285503
175 176 177 178 179 180
32.05338546 -21.18973451 -6.78374731 26.84008668 1.30854507 12.79920686
181 182 183 184 185 186
15.13078935 -19.45151218 -5.40014617 16.56941021 -11.39936768 -18.10238320
187 188 189 190 191 192
-7.28499324 -11.50405135 7.45205065 24.13143999 -9.06876058 -1.13311780
193 194 195 196 197 198
-15.43747382 -1.55540711 -0.73323678 -10.02881457 19.26731213 -55.05102952
199 200 201 202 203 204
17.37379390 -12.70526458 7.84102900 -11.05015639 5.40611862 -22.16344956
205 206 207 208 209 210
11.64667746 -26.26504933 16.37597191 -8.66106209 9.99636726 -41.32304707
211 212 213 214 215 216
2.46959223 -17.35276107 -0.38983909 -6.65021979 -15.04927053 -31.58719093
217 218 219 220 221 222
-26.96342395 6.22737850 9.03644522 23.26944961 4.26304706 -34.16425993
223 224 225 226 227 228
4.73926048 -17.99726912 7.97791339 -14.04951725 2.49204513 -28.38978358
229 230 231 232 233 234
-11.47283658 -4.98969719 5.64718578 -4.09337300 40.24060796 -18.07696775
235 236 237 238 239 240
-2.87375409 9.09845206 18.13815526 -29.45632533 -23.91445620 -42.55590139
241 242 243 244 245 246
6.81775079 -17.83811391 -9.51510050 -2.91857095 53.66200003 -20.30982875
247 248 249 250 251 252
-17.05320510 -3.41938956 1.73096514 -19.34113975 -22.51727845 -33.29742099
253 254 255 256 257 258
-10.47120191 -0.83166408 13.03763261 -8.59449718 31.25120798 -2.16253620
259 260 261 262 263 264
-4.14001244 21.81993318 0.19067067 -38.43292844 -14.98967989 -0.88591449
265 266 267 268 269 270
24.52988268 12.50313650 17.55442536 0.98114611 53.10830710 5.57272357
271 272 273 274 275 276
1.01540052 23.22929247 11.66079626 12.54562615 0.56098130 3.63938256
277 278 279 280 281 282
-6.84727238 -4.35677666 -9.21062161 -9.71953262 36.38395040 7.18491885
283 284 285 286 287 288
4.82514370 -4.30947013 -10.99643335 2.70724744 -14.12996431 0.88307318
289 290 291 292 293 294
-13.36733651 2.26867653 -13.11352101 -15.31315993 34.56036147 -2.57299955
295 296 297 298 299 300
-0.56082055 -2.91068336 -3.54370025 -42.73894677 -18.77715406 -20.13767975
301 302 303 304 305 306
4.93865413 -13.02265112 2.86166494 -19.09659493 29.52298015 -8.69375248
307 308 309 310 311 312
-4.98946614 10.79691631 -26.45357207 4.92643075 -4.39307992 18.51911448
313 314 315 316 317 318
1.65422175 -17.80026352 -8.44345697 2.71383889 48.86797304 10.01223632
319 320 321 322 323 324
-6.84945460 48.15600835 0.18827808 42.56659473 41.20041691 135.64004366
325 326 327 328 329 330
8.83131793 33.16947633 -8.40705106 7.04181579 28.09786571 -6.46898171
331 332 333 334 335 336
-13.71917804 5.64789430 -6.42381994 -17.73975599 -1.00961106 28.50940332
337 338 339 340 341 342
-18.48437834 -23.60828852 -20.35309098 -34.43962629 65.06255445 19.18880990
343 344 345 346 347 348
10.23010743 -7.77017692 0.55895192 8.45144487 -5.34408109 12.48420537
349 350 351 352 353 354
20.61525152 -28.22291210 -55.87805933 -18.63018801 59.48639862 -25.00749911
355 356 357 358 359 360
15.46958447 -11.85660036 -3.48632207 -7.05022755 -46.78169201 28.48291685
361 362 363 364 365 366
-23.91768479 -2.58328077 -39.11996097 -2.48902480 14.18365352 34.32799395
367 368 369 370 371
-18.36480841 4.41697656 -17.45665345 -4.81726374 7.35916446
> postscript(file="/var/www/html/rcomp/tmp/65pu71291067944.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 = 371
Frequency = 1
lag(myerror, k = 1) myerror
0 35.36455085 NA
1 6.70454787 35.36455085
2 15.71062614 6.70454787
3 -17.70487525 15.71062614
4 -32.72943808 -17.70487525
5 22.85015206 -32.72943808
6 14.19007016 22.85015206
7 0.09085850 14.19007016
8 -15.28821207 0.09085850
9 6.80757607 -15.28821207
10 15.17090066 6.80757607
11 5.49995306 15.17090066
12 38.94272339 5.49995306
13 15.03911885 38.94272339
14 30.51684453 15.03911885
15 47.32747322 30.51684453
16 -23.74735870 47.32747322
17 68.26954937 -23.74735870
18 -7.16310017 68.26954937
19 -10.39740726 -7.16310017
20 34.97041893 -10.39740726
21 -38.88865949 34.97041893
22 13.43880375 -38.88865949
23 25.64034664 13.43880375
24 9.09507076 25.64034664
25 -20.73244136 9.09507076
26 -21.70368064 -20.73244136
27 -16.12209333 -21.70368064
28 -40.86872511 -16.12209333
29 1.25094181 -40.86872511
30 -37.19274129 1.25094181
31 5.80843094 -37.19274129
32 -26.93822591 5.80843094
33 8.46085742 -26.93822591
34 3.46096360 8.46085742
35 -49.60178460 3.46096360
36 -21.50767250 -49.60178460
37 -0.25801950 -21.50767250
38 -0.58435494 -0.25801950
39 2.74213621 -0.58435494
40 -37.43070280 2.74213621
41 14.97041996 -37.43070280
42 3.15585539 14.97041996
43 23.82859788 3.15585539
44 1.57971852 23.82859788
45 0.92178992 1.57971852
46 -22.43749078 0.92178992
47 -29.20590913 -22.43749078
48 -3.46742952 -29.20590913
49 -13.34452009 -3.46742952
50 20.22753544 -13.34452009
51 13.59103779 20.22753544
52 -48.90226116 13.59103779
53 25.72422574 -48.90226116
54 12.78674913 25.72422574
55 -3.19774990 12.78674913
56 -10.70869784 -3.19774990
57 -12.25107071 -10.70869784
58 -9.20950833 -12.25107071
59 -17.62237133 -9.20950833
60 -29.07737849 -17.62237133
61 5.63250448 -29.07737849
62 29.69988539 5.63250448
63 -4.28649747 29.69988539
64 -55.20646283 -4.28649747
65 17.18761035 -55.20646283
66 8.46622580 17.18761035
67 25.20571149 8.46622580
68 8.82303899 25.20571149
69 20.77353940 8.82303899
70 31.12674882 20.77353940
71 45.08491974 31.12674882
72 33.12569716 45.08491974
73 29.28232259 33.12569716
74 22.11560362 29.28232259
75 4.51780331 22.11560362
76 -67.60407781 4.51780331
77 23.66578105 -67.60407781
78 11.89343862 23.66578105
79 15.30595114 11.89343862
80 -32.72982460 15.30595114
81 -2.09993657 -32.72982460
82 -11.78182257 -2.09993657
83 -7.33445560 -11.78182257
84 -19.11045903 -7.33445560
85 -4.63383287 -19.11045903
86 25.60006165 -4.63383287
87 -25.86042073 25.60006165
88 -52.27869992 -25.86042073
89 -1.46746200 -52.27869992
90 17.39866333 -1.46746200
91 -3.38529936 17.39866333
92 9.28413585 -3.38529936
93 2.61747151 9.28413585
94 3.59742450 2.61747151
95 -28.13589843 3.59742450
96 -8.29006250 -28.13589843
97 21.39552900 -8.29006250
98 -0.19624737 21.39552900
99 28.83024379 -0.19624737
100 -34.61240401 28.83024379
101 2.53285665 -34.61240401
102 -21.21274221 2.53285665
103 -3.45547830 -21.21274221
104 -3.97623466 -3.45547830
105 27.44323145 -3.97623466
106 3.05092354 27.44323145
107 -20.19220781 3.05092354
108 -22.94775131 -20.19220781
109 -5.52261937 -22.94775131
110 17.83334410 -5.52261937
111 20.22573538 17.83334410
112 -23.71553300 20.22573538
113 -7.18582806 -23.71553300
114 -1.85947277 -7.18582806
115 13.48821232 -1.85947277
116 10.68676606 13.48821232
117 43.45933542 10.68676606
118 18.44465181 43.45933542
119 39.75462370 18.44465181
120 57.13601424 39.75462370
121 29.35662401 57.13601424
122 33.65312346 29.35662401
123 1.90053374 33.65312346
124 -29.12924005 1.90053374
125 13.94299377 -29.12924005
126 -14.03095768 13.94299377
127 -34.30993901 -14.03095768
128 -12.80119295 -34.30993901
129 -16.39069218 -12.80119295
130 27.55715384 -16.39069218
131 -10.94161001 27.55715384
132 -5.84021874 -10.94161001
133 -15.86933987 -5.84021874
134 -33.64931490 -15.86933987
135 -1.99332132 -33.64931490
136 -26.92064300 -1.99332132
137 5.10362138 -26.92064300
138 5.30706464 5.10362138
139 1.99942397 5.30706464
140 19.18165606 1.99942397
141 19.03568125 19.18165606
142 -12.90919356 19.03568125
143 -13.78389555 -12.90919356
144 -32.81192954 -13.78389555
145 49.63856654 -32.81192954
146 -15.97888072 49.63856654
147 -1.77415177 -15.97888072
148 6.80833498 -1.77415177
149 -5.53613675 6.80833498
150 14.19021855 -5.53613675
151 -21.80899312 14.19021855
152 37.77492513 -21.80899312
153 21.98504201 37.77492513
154 49.40146985 21.98504201
155 14.94216928 49.40146985
156 25.06884756 14.94216928
157 2.77290608 25.06884756
158 -11.09266306 2.77290608
159 2.16356011 -11.09266306
160 -5.32697998 2.16356011
161 -9.43926759 -5.32697998
162 -18.26984707 -9.43926759
163 -21.32239158 -18.26984707
164 -0.06299438 -21.32239158
165 -12.71655510 -0.06299438
166 8.73673146 -12.71655510
167 -14.91076776 8.73673146
168 -22.88293966 -14.91076776
169 6.89560227 -22.88293966
170 -6.49096314 6.89560227
171 29.85162007 -6.49096314
172 -44.89102773 29.85162007
173 -16.22285503 -44.89102773
174 32.05338546 -16.22285503
175 -21.18973451 32.05338546
176 -6.78374731 -21.18973451
177 26.84008668 -6.78374731
178 1.30854507 26.84008668
179 12.79920686 1.30854507
180 15.13078935 12.79920686
181 -19.45151218 15.13078935
182 -5.40014617 -19.45151218
183 16.56941021 -5.40014617
184 -11.39936768 16.56941021
185 -18.10238320 -11.39936768
186 -7.28499324 -18.10238320
187 -11.50405135 -7.28499324
188 7.45205065 -11.50405135
189 24.13143999 7.45205065
190 -9.06876058 24.13143999
191 -1.13311780 -9.06876058
192 -15.43747382 -1.13311780
193 -1.55540711 -15.43747382
194 -0.73323678 -1.55540711
195 -10.02881457 -0.73323678
196 19.26731213 -10.02881457
197 -55.05102952 19.26731213
198 17.37379390 -55.05102952
199 -12.70526458 17.37379390
200 7.84102900 -12.70526458
201 -11.05015639 7.84102900
202 5.40611862 -11.05015639
203 -22.16344956 5.40611862
204 11.64667746 -22.16344956
205 -26.26504933 11.64667746
206 16.37597191 -26.26504933
207 -8.66106209 16.37597191
208 9.99636726 -8.66106209
209 -41.32304707 9.99636726
210 2.46959223 -41.32304707
211 -17.35276107 2.46959223
212 -0.38983909 -17.35276107
213 -6.65021979 -0.38983909
214 -15.04927053 -6.65021979
215 -31.58719093 -15.04927053
216 -26.96342395 -31.58719093
217 6.22737850 -26.96342395
218 9.03644522 6.22737850
219 23.26944961 9.03644522
220 4.26304706 23.26944961
221 -34.16425993 4.26304706
222 4.73926048 -34.16425993
223 -17.99726912 4.73926048
224 7.97791339 -17.99726912
225 -14.04951725 7.97791339
226 2.49204513 -14.04951725
227 -28.38978358 2.49204513
228 -11.47283658 -28.38978358
229 -4.98969719 -11.47283658
230 5.64718578 -4.98969719
231 -4.09337300 5.64718578
232 40.24060796 -4.09337300
233 -18.07696775 40.24060796
234 -2.87375409 -18.07696775
235 9.09845206 -2.87375409
236 18.13815526 9.09845206
237 -29.45632533 18.13815526
238 -23.91445620 -29.45632533
239 -42.55590139 -23.91445620
240 6.81775079 -42.55590139
241 -17.83811391 6.81775079
242 -9.51510050 -17.83811391
243 -2.91857095 -9.51510050
244 53.66200003 -2.91857095
245 -20.30982875 53.66200003
246 -17.05320510 -20.30982875
247 -3.41938956 -17.05320510
248 1.73096514 -3.41938956
249 -19.34113975 1.73096514
250 -22.51727845 -19.34113975
251 -33.29742099 -22.51727845
252 -10.47120191 -33.29742099
253 -0.83166408 -10.47120191
254 13.03763261 -0.83166408
255 -8.59449718 13.03763261
256 31.25120798 -8.59449718
257 -2.16253620 31.25120798
258 -4.14001244 -2.16253620
259 21.81993318 -4.14001244
260 0.19067067 21.81993318
261 -38.43292844 0.19067067
262 -14.98967989 -38.43292844
263 -0.88591449 -14.98967989
264 24.52988268 -0.88591449
265 12.50313650 24.52988268
266 17.55442536 12.50313650
267 0.98114611 17.55442536
268 53.10830710 0.98114611
269 5.57272357 53.10830710
270 1.01540052 5.57272357
271 23.22929247 1.01540052
272 11.66079626 23.22929247
273 12.54562615 11.66079626
274 0.56098130 12.54562615
275 3.63938256 0.56098130
276 -6.84727238 3.63938256
277 -4.35677666 -6.84727238
278 -9.21062161 -4.35677666
279 -9.71953262 -9.21062161
280 36.38395040 -9.71953262
281 7.18491885 36.38395040
282 4.82514370 7.18491885
283 -4.30947013 4.82514370
284 -10.99643335 -4.30947013
285 2.70724744 -10.99643335
286 -14.12996431 2.70724744
287 0.88307318 -14.12996431
288 -13.36733651 0.88307318
289 2.26867653 -13.36733651
290 -13.11352101 2.26867653
291 -15.31315993 -13.11352101
292 34.56036147 -15.31315993
293 -2.57299955 34.56036147
294 -0.56082055 -2.57299955
295 -2.91068336 -0.56082055
296 -3.54370025 -2.91068336
297 -42.73894677 -3.54370025
298 -18.77715406 -42.73894677
299 -20.13767975 -18.77715406
300 4.93865413 -20.13767975
301 -13.02265112 4.93865413
302 2.86166494 -13.02265112
303 -19.09659493 2.86166494
304 29.52298015 -19.09659493
305 -8.69375248 29.52298015
306 -4.98946614 -8.69375248
307 10.79691631 -4.98946614
308 -26.45357207 10.79691631
309 4.92643075 -26.45357207
310 -4.39307992 4.92643075
311 18.51911448 -4.39307992
312 1.65422175 18.51911448
313 -17.80026352 1.65422175
314 -8.44345697 -17.80026352
315 2.71383889 -8.44345697
316 48.86797304 2.71383889
317 10.01223632 48.86797304
318 -6.84945460 10.01223632
319 48.15600835 -6.84945460
320 0.18827808 48.15600835
321 42.56659473 0.18827808
322 41.20041691 42.56659473
323 135.64004366 41.20041691
324 8.83131793 135.64004366
325 33.16947633 8.83131793
326 -8.40705106 33.16947633
327 7.04181579 -8.40705106
328 28.09786571 7.04181579
329 -6.46898171 28.09786571
330 -13.71917804 -6.46898171
331 5.64789430 -13.71917804
332 -6.42381994 5.64789430
333 -17.73975599 -6.42381994
334 -1.00961106 -17.73975599
335 28.50940332 -1.00961106
336 -18.48437834 28.50940332
337 -23.60828852 -18.48437834
338 -20.35309098 -23.60828852
339 -34.43962629 -20.35309098
340 65.06255445 -34.43962629
341 19.18880990 65.06255445
342 10.23010743 19.18880990
343 -7.77017692 10.23010743
344 0.55895192 -7.77017692
345 8.45144487 0.55895192
346 -5.34408109 8.45144487
347 12.48420537 -5.34408109
348 20.61525152 12.48420537
349 -28.22291210 20.61525152
350 -55.87805933 -28.22291210
351 -18.63018801 -55.87805933
352 59.48639862 -18.63018801
353 -25.00749911 59.48639862
354 15.46958447 -25.00749911
355 -11.85660036 15.46958447
356 -3.48632207 -11.85660036
357 -7.05022755 -3.48632207
358 -46.78169201 -7.05022755
359 28.48291685 -46.78169201
360 -23.91768479 28.48291685
361 -2.58328077 -23.91768479
362 -39.11996097 -2.58328077
363 -2.48902480 -39.11996097
364 14.18365352 -2.48902480
365 34.32799395 14.18365352
366 -18.36480841 34.32799395
367 4.41697656 -18.36480841
368 -17.45665345 4.41697656
369 -4.81726374 -17.45665345
370 7.35916446 -4.81726374
371 NA 7.35916446
> dum1 <- dum[2:length(myerror),]
> dum1
lag(myerror, k = 1) myerror
[1,] 6.70454787 35.36455085
[2,] 15.71062614 6.70454787
[3,] -17.70487525 15.71062614
[4,] -32.72943808 -17.70487525
[5,] 22.85015206 -32.72943808
[6,] 14.19007016 22.85015206
[7,] 0.09085850 14.19007016
[8,] -15.28821207 0.09085850
[9,] 6.80757607 -15.28821207
[10,] 15.17090066 6.80757607
[11,] 5.49995306 15.17090066
[12,] 38.94272339 5.49995306
[13,] 15.03911885 38.94272339
[14,] 30.51684453 15.03911885
[15,] 47.32747322 30.51684453
[16,] -23.74735870 47.32747322
[17,] 68.26954937 -23.74735870
[18,] -7.16310017 68.26954937
[19,] -10.39740726 -7.16310017
[20,] 34.97041893 -10.39740726
[21,] -38.88865949 34.97041893
[22,] 13.43880375 -38.88865949
[23,] 25.64034664 13.43880375
[24,] 9.09507076 25.64034664
[25,] -20.73244136 9.09507076
[26,] -21.70368064 -20.73244136
[27,] -16.12209333 -21.70368064
[28,] -40.86872511 -16.12209333
[29,] 1.25094181 -40.86872511
[30,] -37.19274129 1.25094181
[31,] 5.80843094 -37.19274129
[32,] -26.93822591 5.80843094
[33,] 8.46085742 -26.93822591
[34,] 3.46096360 8.46085742
[35,] -49.60178460 3.46096360
[36,] -21.50767250 -49.60178460
[37,] -0.25801950 -21.50767250
[38,] -0.58435494 -0.25801950
[39,] 2.74213621 -0.58435494
[40,] -37.43070280 2.74213621
[41,] 14.97041996 -37.43070280
[42,] 3.15585539 14.97041996
[43,] 23.82859788 3.15585539
[44,] 1.57971852 23.82859788
[45,] 0.92178992 1.57971852
[46,] -22.43749078 0.92178992
[47,] -29.20590913 -22.43749078
[48,] -3.46742952 -29.20590913
[49,] -13.34452009 -3.46742952
[50,] 20.22753544 -13.34452009
[51,] 13.59103779 20.22753544
[52,] -48.90226116 13.59103779
[53,] 25.72422574 -48.90226116
[54,] 12.78674913 25.72422574
[55,] -3.19774990 12.78674913
[56,] -10.70869784 -3.19774990
[57,] -12.25107071 -10.70869784
[58,] -9.20950833 -12.25107071
[59,] -17.62237133 -9.20950833
[60,] -29.07737849 -17.62237133
[61,] 5.63250448 -29.07737849
[62,] 29.69988539 5.63250448
[63,] -4.28649747 29.69988539
[64,] -55.20646283 -4.28649747
[65,] 17.18761035 -55.20646283
[66,] 8.46622580 17.18761035
[67,] 25.20571149 8.46622580
[68,] 8.82303899 25.20571149
[69,] 20.77353940 8.82303899
[70,] 31.12674882 20.77353940
[71,] 45.08491974 31.12674882
[72,] 33.12569716 45.08491974
[73,] 29.28232259 33.12569716
[74,] 22.11560362 29.28232259
[75,] 4.51780331 22.11560362
[76,] -67.60407781 4.51780331
[77,] 23.66578105 -67.60407781
[78,] 11.89343862 23.66578105
[79,] 15.30595114 11.89343862
[80,] -32.72982460 15.30595114
[81,] -2.09993657 -32.72982460
[82,] -11.78182257 -2.09993657
[83,] -7.33445560 -11.78182257
[84,] -19.11045903 -7.33445560
[85,] -4.63383287 -19.11045903
[86,] 25.60006165 -4.63383287
[87,] -25.86042073 25.60006165
[88,] -52.27869992 -25.86042073
[89,] -1.46746200 -52.27869992
[90,] 17.39866333 -1.46746200
[91,] -3.38529936 17.39866333
[92,] 9.28413585 -3.38529936
[93,] 2.61747151 9.28413585
[94,] 3.59742450 2.61747151
[95,] -28.13589843 3.59742450
[96,] -8.29006250 -28.13589843
[97,] 21.39552900 -8.29006250
[98,] -0.19624737 21.39552900
[99,] 28.83024379 -0.19624737
[100,] -34.61240401 28.83024379
[101,] 2.53285665 -34.61240401
[102,] -21.21274221 2.53285665
[103,] -3.45547830 -21.21274221
[104,] -3.97623466 -3.45547830
[105,] 27.44323145 -3.97623466
[106,] 3.05092354 27.44323145
[107,] -20.19220781 3.05092354
[108,] -22.94775131 -20.19220781
[109,] -5.52261937 -22.94775131
[110,] 17.83334410 -5.52261937
[111,] 20.22573538 17.83334410
[112,] -23.71553300 20.22573538
[113,] -7.18582806 -23.71553300
[114,] -1.85947277 -7.18582806
[115,] 13.48821232 -1.85947277
[116,] 10.68676606 13.48821232
[117,] 43.45933542 10.68676606
[118,] 18.44465181 43.45933542
[119,] 39.75462370 18.44465181
[120,] 57.13601424 39.75462370
[121,] 29.35662401 57.13601424
[122,] 33.65312346 29.35662401
[123,] 1.90053374 33.65312346
[124,] -29.12924005 1.90053374
[125,] 13.94299377 -29.12924005
[126,] -14.03095768 13.94299377
[127,] -34.30993901 -14.03095768
[128,] -12.80119295 -34.30993901
[129,] -16.39069218 -12.80119295
[130,] 27.55715384 -16.39069218
[131,] -10.94161001 27.55715384
[132,] -5.84021874 -10.94161001
[133,] -15.86933987 -5.84021874
[134,] -33.64931490 -15.86933987
[135,] -1.99332132 -33.64931490
[136,] -26.92064300 -1.99332132
[137,] 5.10362138 -26.92064300
[138,] 5.30706464 5.10362138
[139,] 1.99942397 5.30706464
[140,] 19.18165606 1.99942397
[141,] 19.03568125 19.18165606
[142,] -12.90919356 19.03568125
[143,] -13.78389555 -12.90919356
[144,] -32.81192954 -13.78389555
[145,] 49.63856654 -32.81192954
[146,] -15.97888072 49.63856654
[147,] -1.77415177 -15.97888072
[148,] 6.80833498 -1.77415177
[149,] -5.53613675 6.80833498
[150,] 14.19021855 -5.53613675
[151,] -21.80899312 14.19021855
[152,] 37.77492513 -21.80899312
[153,] 21.98504201 37.77492513
[154,] 49.40146985 21.98504201
[155,] 14.94216928 49.40146985
[156,] 25.06884756 14.94216928
[157,] 2.77290608 25.06884756
[158,] -11.09266306 2.77290608
[159,] 2.16356011 -11.09266306
[160,] -5.32697998 2.16356011
[161,] -9.43926759 -5.32697998
[162,] -18.26984707 -9.43926759
[163,] -21.32239158 -18.26984707
[164,] -0.06299438 -21.32239158
[165,] -12.71655510 -0.06299438
[166,] 8.73673146 -12.71655510
[167,] -14.91076776 8.73673146
[168,] -22.88293966 -14.91076776
[169,] 6.89560227 -22.88293966
[170,] -6.49096314 6.89560227
[171,] 29.85162007 -6.49096314
[172,] -44.89102773 29.85162007
[173,] -16.22285503 -44.89102773
[174,] 32.05338546 -16.22285503
[175,] -21.18973451 32.05338546
[176,] -6.78374731 -21.18973451
[177,] 26.84008668 -6.78374731
[178,] 1.30854507 26.84008668
[179,] 12.79920686 1.30854507
[180,] 15.13078935 12.79920686
[181,] -19.45151218 15.13078935
[182,] -5.40014617 -19.45151218
[183,] 16.56941021 -5.40014617
[184,] -11.39936768 16.56941021
[185,] -18.10238320 -11.39936768
[186,] -7.28499324 -18.10238320
[187,] -11.50405135 -7.28499324
[188,] 7.45205065 -11.50405135
[189,] 24.13143999 7.45205065
[190,] -9.06876058 24.13143999
[191,] -1.13311780 -9.06876058
[192,] -15.43747382 -1.13311780
[193,] -1.55540711 -15.43747382
[194,] -0.73323678 -1.55540711
[195,] -10.02881457 -0.73323678
[196,] 19.26731213 -10.02881457
[197,] -55.05102952 19.26731213
[198,] 17.37379390 -55.05102952
[199,] -12.70526458 17.37379390
[200,] 7.84102900 -12.70526458
[201,] -11.05015639 7.84102900
[202,] 5.40611862 -11.05015639
[203,] -22.16344956 5.40611862
[204,] 11.64667746 -22.16344956
[205,] -26.26504933 11.64667746
[206,] 16.37597191 -26.26504933
[207,] -8.66106209 16.37597191
[208,] 9.99636726 -8.66106209
[209,] -41.32304707 9.99636726
[210,] 2.46959223 -41.32304707
[211,] -17.35276107 2.46959223
[212,] -0.38983909 -17.35276107
[213,] -6.65021979 -0.38983909
[214,] -15.04927053 -6.65021979
[215,] -31.58719093 -15.04927053
[216,] -26.96342395 -31.58719093
[217,] 6.22737850 -26.96342395
[218,] 9.03644522 6.22737850
[219,] 23.26944961 9.03644522
[220,] 4.26304706 23.26944961
[221,] -34.16425993 4.26304706
[222,] 4.73926048 -34.16425993
[223,] -17.99726912 4.73926048
[224,] 7.97791339 -17.99726912
[225,] -14.04951725 7.97791339
[226,] 2.49204513 -14.04951725
[227,] -28.38978358 2.49204513
[228,] -11.47283658 -28.38978358
[229,] -4.98969719 -11.47283658
[230,] 5.64718578 -4.98969719
[231,] -4.09337300 5.64718578
[232,] 40.24060796 -4.09337300
[233,] -18.07696775 40.24060796
[234,] -2.87375409 -18.07696775
[235,] 9.09845206 -2.87375409
[236,] 18.13815526 9.09845206
[237,] -29.45632533 18.13815526
[238,] -23.91445620 -29.45632533
[239,] -42.55590139 -23.91445620
[240,] 6.81775079 -42.55590139
[241,] -17.83811391 6.81775079
[242,] -9.51510050 -17.83811391
[243,] -2.91857095 -9.51510050
[244,] 53.66200003 -2.91857095
[245,] -20.30982875 53.66200003
[246,] -17.05320510 -20.30982875
[247,] -3.41938956 -17.05320510
[248,] 1.73096514 -3.41938956
[249,] -19.34113975 1.73096514
[250,] -22.51727845 -19.34113975
[251,] -33.29742099 -22.51727845
[252,] -10.47120191 -33.29742099
[253,] -0.83166408 -10.47120191
[254,] 13.03763261 -0.83166408
[255,] -8.59449718 13.03763261
[256,] 31.25120798 -8.59449718
[257,] -2.16253620 31.25120798
[258,] -4.14001244 -2.16253620
[259,] 21.81993318 -4.14001244
[260,] 0.19067067 21.81993318
[261,] -38.43292844 0.19067067
[262,] -14.98967989 -38.43292844
[263,] -0.88591449 -14.98967989
[264,] 24.52988268 -0.88591449
[265,] 12.50313650 24.52988268
[266,] 17.55442536 12.50313650
[267,] 0.98114611 17.55442536
[268,] 53.10830710 0.98114611
[269,] 5.57272357 53.10830710
[270,] 1.01540052 5.57272357
[271,] 23.22929247 1.01540052
[272,] 11.66079626 23.22929247
[273,] 12.54562615 11.66079626
[274,] 0.56098130 12.54562615
[275,] 3.63938256 0.56098130
[276,] -6.84727238 3.63938256
[277,] -4.35677666 -6.84727238
[278,] -9.21062161 -4.35677666
[279,] -9.71953262 -9.21062161
[280,] 36.38395040 -9.71953262
[281,] 7.18491885 36.38395040
[282,] 4.82514370 7.18491885
[283,] -4.30947013 4.82514370
[284,] -10.99643335 -4.30947013
[285,] 2.70724744 -10.99643335
[286,] -14.12996431 2.70724744
[287,] 0.88307318 -14.12996431
[288,] -13.36733651 0.88307318
[289,] 2.26867653 -13.36733651
[290,] -13.11352101 2.26867653
[291,] -15.31315993 -13.11352101
[292,] 34.56036147 -15.31315993
[293,] -2.57299955 34.56036147
[294,] -0.56082055 -2.57299955
[295,] -2.91068336 -0.56082055
[296,] -3.54370025 -2.91068336
[297,] -42.73894677 -3.54370025
[298,] -18.77715406 -42.73894677
[299,] -20.13767975 -18.77715406
[300,] 4.93865413 -20.13767975
[301,] -13.02265112 4.93865413
[302,] 2.86166494 -13.02265112
[303,] -19.09659493 2.86166494
[304,] 29.52298015 -19.09659493
[305,] -8.69375248 29.52298015
[306,] -4.98946614 -8.69375248
[307,] 10.79691631 -4.98946614
[308,] -26.45357207 10.79691631
[309,] 4.92643075 -26.45357207
[310,] -4.39307992 4.92643075
[311,] 18.51911448 -4.39307992
[312,] 1.65422175 18.51911448
[313,] -17.80026352 1.65422175
[314,] -8.44345697 -17.80026352
[315,] 2.71383889 -8.44345697
[316,] 48.86797304 2.71383889
[317,] 10.01223632 48.86797304
[318,] -6.84945460 10.01223632
[319,] 48.15600835 -6.84945460
[320,] 0.18827808 48.15600835
[321,] 42.56659473 0.18827808
[322,] 41.20041691 42.56659473
[323,] 135.64004366 41.20041691
[324,] 8.83131793 135.64004366
[325,] 33.16947633 8.83131793
[326,] -8.40705106 33.16947633
[327,] 7.04181579 -8.40705106
[328,] 28.09786571 7.04181579
[329,] -6.46898171 28.09786571
[330,] -13.71917804 -6.46898171
[331,] 5.64789430 -13.71917804
[332,] -6.42381994 5.64789430
[333,] -17.73975599 -6.42381994
[334,] -1.00961106 -17.73975599
[335,] 28.50940332 -1.00961106
[336,] -18.48437834 28.50940332
[337,] -23.60828852 -18.48437834
[338,] -20.35309098 -23.60828852
[339,] -34.43962629 -20.35309098
[340,] 65.06255445 -34.43962629
[341,] 19.18880990 65.06255445
[342,] 10.23010743 19.18880990
[343,] -7.77017692 10.23010743
[344,] 0.55895192 -7.77017692
[345,] 8.45144487 0.55895192
[346,] -5.34408109 8.45144487
[347,] 12.48420537 -5.34408109
[348,] 20.61525152 12.48420537
[349,] -28.22291210 20.61525152
[350,] -55.87805933 -28.22291210
[351,] -18.63018801 -55.87805933
[352,] 59.48639862 -18.63018801
[353,] -25.00749911 59.48639862
[354,] 15.46958447 -25.00749911
[355,] -11.85660036 15.46958447
[356,] -3.48632207 -11.85660036
[357,] -7.05022755 -3.48632207
[358,] -46.78169201 -7.05022755
[359,] 28.48291685 -46.78169201
[360,] -23.91768479 28.48291685
[361,] -2.58328077 -23.91768479
[362,] -39.11996097 -2.58328077
[363,] -2.48902480 -39.11996097
[364,] 14.18365352 -2.48902480
[365,] 34.32799395 14.18365352
[366,] -18.36480841 34.32799395
[367,] 4.41697656 -18.36480841
[368,] -17.45665345 4.41697656
[369,] -4.81726374 -17.45665345
[370,] 7.35916446 -4.81726374
> z <- as.data.frame(dum1)
> z
lag(myerror, k = 1) myerror
1 6.70454787 35.36455085
2 15.71062614 6.70454787
3 -17.70487525 15.71062614
4 -32.72943808 -17.70487525
5 22.85015206 -32.72943808
6 14.19007016 22.85015206
7 0.09085850 14.19007016
8 -15.28821207 0.09085850
9 6.80757607 -15.28821207
10 15.17090066 6.80757607
11 5.49995306 15.17090066
12 38.94272339 5.49995306
13 15.03911885 38.94272339
14 30.51684453 15.03911885
15 47.32747322 30.51684453
16 -23.74735870 47.32747322
17 68.26954937 -23.74735870
18 -7.16310017 68.26954937
19 -10.39740726 -7.16310017
20 34.97041893 -10.39740726
21 -38.88865949 34.97041893
22 13.43880375 -38.88865949
23 25.64034664 13.43880375
24 9.09507076 25.64034664
25 -20.73244136 9.09507076
26 -21.70368064 -20.73244136
27 -16.12209333 -21.70368064
28 -40.86872511 -16.12209333
29 1.25094181 -40.86872511
30 -37.19274129 1.25094181
31 5.80843094 -37.19274129
32 -26.93822591 5.80843094
33 8.46085742 -26.93822591
34 3.46096360 8.46085742
35 -49.60178460 3.46096360
36 -21.50767250 -49.60178460
37 -0.25801950 -21.50767250
38 -0.58435494 -0.25801950
39 2.74213621 -0.58435494
40 -37.43070280 2.74213621
41 14.97041996 -37.43070280
42 3.15585539 14.97041996
43 23.82859788 3.15585539
44 1.57971852 23.82859788
45 0.92178992 1.57971852
46 -22.43749078 0.92178992
47 -29.20590913 -22.43749078
48 -3.46742952 -29.20590913
49 -13.34452009 -3.46742952
50 20.22753544 -13.34452009
51 13.59103779 20.22753544
52 -48.90226116 13.59103779
53 25.72422574 -48.90226116
54 12.78674913 25.72422574
55 -3.19774990 12.78674913
56 -10.70869784 -3.19774990
57 -12.25107071 -10.70869784
58 -9.20950833 -12.25107071
59 -17.62237133 -9.20950833
60 -29.07737849 -17.62237133
61 5.63250448 -29.07737849
62 29.69988539 5.63250448
63 -4.28649747 29.69988539
64 -55.20646283 -4.28649747
65 17.18761035 -55.20646283
66 8.46622580 17.18761035
67 25.20571149 8.46622580
68 8.82303899 25.20571149
69 20.77353940 8.82303899
70 31.12674882 20.77353940
71 45.08491974 31.12674882
72 33.12569716 45.08491974
73 29.28232259 33.12569716
74 22.11560362 29.28232259
75 4.51780331 22.11560362
76 -67.60407781 4.51780331
77 23.66578105 -67.60407781
78 11.89343862 23.66578105
79 15.30595114 11.89343862
80 -32.72982460 15.30595114
81 -2.09993657 -32.72982460
82 -11.78182257 -2.09993657
83 -7.33445560 -11.78182257
84 -19.11045903 -7.33445560
85 -4.63383287 -19.11045903
86 25.60006165 -4.63383287
87 -25.86042073 25.60006165
88 -52.27869992 -25.86042073
89 -1.46746200 -52.27869992
90 17.39866333 -1.46746200
91 -3.38529936 17.39866333
92 9.28413585 -3.38529936
93 2.61747151 9.28413585
94 3.59742450 2.61747151
95 -28.13589843 3.59742450
96 -8.29006250 -28.13589843
97 21.39552900 -8.29006250
98 -0.19624737 21.39552900
99 28.83024379 -0.19624737
100 -34.61240401 28.83024379
101 2.53285665 -34.61240401
102 -21.21274221 2.53285665
103 -3.45547830 -21.21274221
104 -3.97623466 -3.45547830
105 27.44323145 -3.97623466
106 3.05092354 27.44323145
107 -20.19220781 3.05092354
108 -22.94775131 -20.19220781
109 -5.52261937 -22.94775131
110 17.83334410 -5.52261937
111 20.22573538 17.83334410
112 -23.71553300 20.22573538
113 -7.18582806 -23.71553300
114 -1.85947277 -7.18582806
115 13.48821232 -1.85947277
116 10.68676606 13.48821232
117 43.45933542 10.68676606
118 18.44465181 43.45933542
119 39.75462370 18.44465181
120 57.13601424 39.75462370
121 29.35662401 57.13601424
122 33.65312346 29.35662401
123 1.90053374 33.65312346
124 -29.12924005 1.90053374
125 13.94299377 -29.12924005
126 -14.03095768 13.94299377
127 -34.30993901 -14.03095768
128 -12.80119295 -34.30993901
129 -16.39069218 -12.80119295
130 27.55715384 -16.39069218
131 -10.94161001 27.55715384
132 -5.84021874 -10.94161001
133 -15.86933987 -5.84021874
134 -33.64931490 -15.86933987
135 -1.99332132 -33.64931490
136 -26.92064300 -1.99332132
137 5.10362138 -26.92064300
138 5.30706464 5.10362138
139 1.99942397 5.30706464
140 19.18165606 1.99942397
141 19.03568125 19.18165606
142 -12.90919356 19.03568125
143 -13.78389555 -12.90919356
144 -32.81192954 -13.78389555
145 49.63856654 -32.81192954
146 -15.97888072 49.63856654
147 -1.77415177 -15.97888072
148 6.80833498 -1.77415177
149 -5.53613675 6.80833498
150 14.19021855 -5.53613675
151 -21.80899312 14.19021855
152 37.77492513 -21.80899312
153 21.98504201 37.77492513
154 49.40146985 21.98504201
155 14.94216928 49.40146985
156 25.06884756 14.94216928
157 2.77290608 25.06884756
158 -11.09266306 2.77290608
159 2.16356011 -11.09266306
160 -5.32697998 2.16356011
161 -9.43926759 -5.32697998
162 -18.26984707 -9.43926759
163 -21.32239158 -18.26984707
164 -0.06299438 -21.32239158
165 -12.71655510 -0.06299438
166 8.73673146 -12.71655510
167 -14.91076776 8.73673146
168 -22.88293966 -14.91076776
169 6.89560227 -22.88293966
170 -6.49096314 6.89560227
171 29.85162007 -6.49096314
172 -44.89102773 29.85162007
173 -16.22285503 -44.89102773
174 32.05338546 -16.22285503
175 -21.18973451 32.05338546
176 -6.78374731 -21.18973451
177 26.84008668 -6.78374731
178 1.30854507 26.84008668
179 12.79920686 1.30854507
180 15.13078935 12.79920686
181 -19.45151218 15.13078935
182 -5.40014617 -19.45151218
183 16.56941021 -5.40014617
184 -11.39936768 16.56941021
185 -18.10238320 -11.39936768
186 -7.28499324 -18.10238320
187 -11.50405135 -7.28499324
188 7.45205065 -11.50405135
189 24.13143999 7.45205065
190 -9.06876058 24.13143999
191 -1.13311780 -9.06876058
192 -15.43747382 -1.13311780
193 -1.55540711 -15.43747382
194 -0.73323678 -1.55540711
195 -10.02881457 -0.73323678
196 19.26731213 -10.02881457
197 -55.05102952 19.26731213
198 17.37379390 -55.05102952
199 -12.70526458 17.37379390
200 7.84102900 -12.70526458
201 -11.05015639 7.84102900
202 5.40611862 -11.05015639
203 -22.16344956 5.40611862
204 11.64667746 -22.16344956
205 -26.26504933 11.64667746
206 16.37597191 -26.26504933
207 -8.66106209 16.37597191
208 9.99636726 -8.66106209
209 -41.32304707 9.99636726
210 2.46959223 -41.32304707
211 -17.35276107 2.46959223
212 -0.38983909 -17.35276107
213 -6.65021979 -0.38983909
214 -15.04927053 -6.65021979
215 -31.58719093 -15.04927053
216 -26.96342395 -31.58719093
217 6.22737850 -26.96342395
218 9.03644522 6.22737850
219 23.26944961 9.03644522
220 4.26304706 23.26944961
221 -34.16425993 4.26304706
222 4.73926048 -34.16425993
223 -17.99726912 4.73926048
224 7.97791339 -17.99726912
225 -14.04951725 7.97791339
226 2.49204513 -14.04951725
227 -28.38978358 2.49204513
228 -11.47283658 -28.38978358
229 -4.98969719 -11.47283658
230 5.64718578 -4.98969719
231 -4.09337300 5.64718578
232 40.24060796 -4.09337300
233 -18.07696775 40.24060796
234 -2.87375409 -18.07696775
235 9.09845206 -2.87375409
236 18.13815526 9.09845206
237 -29.45632533 18.13815526
238 -23.91445620 -29.45632533
239 -42.55590139 -23.91445620
240 6.81775079 -42.55590139
241 -17.83811391 6.81775079
242 -9.51510050 -17.83811391
243 -2.91857095 -9.51510050
244 53.66200003 -2.91857095
245 -20.30982875 53.66200003
246 -17.05320510 -20.30982875
247 -3.41938956 -17.05320510
248 1.73096514 -3.41938956
249 -19.34113975 1.73096514
250 -22.51727845 -19.34113975
251 -33.29742099 -22.51727845
252 -10.47120191 -33.29742099
253 -0.83166408 -10.47120191
254 13.03763261 -0.83166408
255 -8.59449718 13.03763261
256 31.25120798 -8.59449718
257 -2.16253620 31.25120798
258 -4.14001244 -2.16253620
259 21.81993318 -4.14001244
260 0.19067067 21.81993318
261 -38.43292844 0.19067067
262 -14.98967989 -38.43292844
263 -0.88591449 -14.98967989
264 24.52988268 -0.88591449
265 12.50313650 24.52988268
266 17.55442536 12.50313650
267 0.98114611 17.55442536
268 53.10830710 0.98114611
269 5.57272357 53.10830710
270 1.01540052 5.57272357
271 23.22929247 1.01540052
272 11.66079626 23.22929247
273 12.54562615 11.66079626
274 0.56098130 12.54562615
275 3.63938256 0.56098130
276 -6.84727238 3.63938256
277 -4.35677666 -6.84727238
278 -9.21062161 -4.35677666
279 -9.71953262 -9.21062161
280 36.38395040 -9.71953262
281 7.18491885 36.38395040
282 4.82514370 7.18491885
283 -4.30947013 4.82514370
284 -10.99643335 -4.30947013
285 2.70724744 -10.99643335
286 -14.12996431 2.70724744
287 0.88307318 -14.12996431
288 -13.36733651 0.88307318
289 2.26867653 -13.36733651
290 -13.11352101 2.26867653
291 -15.31315993 -13.11352101
292 34.56036147 -15.31315993
293 -2.57299955 34.56036147
294 -0.56082055 -2.57299955
295 -2.91068336 -0.56082055
296 -3.54370025 -2.91068336
297 -42.73894677 -3.54370025
298 -18.77715406 -42.73894677
299 -20.13767975 -18.77715406
300 4.93865413 -20.13767975
301 -13.02265112 4.93865413
302 2.86166494 -13.02265112
303 -19.09659493 2.86166494
304 29.52298015 -19.09659493
305 -8.69375248 29.52298015
306 -4.98946614 -8.69375248
307 10.79691631 -4.98946614
308 -26.45357207 10.79691631
309 4.92643075 -26.45357207
310 -4.39307992 4.92643075
311 18.51911448 -4.39307992
312 1.65422175 18.51911448
313 -17.80026352 1.65422175
314 -8.44345697 -17.80026352
315 2.71383889 -8.44345697
316 48.86797304 2.71383889
317 10.01223632 48.86797304
318 -6.84945460 10.01223632
319 48.15600835 -6.84945460
320 0.18827808 48.15600835
321 42.56659473 0.18827808
322 41.20041691 42.56659473
323 135.64004366 41.20041691
324 8.83131793 135.64004366
325 33.16947633 8.83131793
326 -8.40705106 33.16947633
327 7.04181579 -8.40705106
328 28.09786571 7.04181579
329 -6.46898171 28.09786571
330 -13.71917804 -6.46898171
331 5.64789430 -13.71917804
332 -6.42381994 5.64789430
333 -17.73975599 -6.42381994
334 -1.00961106 -17.73975599
335 28.50940332 -1.00961106
336 -18.48437834 28.50940332
337 -23.60828852 -18.48437834
338 -20.35309098 -23.60828852
339 -34.43962629 -20.35309098
340 65.06255445 -34.43962629
341 19.18880990 65.06255445
342 10.23010743 19.18880990
343 -7.77017692 10.23010743
344 0.55895192 -7.77017692
345 8.45144487 0.55895192
346 -5.34408109 8.45144487
347 12.48420537 -5.34408109
348 20.61525152 12.48420537
349 -28.22291210 20.61525152
350 -55.87805933 -28.22291210
351 -18.63018801 -55.87805933
352 59.48639862 -18.63018801
353 -25.00749911 59.48639862
354 15.46958447 -25.00749911
355 -11.85660036 15.46958447
356 -3.48632207 -11.85660036
357 -7.05022755 -3.48632207
358 -46.78169201 -7.05022755
359 28.48291685 -46.78169201
360 -23.91768479 28.48291685
361 -2.58328077 -23.91768479
362 -39.11996097 -2.58328077
363 -2.48902480 -39.11996097
364 14.18365352 -2.48902480
365 34.32799395 14.18365352
366 -18.36480841 34.32799395
367 4.41697656 -18.36480841
368 -17.45665345 4.41697656
369 -4.81726374 -17.45665345
370 7.35916446 -4.81726374
> 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/7yyta1291067944.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> acf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/8jhdq1291067945.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> pacf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Partial Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/9jhdq1291067945.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> opar <- par(mfrow = c(2,2), oma = c(0, 0, 1.1, 0))
> plot(mylm, las = 1, sub='Residual Diagnostics')
> par(opar)
> dev.off()
null device
1
> if (n > n25) {
+ postscript(file="/var/www/html/rcomp/tmp/10jhdq1291067945.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
+ plot(kp3:nmkm3,gqarr[,2], main='Goldfeld-Quandt test',ylab='2-sided p-value',xlab='breakpoint')
+ grid()
+ dev.off()
+ }
null device
1
>
> #Note: the /var/www/html/rcomp/createtable file can be downloaded at http://www.wessa.net/cretab
> load(file="/var/www/html/rcomp/createtable")
>
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a, 'Multiple Linear Regression - Estimated Regression Equation', 1, TRUE)
> a<-table.row.end(a)
> myeq <- colnames(x)[1]
> myeq <- paste(myeq, '[t] = ', sep='')
> for (i in 1:k){
+ if (mysum$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/11niuw1291067945.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/12qjsj1291067945.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/13xjpv1291067945.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/14pb6g1291067945.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/15btn41291067945.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/1673lv1291067945.tab")
+ }
>
> try(system("convert tmp/12ovj1291067944.ps tmp/12ovj1291067944.png",intern=TRUE))
character(0)
> try(system("convert tmp/2dydm1291067944.ps tmp/2dydm1291067944.png",intern=TRUE))
character(0)
> try(system("convert tmp/3dydm1291067944.ps tmp/3dydm1291067944.png",intern=TRUE))
character(0)
> try(system("convert tmp/45pu71291067944.ps tmp/45pu71291067944.png",intern=TRUE))
character(0)
> try(system("convert tmp/55pu71291067944.ps tmp/55pu71291067944.png",intern=TRUE))
character(0)
> try(system("convert tmp/65pu71291067944.ps tmp/65pu71291067944.png",intern=TRUE))
character(0)
> try(system("convert tmp/7yyta1291067944.ps tmp/7yyta1291067944.png",intern=TRUE))
character(0)
> try(system("convert tmp/8jhdq1291067945.ps tmp/8jhdq1291067945.png",intern=TRUE))
character(0)
> try(system("convert tmp/9jhdq1291067945.ps tmp/9jhdq1291067945.png",intern=TRUE))
character(0)
> try(system("convert tmp/10jhdq1291067945.ps tmp/10jhdq1291067945.png",intern=TRUE))
character(0)
>
>
> proc.time()
user system elapsed
10.303 2.129 21.397