R version 2.7.0 (2008-04-22)
Copyright (C) 2008 The R Foundation for Statistical Computing
ISBN 3-900051-07-0
R is free software and comes with ABSOLUTELY NO WARRANTY.
You are welcome to redistribute it under certain conditions.
Type 'license()' or 'licence()' for distribution details.
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Type 'contributors()' for more information and
'citation()' on how to cite R or R packages in publications.
Type 'demo()' for some demos, 'help()' for on-line help, or
'help.start()' for an HTML browser interface to help.
Type 'q()' to quit R.
> x <- array(list(13363
+ ,0
+ ,12530
+ ,0
+ ,11420
+ ,0
+ ,10948
+ ,0
+ ,10173
+ ,0
+ ,10602
+ ,0
+ ,16094
+ ,0
+ ,19631
+ ,0
+ ,17140
+ ,0
+ ,14345
+ ,0
+ ,12632
+ ,0
+ ,12894
+ ,0
+ ,11808
+ ,0
+ ,10673
+ ,0
+ ,9939
+ ,0
+ ,9890
+ ,0
+ ,9283
+ ,0
+ ,10131
+ ,0
+ ,15864
+ ,0
+ ,19283
+ ,0
+ ,16203
+ ,0
+ ,13919
+ ,0
+ ,11937
+ ,0
+ ,11795
+ ,0
+ ,11268
+ ,0
+ ,10522
+ ,0
+ ,9929
+ ,0
+ ,9725
+ ,0
+ ,9372
+ ,0
+ ,10068
+ ,0
+ ,16230
+ ,0
+ ,19115
+ ,0
+ ,18351
+ ,0
+ ,16265
+ ,0
+ ,14103
+ ,0
+ ,14115
+ ,0
+ ,13327
+ ,0
+ ,12618
+ ,0
+ ,12129
+ ,0
+ ,11775
+ ,0
+ ,11493
+ ,0
+ ,12470
+ ,0
+ ,20792
+ ,0
+ ,22337
+ ,0
+ ,21325
+ ,0
+ ,18581
+ ,0
+ ,16475
+ ,0
+ ,16581
+ ,0
+ ,15745
+ ,0
+ ,14453
+ ,0
+ ,13712
+ ,0
+ ,13766
+ ,0
+ ,13336
+ ,0
+ ,15346
+ ,0
+ ,24446
+ ,0
+ ,26178
+ ,0
+ ,24628
+ ,0
+ ,21282
+ ,0
+ ,18850
+ ,0
+ ,18822
+ ,0
+ ,18060
+ ,0
+ ,17536
+ ,0
+ ,16417
+ ,0
+ ,15842
+ ,0
+ ,15188
+ ,0
+ ,16905
+ ,0
+ ,25430
+ ,0
+ ,27962
+ ,0
+ ,26607
+ ,0
+ ,23364
+ ,0
+ ,20827
+ ,0
+ ,20506
+ ,0
+ ,19181
+ ,0
+ ,18016
+ ,0
+ ,17354
+ ,0
+ ,16256
+ ,0
+ ,15770
+ ,0
+ ,17538
+ ,0
+ ,26899
+ ,1
+ ,28915
+ ,1
+ ,25247
+ ,1
+ ,22856
+ ,1
+ ,19980
+ ,1
+ ,19856
+ ,1
+ ,16994
+ ,1
+ ,16839
+ ,1
+ ,15618
+ ,1
+ ,15883
+ ,1
+ ,15513
+ ,1
+ ,17106
+ ,1
+ ,25272
+ ,1
+ ,26731
+ ,1
+ ,22891
+ ,1
+ ,19583
+ ,1
+ ,16939
+ ,1
+ ,16757
+ ,1
+ ,15435
+ ,1
+ ,14786
+ ,1
+ ,13680
+ ,1
+ ,13208
+ ,1
+ ,12707
+ ,1
+ ,14277
+ ,1
+ ,22436
+ ,1
+ ,23229
+ ,1
+ ,18241
+ ,1
+ ,16145
+ ,1
+ ,13994
+ ,1
+ ,14780
+ ,1
+ ,13100
+ ,1
+ ,12329
+ ,1
+ ,12463
+ ,1
+ ,11532
+ ,1
+ ,10784
+ ,1
+ ,13106
+ ,1
+ ,19491
+ ,1
+ ,20418
+ ,1
+ ,16094
+ ,1
+ ,14491
+ ,1
+ ,13067
+ ,1)
+ ,dim=c(2
+ ,119)
+ ,dimnames=list(c('NWWZpb'
+ ,'Dummy')
+ ,1:119))
> y <- array(NA,dim=c(2,119),dimnames=list(c('NWWZpb','Dummy'),1:119))
> 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
NWWZpb Dummy M1 M2 M3 M4 M5 M6 M7 M8 M9 M10 M11 t
1 13363 0 1 0 0 0 0 0 0 0 0 0 0 1
2 12530 0 0 1 0 0 0 0 0 0 0 0 0 2
3 11420 0 0 0 1 0 0 0 0 0 0 0 0 3
4 10948 0 0 0 0 1 0 0 0 0 0 0 0 4
5 10173 0 0 0 0 0 1 0 0 0 0 0 0 5
6 10602 0 0 0 0 0 0 1 0 0 0 0 0 6
7 16094 0 0 0 0 0 0 0 1 0 0 0 0 7
8 19631 0 0 0 0 0 0 0 0 1 0 0 0 8
9 17140 0 0 0 0 0 0 0 0 0 1 0 0 9
10 14345 0 0 0 0 0 0 0 0 0 0 1 0 10
11 12632 0 0 0 0 0 0 0 0 0 0 0 1 11
12 12894 0 0 0 0 0 0 0 0 0 0 0 0 12
13 11808 0 1 0 0 0 0 0 0 0 0 0 0 13
14 10673 0 0 1 0 0 0 0 0 0 0 0 0 14
15 9939 0 0 0 1 0 0 0 0 0 0 0 0 15
16 9890 0 0 0 0 1 0 0 0 0 0 0 0 16
17 9283 0 0 0 0 0 1 0 0 0 0 0 0 17
18 10131 0 0 0 0 0 0 1 0 0 0 0 0 18
19 15864 0 0 0 0 0 0 0 1 0 0 0 0 19
20 19283 0 0 0 0 0 0 0 0 1 0 0 0 20
21 16203 0 0 0 0 0 0 0 0 0 1 0 0 21
22 13919 0 0 0 0 0 0 0 0 0 0 1 0 22
23 11937 0 0 0 0 0 0 0 0 0 0 0 1 23
24 11795 0 0 0 0 0 0 0 0 0 0 0 0 24
25 11268 0 1 0 0 0 0 0 0 0 0 0 0 25
26 10522 0 0 1 0 0 0 0 0 0 0 0 0 26
27 9929 0 0 0 1 0 0 0 0 0 0 0 0 27
28 9725 0 0 0 0 1 0 0 0 0 0 0 0 28
29 9372 0 0 0 0 0 1 0 0 0 0 0 0 29
30 10068 0 0 0 0 0 0 1 0 0 0 0 0 30
31 16230 0 0 0 0 0 0 0 1 0 0 0 0 31
32 19115 0 0 0 0 0 0 0 0 1 0 0 0 32
33 18351 0 0 0 0 0 0 0 0 0 1 0 0 33
34 16265 0 0 0 0 0 0 0 0 0 0 1 0 34
35 14103 0 0 0 0 0 0 0 0 0 0 0 1 35
36 14115 0 0 0 0 0 0 0 0 0 0 0 0 36
37 13327 0 1 0 0 0 0 0 0 0 0 0 0 37
38 12618 0 0 1 0 0 0 0 0 0 0 0 0 38
39 12129 0 0 0 1 0 0 0 0 0 0 0 0 39
40 11775 0 0 0 0 1 0 0 0 0 0 0 0 40
41 11493 0 0 0 0 0 1 0 0 0 0 0 0 41
42 12470 0 0 0 0 0 0 1 0 0 0 0 0 42
43 20792 0 0 0 0 0 0 0 1 0 0 0 0 43
44 22337 0 0 0 0 0 0 0 0 1 0 0 0 44
45 21325 0 0 0 0 0 0 0 0 0 1 0 0 45
46 18581 0 0 0 0 0 0 0 0 0 0 1 0 46
47 16475 0 0 0 0 0 0 0 0 0 0 0 1 47
48 16581 0 0 0 0 0 0 0 0 0 0 0 0 48
49 15745 0 1 0 0 0 0 0 0 0 0 0 0 49
50 14453 0 0 1 0 0 0 0 0 0 0 0 0 50
51 13712 0 0 0 1 0 0 0 0 0 0 0 0 51
52 13766 0 0 0 0 1 0 0 0 0 0 0 0 52
53 13336 0 0 0 0 0 1 0 0 0 0 0 0 53
54 15346 0 0 0 0 0 0 1 0 0 0 0 0 54
55 24446 0 0 0 0 0 0 0 1 0 0 0 0 55
56 26178 0 0 0 0 0 0 0 0 1 0 0 0 56
57 24628 0 0 0 0 0 0 0 0 0 1 0 0 57
58 21282 0 0 0 0 0 0 0 0 0 0 1 0 58
59 18850 0 0 0 0 0 0 0 0 0 0 0 1 59
60 18822 0 0 0 0 0 0 0 0 0 0 0 0 60
61 18060 0 1 0 0 0 0 0 0 0 0 0 0 61
62 17536 0 0 1 0 0 0 0 0 0 0 0 0 62
63 16417 0 0 0 1 0 0 0 0 0 0 0 0 63
64 15842 0 0 0 0 1 0 0 0 0 0 0 0 64
65 15188 0 0 0 0 0 1 0 0 0 0 0 0 65
66 16905 0 0 0 0 0 0 1 0 0 0 0 0 66
67 25430 0 0 0 0 0 0 0 1 0 0 0 0 67
68 27962 0 0 0 0 0 0 0 0 1 0 0 0 68
69 26607 0 0 0 0 0 0 0 0 0 1 0 0 69
70 23364 0 0 0 0 0 0 0 0 0 0 1 0 70
71 20827 0 0 0 0 0 0 0 0 0 0 0 1 71
72 20506 0 0 0 0 0 0 0 0 0 0 0 0 72
73 19181 0 1 0 0 0 0 0 0 0 0 0 0 73
74 18016 0 0 1 0 0 0 0 0 0 0 0 0 74
75 17354 0 0 0 1 0 0 0 0 0 0 0 0 75
76 16256 0 0 0 0 1 0 0 0 0 0 0 0 76
77 15770 0 0 0 0 0 1 0 0 0 0 0 0 77
78 17538 0 0 0 0 0 0 1 0 0 0 0 0 78
79 26899 1 0 0 0 0 0 0 1 0 0 0 0 79
80 28915 1 0 0 0 0 0 0 0 1 0 0 0 80
81 25247 1 0 0 0 0 0 0 0 0 1 0 0 81
82 22856 1 0 0 0 0 0 0 0 0 0 1 0 82
83 19980 1 0 0 0 0 0 0 0 0 0 0 1 83
84 19856 1 0 0 0 0 0 0 0 0 0 0 0 84
85 16994 1 1 0 0 0 0 0 0 0 0 0 0 85
86 16839 1 0 1 0 0 0 0 0 0 0 0 0 86
87 15618 1 0 0 1 0 0 0 0 0 0 0 0 87
88 15883 1 0 0 0 1 0 0 0 0 0 0 0 88
89 15513 1 0 0 0 0 1 0 0 0 0 0 0 89
90 17106 1 0 0 0 0 0 1 0 0 0 0 0 90
91 25272 1 0 0 0 0 0 0 1 0 0 0 0 91
92 26731 1 0 0 0 0 0 0 0 1 0 0 0 92
93 22891 1 0 0 0 0 0 0 0 0 1 0 0 93
94 19583 1 0 0 0 0 0 0 0 0 0 1 0 94
95 16939 1 0 0 0 0 0 0 0 0 0 0 1 95
96 16757 1 0 0 0 0 0 0 0 0 0 0 0 96
97 15435 1 1 0 0 0 0 0 0 0 0 0 0 97
98 14786 1 0 1 0 0 0 0 0 0 0 0 0 98
99 13680 1 0 0 1 0 0 0 0 0 0 0 0 99
100 13208 1 0 0 0 1 0 0 0 0 0 0 0 100
101 12707 1 0 0 0 0 1 0 0 0 0 0 0 101
102 14277 1 0 0 0 0 0 1 0 0 0 0 0 102
103 22436 1 0 0 0 0 0 0 1 0 0 0 0 103
104 23229 1 0 0 0 0 0 0 0 1 0 0 0 104
105 18241 1 0 0 0 0 0 0 0 0 1 0 0 105
106 16145 1 0 0 0 0 0 0 0 0 0 1 0 106
107 13994 1 0 0 0 0 0 0 0 0 0 0 1 107
108 14780 1 0 0 0 0 0 0 0 0 0 0 0 108
109 13100 1 1 0 0 0 0 0 0 0 0 0 0 109
110 12329 1 0 1 0 0 0 0 0 0 0 0 0 110
111 12463 1 0 0 1 0 0 0 0 0 0 0 0 111
112 11532 1 0 0 0 1 0 0 0 0 0 0 0 112
113 10784 1 0 0 0 0 1 0 0 0 0 0 0 113
114 13106 1 0 0 0 0 0 1 0 0 0 0 0 114
115 19491 1 0 0 0 0 0 0 1 0 0 0 0 115
116 20418 1 0 0 0 0 0 0 0 1 0 0 0 116
117 16094 1 0 0 0 0 0 0 0 0 1 0 0 117
118 14491 1 0 0 0 0 0 0 0 0 0 1 0 118
119 13067 1 0 0 0 0 0 0 0 0 0 0 1 119
> k <- length(x[1,])
> df <- as.data.frame(x)
> (mylm <- lm(df))
Call:
lm(formula = df)
Coefficients:
(Intercept) Dummy M1 M2 M3 M4
12483.67 -3857.07 -1114.80 -1996.63 -2844.67 -3312.20
M5 M6 M7 M8 M9 M10
-3916.74 -2607.67 5234.60 7235.17 4444.04 1770.50
M11 t
-516.13 83.93
> (mysum <- summary(mylm))
Call:
lm(formula = df)
Residuals:
Min 1Q Median 3Q Max
-6796.9 -1509.6 -218.4 1628.1 6407.0
Coefficients:
Estimate Std. Error t value Pr(>|t|)
(Intercept) 12483.67 1036.11 12.049 < 2e-16 ***
Dummy -3857.07 909.36 -4.242 4.79e-05 ***
M1 -1114.80 1225.34 -0.910 0.365018
M2 -1996.63 1225.02 -1.630 0.106123
M3 -2844.67 1224.82 -2.323 0.022134 *
M4 -3312.20 1224.76 -2.704 0.007985 **
M5 -3916.74 1224.82 -3.198 0.001831 **
M6 -2607.67 1225.01 -2.129 0.035618 *
M7 5234.60 1225.69 4.271 4.29e-05 ***
M8 7235.17 1225.37 5.904 4.40e-08 ***
M9 4444.04 1225.18 3.627 0.000444 ***
M10 1770.50 1225.12 1.445 0.151388
M11 -516.13 1225.19 -0.421 0.674421
t 83.93 12.57 6.680 1.17e-09 ***
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
Residual standard error: 2665 on 105 degrees of freedom
Multiple R-squared: 0.7102, Adjusted R-squared: 0.6743
F-statistic: 19.8 on 13 and 105 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,] 1.908865e-03 3.817730e-03 9.980911e-01
[2,] 7.471327e-04 1.494265e-03 9.992529e-01
[3,] 3.192400e-04 6.384801e-04 9.996808e-01
[4,] 8.203973e-05 1.640795e-04 9.999180e-01
[5,] 1.233815e-05 2.467629e-05 9.999877e-01
[6,] 2.600734e-06 5.201468e-06 9.999974e-01
[7,] 3.944770e-07 7.889540e-07 9.999996e-01
[8,] 5.941620e-08 1.188324e-07 9.999999e-01
[9,] 8.020926e-09 1.604185e-08 1.000000e+00
[10,] 1.258451e-09 2.516902e-09 1.000000e+00
[11,] 3.391675e-10 6.783350e-10 1.000000e+00
[12,] 8.756245e-11 1.751249e-10 1.000000e+00
[13,] 4.837988e-11 9.675976e-11 1.000000e+00
[14,] 2.564559e-11 5.129118e-11 1.000000e+00
[15,] 8.773127e-11 1.754625e-10 1.000000e+00
[16,] 3.809325e-11 7.618649e-11 1.000000e+00
[17,] 5.266307e-09 1.053261e-08 1.000000e+00
[18,] 1.333837e-07 2.667674e-07 9.999999e-01
[19,] 4.235536e-07 8.471073e-07 9.999996e-01
[20,] 9.048930e-07 1.809786e-06 9.999991e-01
[21,] 8.634401e-07 1.726880e-06 9.999991e-01
[22,] 9.068661e-07 1.813732e-06 9.999991e-01
[23,] 1.148926e-06 2.297853e-06 9.999989e-01
[24,] 1.210179e-06 2.420359e-06 9.999988e-01
[25,] 1.548867e-06 3.097734e-06 9.999985e-01
[26,] 3.348403e-06 6.696805e-06 9.999967e-01
[27,] 1.507123e-04 3.014247e-04 9.998493e-01
[28,] 4.519573e-04 9.039146e-04 9.995480e-01
[29,] 1.518806e-03 3.037613e-03 9.984812e-01
[30,] 3.320671e-03 6.641343e-03 9.966793e-01
[31,] 6.056709e-03 1.211342e-02 9.939433e-01
[32,] 1.186747e-02 2.373494e-02 9.881325e-01
[33,] 1.569766e-02 3.139531e-02 9.843023e-01
[34,] 2.498342e-02 4.996683e-02 9.750166e-01
[35,] 4.488850e-02 8.977700e-02 9.551115e-01
[36,] 7.811187e-02 1.562237e-01 9.218881e-01
[37,] 1.470763e-01 2.941526e-01 8.529237e-01
[38,] 3.338457e-01 6.676913e-01 6.661543e-01
[39,] 7.075067e-01 5.849866e-01 2.924933e-01
[40,] 8.756803e-01 2.486394e-01 1.243197e-01
[41,] 9.223378e-01 1.553245e-01 7.766225e-02
[42,] 9.527201e-01 9.455971e-02 4.727986e-02
[43,] 9.738540e-01 5.229196e-02 2.614598e-02
[44,] 9.881197e-01 2.376063e-02 1.188032e-02
[45,] 9.905421e-01 1.891582e-02 9.457912e-03
[46,] 9.928831e-01 1.423390e-02 7.116948e-03
[47,] 9.963131e-01 7.373833e-03 3.686917e-03
[48,] 9.985929e-01 2.814220e-03 1.407110e-03
[49,] 9.997523e-01 4.953449e-04 2.476724e-04
[50,] 9.999922e-01 1.553388e-05 7.766938e-06
[51,] 9.999997e-01 5.588539e-07 2.794270e-07
[52,] 9.999999e-01 1.717606e-07 8.588029e-08
[53,] 1.000000e+00 6.130673e-08 3.065336e-08
[54,] 1.000000e+00 9.148454e-08 4.574227e-08
[55,] 9.999999e-01 1.832429e-07 9.162143e-08
[56,] 9.999998e-01 4.191384e-07 2.095692e-07
[57,] 9.999997e-01 5.734770e-07 2.867385e-07
[58,] 9.999994e-01 1.248191e-06 6.240956e-07
[59,] 9.999988e-01 2.348197e-06 1.174099e-06
[60,] 9.999974e-01 5.209572e-06 2.604786e-06
[61,] 9.999943e-01 1.147974e-05 5.739869e-06
[62,] 9.999868e-01 2.637148e-05 1.318574e-05
[63,] 9.999759e-01 4.829304e-05 2.414652e-05
[64,] 9.999504e-01 9.921172e-05 4.960586e-05
[65,] 9.999571e-01 8.576539e-05 4.288270e-05
[66,] 9.999625e-01 7.494683e-05 3.747342e-05
[67,] 9.999331e-01 1.338594e-04 6.692970e-05
[68,] 9.998777e-01 2.445646e-04 1.222823e-04
[69,] 9.998897e-01 2.205274e-04 1.102637e-04
[70,] 9.998062e-01 3.876876e-04 1.938438e-04
[71,] 9.998259e-01 3.481078e-04 1.740539e-04
[72,] 9.996368e-01 7.263899e-04 3.631949e-04
[73,] 9.992144e-01 1.571194e-03 7.855968e-04
[74,] 9.984065e-01 3.187020e-03 1.593510e-03
[75,] 9.970095e-01 5.981016e-03 2.990508e-03
[76,] 9.970205e-01 5.959043e-03 2.979522e-03
[77,] 9.998722e-01 2.555525e-04 1.277762e-04
[78,] 9.999376e-01 1.247066e-04 6.235330e-05
[79,] 9.998742e-01 2.515576e-04 1.257788e-04
[80,] 9.996527e-01 6.946816e-04 3.473408e-04
[81,] 9.992037e-01 1.592668e-03 7.963342e-04
[82,] 9.982770e-01 3.445900e-03 1.722950e-03
[83,] 9.963197e-01 7.360540e-03 3.680270e-03
[84,] 9.893555e-01 2.128897e-02 1.064448e-02
[85,] 9.685911e-01 6.281774e-02 3.140887e-02
[86,] 9.347987e-01 1.304026e-01 6.520131e-02
> postscript(file="/var/www/html/rcomp/tmp/1jqm41229095635.ps",horizontal=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$resid)
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/2f24d1229095635.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> plot(mysum$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/3vrv71229095635.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> hist(mysum$resid, main='Residual Histogram', xlab='values of Residuals')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/48s5j1229095635.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> densityplot(~mysum$resid,col='black',main='Residual Density Plot', xlab='values of Residuals')
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/58mzq1229095635.ps",horizontal=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 = 119
Frequency = 1
1 2 3 4 5 6
1910.19932 1875.09932 1529.19932 1440.79932 1186.39932 222.39932
7 8 9 10 11 12
-2211.80787 -759.30787 -543.10787 -748.50787 -258.80787 -596.87206
13 14 15 16 17 18
-652.00532 -989.10532 -959.00532 -624.40532 -710.80532 -1255.80532
19 20 21 22 23 24
-3449.01251 -2114.51251 -2487.31251 -2181.71251 -1961.01251 -2703.07671
25 26 27 28 29 30
-2199.20997 -2147.30997 -1976.20997 -1796.60997 -1629.00997 -2326.00997
31 32 33 34 35 36
-4090.21716 -3289.71716 -1346.51716 -842.91716 -802.21716 -1390.28135
37 38 39 40 41 42
-1147.41461 -1058.51461 -783.41461 -753.81461 -515.21461 -931.21461
43 44 45 46 47 48
-535.42180 -1074.92180 620.27820 465.87820 562.57820 68.51400
49 50 51 52 53 54
263.38075 -230.71925 -207.61925 229.98075 320.58075 937.58075
55 56 57 58 59 60
2111.37355 1758.87355 2916.07355 2159.67355 1930.37355 1302.30936
61 62 63 64 65 66
1571.17610 1845.07610 1490.17610 1298.77610 1165.37610 1489.37610
67 68 69 70 71 72
2088.16891 2535.66891 3887.86891 3234.46891 2900.16891 1979.10472
73 74 75 76 77 78
1684.97146 1317.87146 1419.97146 705.57146 740.17146 1115.17146
79 80 81 82 83 84
6407.03618 6338.53618 5377.73618 5576.33618 4903.03618 4178.97199
85 86 87 88 89 90
2347.83873 2990.73873 2533.83873 3182.43873 3333.03873 3533.03873
91 92 93 94 95 96
3772.83154 3147.33154 2014.53154 1296.13154 854.83154 72.76735
97 98 99 100 101 102
-218.36591 -69.46591 -411.36591 -499.76591 -480.16591 -303.16591
103 104 105 106 107 108
-70.37310 -1361.87310 -3642.67310 -3149.07310 -3097.37310 -2911.43730
109 110 111 112 113 114
-3560.57056 -3533.67056 -2635.57056 -3182.97056 -3410.37056 -2481.37056
115 116 117 118 119
-4022.57775 -5180.07775 -6796.87775 -5810.27775 -5031.57775
> postscript(file="/var/www/html/rcomp/tmp/6pgso1229095635.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> dum <- cbind(lag(myerror,k=1),myerror)
> dum
Time Series:
Start = 0
End = 119
Frequency = 1
lag(myerror, k = 1) myerror
0 1910.19932 NA
1 1875.09932 1910.19932
2 1529.19932 1875.09932
3 1440.79932 1529.19932
4 1186.39932 1440.79932
5 222.39932 1186.39932
6 -2211.80787 222.39932
7 -759.30787 -2211.80787
8 -543.10787 -759.30787
9 -748.50787 -543.10787
10 -258.80787 -748.50787
11 -596.87206 -258.80787
12 -652.00532 -596.87206
13 -989.10532 -652.00532
14 -959.00532 -989.10532
15 -624.40532 -959.00532
16 -710.80532 -624.40532
17 -1255.80532 -710.80532
18 -3449.01251 -1255.80532
19 -2114.51251 -3449.01251
20 -2487.31251 -2114.51251
21 -2181.71251 -2487.31251
22 -1961.01251 -2181.71251
23 -2703.07671 -1961.01251
24 -2199.20997 -2703.07671
25 -2147.30997 -2199.20997
26 -1976.20997 -2147.30997
27 -1796.60997 -1976.20997
28 -1629.00997 -1796.60997
29 -2326.00997 -1629.00997
30 -4090.21716 -2326.00997
31 -3289.71716 -4090.21716
32 -1346.51716 -3289.71716
33 -842.91716 -1346.51716
34 -802.21716 -842.91716
35 -1390.28135 -802.21716
36 -1147.41461 -1390.28135
37 -1058.51461 -1147.41461
38 -783.41461 -1058.51461
39 -753.81461 -783.41461
40 -515.21461 -753.81461
41 -931.21461 -515.21461
42 -535.42180 -931.21461
43 -1074.92180 -535.42180
44 620.27820 -1074.92180
45 465.87820 620.27820
46 562.57820 465.87820
47 68.51400 562.57820
48 263.38075 68.51400
49 -230.71925 263.38075
50 -207.61925 -230.71925
51 229.98075 -207.61925
52 320.58075 229.98075
53 937.58075 320.58075
54 2111.37355 937.58075
55 1758.87355 2111.37355
56 2916.07355 1758.87355
57 2159.67355 2916.07355
58 1930.37355 2159.67355
59 1302.30936 1930.37355
60 1571.17610 1302.30936
61 1845.07610 1571.17610
62 1490.17610 1845.07610
63 1298.77610 1490.17610
64 1165.37610 1298.77610
65 1489.37610 1165.37610
66 2088.16891 1489.37610
67 2535.66891 2088.16891
68 3887.86891 2535.66891
69 3234.46891 3887.86891
70 2900.16891 3234.46891
71 1979.10472 2900.16891
72 1684.97146 1979.10472
73 1317.87146 1684.97146
74 1419.97146 1317.87146
75 705.57146 1419.97146
76 740.17146 705.57146
77 1115.17146 740.17146
78 6407.03618 1115.17146
79 6338.53618 6407.03618
80 5377.73618 6338.53618
81 5576.33618 5377.73618
82 4903.03618 5576.33618
83 4178.97199 4903.03618
84 2347.83873 4178.97199
85 2990.73873 2347.83873
86 2533.83873 2990.73873
87 3182.43873 2533.83873
88 3333.03873 3182.43873
89 3533.03873 3333.03873
90 3772.83154 3533.03873
91 3147.33154 3772.83154
92 2014.53154 3147.33154
93 1296.13154 2014.53154
94 854.83154 1296.13154
95 72.76735 854.83154
96 -218.36591 72.76735
97 -69.46591 -218.36591
98 -411.36591 -69.46591
99 -499.76591 -411.36591
100 -480.16591 -499.76591
101 -303.16591 -480.16591
102 -70.37310 -303.16591
103 -1361.87310 -70.37310
104 -3642.67310 -1361.87310
105 -3149.07310 -3642.67310
106 -3097.37310 -3149.07310
107 -2911.43730 -3097.37310
108 -3560.57056 -2911.43730
109 -3533.67056 -3560.57056
110 -2635.57056 -3533.67056
111 -3182.97056 -2635.57056
112 -3410.37056 -3182.97056
113 -2481.37056 -3410.37056
114 -4022.57775 -2481.37056
115 -5180.07775 -4022.57775
116 -6796.87775 -5180.07775
117 -5810.27775 -6796.87775
118 -5031.57775 -5810.27775
119 NA -5031.57775
> dum1 <- dum[2:length(myerror),]
> dum1
lag(myerror, k = 1) myerror
[1,] 1875.09932 1910.19932
[2,] 1529.19932 1875.09932
[3,] 1440.79932 1529.19932
[4,] 1186.39932 1440.79932
[5,] 222.39932 1186.39932
[6,] -2211.80787 222.39932
[7,] -759.30787 -2211.80787
[8,] -543.10787 -759.30787
[9,] -748.50787 -543.10787
[10,] -258.80787 -748.50787
[11,] -596.87206 -258.80787
[12,] -652.00532 -596.87206
[13,] -989.10532 -652.00532
[14,] -959.00532 -989.10532
[15,] -624.40532 -959.00532
[16,] -710.80532 -624.40532
[17,] -1255.80532 -710.80532
[18,] -3449.01251 -1255.80532
[19,] -2114.51251 -3449.01251
[20,] -2487.31251 -2114.51251
[21,] -2181.71251 -2487.31251
[22,] -1961.01251 -2181.71251
[23,] -2703.07671 -1961.01251
[24,] -2199.20997 -2703.07671
[25,] -2147.30997 -2199.20997
[26,] -1976.20997 -2147.30997
[27,] -1796.60997 -1976.20997
[28,] -1629.00997 -1796.60997
[29,] -2326.00997 -1629.00997
[30,] -4090.21716 -2326.00997
[31,] -3289.71716 -4090.21716
[32,] -1346.51716 -3289.71716
[33,] -842.91716 -1346.51716
[34,] -802.21716 -842.91716
[35,] -1390.28135 -802.21716
[36,] -1147.41461 -1390.28135
[37,] -1058.51461 -1147.41461
[38,] -783.41461 -1058.51461
[39,] -753.81461 -783.41461
[40,] -515.21461 -753.81461
[41,] -931.21461 -515.21461
[42,] -535.42180 -931.21461
[43,] -1074.92180 -535.42180
[44,] 620.27820 -1074.92180
[45,] 465.87820 620.27820
[46,] 562.57820 465.87820
[47,] 68.51400 562.57820
[48,] 263.38075 68.51400
[49,] -230.71925 263.38075
[50,] -207.61925 -230.71925
[51,] 229.98075 -207.61925
[52,] 320.58075 229.98075
[53,] 937.58075 320.58075
[54,] 2111.37355 937.58075
[55,] 1758.87355 2111.37355
[56,] 2916.07355 1758.87355
[57,] 2159.67355 2916.07355
[58,] 1930.37355 2159.67355
[59,] 1302.30936 1930.37355
[60,] 1571.17610 1302.30936
[61,] 1845.07610 1571.17610
[62,] 1490.17610 1845.07610
[63,] 1298.77610 1490.17610
[64,] 1165.37610 1298.77610
[65,] 1489.37610 1165.37610
[66,] 2088.16891 1489.37610
[67,] 2535.66891 2088.16891
[68,] 3887.86891 2535.66891
[69,] 3234.46891 3887.86891
[70,] 2900.16891 3234.46891
[71,] 1979.10472 2900.16891
[72,] 1684.97146 1979.10472
[73,] 1317.87146 1684.97146
[74,] 1419.97146 1317.87146
[75,] 705.57146 1419.97146
[76,] 740.17146 705.57146
[77,] 1115.17146 740.17146
[78,] 6407.03618 1115.17146
[79,] 6338.53618 6407.03618
[80,] 5377.73618 6338.53618
[81,] 5576.33618 5377.73618
[82,] 4903.03618 5576.33618
[83,] 4178.97199 4903.03618
[84,] 2347.83873 4178.97199
[85,] 2990.73873 2347.83873
[86,] 2533.83873 2990.73873
[87,] 3182.43873 2533.83873
[88,] 3333.03873 3182.43873
[89,] 3533.03873 3333.03873
[90,] 3772.83154 3533.03873
[91,] 3147.33154 3772.83154
[92,] 2014.53154 3147.33154
[93,] 1296.13154 2014.53154
[94,] 854.83154 1296.13154
[95,] 72.76735 854.83154
[96,] -218.36591 72.76735
[97,] -69.46591 -218.36591
[98,] -411.36591 -69.46591
[99,] -499.76591 -411.36591
[100,] -480.16591 -499.76591
[101,] -303.16591 -480.16591
[102,] -70.37310 -303.16591
[103,] -1361.87310 -70.37310
[104,] -3642.67310 -1361.87310
[105,] -3149.07310 -3642.67310
[106,] -3097.37310 -3149.07310
[107,] -2911.43730 -3097.37310
[108,] -3560.57056 -2911.43730
[109,] -3533.67056 -3560.57056
[110,] -2635.57056 -3533.67056
[111,] -3182.97056 -2635.57056
[112,] -3410.37056 -3182.97056
[113,] -2481.37056 -3410.37056
[114,] -4022.57775 -2481.37056
[115,] -5180.07775 -4022.57775
[116,] -6796.87775 -5180.07775
[117,] -5810.27775 -6796.87775
[118,] -5031.57775 -5810.27775
> z <- as.data.frame(dum1)
> z
lag(myerror, k = 1) myerror
1 1875.09932 1910.19932
2 1529.19932 1875.09932
3 1440.79932 1529.19932
4 1186.39932 1440.79932
5 222.39932 1186.39932
6 -2211.80787 222.39932
7 -759.30787 -2211.80787
8 -543.10787 -759.30787
9 -748.50787 -543.10787
10 -258.80787 -748.50787
11 -596.87206 -258.80787
12 -652.00532 -596.87206
13 -989.10532 -652.00532
14 -959.00532 -989.10532
15 -624.40532 -959.00532
16 -710.80532 -624.40532
17 -1255.80532 -710.80532
18 -3449.01251 -1255.80532
19 -2114.51251 -3449.01251
20 -2487.31251 -2114.51251
21 -2181.71251 -2487.31251
22 -1961.01251 -2181.71251
23 -2703.07671 -1961.01251
24 -2199.20997 -2703.07671
25 -2147.30997 -2199.20997
26 -1976.20997 -2147.30997
27 -1796.60997 -1976.20997
28 -1629.00997 -1796.60997
29 -2326.00997 -1629.00997
30 -4090.21716 -2326.00997
31 -3289.71716 -4090.21716
32 -1346.51716 -3289.71716
33 -842.91716 -1346.51716
34 -802.21716 -842.91716
35 -1390.28135 -802.21716
36 -1147.41461 -1390.28135
37 -1058.51461 -1147.41461
38 -783.41461 -1058.51461
39 -753.81461 -783.41461
40 -515.21461 -753.81461
41 -931.21461 -515.21461
42 -535.42180 -931.21461
43 -1074.92180 -535.42180
44 620.27820 -1074.92180
45 465.87820 620.27820
46 562.57820 465.87820
47 68.51400 562.57820
48 263.38075 68.51400
49 -230.71925 263.38075
50 -207.61925 -230.71925
51 229.98075 -207.61925
52 320.58075 229.98075
53 937.58075 320.58075
54 2111.37355 937.58075
55 1758.87355 2111.37355
56 2916.07355 1758.87355
57 2159.67355 2916.07355
58 1930.37355 2159.67355
59 1302.30936 1930.37355
60 1571.17610 1302.30936
61 1845.07610 1571.17610
62 1490.17610 1845.07610
63 1298.77610 1490.17610
64 1165.37610 1298.77610
65 1489.37610 1165.37610
66 2088.16891 1489.37610
67 2535.66891 2088.16891
68 3887.86891 2535.66891
69 3234.46891 3887.86891
70 2900.16891 3234.46891
71 1979.10472 2900.16891
72 1684.97146 1979.10472
73 1317.87146 1684.97146
74 1419.97146 1317.87146
75 705.57146 1419.97146
76 740.17146 705.57146
77 1115.17146 740.17146
78 6407.03618 1115.17146
79 6338.53618 6407.03618
80 5377.73618 6338.53618
81 5576.33618 5377.73618
82 4903.03618 5576.33618
83 4178.97199 4903.03618
84 2347.83873 4178.97199
85 2990.73873 2347.83873
86 2533.83873 2990.73873
87 3182.43873 2533.83873
88 3333.03873 3182.43873
89 3533.03873 3333.03873
90 3772.83154 3533.03873
91 3147.33154 3772.83154
92 2014.53154 3147.33154
93 1296.13154 2014.53154
94 854.83154 1296.13154
95 72.76735 854.83154
96 -218.36591 72.76735
97 -69.46591 -218.36591
98 -411.36591 -69.46591
99 -499.76591 -411.36591
100 -480.16591 -499.76591
101 -303.16591 -480.16591
102 -70.37310 -303.16591
103 -1361.87310 -70.37310
104 -3642.67310 -1361.87310
105 -3149.07310 -3642.67310
106 -3097.37310 -3149.07310
107 -2911.43730 -3097.37310
108 -3560.57056 -2911.43730
109 -3533.67056 -3560.57056
110 -2635.57056 -3533.67056
111 -3182.97056 -2635.57056
112 -3410.37056 -3182.97056
113 -2481.37056 -3410.37056
114 -4022.57775 -2481.37056
115 -5180.07775 -4022.57775
116 -6796.87775 -5180.07775
117 -5810.27775 -6796.87775
118 -5031.57775 -5810.27775
> 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/7jldp1229095635.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> acf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/80ffa1229095635.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> pacf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Partial Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/9pxg41229095635.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> opar <- par(mfrow = c(2,2), oma = c(0, 0, 1.1, 0))
> plot(mylm, las = 1, sub='Residual Diagnostics')
> par(opar)
> dev.off()
null device
1
> if (n > n25) {
+ postscript(file="/var/www/html/rcomp/tmp/10mbn41229095635.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
+ plot(kp3:nmkm3,gqarr[,2], main='Goldfeld-Quandt test',ylab='2-sided p-value',xlab='breakpoint')
+ grid()
+ dev.off()
+ }
null device
1
>
> #Note: the /var/www/html/rcomp/createtable file can be downloaded at http://www.wessa.net/cretab
> load(file="/var/www/html/rcomp/createtable")
>
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a, 'Multiple Linear Regression - Estimated Regression Equation', 1, TRUE)
> a<-table.row.end(a)
> myeq <- colnames(x)[1]
> myeq <- paste(myeq, '[t] = ', sep='')
> for (i in 1:k){
+ if (mysum$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/11imk71229095636.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/128eme1229095636.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/13totm1229095636.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/146cq41229095636.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/15fe7y1229095636.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/16mouy1229095636.tab")
+ }
>
> system("convert tmp/1jqm41229095635.ps tmp/1jqm41229095635.png")
> system("convert tmp/2f24d1229095635.ps tmp/2f24d1229095635.png")
> system("convert tmp/3vrv71229095635.ps tmp/3vrv71229095635.png")
> system("convert tmp/48s5j1229095635.ps tmp/48s5j1229095635.png")
> system("convert tmp/58mzq1229095635.ps tmp/58mzq1229095635.png")
> system("convert tmp/6pgso1229095635.ps tmp/6pgso1229095635.png")
> system("convert tmp/7jldp1229095635.ps tmp/7jldp1229095635.png")
> system("convert tmp/80ffa1229095635.ps tmp/80ffa1229095635.png")
> system("convert tmp/9pxg41229095635.ps tmp/9pxg41229095635.png")
> system("convert tmp/10mbn41229095635.ps tmp/10mbn41229095635.png")
>
>
> proc.time()
user system elapsed
6.472 2.873 6.899