R version 2.9.0 (2009-04-17)
Copyright (C) 2009 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.
R is a collaborative project with many contributors.
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(403.5
+ ,0
+ ,395.1
+ ,395.3
+ ,403.3
+ ,0
+ ,403.5
+ ,395.1
+ ,405.7
+ ,0
+ ,403.3
+ ,403.5
+ ,406.7
+ ,0
+ ,405.7
+ ,403.3
+ ,407.2
+ ,0
+ ,406.7
+ ,405.7
+ ,412.4
+ ,0
+ ,407.2
+ ,406.7
+ ,415.9
+ ,0
+ ,412.4
+ ,407.2
+ ,414.0
+ ,0
+ ,415.9
+ ,412.4
+ ,411.8
+ ,0
+ ,414.0
+ ,415.9
+ ,409.9
+ ,0
+ ,411.8
+ ,414.0
+ ,412.4
+ ,0
+ ,409.9
+ ,411.8
+ ,415.9
+ ,0
+ ,412.4
+ ,409.9
+ ,416.3
+ ,0
+ ,415.9
+ ,412.4
+ ,417.2
+ ,0
+ ,416.3
+ ,415.9
+ ,421.8
+ ,0
+ ,417.2
+ ,416.3
+ ,421.4
+ ,0
+ ,421.8
+ ,417.2
+ ,415.1
+ ,0
+ ,421.4
+ ,421.8
+ ,412.4
+ ,0
+ ,415.1
+ ,421.4
+ ,411.8
+ ,0
+ ,412.4
+ ,415.1
+ ,408.8
+ ,0
+ ,411.8
+ ,412.4
+ ,404.5
+ ,0
+ ,408.8
+ ,411.8
+ ,402.5
+ ,0
+ ,404.5
+ ,408.8
+ ,409.4
+ ,0
+ ,402.5
+ ,404.5
+ ,410.7
+ ,0
+ ,409.4
+ ,402.5
+ ,413.4
+ ,0
+ ,410.7
+ ,409.4
+ ,415.2
+ ,0
+ ,413.4
+ ,410.7
+ ,417.7
+ ,0
+ ,415.2
+ ,413.4
+ ,417.8
+ ,0
+ ,417.7
+ ,415.2
+ ,417.9
+ ,0
+ ,417.8
+ ,417.7
+ ,418.4
+ ,0
+ ,417.9
+ ,417.8
+ ,418.2
+ ,0
+ ,418.4
+ ,417.9
+ ,416.6
+ ,0
+ ,418.2
+ ,418.4
+ ,418.9
+ ,0
+ ,416.6
+ ,418.2
+ ,421.0
+ ,0
+ ,418.9
+ ,416.6
+ ,423.5
+ ,0
+ ,421.0
+ ,418.9
+ ,432.3
+ ,0
+ ,423.5
+ ,421.0
+ ,432.3
+ ,0
+ ,432.3
+ ,423.5
+ ,428.6
+ ,0
+ ,432.3
+ ,432.3
+ ,426.7
+ ,0
+ ,428.6
+ ,432.3
+ ,427.3
+ ,0
+ ,426.7
+ ,428.6
+ ,428.5
+ ,0
+ ,427.3
+ ,426.7
+ ,437.0
+ ,0
+ ,428.5
+ ,427.3
+ ,442.0
+ ,0
+ ,437.0
+ ,428.5
+ ,444.9
+ ,0
+ ,442.0
+ ,437.0
+ ,441.4
+ ,0
+ ,444.9
+ ,442.0
+ ,440.3
+ ,0
+ ,441.4
+ ,444.9
+ ,447.1
+ ,0
+ ,440.3
+ ,441.4
+ ,455.3
+ ,0
+ ,447.1
+ ,440.3
+ ,478.6
+ ,0
+ ,455.3
+ ,447.1
+ ,486.5
+ ,0
+ ,478.6
+ ,455.3
+ ,487.8
+ ,0
+ ,486.5
+ ,478.6
+ ,485.9
+ ,0
+ ,487.8
+ ,486.5
+ ,483.8
+ ,0
+ ,485.9
+ ,487.8
+ ,488.4
+ ,0
+ ,483.8
+ ,485.9
+ ,494.0
+ ,0
+ ,488.4
+ ,483.8
+ ,493.6
+ ,0
+ ,494.0
+ ,488.4
+ ,487.3
+ ,0
+ ,493.6
+ ,494.0
+ ,482.1
+ ,0
+ ,487.3
+ ,493.6
+ ,484.2
+ ,0
+ ,482.1
+ ,487.3
+ ,496.8
+ ,0
+ ,484.2
+ ,482.1
+ ,501.1
+ ,0
+ ,496.8
+ ,484.2
+ ,499.8
+ ,0
+ ,501.1
+ ,496.8
+ ,495.5
+ ,0
+ ,499.8
+ ,501.1
+ ,498.1
+ ,0
+ ,495.5
+ ,499.8
+ ,503.8
+ ,0
+ ,498.1
+ ,495.5
+ ,516.2
+ ,0
+ ,503.8
+ ,498.1
+ ,526.1
+ ,0
+ ,516.2
+ ,503.8
+ ,527.1
+ ,0
+ ,526.1
+ ,516.2
+ ,525.1
+ ,0
+ ,527.1
+ ,526.1
+ ,528.9
+ ,0
+ ,525.1
+ ,527.1
+ ,540.1
+ ,0
+ ,528.9
+ ,525.1
+ ,549.0
+ ,0
+ ,540.1
+ ,528.9
+ ,556.0
+ ,0
+ ,549.0
+ ,540.1
+ ,568.9
+ ,0
+ ,556.0
+ ,549.0
+ ,589.1
+ ,0
+ ,568.9
+ ,556.0
+ ,590.3
+ ,0
+ ,589.1
+ ,568.9
+ ,603.3
+ ,0
+ ,590.3
+ ,589.1
+ ,638.8
+ ,0
+ ,603.3
+ ,590.3
+ ,643.0
+ ,0
+ ,638.8
+ ,603.3
+ ,656.7
+ ,0
+ ,643.0
+ ,638.8
+ ,656.1
+ ,0
+ ,656.7
+ ,643.0
+ ,654.1
+ ,0
+ ,656.1
+ ,656.7
+ ,659.9
+ ,0
+ ,654.1
+ ,656.1
+ ,662.1
+ ,0
+ ,659.9
+ ,654.1
+ ,669.2
+ ,0
+ ,662.1
+ ,659.9
+ ,673.1
+ ,0
+ ,669.2
+ ,662.1
+ ,678.3
+ ,0
+ ,673.1
+ ,669.2
+ ,677.4
+ ,0
+ ,678.3
+ ,673.1
+ ,678.5
+ ,0
+ ,677.4
+ ,678.3
+ ,672.4
+ ,0
+ ,678.5
+ ,677.4
+ ,665.3
+ ,0
+ ,672.4
+ ,678.5
+ ,667.9
+ ,0
+ ,665.3
+ ,672.4
+ ,672.1
+ ,0
+ ,667.9
+ ,665.3
+ ,662.5
+ ,0
+ ,672.1
+ ,667.9
+ ,682.3
+ ,0
+ ,662.5
+ ,672.1
+ ,692.1
+ ,0
+ ,682.3
+ ,662.5
+ ,702.7
+ ,0
+ ,692.1
+ ,682.3
+ ,721.4
+ ,0
+ ,702.7
+ ,692.1
+ ,733.2
+ ,0
+ ,721.4
+ ,702.7
+ ,747.7
+ ,0
+ ,733.2
+ ,721.4
+ ,737.6
+ ,0
+ ,747.7
+ ,733.2
+ ,729.3
+ ,0
+ ,737.6
+ ,747.7
+ ,706.1
+ ,0
+ ,729.3
+ ,737.6
+ ,674.3
+ ,0
+ ,706.1
+ ,729.3
+ ,659.0
+ ,0
+ ,674.3
+ ,706.1
+ ,645.7
+ ,0
+ ,659.0
+ ,674.3
+ ,646.1
+ ,0
+ ,645.7
+ ,659.0
+ ,633.0
+ ,1
+ ,646.1
+ ,645.7
+ ,622.3
+ ,1
+ ,633.0
+ ,646.1
+ ,628.2
+ ,1
+ ,622.3
+ ,633.0
+ ,637.3
+ ,1
+ ,628.2
+ ,622.3
+ ,639.6
+ ,1
+ ,637.3
+ ,628.2
+ ,638.5
+ ,1
+ ,639.6
+ ,637.3
+ ,650.5
+ ,1
+ ,638.5
+ ,639.6
+ ,655.4
+ ,1
+ ,650.5
+ ,638.5)
+ ,dim=c(4
+ ,115)
+ ,dimnames=list(c('Y'
+ ,'X'
+ ,'Y1'
+ ,'Y2')
+ ,1:115))
> y <- array(NA,dim=c(4,115),dimnames=list(c('Y','X','Y1','Y2'),1:115))
> 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 = 'Do not include Seasonal 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
Y X Y1 Y2 t
1 403.5 0 395.1 395.3 1
2 403.3 0 403.5 395.1 2
3 405.7 0 403.3 403.5 3
4 406.7 0 405.7 403.3 4
5 407.2 0 406.7 405.7 5
6 412.4 0 407.2 406.7 6
7 415.9 0 412.4 407.2 7
8 414.0 0 415.9 412.4 8
9 411.8 0 414.0 415.9 9
10 409.9 0 411.8 414.0 10
11 412.4 0 409.9 411.8 11
12 415.9 0 412.4 409.9 12
13 416.3 0 415.9 412.4 13
14 417.2 0 416.3 415.9 14
15 421.8 0 417.2 416.3 15
16 421.4 0 421.8 417.2 16
17 415.1 0 421.4 421.8 17
18 412.4 0 415.1 421.4 18
19 411.8 0 412.4 415.1 19
20 408.8 0 411.8 412.4 20
21 404.5 0 408.8 411.8 21
22 402.5 0 404.5 408.8 22
23 409.4 0 402.5 404.5 23
24 410.7 0 409.4 402.5 24
25 413.4 0 410.7 409.4 25
26 415.2 0 413.4 410.7 26
27 417.7 0 415.2 413.4 27
28 417.8 0 417.7 415.2 28
29 417.9 0 417.8 417.7 29
30 418.4 0 417.9 417.8 30
31 418.2 0 418.4 417.9 31
32 416.6 0 418.2 418.4 32
33 418.9 0 416.6 418.2 33
34 421.0 0 418.9 416.6 34
35 423.5 0 421.0 418.9 35
36 432.3 0 423.5 421.0 36
37 432.3 0 432.3 423.5 37
38 428.6 0 432.3 432.3 38
39 426.7 0 428.6 432.3 39
40 427.3 0 426.7 428.6 40
41 428.5 0 427.3 426.7 41
42 437.0 0 428.5 427.3 42
43 442.0 0 437.0 428.5 43
44 444.9 0 442.0 437.0 44
45 441.4 0 444.9 442.0 45
46 440.3 0 441.4 444.9 46
47 447.1 0 440.3 441.4 47
48 455.3 0 447.1 440.3 48
49 478.6 0 455.3 447.1 49
50 486.5 0 478.6 455.3 50
51 487.8 0 486.5 478.6 51
52 485.9 0 487.8 486.5 52
53 483.8 0 485.9 487.8 53
54 488.4 0 483.8 485.9 54
55 494.0 0 488.4 483.8 55
56 493.6 0 494.0 488.4 56
57 487.3 0 493.6 494.0 57
58 482.1 0 487.3 493.6 58
59 484.2 0 482.1 487.3 59
60 496.8 0 484.2 482.1 60
61 501.1 0 496.8 484.2 61
62 499.8 0 501.1 496.8 62
63 495.5 0 499.8 501.1 63
64 498.1 0 495.5 499.8 64
65 503.8 0 498.1 495.5 65
66 516.2 0 503.8 498.1 66
67 526.1 0 516.2 503.8 67
68 527.1 0 526.1 516.2 68
69 525.1 0 527.1 526.1 69
70 528.9 0 525.1 527.1 70
71 540.1 0 528.9 525.1 71
72 549.0 0 540.1 528.9 72
73 556.0 0 549.0 540.1 73
74 568.9 0 556.0 549.0 74
75 589.1 0 568.9 556.0 75
76 590.3 0 589.1 568.9 76
77 603.3 0 590.3 589.1 77
78 638.8 0 603.3 590.3 78
79 643.0 0 638.8 603.3 79
80 656.7 0 643.0 638.8 80
81 656.1 0 656.7 643.0 81
82 654.1 0 656.1 656.7 82
83 659.9 0 654.1 656.1 83
84 662.1 0 659.9 654.1 84
85 669.2 0 662.1 659.9 85
86 673.1 0 669.2 662.1 86
87 678.3 0 673.1 669.2 87
88 677.4 0 678.3 673.1 88
89 678.5 0 677.4 678.3 89
90 672.4 0 678.5 677.4 90
91 665.3 0 672.4 678.5 91
92 667.9 0 665.3 672.4 92
93 672.1 0 667.9 665.3 93
94 662.5 0 672.1 667.9 94
95 682.3 0 662.5 672.1 95
96 692.1 0 682.3 662.5 96
97 702.7 0 692.1 682.3 97
98 721.4 0 702.7 692.1 98
99 733.2 0 721.4 702.7 99
100 747.7 0 733.2 721.4 100
101 737.6 0 747.7 733.2 101
102 729.3 0 737.6 747.7 102
103 706.1 0 729.3 737.6 103
104 674.3 0 706.1 729.3 104
105 659.0 0 674.3 706.1 105
106 645.7 0 659.0 674.3 106
107 646.1 0 645.7 659.0 107
108 633.0 1 646.1 645.7 108
109 622.3 1 633.0 646.1 109
110 628.2 1 622.3 633.0 110
111 637.3 1 628.2 622.3 111
112 639.6 1 637.3 628.2 112
113 638.5 1 639.6 637.3 113
114 650.5 1 638.5 639.6 114
115 655.4 1 650.5 638.5 115
> k <- length(x[1,])
> df <- as.data.frame(x)
> (mylm <- lm(df))
Call:
lm(formula = df)
Coefficients:
(Intercept) X Y1 Y2 t
14.3225 -3.1810 1.4792 -0.5187 0.1334
> (mysum <- summary(mylm))
Call:
lm(formula = df)
Residuals:
Min 1Q Median 3Q Max
-20.0666 -3.5972 -0.4959 3.7778 27.8648
Coefficients:
Estimate Std. Error t value Pr(>|t|)
(Intercept) 14.32250 6.27913 2.281 0.0245 *
X -3.18099 3.24808 -0.979 0.3296
Y1 1.47915 0.08157 18.134 < 2e-16 ***
Y2 -0.51866 0.08114 -6.392 4.07e-09 ***
t 0.13339 0.06534 2.042 0.0436 *
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
Residual standard error: 7.277 on 110 degrees of freedom
Multiple R-squared: 0.9959, Adjusted R-squared: 0.9957
F-statistic: 6654 on 4 and 110 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,] 2.297690e-02 4.595380e-02 0.9770231
[2,] 2.433115e-02 4.866230e-02 0.9756689
[3,] 2.909905e-02 5.819811e-02 0.9709009
[4,] 1.060035e-02 2.120070e-02 0.9893997
[5,] 3.821292e-03 7.642585e-03 0.9961787
[6,] 1.256333e-03 2.512667e-03 0.9987437
[7,] 3.812032e-04 7.624064e-04 0.9996188
[8,] 2.536672e-04 5.073343e-04 0.9997463
[9,] 7.642271e-05 1.528454e-04 0.9999236
[10,] 2.002524e-04 4.005047e-04 0.9997997
[11,] 1.624485e-04 3.248971e-04 0.9998376
[12,] 9.847524e-05 1.969505e-04 0.9999015
[13,] 8.996522e-05 1.799304e-04 0.9999100
[14,] 6.611736e-05 1.322347e-04 0.9999339
[15,] 2.517528e-05 5.035057e-05 0.9999748
[16,] 5.447067e-05 1.089413e-04 0.9999455
[17,] 2.163513e-05 4.327025e-05 0.9999784
[18,] 1.034192e-05 2.068384e-05 0.9999897
[19,] 4.243815e-06 8.487630e-06 0.9999958
[20,] 2.108131e-06 4.216262e-06 0.9999979
[21,] 7.651253e-07 1.530251e-06 0.9999992
[22,] 2.822214e-07 5.644429e-07 0.9999997
[23,] 1.048186e-07 2.096371e-07 0.9999999
[24,] 3.546459e-08 7.092918e-08 1.0000000
[25,] 1.216911e-08 2.433821e-08 1.0000000
[26,] 6.212592e-09 1.242518e-08 1.0000000
[27,] 2.412855e-09 4.825710e-09 1.0000000
[28,] 1.110396e-09 2.220791e-09 1.0000000
[29,] 1.618685e-08 3.237370e-08 1.0000000
[30,] 6.224988e-09 1.244998e-08 1.0000000
[31,] 2.440821e-09 4.881641e-09 1.0000000
[32,] 8.523222e-10 1.704644e-09 1.0000000
[33,] 3.323688e-10 6.647375e-10 1.0000000
[34,] 1.214412e-10 2.428823e-10 1.0000000
[35,] 9.446810e-10 1.889362e-09 1.0000000
[36,] 5.203738e-10 1.040748e-09 1.0000000
[37,] 2.512964e-10 5.025927e-10 1.0000000
[38,] 1.303720e-10 2.607439e-10 1.0000000
[39,] 5.170315e-11 1.034063e-10 1.0000000
[40,] 1.895345e-10 3.790691e-10 1.0000000
[41,] 2.890598e-10 5.781196e-10 1.0000000
[42,] 1.341921e-06 2.683843e-06 0.9999987
[43,] 1.014177e-06 2.028353e-06 0.9999990
[44,] 5.544311e-07 1.108862e-06 0.9999994
[45,] 2.834092e-07 5.668184e-07 0.9999997
[46,] 1.334366e-07 2.668732e-07 0.9999999
[47,] 1.113933e-07 2.227867e-07 0.9999999
[48,] 5.931540e-08 1.186308e-07 0.9999999
[49,] 3.597403e-08 7.194806e-08 1.0000000
[50,] 4.183048e-08 8.366096e-08 1.0000000
[51,] 2.339448e-08 4.678897e-08 1.0000000
[52,] 1.411774e-08 2.823547e-08 1.0000000
[53,] 5.327457e-08 1.065491e-07 0.9999999
[54,] 3.113108e-08 6.226215e-08 1.0000000
[55,] 2.338393e-08 4.676785e-08 1.0000000
[56,] 2.068784e-08 4.137567e-08 1.0000000
[57,] 1.236155e-08 2.472309e-08 1.0000000
[58,] 7.419131e-09 1.483826e-08 1.0000000
[59,] 1.212551e-08 2.425102e-08 1.0000000
[60,] 7.018722e-09 1.403744e-08 1.0000000
[61,] 7.472327e-09 1.494465e-08 1.0000000
[62,] 7.319196e-09 1.463839e-08 1.0000000
[63,] 5.270219e-09 1.054044e-08 1.0000000
[64,] 7.309627e-09 1.461925e-08 1.0000000
[65,] 5.325856e-09 1.065171e-08 1.0000000
[66,] 4.372940e-09 8.745880e-09 1.0000000
[67,] 5.619442e-09 1.123888e-08 1.0000000
[68,] 1.495990e-08 2.991980e-08 1.0000000
[69,] 2.839616e-07 5.679232e-07 0.9999997
[70,] 3.421524e-07 6.843048e-07 0.9999997
[71,] 1.024143e-04 2.048285e-04 0.9998976
[72,] 1.679254e-03 3.358508e-03 0.9983207
[73,] 1.398623e-03 2.797246e-03 0.9986014
[74,] 3.150578e-03 6.301155e-03 0.9968494
[75,] 2.792961e-03 5.585922e-03 0.9972070
[76,] 1.873437e-03 3.746875e-03 0.9981266
[77,] 1.391428e-03 2.782857e-03 0.9986086
[78,] 8.822913e-04 1.764583e-03 0.9991177
[79,] 5.589378e-04 1.117876e-03 0.9994411
[80,] 3.251390e-04 6.502779e-04 0.9996749
[81,] 2.573195e-04 5.146389e-04 0.9997427
[82,] 1.460640e-04 2.921280e-04 0.9998539
[83,] 1.889913e-04 3.779825e-04 0.9998110
[84,] 1.862116e-04 3.724232e-04 0.9998138
[85,] 1.008492e-04 2.016984e-04 0.9998992
[86,] 5.912166e-05 1.182433e-04 0.9999409
[87,] 1.650845e-03 3.301689e-03 0.9983492
[88,] 9.942215e-03 1.988443e-02 0.9900578
[89,] 1.415753e-02 2.831505e-02 0.9858425
[90,] 9.648274e-03 1.929655e-02 0.9903517
[91,] 1.226678e-02 2.453357e-02 0.9877332
[92,] 7.783198e-03 1.556640e-02 0.9922168
[93,] 7.863661e-02 1.572732e-01 0.9213634
[94,] 8.006866e-02 1.601373e-01 0.9199313
[95,] 5.041312e-01 9.917377e-01 0.4958688
[96,] 8.472235e-01 3.055531e-01 0.1527765
[97,] 8.221473e-01 3.557053e-01 0.1778527
[98,] 8.991385e-01 2.017230e-01 0.1008615
[99,] 8.073661e-01 3.852678e-01 0.1926339
[100,] 6.573460e-01 6.853080e-01 0.3426540
> postscript(file="/var/www/html/rcomp/tmp/1t2f41258473450.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$resid)
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/23wx21258473450.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> plot(mysum$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/3salx1258473450.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> hist(mysum$resid, main='Residual Histogram', xlab='values of Residuals')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/4kxn31258473450.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> densityplot(~mysum$resid,col='black',main='Residual Density Plot', xlab='values of Residuals')
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/57a5j1258473450.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 = 115
Frequency = 1
1 2 3 4 5 6
9.65679098 -3.20520619 3.71396521 0.92687995 1.05911909 5.90481258
7 8 9 10 11 12
1.83916258 -2.67423497 -0.38193093 -0.14663618 3.88931548 2.57259590
13 14 15 16 17 18
-1.04117910 0.94907537 4.29191308 -2.57878240 -6.03468219 0.24312317
19 20 21 22 23 24
0.23589734 -3.41037774 -3.71750559 -1.04651581 6.44816859 -3.62868556
25 26 27 28 29 30
0.59377038 -1.05907300 0.04544204 -2.75224179 -1.63690003 -1.36633822
31 32 33 34 35 36
-2.38743721 -3.56566648 0.86385621 -1.40143549 -0.94812937 5.10978430
37 38 39 40 41 42
-6.74349623 -6.01269190 -2.57321838 -1.21525419 -2.02158500 4.88123878
43 44 45 46 47 48
-2.20255196 -2.42310506 -7.75274308 -2.30499085 4.17338342 1.61123694
49 50 51 52 53 54
16.17567835 -6.26895360 -4.70290444 -4.56179018 -3.31053443 3.27684513
55 56 57 58 59 60
0.85017471 -5.58063701 -8.51787849 -4.74007312 1.65058101 8.31394979
61 62 63 64 65 66
-5.06757161 -6.32621924 -6.60647974 1.54622917 1.03681444 6.22077090
67 68 69 70 71 72
0.60224982 -6.74338060 -5.22120412 1.92236934 6.33088635 0.50189686
73 74 75 76 77 78
0.01302845 7.04163470 11.65779344 -10.46377329 11.10475341 27.86477874
79 80 81 82 83 84
-13.83594754 11.93059538 -6.88881075 -1.02908951 7.28463065 -0.26515632
85 86 87 88 89 90
6.45553870 0.86121906 3.84161150 -2.86060024 2.13427095 -6.19297754
91 92 93 94 95 96
-3.83301511 5.97175947 2.51010146 -12.08721410 23.95762106 -0.64209690
97 98 99 100 101 102
5.59825939 13.56871097 3.07295811 9.68448629 -15.87643826 -1.84984649
103 104 105 106 107 108
-18.14472278 -20.06664952 -0.49587802 -7.79157579 4.21228463 -13.32993074
109 110 111 112 113 114
-4.57896521 10.22014832 4.91011883 -3.32346902 -3.23911678 11.44747570
115
-2.10626111
> postscript(file="/var/www/html/rcomp/tmp/6ingw1258473450.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 = 115
Frequency = 1
lag(myerror, k = 1) myerror
0 9.65679098 NA
1 -3.20520619 9.65679098
2 3.71396521 -3.20520619
3 0.92687995 3.71396521
4 1.05911909 0.92687995
5 5.90481258 1.05911909
6 1.83916258 5.90481258
7 -2.67423497 1.83916258
8 -0.38193093 -2.67423497
9 -0.14663618 -0.38193093
10 3.88931548 -0.14663618
11 2.57259590 3.88931548
12 -1.04117910 2.57259590
13 0.94907537 -1.04117910
14 4.29191308 0.94907537
15 -2.57878240 4.29191308
16 -6.03468219 -2.57878240
17 0.24312317 -6.03468219
18 0.23589734 0.24312317
19 -3.41037774 0.23589734
20 -3.71750559 -3.41037774
21 -1.04651581 -3.71750559
22 6.44816859 -1.04651581
23 -3.62868556 6.44816859
24 0.59377038 -3.62868556
25 -1.05907300 0.59377038
26 0.04544204 -1.05907300
27 -2.75224179 0.04544204
28 -1.63690003 -2.75224179
29 -1.36633822 -1.63690003
30 -2.38743721 -1.36633822
31 -3.56566648 -2.38743721
32 0.86385621 -3.56566648
33 -1.40143549 0.86385621
34 -0.94812937 -1.40143549
35 5.10978430 -0.94812937
36 -6.74349623 5.10978430
37 -6.01269190 -6.74349623
38 -2.57321838 -6.01269190
39 -1.21525419 -2.57321838
40 -2.02158500 -1.21525419
41 4.88123878 -2.02158500
42 -2.20255196 4.88123878
43 -2.42310506 -2.20255196
44 -7.75274308 -2.42310506
45 -2.30499085 -7.75274308
46 4.17338342 -2.30499085
47 1.61123694 4.17338342
48 16.17567835 1.61123694
49 -6.26895360 16.17567835
50 -4.70290444 -6.26895360
51 -4.56179018 -4.70290444
52 -3.31053443 -4.56179018
53 3.27684513 -3.31053443
54 0.85017471 3.27684513
55 -5.58063701 0.85017471
56 -8.51787849 -5.58063701
57 -4.74007312 -8.51787849
58 1.65058101 -4.74007312
59 8.31394979 1.65058101
60 -5.06757161 8.31394979
61 -6.32621924 -5.06757161
62 -6.60647974 -6.32621924
63 1.54622917 -6.60647974
64 1.03681444 1.54622917
65 6.22077090 1.03681444
66 0.60224982 6.22077090
67 -6.74338060 0.60224982
68 -5.22120412 -6.74338060
69 1.92236934 -5.22120412
70 6.33088635 1.92236934
71 0.50189686 6.33088635
72 0.01302845 0.50189686
73 7.04163470 0.01302845
74 11.65779344 7.04163470
75 -10.46377329 11.65779344
76 11.10475341 -10.46377329
77 27.86477874 11.10475341
78 -13.83594754 27.86477874
79 11.93059538 -13.83594754
80 -6.88881075 11.93059538
81 -1.02908951 -6.88881075
82 7.28463065 -1.02908951
83 -0.26515632 7.28463065
84 6.45553870 -0.26515632
85 0.86121906 6.45553870
86 3.84161150 0.86121906
87 -2.86060024 3.84161150
88 2.13427095 -2.86060024
89 -6.19297754 2.13427095
90 -3.83301511 -6.19297754
91 5.97175947 -3.83301511
92 2.51010146 5.97175947
93 -12.08721410 2.51010146
94 23.95762106 -12.08721410
95 -0.64209690 23.95762106
96 5.59825939 -0.64209690
97 13.56871097 5.59825939
98 3.07295811 13.56871097
99 9.68448629 3.07295811
100 -15.87643826 9.68448629
101 -1.84984649 -15.87643826
102 -18.14472278 -1.84984649
103 -20.06664952 -18.14472278
104 -0.49587802 -20.06664952
105 -7.79157579 -0.49587802
106 4.21228463 -7.79157579
107 -13.32993074 4.21228463
108 -4.57896521 -13.32993074
109 10.22014832 -4.57896521
110 4.91011883 10.22014832
111 -3.32346902 4.91011883
112 -3.23911678 -3.32346902
113 11.44747570 -3.23911678
114 -2.10626111 11.44747570
115 NA -2.10626111
> dum1 <- dum[2:length(myerror),]
> dum1
lag(myerror, k = 1) myerror
[1,] -3.20520619 9.65679098
[2,] 3.71396521 -3.20520619
[3,] 0.92687995 3.71396521
[4,] 1.05911909 0.92687995
[5,] 5.90481258 1.05911909
[6,] 1.83916258 5.90481258
[7,] -2.67423497 1.83916258
[8,] -0.38193093 -2.67423497
[9,] -0.14663618 -0.38193093
[10,] 3.88931548 -0.14663618
[11,] 2.57259590 3.88931548
[12,] -1.04117910 2.57259590
[13,] 0.94907537 -1.04117910
[14,] 4.29191308 0.94907537
[15,] -2.57878240 4.29191308
[16,] -6.03468219 -2.57878240
[17,] 0.24312317 -6.03468219
[18,] 0.23589734 0.24312317
[19,] -3.41037774 0.23589734
[20,] -3.71750559 -3.41037774
[21,] -1.04651581 -3.71750559
[22,] 6.44816859 -1.04651581
[23,] -3.62868556 6.44816859
[24,] 0.59377038 -3.62868556
[25,] -1.05907300 0.59377038
[26,] 0.04544204 -1.05907300
[27,] -2.75224179 0.04544204
[28,] -1.63690003 -2.75224179
[29,] -1.36633822 -1.63690003
[30,] -2.38743721 -1.36633822
[31,] -3.56566648 -2.38743721
[32,] 0.86385621 -3.56566648
[33,] -1.40143549 0.86385621
[34,] -0.94812937 -1.40143549
[35,] 5.10978430 -0.94812937
[36,] -6.74349623 5.10978430
[37,] -6.01269190 -6.74349623
[38,] -2.57321838 -6.01269190
[39,] -1.21525419 -2.57321838
[40,] -2.02158500 -1.21525419
[41,] 4.88123878 -2.02158500
[42,] -2.20255196 4.88123878
[43,] -2.42310506 -2.20255196
[44,] -7.75274308 -2.42310506
[45,] -2.30499085 -7.75274308
[46,] 4.17338342 -2.30499085
[47,] 1.61123694 4.17338342
[48,] 16.17567835 1.61123694
[49,] -6.26895360 16.17567835
[50,] -4.70290444 -6.26895360
[51,] -4.56179018 -4.70290444
[52,] -3.31053443 -4.56179018
[53,] 3.27684513 -3.31053443
[54,] 0.85017471 3.27684513
[55,] -5.58063701 0.85017471
[56,] -8.51787849 -5.58063701
[57,] -4.74007312 -8.51787849
[58,] 1.65058101 -4.74007312
[59,] 8.31394979 1.65058101
[60,] -5.06757161 8.31394979
[61,] -6.32621924 -5.06757161
[62,] -6.60647974 -6.32621924
[63,] 1.54622917 -6.60647974
[64,] 1.03681444 1.54622917
[65,] 6.22077090 1.03681444
[66,] 0.60224982 6.22077090
[67,] -6.74338060 0.60224982
[68,] -5.22120412 -6.74338060
[69,] 1.92236934 -5.22120412
[70,] 6.33088635 1.92236934
[71,] 0.50189686 6.33088635
[72,] 0.01302845 0.50189686
[73,] 7.04163470 0.01302845
[74,] 11.65779344 7.04163470
[75,] -10.46377329 11.65779344
[76,] 11.10475341 -10.46377329
[77,] 27.86477874 11.10475341
[78,] -13.83594754 27.86477874
[79,] 11.93059538 -13.83594754
[80,] -6.88881075 11.93059538
[81,] -1.02908951 -6.88881075
[82,] 7.28463065 -1.02908951
[83,] -0.26515632 7.28463065
[84,] 6.45553870 -0.26515632
[85,] 0.86121906 6.45553870
[86,] 3.84161150 0.86121906
[87,] -2.86060024 3.84161150
[88,] 2.13427095 -2.86060024
[89,] -6.19297754 2.13427095
[90,] -3.83301511 -6.19297754
[91,] 5.97175947 -3.83301511
[92,] 2.51010146 5.97175947
[93,] -12.08721410 2.51010146
[94,] 23.95762106 -12.08721410
[95,] -0.64209690 23.95762106
[96,] 5.59825939 -0.64209690
[97,] 13.56871097 5.59825939
[98,] 3.07295811 13.56871097
[99,] 9.68448629 3.07295811
[100,] -15.87643826 9.68448629
[101,] -1.84984649 -15.87643826
[102,] -18.14472278 -1.84984649
[103,] -20.06664952 -18.14472278
[104,] -0.49587802 -20.06664952
[105,] -7.79157579 -0.49587802
[106,] 4.21228463 -7.79157579
[107,] -13.32993074 4.21228463
[108,] -4.57896521 -13.32993074
[109,] 10.22014832 -4.57896521
[110,] 4.91011883 10.22014832
[111,] -3.32346902 4.91011883
[112,] -3.23911678 -3.32346902
[113,] 11.44747570 -3.23911678
[114,] -2.10626111 11.44747570
> z <- as.data.frame(dum1)
> z
lag(myerror, k = 1) myerror
1 -3.20520619 9.65679098
2 3.71396521 -3.20520619
3 0.92687995 3.71396521
4 1.05911909 0.92687995
5 5.90481258 1.05911909
6 1.83916258 5.90481258
7 -2.67423497 1.83916258
8 -0.38193093 -2.67423497
9 -0.14663618 -0.38193093
10 3.88931548 -0.14663618
11 2.57259590 3.88931548
12 -1.04117910 2.57259590
13 0.94907537 -1.04117910
14 4.29191308 0.94907537
15 -2.57878240 4.29191308
16 -6.03468219 -2.57878240
17 0.24312317 -6.03468219
18 0.23589734 0.24312317
19 -3.41037774 0.23589734
20 -3.71750559 -3.41037774
21 -1.04651581 -3.71750559
22 6.44816859 -1.04651581
23 -3.62868556 6.44816859
24 0.59377038 -3.62868556
25 -1.05907300 0.59377038
26 0.04544204 -1.05907300
27 -2.75224179 0.04544204
28 -1.63690003 -2.75224179
29 -1.36633822 -1.63690003
30 -2.38743721 -1.36633822
31 -3.56566648 -2.38743721
32 0.86385621 -3.56566648
33 -1.40143549 0.86385621
34 -0.94812937 -1.40143549
35 5.10978430 -0.94812937
36 -6.74349623 5.10978430
37 -6.01269190 -6.74349623
38 -2.57321838 -6.01269190
39 -1.21525419 -2.57321838
40 -2.02158500 -1.21525419
41 4.88123878 -2.02158500
42 -2.20255196 4.88123878
43 -2.42310506 -2.20255196
44 -7.75274308 -2.42310506
45 -2.30499085 -7.75274308
46 4.17338342 -2.30499085
47 1.61123694 4.17338342
48 16.17567835 1.61123694
49 -6.26895360 16.17567835
50 -4.70290444 -6.26895360
51 -4.56179018 -4.70290444
52 -3.31053443 -4.56179018
53 3.27684513 -3.31053443
54 0.85017471 3.27684513
55 -5.58063701 0.85017471
56 -8.51787849 -5.58063701
57 -4.74007312 -8.51787849
58 1.65058101 -4.74007312
59 8.31394979 1.65058101
60 -5.06757161 8.31394979
61 -6.32621924 -5.06757161
62 -6.60647974 -6.32621924
63 1.54622917 -6.60647974
64 1.03681444 1.54622917
65 6.22077090 1.03681444
66 0.60224982 6.22077090
67 -6.74338060 0.60224982
68 -5.22120412 -6.74338060
69 1.92236934 -5.22120412
70 6.33088635 1.92236934
71 0.50189686 6.33088635
72 0.01302845 0.50189686
73 7.04163470 0.01302845
74 11.65779344 7.04163470
75 -10.46377329 11.65779344
76 11.10475341 -10.46377329
77 27.86477874 11.10475341
78 -13.83594754 27.86477874
79 11.93059538 -13.83594754
80 -6.88881075 11.93059538
81 -1.02908951 -6.88881075
82 7.28463065 -1.02908951
83 -0.26515632 7.28463065
84 6.45553870 -0.26515632
85 0.86121906 6.45553870
86 3.84161150 0.86121906
87 -2.86060024 3.84161150
88 2.13427095 -2.86060024
89 -6.19297754 2.13427095
90 -3.83301511 -6.19297754
91 5.97175947 -3.83301511
92 2.51010146 5.97175947
93 -12.08721410 2.51010146
94 23.95762106 -12.08721410
95 -0.64209690 23.95762106
96 5.59825939 -0.64209690
97 13.56871097 5.59825939
98 3.07295811 13.56871097
99 9.68448629 3.07295811
100 -15.87643826 9.68448629
101 -1.84984649 -15.87643826
102 -18.14472278 -1.84984649
103 -20.06664952 -18.14472278
104 -0.49587802 -20.06664952
105 -7.79157579 -0.49587802
106 4.21228463 -7.79157579
107 -13.32993074 4.21228463
108 -4.57896521 -13.32993074
109 10.22014832 -4.57896521
110 4.91011883 10.22014832
111 -3.32346902 4.91011883
112 -3.23911678 -3.32346902
113 11.44747570 -3.23911678
114 -2.10626111 11.44747570
> 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/7fiml1258473450.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> acf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/89us11258473450.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> pacf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Partial Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/9p7u81258473450.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> opar <- par(mfrow = c(2,2), oma = c(0, 0, 1.1, 0))
> plot(mylm, las = 1, sub='Residual Diagnostics')
> par(opar)
> dev.off()
null device
1
> if (n > n25) {
+ postscript(file="/var/www/html/rcomp/tmp/10vhw51258473450.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
+ plot(kp3:nmkm3,gqarr[,2], main='Goldfeld-Quandt test',ylab='2-sided p-value',xlab='breakpoint')
+ grid()
+ dev.off()
+ }
null device
1
>
> #Note: the /var/www/html/rcomp/createtable file can be downloaded at http://www.wessa.net/cretab
> load(file="/var/www/html/rcomp/createtable")
>
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a, 'Multiple Linear Regression - Estimated Regression Equation', 1, TRUE)
> a<-table.row.end(a)
> myeq <- colnames(x)[1]
> myeq <- paste(myeq, '[t] = ', sep='')
> for (i in 1:k){
+ if (mysum$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/11wq6f1258473450.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/12n8cs1258473450.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/1389ht1258473450.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/14cqka1258473450.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/15hrcf1258473450.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/16bc6k1258473450.tab")
+ }
>
> system("convert tmp/1t2f41258473450.ps tmp/1t2f41258473450.png")
> system("convert tmp/23wx21258473450.ps tmp/23wx21258473450.png")
> system("convert tmp/3salx1258473450.ps tmp/3salx1258473450.png")
> system("convert tmp/4kxn31258473450.ps tmp/4kxn31258473450.png")
> system("convert tmp/57a5j1258473450.ps tmp/57a5j1258473450.png")
> system("convert tmp/6ingw1258473450.ps tmp/6ingw1258473450.png")
> system("convert tmp/7fiml1258473450.ps tmp/7fiml1258473450.png")
> system("convert tmp/89us11258473450.ps tmp/89us11258473450.png")
> system("convert tmp/9p7u81258473450.ps tmp/9p7u81258473450.png")
> system("convert tmp/10vhw51258473450.ps tmp/10vhw51258473450.png")
>
>
> proc.time()
user system elapsed
3.215 1.636 4.475