R version 2.8.0 (2008-10-20)
Copyright (C) 2008 The R Foundation for Statistical Computing
ISBN 3-900051-07-0
R is free software and comes with ABSOLUTELY NO WARRANTY.
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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
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> x <- array(list(121148,0,114624,0,109822,0,112081,0,113534,0,112110,0,109826,0,107423,0,105540,0,108573,0,128591,0,139145,0,129700,0,132828,0,126868,0,128390,0,126830,0,124105,0,122323,0,119296,0,116822,0,119224,0,139357,0,144322,0,133676,0,128283,0,121640,0,122877,1,117284,1,116463,1,112685,1,113235,1,111692,1,113152,1,129889,1,131153,1,123770,1,112516,1,105940,1,104320,1,103582,1,99064,1,94989,1,92241,1,89752,1,90610,1,109456,1,110213,1,97694,1,91844,1,87572,1,89812,1,89050,1,85990,1,85070,1,83277,1,79586,1,84215,1,99708,1,100698,1,90861,1,86700,1),dim=c(2,62),dimnames=list(c('werkl.vrouwen','Wetswijziging'),1:62))
> y <- array(NA,dim=c(2,62),dimnames=list(c('werkl.vrouwen','Wetswijziging'),1:62))
> 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
werkl.vrouwen Wetswijziging t
1 121148 0 1
2 114624 0 2
3 109822 0 3
4 112081 0 4
5 113534 0 5
6 112110 0 6
7 109826 0 7
8 107423 0 8
9 105540 0 9
10 108573 0 10
11 128591 0 11
12 139145 0 12
13 129700 0 13
14 132828 0 14
15 126868 0 15
16 128390 0 16
17 126830 0 17
18 124105 0 18
19 122323 0 19
20 119296 0 20
21 116822 0 21
22 119224 0 22
23 139357 0 23
24 144322 0 24
25 133676 0 25
26 128283 0 26
27 121640 0 27
28 122877 1 28
29 117284 1 29
30 116463 1 30
31 112685 1 31
32 113235 1 32
33 111692 1 33
34 113152 1 34
35 129889 1 35
36 131153 1 36
37 123770 1 37
38 112516 1 38
39 105940 1 39
40 104320 1 40
41 103582 1 41
42 99064 1 42
43 94989 1 43
44 92241 1 44
45 89752 1 45
46 90610 1 46
47 109456 1 47
48 110213 1 48
49 97694 1 49
50 91844 1 50
51 87572 1 51
52 89812 1 52
53 89050 1 53
54 85990 1 54
55 85070 1 55
56 83277 1 56
57 79586 1 57
58 84215 1 58
59 99708 1 59
60 100698 1 60
61 90861 1 61
62 86700 1 62
> k <- length(x[1,])
> df <- as.data.frame(x)
> (mylm <- lm(df))
Call:
lm(formula = df)
Coefficients:
(Intercept) Wetswijziging t
129316 -4421 -517
> (mysum <- summary(mylm))
Call:
lm(formula = df)
Residuals:
Min 1Q Median 3Q Max
-19122.3 -10643.2 765.7 7099.4 27415.4
Coefficients:
Estimate Std. Error t value Pr(>|t|)
(Intercept) 129316 3253 39.751 < 2e-16 ***
Wetswijziging -4421 5954 -0.743 0.46068
t -517 165 -3.134 0.00268 **
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
Residual standard error: 11900 on 59 degrees of freedom
Multiple R-squared: 0.4815, Adjusted R-squared: 0.464
F-statistic: 27.4 on 2 and 59 DF, p-value: 3.838e-09
> 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,] 0.053683184 0.107366367 0.94631682
[2,] 0.017551704 0.035103408 0.98244830
[3,] 0.006232561 0.012465122 0.99376744
[4,] 0.002718816 0.005437633 0.99728118
[5,] 0.002318308 0.004636616 0.99768169
[6,] 0.328482426 0.656964852 0.67151757
[7,] 0.765615198 0.468769603 0.23438480
[8,] 0.726307662 0.547384677 0.27369234
[9,] 0.677689929 0.644620142 0.32231007
[10,] 0.600102831 0.799794338 0.39989717
[11,] 0.514411217 0.971177565 0.48558878
[12,] 0.440577996 0.881155991 0.55942200
[13,] 0.400440244 0.800880488 0.59955976
[14,] 0.386149524 0.772299048 0.61385048
[15,] 0.424736877 0.849473754 0.57526312
[16,] 0.520570216 0.958859569 0.47942978
[17,] 0.571640161 0.856719677 0.42835984
[18,] 0.585497615 0.829004769 0.41450238
[19,] 0.673487115 0.653025770 0.32651289
[20,] 0.613535356 0.772929288 0.38646464
[21,] 0.559286101 0.881427798 0.44071390
[22,] 0.555453384 0.889093232 0.44454662
[23,] 0.481106798 0.962213596 0.51889320
[24,] 0.417528742 0.835057485 0.58247126
[25,] 0.353506301 0.707012602 0.64649370
[26,] 0.315435756 0.630871513 0.68456424
[27,] 0.268358479 0.536716957 0.73164152
[28,] 0.232817357 0.465634714 0.76718264
[29,] 0.188221185 0.376442369 0.81177882
[30,] 0.266695344 0.533390687 0.73330466
[31,] 0.476395917 0.952791835 0.52360408
[32,] 0.621699397 0.756601207 0.37830060
[33,] 0.660823806 0.678352389 0.33917619
[34,] 0.700167120 0.599665759 0.29983288
[35,] 0.730906626 0.538186748 0.26909337
[36,] 0.752835420 0.494329160 0.24716458
[37,] 0.773734218 0.452531563 0.22626578
[38,] 0.797554337 0.404891326 0.20244566
[39,] 0.820932449 0.358135101 0.17906755
[40,] 0.851475255 0.297049491 0.14852475
[41,] 0.861951939 0.276096122 0.13804806
[42,] 0.881009465 0.237981070 0.11899054
[43,] 0.962800708 0.074398583 0.03719929
[44,] 0.968221379 0.063557242 0.03177862
[45,] 0.960192564 0.079614872 0.03980744
[46,] 0.939464906 0.121070188 0.06053509
[47,] 0.914694769 0.170610462 0.08530523
[48,] 0.881025864 0.237948272 0.11897414
[49,] 0.813347317 0.373305366 0.18665268
[50,] 0.704283192 0.591433615 0.29571681
[51,] 0.548060587 0.903878826 0.45193941
> postscript(file="/var/www/html/rcomp/tmp/1oeyd1229886419.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$resid)
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/2kzuf1229886419.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> plot(mysum$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/3hh2j1229886419.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> hist(mysum$resid, main='Residual Histogram', xlab='values of Residuals')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/4bgus1229886419.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> densityplot(~mysum$resid,col='black',main='Residual Density Plot', xlab='values of Residuals')
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/5ki7k1229886419.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 = 62
Frequency = 1
1 2 3 4 5 6
-7650.6507 -13657.6063 -17942.5620 -15166.5176 -13196.4733 -14103.4289
7 8 9 10 11 12
-15870.3846 -17756.3402 -19122.2958 -15572.2515 4962.7929 16033.8372
13 14 15 16 17 18
7105.8816 10750.9259 5307.9703 7347.0146 6304.0590 4096.1033
19 20 21 22 23 24
2831.1477 321.1921 -1635.7636 1283.2808 21933.3251 27415.3695
25 26 27 28 29 30
17286.4138 12410.4582 6284.5025 12459.8174 7383.8618 7079.9061
31 32 33 34 35 36
3818.9505 4885.9948 3860.0392 5837.0835 23091.1279 24872.1722
37 38 39 40 41 42
18006.2166 7269.2609 1210.3053 107.3497 -113.6060 -4114.5616
43 44 45 46 47 48
-7672.5173 -9903.4729 -11875.4286 -10500.3842 8862.6601 10136.7045
49 50 51 52 53 54
-1865.2512 -7198.2068 -10953.1624 -8196.1181 -8441.0737 -10984.0294
55 56 57 58 59 60
-11386.9850 -12662.9407 -15836.8963 -10690.8520 5319.1924 6826.2368
61 62
-2493.7189 -6137.6745
> postscript(file="/var/www/html/rcomp/tmp/6fk6u1229886419.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 = 62
Frequency = 1
lag(myerror, k = 1) myerror
0 -7650.6507 NA
1 -13657.6063 -7650.6507
2 -17942.5620 -13657.6063
3 -15166.5176 -17942.5620
4 -13196.4733 -15166.5176
5 -14103.4289 -13196.4733
6 -15870.3846 -14103.4289
7 -17756.3402 -15870.3846
8 -19122.2958 -17756.3402
9 -15572.2515 -19122.2958
10 4962.7929 -15572.2515
11 16033.8372 4962.7929
12 7105.8816 16033.8372
13 10750.9259 7105.8816
14 5307.9703 10750.9259
15 7347.0146 5307.9703
16 6304.0590 7347.0146
17 4096.1033 6304.0590
18 2831.1477 4096.1033
19 321.1921 2831.1477
20 -1635.7636 321.1921
21 1283.2808 -1635.7636
22 21933.3251 1283.2808
23 27415.3695 21933.3251
24 17286.4138 27415.3695
25 12410.4582 17286.4138
26 6284.5025 12410.4582
27 12459.8174 6284.5025
28 7383.8618 12459.8174
29 7079.9061 7383.8618
30 3818.9505 7079.9061
31 4885.9948 3818.9505
32 3860.0392 4885.9948
33 5837.0835 3860.0392
34 23091.1279 5837.0835
35 24872.1722 23091.1279
36 18006.2166 24872.1722
37 7269.2609 18006.2166
38 1210.3053 7269.2609
39 107.3497 1210.3053
40 -113.6060 107.3497
41 -4114.5616 -113.6060
42 -7672.5173 -4114.5616
43 -9903.4729 -7672.5173
44 -11875.4286 -9903.4729
45 -10500.3842 -11875.4286
46 8862.6601 -10500.3842
47 10136.7045 8862.6601
48 -1865.2512 10136.7045
49 -7198.2068 -1865.2512
50 -10953.1624 -7198.2068
51 -8196.1181 -10953.1624
52 -8441.0737 -8196.1181
53 -10984.0294 -8441.0737
54 -11386.9850 -10984.0294
55 -12662.9407 -11386.9850
56 -15836.8963 -12662.9407
57 -10690.8520 -15836.8963
58 5319.1924 -10690.8520
59 6826.2368 5319.1924
60 -2493.7189 6826.2368
61 -6137.6745 -2493.7189
62 NA -6137.6745
> dum1 <- dum[2:length(myerror),]
> dum1
lag(myerror, k = 1) myerror
[1,] -13657.6063 -7650.6507
[2,] -17942.5620 -13657.6063
[3,] -15166.5176 -17942.5620
[4,] -13196.4733 -15166.5176
[5,] -14103.4289 -13196.4733
[6,] -15870.3846 -14103.4289
[7,] -17756.3402 -15870.3846
[8,] -19122.2958 -17756.3402
[9,] -15572.2515 -19122.2958
[10,] 4962.7929 -15572.2515
[11,] 16033.8372 4962.7929
[12,] 7105.8816 16033.8372
[13,] 10750.9259 7105.8816
[14,] 5307.9703 10750.9259
[15,] 7347.0146 5307.9703
[16,] 6304.0590 7347.0146
[17,] 4096.1033 6304.0590
[18,] 2831.1477 4096.1033
[19,] 321.1921 2831.1477
[20,] -1635.7636 321.1921
[21,] 1283.2808 -1635.7636
[22,] 21933.3251 1283.2808
[23,] 27415.3695 21933.3251
[24,] 17286.4138 27415.3695
[25,] 12410.4582 17286.4138
[26,] 6284.5025 12410.4582
[27,] 12459.8174 6284.5025
[28,] 7383.8618 12459.8174
[29,] 7079.9061 7383.8618
[30,] 3818.9505 7079.9061
[31,] 4885.9948 3818.9505
[32,] 3860.0392 4885.9948
[33,] 5837.0835 3860.0392
[34,] 23091.1279 5837.0835
[35,] 24872.1722 23091.1279
[36,] 18006.2166 24872.1722
[37,] 7269.2609 18006.2166
[38,] 1210.3053 7269.2609
[39,] 107.3497 1210.3053
[40,] -113.6060 107.3497
[41,] -4114.5616 -113.6060
[42,] -7672.5173 -4114.5616
[43,] -9903.4729 -7672.5173
[44,] -11875.4286 -9903.4729
[45,] -10500.3842 -11875.4286
[46,] 8862.6601 -10500.3842
[47,] 10136.7045 8862.6601
[48,] -1865.2512 10136.7045
[49,] -7198.2068 -1865.2512
[50,] -10953.1624 -7198.2068
[51,] -8196.1181 -10953.1624
[52,] -8441.0737 -8196.1181
[53,] -10984.0294 -8441.0737
[54,] -11386.9850 -10984.0294
[55,] -12662.9407 -11386.9850
[56,] -15836.8963 -12662.9407
[57,] -10690.8520 -15836.8963
[58,] 5319.1924 -10690.8520
[59,] 6826.2368 5319.1924
[60,] -2493.7189 6826.2368
[61,] -6137.6745 -2493.7189
> z <- as.data.frame(dum1)
> z
lag(myerror, k = 1) myerror
1 -13657.6063 -7650.6507
2 -17942.5620 -13657.6063
3 -15166.5176 -17942.5620
4 -13196.4733 -15166.5176
5 -14103.4289 -13196.4733
6 -15870.3846 -14103.4289
7 -17756.3402 -15870.3846
8 -19122.2958 -17756.3402
9 -15572.2515 -19122.2958
10 4962.7929 -15572.2515
11 16033.8372 4962.7929
12 7105.8816 16033.8372
13 10750.9259 7105.8816
14 5307.9703 10750.9259
15 7347.0146 5307.9703
16 6304.0590 7347.0146
17 4096.1033 6304.0590
18 2831.1477 4096.1033
19 321.1921 2831.1477
20 -1635.7636 321.1921
21 1283.2808 -1635.7636
22 21933.3251 1283.2808
23 27415.3695 21933.3251
24 17286.4138 27415.3695
25 12410.4582 17286.4138
26 6284.5025 12410.4582
27 12459.8174 6284.5025
28 7383.8618 12459.8174
29 7079.9061 7383.8618
30 3818.9505 7079.9061
31 4885.9948 3818.9505
32 3860.0392 4885.9948
33 5837.0835 3860.0392
34 23091.1279 5837.0835
35 24872.1722 23091.1279
36 18006.2166 24872.1722
37 7269.2609 18006.2166
38 1210.3053 7269.2609
39 107.3497 1210.3053
40 -113.6060 107.3497
41 -4114.5616 -113.6060
42 -7672.5173 -4114.5616
43 -9903.4729 -7672.5173
44 -11875.4286 -9903.4729
45 -10500.3842 -11875.4286
46 8862.6601 -10500.3842
47 10136.7045 8862.6601
48 -1865.2512 10136.7045
49 -7198.2068 -1865.2512
50 -10953.1624 -7198.2068
51 -8196.1181 -10953.1624
52 -8441.0737 -8196.1181
53 -10984.0294 -8441.0737
54 -11386.9850 -10984.0294
55 -12662.9407 -11386.9850
56 -15836.8963 -12662.9407
57 -10690.8520 -15836.8963
58 5319.1924 -10690.8520
59 6826.2368 5319.1924
60 -2493.7189 6826.2368
61 -6137.6745 -2493.7189
> 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/7vg2t1229886419.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> acf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/8r62v1229886419.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> pacf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Partial Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/99jnb1229886419.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> opar <- par(mfrow = c(2,2), oma = c(0, 0, 1.1, 0))
> plot(mylm, las = 1, sub='Residual Diagnostics')
> par(opar)
> dev.off()
null device
1
> if (n > n25) {
+ postscript(file="/var/www/html/rcomp/tmp/10p5gz1229886419.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
+ plot(kp3:nmkm3,gqarr[,2], main='Goldfeld-Quandt test',ylab='2-sided p-value',xlab='breakpoint')
+ grid()
+ dev.off()
+ }
null device
1
>
> #Note: the /var/www/html/rcomp/createtable file can be downloaded at http://www.wessa.net/cretab
> load(file="/var/www/html/rcomp/createtable")
>
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a, 'Multiple Linear Regression - Estimated Regression Equation', 1, TRUE)
> a<-table.row.end(a)
> myeq <- colnames(x)[1]
> myeq <- paste(myeq, '[t] = ', sep='')
> for (i in 1:k){
+ if (mysum$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/11jyb11229886419.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/124sqn1229886419.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/13xxbo1229886419.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/14uco81229886419.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/15f4pu1229886419.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/16aybb1229886419.tab")
+ }
>
> system("convert tmp/1oeyd1229886419.ps tmp/1oeyd1229886419.png")
> system("convert tmp/2kzuf1229886419.ps tmp/2kzuf1229886419.png")
> system("convert tmp/3hh2j1229886419.ps tmp/3hh2j1229886419.png")
> system("convert tmp/4bgus1229886419.ps tmp/4bgus1229886419.png")
> system("convert tmp/5ki7k1229886419.ps tmp/5ki7k1229886419.png")
> system("convert tmp/6fk6u1229886419.ps tmp/6fk6u1229886419.png")
> system("convert tmp/7vg2t1229886419.ps tmp/7vg2t1229886419.png")
> system("convert tmp/8r62v1229886419.ps tmp/8r62v1229886419.png")
> system("convert tmp/99jnb1229886419.ps tmp/99jnb1229886419.png")
> system("convert tmp/10p5gz1229886419.ps tmp/10p5gz1229886419.png")
>
>
> proc.time()
user system elapsed
2.728 1.724 4.109