R version 2.12.0 (2010-10-15)
Copyright (C) 2010 The R Foundation for Statistical Computing
ISBN 3-900051-07-0
Platform: i486-pc-linux-gnu (32-bit)
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(1038.00,0,934.00,0,988.00,0,870.00,0,854.00,0,834.00,0,872.00,0,954.00,0,870.00,0,1238.00,0,1082.00,0,1053.00,0,934.00,0,787.00,0,1081.00,0,908.00,0,995.00,0,825.00,0,822.00,0,856.00,0,887.00,0,1094.00,0,990.00,0,936.00,0,1097.00,0,918.00,0,926.00,0,907.00,0,899.00,0,971.00,0,1087.00,0,1000.00,0,1071.00,0,1190.00,0,1116.00,0,1070.00,0,1314.00,0,1068.00,0,1185.00,0,1215.00,0,1145.00,0,1251.00,1,1363.00,1,1368.00,1,1535.00,1,1853.00,1,1866.00,1,2023.00,1,1373.00,1,1968.00,1,1424.00,1,1160.00,1,1243.00,1,1375.00,1,1539.00,1,1773.00,1,1906.00,1,2076.00,1,2004.00,1),dim=c(2,59),dimnames=list(c('Asielaanvragen','Verandering'),1:59))
> y <- array(NA,dim=c(2,59),dimnames=list(c('Asielaanvragen','Verandering'),1:59))
> for (i in 1:dim(x)[1])
+ {
+ for (j in 1:dim(x)[2])
+ {
+ y[i,j] <- as.numeric(x[i,j])
+ }
+ }
> par3 = 'No 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
> 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
Asielaanvragen Verandering M1 M2 M3 M4 M5 M6 M7 M8 M9 M10 M11
1 1038 0 1 0 0 0 0 0 0 0 0 0 0
2 934 0 0 1 0 0 0 0 0 0 0 0 0
3 988 0 0 0 1 0 0 0 0 0 0 0 0
4 870 0 0 0 0 1 0 0 0 0 0 0 0
5 854 0 0 0 0 0 1 0 0 0 0 0 0
6 834 0 0 0 0 0 0 1 0 0 0 0 0
7 872 0 0 0 0 0 0 0 1 0 0 0 0
8 954 0 0 0 0 0 0 0 0 1 0 0 0
9 870 0 0 0 0 0 0 0 0 0 1 0 0
10 1238 0 0 0 0 0 0 0 0 0 0 1 0
11 1082 0 0 0 0 0 0 0 0 0 0 0 1
12 1053 0 0 0 0 0 0 0 0 0 0 0 0
13 934 0 1 0 0 0 0 0 0 0 0 0 0
14 787 0 0 1 0 0 0 0 0 0 0 0 0
15 1081 0 0 0 1 0 0 0 0 0 0 0 0
16 908 0 0 0 0 1 0 0 0 0 0 0 0
17 995 0 0 0 0 0 1 0 0 0 0 0 0
18 825 0 0 0 0 0 0 1 0 0 0 0 0
19 822 0 0 0 0 0 0 0 1 0 0 0 0
20 856 0 0 0 0 0 0 0 0 1 0 0 0
21 887 0 0 0 0 0 0 0 0 0 1 0 0
22 1094 0 0 0 0 0 0 0 0 0 0 1 0
23 990 0 0 0 0 0 0 0 0 0 0 0 1
24 936 0 0 0 0 0 0 0 0 0 0 0 0
25 1097 0 1 0 0 0 0 0 0 0 0 0 0
26 918 0 0 1 0 0 0 0 0 0 0 0 0
27 926 0 0 0 1 0 0 0 0 0 0 0 0
28 907 0 0 0 0 1 0 0 0 0 0 0 0
29 899 0 0 0 0 0 1 0 0 0 0 0 0
30 971 0 0 0 0 0 0 1 0 0 0 0 0
31 1087 0 0 0 0 0 0 0 1 0 0 0 0
32 1000 0 0 0 0 0 0 0 0 1 0 0 0
33 1071 0 0 0 0 0 0 0 0 0 1 0 0
34 1190 0 0 0 0 0 0 0 0 0 0 1 0
35 1116 0 0 0 0 0 0 0 0 0 0 0 1
36 1070 0 0 0 0 0 0 0 0 0 0 0 0
37 1314 0 1 0 0 0 0 0 0 0 0 0 0
38 1068 0 0 1 0 0 0 0 0 0 0 0 0
39 1185 0 0 0 1 0 0 0 0 0 0 0 0
40 1215 0 0 0 0 1 0 0 0 0 0 0 0
41 1145 0 0 0 0 0 1 0 0 0 0 0 0
42 1251 1 0 0 0 0 0 1 0 0 0 0 0
43 1363 1 0 0 0 0 0 0 1 0 0 0 0
44 1368 1 0 0 0 0 0 0 0 1 0 0 0
45 1535 1 0 0 0 0 0 0 0 0 1 0 0
46 1853 1 0 0 0 0 0 0 0 0 0 1 0
47 1866 1 0 0 0 0 0 0 0 0 0 0 1
48 2023 1 0 0 0 0 0 0 0 0 0 0 0
49 1373 1 1 0 0 0 0 0 0 0 0 0 0
50 1968 1 0 1 0 0 0 0 0 0 0 0 0
51 1424 1 0 0 1 0 0 0 0 0 0 0 0
52 1160 1 0 0 0 1 0 0 0 0 0 0 0
53 1243 1 0 0 0 0 1 0 0 0 0 0 0
54 1375 1 0 0 0 0 0 1 0 0 0 0 0
55 1539 1 0 0 0 0 0 0 1 0 0 0 0
56 1773 1 0 0 0 0 0 0 0 1 0 0 0
57 1906 1 0 0 0 0 0 0 0 0 1 0 0
58 2076 1 0 0 0 0 0 0 0 0 0 1 0
59 2004 1 0 0 0 0 0 0 0 0 0 0 1
> k <- length(x[1,])
> df <- as.data.frame(x)
> (mylm <- lm(df))
Call:
lm(formula = df)
Coefficients:
(Intercept) Verandering M1 M2 M3 M4
1117.44 612.23 -88.69 -104.89 -119.09 -227.89
M5 M6 M7 M8 M9 M10
-212.69 -311.13 -225.73 -172.13 -108.53 127.87
M11
49.27
> (mysum <- summary(mylm))
Call:
lm(formula = df)
Residuals:
Min 1Q Median 3Q Max
-341.78 -91.93 -10.35 75.45 343.22
Coefficients:
Estimate Std. Error t value Pr(>|t|)
(Intercept) 1117.44 89.51 12.485 2.23e-16 ***
Verandering 612.23 51.25 11.946 1.06e-15 ***
M1 -88.69 118.87 -0.746 0.4594
M2 -104.89 118.87 -0.882 0.3822
M3 -119.09 118.87 -1.002 0.3217
M4 -227.89 118.87 -1.917 0.0615 .
M5 -212.69 118.87 -1.789 0.0802 .
M6 -311.13 119.10 -2.612 0.0121 *
M7 -225.73 119.10 -1.895 0.0643 .
M8 -172.13 119.10 -1.445 0.1551
M9 -108.53 119.10 -0.911 0.3669
M10 127.87 119.10 1.074 0.2886
M11 49.27 119.10 0.414 0.6810
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
Residual standard error: 177.2 on 46 degrees of freedom
Multiple R-squared: 0.797, Adjusted R-squared: 0.744
F-statistic: 15.05 on 12 and 46 DF, p-value: 3.94e-12
> 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,] 8.113603e-02 1.622721e-01 0.9188640
[2,] 5.150542e-02 1.030108e-01 0.9484946
[3,] 1.766426e-02 3.532853e-02 0.9823357
[4,] 6.230862e-03 1.246172e-02 0.9937691
[5,] 2.905960e-03 5.811919e-03 0.9970940
[6,] 9.638371e-04 1.927674e-03 0.9990362
[7,] 8.208605e-04 1.641721e-03 0.9991791
[8,] 4.650920e-04 9.301841e-04 0.9995349
[9,] 3.594790e-04 7.189579e-04 0.9996405
[10,] 2.158567e-04 4.317134e-04 0.9997841
[11,] 1.245015e-04 2.490030e-04 0.9998755
[12,] 7.705183e-05 1.541037e-04 0.9999229
[13,] 2.394471e-05 4.788942e-05 0.9999761
[14,] 7.217799e-06 1.443560e-05 0.9999928
[15,] 7.047686e-06 1.409537e-05 0.9999930
[16,] 3.006141e-05 6.012282e-05 0.9999699
[17,] 1.348457e-05 2.696914e-05 0.9999865
[18,] 1.707400e-05 3.414800e-05 0.9999829
[19,] 9.584583e-06 1.916917e-05 0.9999904
[20,] 1.227382e-05 2.454764e-05 0.9999877
[21,] 7.768302e-05 1.553660e-04 0.9999223
[22,] 4.241812e-04 8.483624e-04 0.9995758
[23,] 2.403377e-02 4.806754e-02 0.9759662
[24,] 2.626511e-02 5.253021e-02 0.9737349
[25,] 4.090361e-02 8.180722e-02 0.9590964
[26,] 3.078646e-02 6.157291e-02 0.9692135
[27,] 1.625937e-02 3.251875e-02 0.9837406
[28,] 9.150203e-03 1.830041e-02 0.9908498
> postscript(file="/var/www/rcomp/tmp/14e6r1292950630.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> plot(x[,1], type='l', main='Actuals and Interpolation', ylab='value of Actuals and Interpolation (dots)', xlab='time or index')
> points(x[,1]-mysum$resid)
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/rcomp/tmp/24e6r1292950630.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> plot(mysum$resid, type='b', pch=19, main='Residuals', ylab='value of Residuals', xlab='time or index')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/rcomp/tmp/3x55c1292950630.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> hist(mysum$resid, main='Residual Histogram', xlab='values of Residuals')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/rcomp/tmp/4x55c1292950630.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> densityplot(~mysum$resid,col='black',main='Residual Density Plot', xlab='values of Residuals')
> dev.off()
null device
1
> postscript(file="/var/www/rcomp/tmp/5x55c1292950630.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> qqnorm(mysum$resid, main='Residual Normal Q-Q Plot')
> qqline(mysum$resid)
> grid()
> dev.off()
null device
1
> (myerror <- as.ts(mysum$resid))
Time Series:
Start = 1
End = 59
Frequency = 1
1 2 3 4 5 6
9.245188 -78.554812 -10.354812 -19.554812 -50.754812 27.690377
7 8 9 10 11 12
-19.709623 8.690377 -138.909623 -7.309623 -84.709623 -64.443515
13 14 15 16 17 18
-94.754812 -225.554812 82.645188 18.445188 90.245188 18.690377
19 20 21 22 23 24
-69.709623 -89.309623 -121.909623 -151.309623 -176.709623 -181.443515
25 26 27 28 29 30
68.245188 -94.554812 -72.354812 17.445188 -5.754812 164.690377
31 32 33 34 35 36
195.290377 54.690377 62.090377 -55.309623 -50.709623 -47.443515
37 38 39 40 41 42
285.245188 55.445188 186.645188 325.445188 240.245188 -167.535565
43 44 45 46 47 48
-140.935565 -189.535565 -86.135565 -4.535565 87.064435 293.330544
49 50 51 52 53 54
-267.980753 343.219247 -186.580753 -341.780753 -273.980753 -43.535565
55 56 57 58 59
35.064435 215.464435 284.864435 218.464435 225.064435
> postscript(file="/var/www/rcomp/tmp/6qemf1292950630.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> dum <- cbind(lag(myerror,k=1),myerror)
> dum
Time Series:
Start = 0
End = 59
Frequency = 1
lag(myerror, k = 1) myerror
0 9.245188 NA
1 -78.554812 9.245188
2 -10.354812 -78.554812
3 -19.554812 -10.354812
4 -50.754812 -19.554812
5 27.690377 -50.754812
6 -19.709623 27.690377
7 8.690377 -19.709623
8 -138.909623 8.690377
9 -7.309623 -138.909623
10 -84.709623 -7.309623
11 -64.443515 -84.709623
12 -94.754812 -64.443515
13 -225.554812 -94.754812
14 82.645188 -225.554812
15 18.445188 82.645188
16 90.245188 18.445188
17 18.690377 90.245188
18 -69.709623 18.690377
19 -89.309623 -69.709623
20 -121.909623 -89.309623
21 -151.309623 -121.909623
22 -176.709623 -151.309623
23 -181.443515 -176.709623
24 68.245188 -181.443515
25 -94.554812 68.245188
26 -72.354812 -94.554812
27 17.445188 -72.354812
28 -5.754812 17.445188
29 164.690377 -5.754812
30 195.290377 164.690377
31 54.690377 195.290377
32 62.090377 54.690377
33 -55.309623 62.090377
34 -50.709623 -55.309623
35 -47.443515 -50.709623
36 285.245188 -47.443515
37 55.445188 285.245188
38 186.645188 55.445188
39 325.445188 186.645188
40 240.245188 325.445188
41 -167.535565 240.245188
42 -140.935565 -167.535565
43 -189.535565 -140.935565
44 -86.135565 -189.535565
45 -4.535565 -86.135565
46 87.064435 -4.535565
47 293.330544 87.064435
48 -267.980753 293.330544
49 343.219247 -267.980753
50 -186.580753 343.219247
51 -341.780753 -186.580753
52 -273.980753 -341.780753
53 -43.535565 -273.980753
54 35.064435 -43.535565
55 215.464435 35.064435
56 284.864435 215.464435
57 218.464435 284.864435
58 225.064435 218.464435
59 NA 225.064435
> dum1 <- dum[2:length(myerror),]
> dum1
lag(myerror, k = 1) myerror
[1,] -78.554812 9.245188
[2,] -10.354812 -78.554812
[3,] -19.554812 -10.354812
[4,] -50.754812 -19.554812
[5,] 27.690377 -50.754812
[6,] -19.709623 27.690377
[7,] 8.690377 -19.709623
[8,] -138.909623 8.690377
[9,] -7.309623 -138.909623
[10,] -84.709623 -7.309623
[11,] -64.443515 -84.709623
[12,] -94.754812 -64.443515
[13,] -225.554812 -94.754812
[14,] 82.645188 -225.554812
[15,] 18.445188 82.645188
[16,] 90.245188 18.445188
[17,] 18.690377 90.245188
[18,] -69.709623 18.690377
[19,] -89.309623 -69.709623
[20,] -121.909623 -89.309623
[21,] -151.309623 -121.909623
[22,] -176.709623 -151.309623
[23,] -181.443515 -176.709623
[24,] 68.245188 -181.443515
[25,] -94.554812 68.245188
[26,] -72.354812 -94.554812
[27,] 17.445188 -72.354812
[28,] -5.754812 17.445188
[29,] 164.690377 -5.754812
[30,] 195.290377 164.690377
[31,] 54.690377 195.290377
[32,] 62.090377 54.690377
[33,] -55.309623 62.090377
[34,] -50.709623 -55.309623
[35,] -47.443515 -50.709623
[36,] 285.245188 -47.443515
[37,] 55.445188 285.245188
[38,] 186.645188 55.445188
[39,] 325.445188 186.645188
[40,] 240.245188 325.445188
[41,] -167.535565 240.245188
[42,] -140.935565 -167.535565
[43,] -189.535565 -140.935565
[44,] -86.135565 -189.535565
[45,] -4.535565 -86.135565
[46,] 87.064435 -4.535565
[47,] 293.330544 87.064435
[48,] -267.980753 293.330544
[49,] 343.219247 -267.980753
[50,] -186.580753 343.219247
[51,] -341.780753 -186.580753
[52,] -273.980753 -341.780753
[53,] -43.535565 -273.980753
[54,] 35.064435 -43.535565
[55,] 215.464435 35.064435
[56,] 284.864435 215.464435
[57,] 218.464435 284.864435
[58,] 225.064435 218.464435
> z <- as.data.frame(dum1)
> z
lag(myerror, k = 1) myerror
1 -78.554812 9.245188
2 -10.354812 -78.554812
3 -19.554812 -10.354812
4 -50.754812 -19.554812
5 27.690377 -50.754812
6 -19.709623 27.690377
7 8.690377 -19.709623
8 -138.909623 8.690377
9 -7.309623 -138.909623
10 -84.709623 -7.309623
11 -64.443515 -84.709623
12 -94.754812 -64.443515
13 -225.554812 -94.754812
14 82.645188 -225.554812
15 18.445188 82.645188
16 90.245188 18.445188
17 18.690377 90.245188
18 -69.709623 18.690377
19 -89.309623 -69.709623
20 -121.909623 -89.309623
21 -151.309623 -121.909623
22 -176.709623 -151.309623
23 -181.443515 -176.709623
24 68.245188 -181.443515
25 -94.554812 68.245188
26 -72.354812 -94.554812
27 17.445188 -72.354812
28 -5.754812 17.445188
29 164.690377 -5.754812
30 195.290377 164.690377
31 54.690377 195.290377
32 62.090377 54.690377
33 -55.309623 62.090377
34 -50.709623 -55.309623
35 -47.443515 -50.709623
36 285.245188 -47.443515
37 55.445188 285.245188
38 186.645188 55.445188
39 325.445188 186.645188
40 240.245188 325.445188
41 -167.535565 240.245188
42 -140.935565 -167.535565
43 -189.535565 -140.935565
44 -86.135565 -189.535565
45 -4.535565 -86.135565
46 87.064435 -4.535565
47 293.330544 87.064435
48 -267.980753 293.330544
49 343.219247 -267.980753
50 -186.580753 343.219247
51 -341.780753 -186.580753
52 -273.980753 -341.780753
53 -43.535565 -273.980753
54 35.064435 -43.535565
55 215.464435 35.064435
56 284.864435 215.464435
57 218.464435 284.864435
58 225.064435 218.464435
> 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/rcomp/tmp/7qemf1292950630.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> acf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/rcomp/tmp/8in3i1292950630.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> pacf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Partial Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/rcomp/tmp/9in3i1292950630.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> opar <- par(mfrow = c(2,2), oma = c(0, 0, 1.1, 0))
> plot(mylm, las = 1, sub='Residual Diagnostics')
> par(opar)
> dev.off()
null device
1
> if (n > n25) {
+ postscript(file="/var/www/rcomp/tmp/10bxll1292950630.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
+ plot(kp3:nmkm3,gqarr[,2], main='Goldfeld-Quandt test',ylab='2-sided p-value',xlab='breakpoint')
+ grid()
+ dev.off()
+ }
null device
1
>
> #Note: the /var/www/rcomp/createtable file can be downloaded at http://www.wessa.net/cretab
> load(file="/var/www/rcomp/createtable")
>
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a, 'Multiple Linear Regression - Estimated Regression Equation', 1, TRUE)
> a<-table.row.end(a)
> myeq <- colnames(x)[1]
> myeq <- paste(myeq, '[t] = ', sep='')
> for (i in 1:k){
+ if (mysum$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/rcomp/tmp/11fx191292950630.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/rcomp/tmp/12iyzx1292950630.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/rcomp/tmp/13w7fn1292950630.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/rcomp/tmp/14iqwc1292950630.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/rcomp/tmp/1539uh1292950630.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/rcomp/tmp/16orb51292950630.tab")
+ }
>
> try(system("convert tmp/14e6r1292950630.ps tmp/14e6r1292950630.png",intern=TRUE))
character(0)
> try(system("convert tmp/24e6r1292950630.ps tmp/24e6r1292950630.png",intern=TRUE))
character(0)
> try(system("convert tmp/3x55c1292950630.ps tmp/3x55c1292950630.png",intern=TRUE))
character(0)
> try(system("convert tmp/4x55c1292950630.ps tmp/4x55c1292950630.png",intern=TRUE))
character(0)
> try(system("convert tmp/5x55c1292950630.ps tmp/5x55c1292950630.png",intern=TRUE))
character(0)
> try(system("convert tmp/6qemf1292950630.ps tmp/6qemf1292950630.png",intern=TRUE))
character(0)
> try(system("convert tmp/7qemf1292950630.ps tmp/7qemf1292950630.png",intern=TRUE))
character(0)
> try(system("convert tmp/8in3i1292950630.ps tmp/8in3i1292950630.png",intern=TRUE))
character(0)
> try(system("convert tmp/9in3i1292950630.ps tmp/9in3i1292950630.png",intern=TRUE))
character(0)
> try(system("convert tmp/10bxll1292950630.ps tmp/10bxll1292950630.png",intern=TRUE))
character(0)
>
>
> proc.time()
user system elapsed
3.260 1.450 4.742