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.
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(147768,0,137507,0,136919,0,136151,0,133001,0,125554,0,119647,0,114158,0,116193,0,152803,0,161761,0,160942,0,149470,0,139208,0,134588,0,130322,0,126611,0,122401,0,117352,0,112135,0,112879,0,148729,0,157230,0,157221,0,146681,0,136524,0,132111,1,125326,1,122716,1,116615,1,113719,1,110737,1,112093,1,143565,1,149946,1,149147,1,134339,1,122683,1,115614,1,116566,1,111272,1,104609,1,101802,1,94542,1,93051,1,124129,1,130374,1,123946,1,114971,1,105531,1,104919,0,104782,0,101281,0,94545,0,93248,0,84031,0,87486,0,115867,0,120327,0,117008,0,108811,0),dim=c(2,61),dimnames=list(c('jonger_dan_25','plan'),1:61))
> y <- array(NA,dim=c(2,61),dimnames=list(c('jonger_dan_25','plan'),1:61))
> 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
jonger_dan_25 plan M1 M2 M3 M4 M5 M6 M7 M8 M9 M10 M11 t
1 147768 0 1 0 0 0 0 0 0 0 0 0 0 1
2 137507 0 0 1 0 0 0 0 0 0 0 0 0 2
3 136919 0 0 0 1 0 0 0 0 0 0 0 0 3
4 136151 0 0 0 0 1 0 0 0 0 0 0 0 4
5 133001 0 0 0 0 0 1 0 0 0 0 0 0 5
6 125554 0 0 0 0 0 0 1 0 0 0 0 0 6
7 119647 0 0 0 0 0 0 0 1 0 0 0 0 7
8 114158 0 0 0 0 0 0 0 0 1 0 0 0 8
9 116193 0 0 0 0 0 0 0 0 0 1 0 0 9
10 152803 0 0 0 0 0 0 0 0 0 0 1 0 10
11 161761 0 0 0 0 0 0 0 0 0 0 0 1 11
12 160942 0 0 0 0 0 0 0 0 0 0 0 0 12
13 149470 0 1 0 0 0 0 0 0 0 0 0 0 13
14 139208 0 0 1 0 0 0 0 0 0 0 0 0 14
15 134588 0 0 0 1 0 0 0 0 0 0 0 0 15
16 130322 0 0 0 0 1 0 0 0 0 0 0 0 16
17 126611 0 0 0 0 0 1 0 0 0 0 0 0 17
18 122401 0 0 0 0 0 0 1 0 0 0 0 0 18
19 117352 0 0 0 0 0 0 0 1 0 0 0 0 19
20 112135 0 0 0 0 0 0 0 0 1 0 0 0 20
21 112879 0 0 0 0 0 0 0 0 0 1 0 0 21
22 148729 0 0 0 0 0 0 0 0 0 0 1 0 22
23 157230 0 0 0 0 0 0 0 0 0 0 0 1 23
24 157221 0 0 0 0 0 0 0 0 0 0 0 0 24
25 146681 0 1 0 0 0 0 0 0 0 0 0 0 25
26 136524 0 0 1 0 0 0 0 0 0 0 0 0 26
27 132111 1 0 0 1 0 0 0 0 0 0 0 0 27
28 125326 1 0 0 0 1 0 0 0 0 0 0 0 28
29 122716 1 0 0 0 0 1 0 0 0 0 0 0 29
30 116615 1 0 0 0 0 0 1 0 0 0 0 0 30
31 113719 1 0 0 0 0 0 0 1 0 0 0 0 31
32 110737 1 0 0 0 0 0 0 0 1 0 0 0 32
33 112093 1 0 0 0 0 0 0 0 0 1 0 0 33
34 143565 1 0 0 0 0 0 0 0 0 0 1 0 34
35 149946 1 0 0 0 0 0 0 0 0 0 0 1 35
36 149147 1 0 0 0 0 0 0 0 0 0 0 0 36
37 134339 1 1 0 0 0 0 0 0 0 0 0 0 37
38 122683 1 0 1 0 0 0 0 0 0 0 0 0 38
39 115614 1 0 0 1 0 0 0 0 0 0 0 0 39
40 116566 1 0 0 0 1 0 0 0 0 0 0 0 40
41 111272 1 0 0 0 0 1 0 0 0 0 0 0 41
42 104609 1 0 0 0 0 0 1 0 0 0 0 0 42
43 101802 1 0 0 0 0 0 0 1 0 0 0 0 43
44 94542 1 0 0 0 0 0 0 0 1 0 0 0 44
45 93051 1 0 0 0 0 0 0 0 0 1 0 0 45
46 124129 1 0 0 0 0 0 0 0 0 0 1 0 46
47 130374 1 0 0 0 0 0 0 0 0 0 0 1 47
48 123946 1 0 0 0 0 0 0 0 0 0 0 0 48
49 114971 1 1 0 0 0 0 0 0 0 0 0 0 49
50 105531 1 0 1 0 0 0 0 0 0 0 0 0 50
51 104919 0 0 0 1 0 0 0 0 0 0 0 0 51
52 104782 0 0 0 0 1 0 0 0 0 0 0 0 52
53 101281 0 0 0 0 0 1 0 0 0 0 0 0 53
54 94545 0 0 0 0 0 0 1 0 0 0 0 0 54
55 93248 0 0 0 0 0 0 0 1 0 0 0 0 55
56 84031 0 0 0 0 0 0 0 0 1 0 0 0 56
57 87486 0 0 0 0 0 0 0 0 0 1 0 0 57
58 115867 0 0 0 0 0 0 0 0 0 0 1 0 58
59 120327 0 0 0 0 0 0 0 0 0 0 0 1 59
60 117008 0 0 0 0 0 0 0 0 0 0 0 0 60
61 108811 0 1 0 0 0 0 0 0 0 0 0 0 61
> k <- length(x[1,])
> df <- as.data.frame(x)
> (mylm <- lm(df))
Call:
lm(formula = df)
Coefficients:
(Intercept) plan M1 M2 M3 M4
167547.7 3044.9 -11542.1 -20893.5 -23600.8 -25048.5
M5 M6 M7 M8 M9 M10
-27948.5 -33426.8 -36264.9 -41544.7 -39571.8 -6140.5
M11 t
1521.7 -753.1
> (mysum <- summary(mylm))
Call:
lm(formula = df)
Residuals:
Min 1Q Median 3Q Max
-10496 -3336 719 2738 9504
Coefficients:
Estimate Std. Error t value Pr(>|t|)
(Intercept) 167547.7 2597.1 64.513 < 2e-16 ***
plan 3044.8 1396.8 2.180 0.034306 *
M1 -11542.1 3028.0 -3.812 0.000400 ***
M2 -20893.5 3181.0 -6.568 3.70e-08 ***
M3 -23600.8 3176.4 -7.430 1.83e-09 ***
M4 -25048.5 3172.3 -7.896 3.64e-10 ***
M5 -27948.5 3168.6 -8.820 1.56e-11 ***
M6 -33426.8 3165.4 -10.560 5.36e-14 ***
M7 -36264.9 3162.8 -11.466 3.23e-15 ***
M8 -41544.7 3160.6 -13.145 < 2e-16 ***
M9 -39571.8 3158.8 -12.527 < 2e-16 ***
M10 -6140.5 3157.6 -1.945 0.057815 .
M11 1521.7 3156.9 0.482 0.632032
t -753.1 39.3 -19.165 < 2e-16 ***
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
Residual standard error: 4991 on 47 degrees of freedom
Multiple R-squared: 0.9466, Adjusted R-squared: 0.9318
F-statistic: 64.05 on 13 and 47 DF, p-value: < 2.2e-16
> if (n > n25) {
+ kp3 <- k + 3
+ nmkm3 <- n - k - 3
+ gqarr <- array(NA, dim=c(nmkm3-kp3+1,3))
+ numgqtests <- 0
+ numsignificant1 <- 0
+ numsignificant5 <- 0
+ numsignificant10 <- 0
+ for (mypoint in kp3:nmkm3) {
+ j <- 0
+ numgqtests <- numgqtests + 1
+ for (myalt in c('greater', 'two.sided', 'less')) {
+ j <- j + 1
+ gqarr[mypoint-kp3+1,j] <- gqtest(mylm, point=mypoint, alternative=myalt)$p.value
+ }
+ if (gqarr[mypoint-kp3+1,2] < 0.01) numsignificant1 <- numsignificant1 + 1
+ if (gqarr[mypoint-kp3+1,2] < 0.05) numsignificant5 <- numsignificant5 + 1
+ if (gqarr[mypoint-kp3+1,2] < 0.10) numsignificant10 <- numsignificant10 + 1
+ }
+ gqarr
+ }
[,1] [,2] [,3]
[1,] 0.39196428 0.78392856 0.60803572
[2,] 0.24791616 0.49583232 0.75208384
[3,] 0.17380454 0.34760907 0.82619546
[4,] 0.13145256 0.26290512 0.86854744
[5,] 0.14678758 0.29357516 0.85321242
[6,] 0.13567536 0.27135072 0.86432464
[7,] 0.12189441 0.24378883 0.87810559
[8,] 0.08307395 0.16614791 0.91692605
[9,] 0.07985658 0.15971316 0.92014342
[10,] 0.10308373 0.20616746 0.89691627
[11,] 0.06339332 0.12678664 0.93660668
[12,] 0.12768877 0.25537754 0.87231123
[13,] 0.15056544 0.30113088 0.84943456
[14,] 0.19708419 0.39416838 0.80291581
[15,] 0.49520335 0.99040671 0.50479665
[16,] 0.57186010 0.85627980 0.42813990
[17,] 0.60733481 0.78533039 0.39266519
[18,] 0.54712025 0.90575949 0.45287975
[19,] 0.55722555 0.88554891 0.44277445
[20,] 0.89336238 0.21327524 0.10663762
[21,] 0.92017627 0.15964746 0.07982373
[22,] 0.93290374 0.13419252 0.06709626
[23,] 0.97361775 0.05276450 0.02638225
[24,] 0.98023764 0.03952473 0.01976236
[25,] 0.97295463 0.05409074 0.02704537
[26,] 0.96324390 0.07351220 0.03675610
[27,] 0.91762822 0.16474356 0.08237178
[28,] 0.91022426 0.17955148 0.08977574
> postscript(file="/var/www/html/rcomp/tmp/1j40b1227723907.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$resid)
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/262g01227723907.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> plot(mysum$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/3j9bo1227723907.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> hist(mysum$resid, main='Residual Histogram', xlab='values of Residuals')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/40i0u1227723907.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> densityplot(~mysum$resid,col='black',main='Residual Density Plot', xlab='values of Residuals')
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/56wyp1227723907.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 = 61
Frequency = 1
1 2 3 4 5 6
-7484.3980 -7640.8717 -4768.4717 -3335.6717 -2832.4717 -4048.0717
7 8 9 10 11 12
-6363.8717 -5819.8717 -5004.6717 -1072.8717 976.1283 2431.9283
13 14 15 16 17 18
3255.2079 3097.7342 1938.1342 -127.0658 -184.8658 1836.5342
19 20 21 22 23 24
378.7342 1194.7342 718.9342 3890.7342 5482.7342 7748.5342
25 26 27 28 29 30
9503.8138 9451.3400 5453.8899 869.6899 1912.8899 2043.2899
31 32 33 34 35 36
2738.4899 5789.4899 5925.6899 4719.4899 4191.4899 5667.2899
37 38 39 40 41 42
3154.5695 1603.0958 -2005.5042 1147.2958 -493.5042 -925.1042
43 44 45 46 47 48
-140.9042 -1367.9042 -4078.7042 -5678.9042 -6342.9042 -10496.1042
49 50 51 52 53 54
-7175.8246 -6511.2983 -618.0482 1445.7518 1597.9518 1093.3518
55 56 57 58 59 60
3387.5518 203.5518 2438.7518 -1858.4482 -4307.4482 -5351.6482
61
-1253.3686
> postscript(file="/var/www/html/rcomp/tmp/6ui3m1227723907.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 = 61
Frequency = 1
lag(myerror, k = 1) myerror
0 -7484.3980 NA
1 -7640.8717 -7484.3980
2 -4768.4717 -7640.8717
3 -3335.6717 -4768.4717
4 -2832.4717 -3335.6717
5 -4048.0717 -2832.4717
6 -6363.8717 -4048.0717
7 -5819.8717 -6363.8717
8 -5004.6717 -5819.8717
9 -1072.8717 -5004.6717
10 976.1283 -1072.8717
11 2431.9283 976.1283
12 3255.2079 2431.9283
13 3097.7342 3255.2079
14 1938.1342 3097.7342
15 -127.0658 1938.1342
16 -184.8658 -127.0658
17 1836.5342 -184.8658
18 378.7342 1836.5342
19 1194.7342 378.7342
20 718.9342 1194.7342
21 3890.7342 718.9342
22 5482.7342 3890.7342
23 7748.5342 5482.7342
24 9503.8138 7748.5342
25 9451.3400 9503.8138
26 5453.8899 9451.3400
27 869.6899 5453.8899
28 1912.8899 869.6899
29 2043.2899 1912.8899
30 2738.4899 2043.2899
31 5789.4899 2738.4899
32 5925.6899 5789.4899
33 4719.4899 5925.6899
34 4191.4899 4719.4899
35 5667.2899 4191.4899
36 3154.5695 5667.2899
37 1603.0958 3154.5695
38 -2005.5042 1603.0958
39 1147.2958 -2005.5042
40 -493.5042 1147.2958
41 -925.1042 -493.5042
42 -140.9042 -925.1042
43 -1367.9042 -140.9042
44 -4078.7042 -1367.9042
45 -5678.9042 -4078.7042
46 -6342.9042 -5678.9042
47 -10496.1042 -6342.9042
48 -7175.8246 -10496.1042
49 -6511.2983 -7175.8246
50 -618.0482 -6511.2983
51 1445.7518 -618.0482
52 1597.9518 1445.7518
53 1093.3518 1597.9518
54 3387.5518 1093.3518
55 203.5518 3387.5518
56 2438.7518 203.5518
57 -1858.4482 2438.7518
58 -4307.4482 -1858.4482
59 -5351.6482 -4307.4482
60 -1253.3686 -5351.6482
61 NA -1253.3686
> dum1 <- dum[2:length(myerror),]
> dum1
lag(myerror, k = 1) myerror
[1,] -7640.8717 -7484.3980
[2,] -4768.4717 -7640.8717
[3,] -3335.6717 -4768.4717
[4,] -2832.4717 -3335.6717
[5,] -4048.0717 -2832.4717
[6,] -6363.8717 -4048.0717
[7,] -5819.8717 -6363.8717
[8,] -5004.6717 -5819.8717
[9,] -1072.8717 -5004.6717
[10,] 976.1283 -1072.8717
[11,] 2431.9283 976.1283
[12,] 3255.2079 2431.9283
[13,] 3097.7342 3255.2079
[14,] 1938.1342 3097.7342
[15,] -127.0658 1938.1342
[16,] -184.8658 -127.0658
[17,] 1836.5342 -184.8658
[18,] 378.7342 1836.5342
[19,] 1194.7342 378.7342
[20,] 718.9342 1194.7342
[21,] 3890.7342 718.9342
[22,] 5482.7342 3890.7342
[23,] 7748.5342 5482.7342
[24,] 9503.8138 7748.5342
[25,] 9451.3400 9503.8138
[26,] 5453.8899 9451.3400
[27,] 869.6899 5453.8899
[28,] 1912.8899 869.6899
[29,] 2043.2899 1912.8899
[30,] 2738.4899 2043.2899
[31,] 5789.4899 2738.4899
[32,] 5925.6899 5789.4899
[33,] 4719.4899 5925.6899
[34,] 4191.4899 4719.4899
[35,] 5667.2899 4191.4899
[36,] 3154.5695 5667.2899
[37,] 1603.0958 3154.5695
[38,] -2005.5042 1603.0958
[39,] 1147.2958 -2005.5042
[40,] -493.5042 1147.2958
[41,] -925.1042 -493.5042
[42,] -140.9042 -925.1042
[43,] -1367.9042 -140.9042
[44,] -4078.7042 -1367.9042
[45,] -5678.9042 -4078.7042
[46,] -6342.9042 -5678.9042
[47,] -10496.1042 -6342.9042
[48,] -7175.8246 -10496.1042
[49,] -6511.2983 -7175.8246
[50,] -618.0482 -6511.2983
[51,] 1445.7518 -618.0482
[52,] 1597.9518 1445.7518
[53,] 1093.3518 1597.9518
[54,] 3387.5518 1093.3518
[55,] 203.5518 3387.5518
[56,] 2438.7518 203.5518
[57,] -1858.4482 2438.7518
[58,] -4307.4482 -1858.4482
[59,] -5351.6482 -4307.4482
[60,] -1253.3686 -5351.6482
> z <- as.data.frame(dum1)
> z
lag(myerror, k = 1) myerror
1 -7640.8717 -7484.3980
2 -4768.4717 -7640.8717
3 -3335.6717 -4768.4717
4 -2832.4717 -3335.6717
5 -4048.0717 -2832.4717
6 -6363.8717 -4048.0717
7 -5819.8717 -6363.8717
8 -5004.6717 -5819.8717
9 -1072.8717 -5004.6717
10 976.1283 -1072.8717
11 2431.9283 976.1283
12 3255.2079 2431.9283
13 3097.7342 3255.2079
14 1938.1342 3097.7342
15 -127.0658 1938.1342
16 -184.8658 -127.0658
17 1836.5342 -184.8658
18 378.7342 1836.5342
19 1194.7342 378.7342
20 718.9342 1194.7342
21 3890.7342 718.9342
22 5482.7342 3890.7342
23 7748.5342 5482.7342
24 9503.8138 7748.5342
25 9451.3400 9503.8138
26 5453.8899 9451.3400
27 869.6899 5453.8899
28 1912.8899 869.6899
29 2043.2899 1912.8899
30 2738.4899 2043.2899
31 5789.4899 2738.4899
32 5925.6899 5789.4899
33 4719.4899 5925.6899
34 4191.4899 4719.4899
35 5667.2899 4191.4899
36 3154.5695 5667.2899
37 1603.0958 3154.5695
38 -2005.5042 1603.0958
39 1147.2958 -2005.5042
40 -493.5042 1147.2958
41 -925.1042 -493.5042
42 -140.9042 -925.1042
43 -1367.9042 -140.9042
44 -4078.7042 -1367.9042
45 -5678.9042 -4078.7042
46 -6342.9042 -5678.9042
47 -10496.1042 -6342.9042
48 -7175.8246 -10496.1042
49 -6511.2983 -7175.8246
50 -618.0482 -6511.2983
51 1445.7518 -618.0482
52 1597.9518 1445.7518
53 1093.3518 1597.9518
54 3387.5518 1093.3518
55 203.5518 3387.5518
56 2438.7518 203.5518
57 -1858.4482 2438.7518
58 -4307.4482 -1858.4482
59 -5351.6482 -4307.4482
60 -1253.3686 -5351.6482
> 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/7lbdc1227723907.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> acf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/8lp0u1227723907.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> pacf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Partial Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/9vmsj1227723907.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> opar <- par(mfrow = c(2,2), oma = c(0, 0, 1.1, 0))
> plot(mylm, las = 1, sub='Residual Diagnostics')
> par(opar)
> dev.off()
null device
1
> if (n > n25) {
+ postscript(file="/var/www/html/rcomp/tmp/10j9071227723907.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
+ plot(kp3:nmkm3,gqarr[,2], main='Goldfeld-Quandt test',ylab='2-sided p-value',xlab='breakpoint')
+ grid()
+ dev.off()
+ }
null device
1
>
> #Note: the /var/www/html/rcomp/createtable file can be downloaded at http://www.wessa.net/cretab
> load(file="/var/www/html/rcomp/createtable")
>
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a, 'Multiple Linear Regression - Estimated Regression Equation', 1, TRUE)
> a<-table.row.end(a)
> myeq <- colnames(x)[1]
> myeq <- paste(myeq, '[t] = ', sep='')
> for (i in 1:k){
+ if (mysum$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/11tvxw1227723907.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/12yq0a1227723907.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/139qvs1227723907.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/148l4l1227723907.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/15nxu71227723907.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/16v5yb1227723908.tab")
+ }
>
> system("convert tmp/1j40b1227723907.ps tmp/1j40b1227723907.png")
> system("convert tmp/262g01227723907.ps tmp/262g01227723907.png")
> system("convert tmp/3j9bo1227723907.ps tmp/3j9bo1227723907.png")
> system("convert tmp/40i0u1227723907.ps tmp/40i0u1227723907.png")
> system("convert tmp/56wyp1227723907.ps tmp/56wyp1227723907.png")
> system("convert tmp/6ui3m1227723907.ps tmp/6ui3m1227723907.png")
> system("convert tmp/7lbdc1227723907.ps tmp/7lbdc1227723907.png")
> system("convert tmp/8lp0u1227723907.ps tmp/8lp0u1227723907.png")
> system("convert tmp/9vmsj1227723907.ps tmp/9vmsj1227723907.png")
> system("convert tmp/10j9071227723907.ps tmp/10j9071227723907.png")
>
>
> proc.time()
user system elapsed
2.345 1.587 2.994