R version 2.11.1 (2010-05-31)
Copyright (C) 2010 The R Foundation for Statistical Computing
ISBN 3-900051-07-0
R is free software and comes with ABSOLUTELY NO WARRANTY.
You are welcome to redistribute it under certain conditions.
Type 'license()' or 'licence()' for distribution details.
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Type 'contributors()' for more information and
'citation()' on how to cite R or R packages in publications.
Type 'demo()' for some demos, 'help()' for on-line help, or
'help.start()' for an HTML browser interface to help.
Type 'q()' to quit R.
> x <- array(list(16198.9
+ ,16896.2
+ ,0
+ ,16554.2
+ ,16698
+ ,0
+ ,19554.2
+ ,19691.6
+ ,0
+ ,15903.8
+ ,15930.7
+ ,0
+ ,18003.8
+ ,17444.6
+ ,0
+ ,18329.6
+ ,17699.4
+ ,0
+ ,16260.7
+ ,15189.8
+ ,0
+ ,14851.9
+ ,15672.7
+ ,0
+ ,18174.1
+ ,17180.8
+ ,0
+ ,18406.6
+ ,17664.9
+ ,0
+ ,18466.5
+ ,17862.9
+ ,0
+ ,16016.5
+ ,16162.3
+ ,0
+ ,17428.5
+ ,17463.6
+ ,0
+ ,17167.2
+ ,16772.1
+ ,0
+ ,19630
+ ,19106.9
+ ,0
+ ,17183.6
+ ,16721.3
+ ,0
+ ,18344.7
+ ,18161.3
+ ,0
+ ,19301.4
+ ,18509.9
+ ,0
+ ,18147.5
+ ,17802.7
+ ,0
+ ,16192.9
+ ,16409.9
+ ,0
+ ,18374.4
+ ,17967.7
+ ,0
+ ,20515.2
+ ,20286.6
+ ,0
+ ,18957.2
+ ,19537.3
+ ,0
+ ,16471.5
+ ,18021.9
+ ,0
+ ,18746.8
+ ,20194.3
+ ,0
+ ,19009.5
+ ,19049.6
+ ,0
+ ,19211.2
+ ,20244.7
+ ,0
+ ,20547.7
+ ,21473.3
+ ,0
+ ,19325.8
+ ,19673.6
+ ,0
+ ,20605.5
+ ,21053.2
+ ,0
+ ,20056.9
+ ,20159.5
+ ,0
+ ,16141.4
+ ,18203.6
+ ,0
+ ,20359.8
+ ,21289.5
+ ,0
+ ,19711.6
+ ,20432.3
+ ,1
+ ,15638.6
+ ,17180.4
+ ,1
+ ,14384.5
+ ,15816.8
+ ,1
+ ,13855.6
+ ,15071.8
+ ,1
+ ,14308.3
+ ,14521.1
+ ,1
+ ,15290.6
+ ,15668.8
+ ,1
+ ,14423.8
+ ,14346.9
+ ,1
+ ,13779.7
+ ,13881
+ ,1
+ ,15686.3
+ ,15465.9
+ ,1
+ ,14733.8
+ ,14238.2
+ ,1
+ ,12522.5
+ ,13557.7
+ ,1
+ ,16189.4
+ ,16127.6
+ ,1
+ ,16059.1
+ ,16793.9
+ ,1
+ ,16007.1
+ ,16014
+ ,1
+ ,15806.8
+ ,16867.9
+ ,1
+ ,15160
+ ,16014.6
+ ,0
+ ,15692.1
+ ,15878.6
+ ,0
+ ,18908.9
+ ,18664.9
+ ,0
+ ,16969.9
+ ,17962.5
+ ,0
+ ,16997.5
+ ,17332.7
+ ,0
+ ,19858.9
+ ,19542.1
+ ,0
+ ,17681.2
+ ,17203.6
+ ,0)
+ ,dim=c(3
+ ,55)
+ ,dimnames=list(c('uitvoer'
+ ,'invoer'
+ ,'crisis')
+ ,1:55))
> y <- array(NA,dim=c(3,55),dimnames=list(c('uitvoer','invoer','crisis'),1:55))
> 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
> 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
uitvoer invoer crisis M1 M2 M3 M4 M5 M6 M7 M8 M9 M10 M11 t
1 16198.9 16896.2 0 1 0 0 0 0 0 0 0 0 0 0 1
2 16554.2 16698.0 0 0 1 0 0 0 0 0 0 0 0 0 2
3 19554.2 19691.6 0 0 0 1 0 0 0 0 0 0 0 0 3
4 15903.8 15930.7 0 0 0 0 1 0 0 0 0 0 0 0 4
5 18003.8 17444.6 0 0 0 0 0 1 0 0 0 0 0 0 5
6 18329.6 17699.4 0 0 0 0 0 0 1 0 0 0 0 0 6
7 16260.7 15189.8 0 0 0 0 0 0 0 1 0 0 0 0 7
8 14851.9 15672.7 0 0 0 0 0 0 0 0 1 0 0 0 8
9 18174.1 17180.8 0 0 0 0 0 0 0 0 0 1 0 0 9
10 18406.6 17664.9 0 0 0 0 0 0 0 0 0 0 1 0 10
11 18466.5 17862.9 0 0 0 0 0 0 0 0 0 0 0 1 11
12 16016.5 16162.3 0 0 0 0 0 0 0 0 0 0 0 0 12
13 17428.5 17463.6 0 1 0 0 0 0 0 0 0 0 0 0 13
14 17167.2 16772.1 0 0 1 0 0 0 0 0 0 0 0 0 14
15 19630.0 19106.9 0 0 0 1 0 0 0 0 0 0 0 0 15
16 17183.6 16721.3 0 0 0 0 1 0 0 0 0 0 0 0 16
17 18344.7 18161.3 0 0 0 0 0 1 0 0 0 0 0 0 17
18 19301.4 18509.9 0 0 0 0 0 0 1 0 0 0 0 0 18
19 18147.5 17802.7 0 0 0 0 0 0 0 1 0 0 0 0 19
20 16192.9 16409.9 0 0 0 0 0 0 0 0 1 0 0 0 20
21 18374.4 17967.7 0 0 0 0 0 0 0 0 0 1 0 0 21
22 20515.2 20286.6 0 0 0 0 0 0 0 0 0 0 1 0 22
23 18957.2 19537.3 0 0 0 0 0 0 0 0 0 0 0 1 23
24 16471.5 18021.9 0 0 0 0 0 0 0 0 0 0 0 0 24
25 18746.8 20194.3 0 1 0 0 0 0 0 0 0 0 0 0 25
26 19009.5 19049.6 0 0 1 0 0 0 0 0 0 0 0 0 26
27 19211.2 20244.7 0 0 0 1 0 0 0 0 0 0 0 0 27
28 20547.7 21473.3 0 0 0 0 1 0 0 0 0 0 0 0 28
29 19325.8 19673.6 0 0 0 0 0 1 0 0 0 0 0 0 29
30 20605.5 21053.2 0 0 0 0 0 0 1 0 0 0 0 0 30
31 20056.9 20159.5 0 0 0 0 0 0 0 1 0 0 0 0 31
32 16141.4 18203.6 0 0 0 0 0 0 0 0 1 0 0 0 32
33 20359.8 21289.5 0 0 0 0 0 0 0 0 0 1 0 0 33
34 19711.6 20432.3 1 0 0 0 0 0 0 0 0 0 1 0 34
35 15638.6 17180.4 1 0 0 0 0 0 0 0 0 0 0 1 35
36 14384.5 15816.8 1 0 0 0 0 0 0 0 0 0 0 0 36
37 13855.6 15071.8 1 1 0 0 0 0 0 0 0 0 0 0 37
38 14308.3 14521.1 1 0 1 0 0 0 0 0 0 0 0 0 38
39 15290.6 15668.8 1 0 0 1 0 0 0 0 0 0 0 0 39
40 14423.8 14346.9 1 0 0 0 1 0 0 0 0 0 0 0 40
41 13779.7 13881.0 1 0 0 0 0 1 0 0 0 0 0 0 41
42 15686.3 15465.9 1 0 0 0 0 0 1 0 0 0 0 0 42
43 14733.8 14238.2 1 0 0 0 0 0 0 1 0 0 0 0 43
44 12522.5 13557.7 1 0 0 0 0 0 0 0 1 0 0 0 44
45 16189.4 16127.6 1 0 0 0 0 0 0 0 0 1 0 0 45
46 16059.1 16793.9 1 0 0 0 0 0 0 0 0 0 1 0 46
47 16007.1 16014.0 1 0 0 0 0 0 0 0 0 0 0 1 47
48 15806.8 16867.9 1 0 0 0 0 0 0 0 0 0 0 0 48
49 15160.0 16014.6 0 1 0 0 0 0 0 0 0 0 0 0 49
50 15692.1 15878.6 0 0 1 0 0 0 0 0 0 0 0 0 50
51 18908.9 18664.9 0 0 0 1 0 0 0 0 0 0 0 0 51
52 16969.9 17962.5 0 0 0 0 1 0 0 0 0 0 0 0 52
53 16997.5 17332.7 0 0 0 0 0 1 0 0 0 0 0 0 53
54 19858.9 19542.1 0 0 0 0 0 0 1 0 0 0 0 0 54
55 17681.2 17203.6 0 0 0 0 0 0 0 1 0 0 0 0 55
> k <- length(x[1,])
> df <- as.data.frame(x)
> (mylm <- lm(df))
Call:
lm(formula = df)
Coefficients:
(Intercept) invoer crisis M1 M2 M3
3664.9954 0.7581 -755.1942 21.5711 712.1540 1108.9865
M4 M5 M6 M7 M8 M9
658.0625 943.4359 1543.2113 1336.5540 -396.9397 1307.0077
M10 M11 t
1409.1436 881.6974 -9.7033
> (mysum <- summary(mylm))
Call:
lm(formula = df)
Residuals:
Min 1Q Median 3Q Max
-837.95 -232.62 37.52 233.94 678.37
Coefficients:
Estimate Std. Error t value Pr(>|t|)
(Intercept) 3664.99536 797.54309 4.595 4.26e-05 ***
invoer 0.75811 0.04339 17.473 < 2e-16 ***
crisis -755.19417 204.57396 -3.692 0.000665 ***
M1 21.57110 284.60683 0.076 0.939962
M2 712.15399 287.24263 2.479 0.017478 *
M3 1108.98646 288.25277 3.847 0.000420 ***
M4 658.06250 284.80601 2.311 0.026096 *
M5 943.43588 285.08977 3.309 0.001987 **
M6 1543.21132 287.19982 5.373 3.58e-06 ***
M7 1336.55398 287.30268 4.652 3.56e-05 ***
M8 -396.93967 304.79381 -1.302 0.200255
M9 1307.00770 300.05155 4.356 8.97e-05 ***
M10 1409.14358 310.61332 4.537 5.11e-05 ***
M11 881.69742 299.41356 2.945 0.005363 **
t -9.70329 4.31070 -2.251 0.029951 *
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
Residual standard error: 419.3 on 40 degrees of freedom
Multiple R-squared: 0.9681, Adjusted R-squared: 0.9569
F-statistic: 86.57 on 14 and 40 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,] 0.2950825 0.5901651 0.7049175
[2,] 0.1575580 0.3151160 0.8424420
[3,] 0.1550811 0.3101622 0.8449189
[4,] 0.2569608 0.5139216 0.7430392
[5,] 0.2542235 0.5084471 0.7457765
[6,] 0.4472282 0.8944564 0.5527718
[7,] 0.5475664 0.9048672 0.4524336
[8,] 0.4329202 0.8658404 0.5670798
[9,] 0.5064725 0.9870549 0.4935275
[10,] 0.7581450 0.4837100 0.2418550
[11,] 0.7051647 0.5896705 0.2948353
[12,] 0.7066966 0.5866068 0.2933034
[13,] 0.6188481 0.7623037 0.3811519
[14,] 0.5554106 0.8891787 0.4445894
[15,] 0.5407634 0.9184732 0.4592366
[16,] 0.4442002 0.8884003 0.5557998
[17,] 0.6482891 0.7034218 0.3517109
[18,] 0.6409604 0.7180791 0.3590396
[19,] 0.4940153 0.9880306 0.5059847
[20,] 0.3265741 0.6531482 0.6734259
> postscript(file="/var/www/rcomp/tmp/168u21290850935.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$resid)
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/rcomp/tmp/2hzb51290850935.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> plot(mysum$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/rcomp/tmp/3hzb51290850935.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> hist(mysum$resid, main='Residual Histogram', xlab='values of Residuals')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/rcomp/tmp/4r8t81290850935.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> densityplot(~mysum$resid,col='black',main='Residual Density Plot', xlab='values of Residuals')
> dev.off()
null device
1
> postscript(file="/var/www/rcomp/tmp/5r8t81290850935.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 = 55
Frequency = 1
1 2 3 4 5 6
-287.171747 -462.493592 -119.106246 -457.696327 218.928128 -238.510898
7 8 9 10 11 12
-188.492897 -220.188143 264.459372 37.524864 484.468181 215.113824
13 14 15 16 17 18
628.715137 210.769843 516.401242 339.180004 132.928921 235.279008
19 20 21 22 23 24
-166.123698 678.371357 -15.359284 275.022679 -177.774696 -623.231358
25 26 27 28 29 30
-6.721234 442.909739 -648.538844 217.172253 83.975966 -272.287212
31 32 33 34 35 36
72.997933 -616.514258 -431.815539 232.599483 -837.947303 -166.885337
37 38 39 40 41 42
-142.859849 46.452716 -228.461368 367.513873 -199.051932 -84.055463
43 44 45 46 47 48
110.539023 158.331044 182.715451 -545.147027 531.253819 575.002870
49 50 51 52 53 54
-191.962308 -237.638706 479.705216 -466.169803 -236.781084 359.574566
55
171.079639
> postscript(file="/var/www/rcomp/tmp/6r8t81290850935.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 = 55
Frequency = 1
lag(myerror, k = 1) myerror
0 -287.171747 NA
1 -462.493592 -287.171747
2 -119.106246 -462.493592
3 -457.696327 -119.106246
4 218.928128 -457.696327
5 -238.510898 218.928128
6 -188.492897 -238.510898
7 -220.188143 -188.492897
8 264.459372 -220.188143
9 37.524864 264.459372
10 484.468181 37.524864
11 215.113824 484.468181
12 628.715137 215.113824
13 210.769843 628.715137
14 516.401242 210.769843
15 339.180004 516.401242
16 132.928921 339.180004
17 235.279008 132.928921
18 -166.123698 235.279008
19 678.371357 -166.123698
20 -15.359284 678.371357
21 275.022679 -15.359284
22 -177.774696 275.022679
23 -623.231358 -177.774696
24 -6.721234 -623.231358
25 442.909739 -6.721234
26 -648.538844 442.909739
27 217.172253 -648.538844
28 83.975966 217.172253
29 -272.287212 83.975966
30 72.997933 -272.287212
31 -616.514258 72.997933
32 -431.815539 -616.514258
33 232.599483 -431.815539
34 -837.947303 232.599483
35 -166.885337 -837.947303
36 -142.859849 -166.885337
37 46.452716 -142.859849
38 -228.461368 46.452716
39 367.513873 -228.461368
40 -199.051932 367.513873
41 -84.055463 -199.051932
42 110.539023 -84.055463
43 158.331044 110.539023
44 182.715451 158.331044
45 -545.147027 182.715451
46 531.253819 -545.147027
47 575.002870 531.253819
48 -191.962308 575.002870
49 -237.638706 -191.962308
50 479.705216 -237.638706
51 -466.169803 479.705216
52 -236.781084 -466.169803
53 359.574566 -236.781084
54 171.079639 359.574566
55 NA 171.079639
> dum1 <- dum[2:length(myerror),]
> dum1
lag(myerror, k = 1) myerror
[1,] -462.493592 -287.171747
[2,] -119.106246 -462.493592
[3,] -457.696327 -119.106246
[4,] 218.928128 -457.696327
[5,] -238.510898 218.928128
[6,] -188.492897 -238.510898
[7,] -220.188143 -188.492897
[8,] 264.459372 -220.188143
[9,] 37.524864 264.459372
[10,] 484.468181 37.524864
[11,] 215.113824 484.468181
[12,] 628.715137 215.113824
[13,] 210.769843 628.715137
[14,] 516.401242 210.769843
[15,] 339.180004 516.401242
[16,] 132.928921 339.180004
[17,] 235.279008 132.928921
[18,] -166.123698 235.279008
[19,] 678.371357 -166.123698
[20,] -15.359284 678.371357
[21,] 275.022679 -15.359284
[22,] -177.774696 275.022679
[23,] -623.231358 -177.774696
[24,] -6.721234 -623.231358
[25,] 442.909739 -6.721234
[26,] -648.538844 442.909739
[27,] 217.172253 -648.538844
[28,] 83.975966 217.172253
[29,] -272.287212 83.975966
[30,] 72.997933 -272.287212
[31,] -616.514258 72.997933
[32,] -431.815539 -616.514258
[33,] 232.599483 -431.815539
[34,] -837.947303 232.599483
[35,] -166.885337 -837.947303
[36,] -142.859849 -166.885337
[37,] 46.452716 -142.859849
[38,] -228.461368 46.452716
[39,] 367.513873 -228.461368
[40,] -199.051932 367.513873
[41,] -84.055463 -199.051932
[42,] 110.539023 -84.055463
[43,] 158.331044 110.539023
[44,] 182.715451 158.331044
[45,] -545.147027 182.715451
[46,] 531.253819 -545.147027
[47,] 575.002870 531.253819
[48,] -191.962308 575.002870
[49,] -237.638706 -191.962308
[50,] 479.705216 -237.638706
[51,] -466.169803 479.705216
[52,] -236.781084 -466.169803
[53,] 359.574566 -236.781084
[54,] 171.079639 359.574566
> z <- as.data.frame(dum1)
> z
lag(myerror, k = 1) myerror
1 -462.493592 -287.171747
2 -119.106246 -462.493592
3 -457.696327 -119.106246
4 218.928128 -457.696327
5 -238.510898 218.928128
6 -188.492897 -238.510898
7 -220.188143 -188.492897
8 264.459372 -220.188143
9 37.524864 264.459372
10 484.468181 37.524864
11 215.113824 484.468181
12 628.715137 215.113824
13 210.769843 628.715137
14 516.401242 210.769843
15 339.180004 516.401242
16 132.928921 339.180004
17 235.279008 132.928921
18 -166.123698 235.279008
19 678.371357 -166.123698
20 -15.359284 678.371357
21 275.022679 -15.359284
22 -177.774696 275.022679
23 -623.231358 -177.774696
24 -6.721234 -623.231358
25 442.909739 -6.721234
26 -648.538844 442.909739
27 217.172253 -648.538844
28 83.975966 217.172253
29 -272.287212 83.975966
30 72.997933 -272.287212
31 -616.514258 72.997933
32 -431.815539 -616.514258
33 232.599483 -431.815539
34 -837.947303 232.599483
35 -166.885337 -837.947303
36 -142.859849 -166.885337
37 46.452716 -142.859849
38 -228.461368 46.452716
39 367.513873 -228.461368
40 -199.051932 367.513873
41 -84.055463 -199.051932
42 110.539023 -84.055463
43 158.331044 110.539023
44 182.715451 158.331044
45 -545.147027 182.715451
46 531.253819 -545.147027
47 575.002870 531.253819
48 -191.962308 575.002870
49 -237.638706 -191.962308
50 479.705216 -237.638706
51 -466.169803 479.705216
52 -236.781084 -466.169803
53 359.574566 -236.781084
54 171.079639 359.574566
> 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/720st1290850935.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> acf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/rcomp/tmp/8dr9e1290850935.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> pacf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Partial Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/rcomp/tmp/9dr9e1290850935.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> opar <- par(mfrow = c(2,2), oma = c(0, 0, 1.1, 0))
> plot(mylm, las = 1, sub='Residual Diagnostics')
> par(opar)
> dev.off()
null device
1
> if (n > n25) {
+ postscript(file="/var/www/rcomp/tmp/10dr9e1290850935.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
+ plot(kp3:nmkm3,gqarr[,2], main='Goldfeld-Quandt test',ylab='2-sided p-value',xlab='breakpoint')
+ grid()
+ dev.off()
+ }
null device
1
>
> #Note: the /var/www/rcomp/createtable file can be downloaded at http://www.wessa.net/cretab
> load(file="/var/www/rcomp/createtable")
>
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a, 'Multiple Linear Regression - Estimated Regression Equation', 1, TRUE)
> a<-table.row.end(a)
> myeq <- colnames(x)[1]
> myeq <- paste(myeq, '[t] = ', sep='')
> for (i in 1:k){
+ if (mysum$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/11yrp11290850935.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/12js671290850935.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/13qbl11290850935.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/14j22m1290850935.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/154lja1290850935.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/161dz11290850935.tab")
+ }
>
> try(system("convert tmp/168u21290850935.ps tmp/168u21290850935.png",intern=TRUE))
character(0)
> try(system("convert tmp/2hzb51290850935.ps tmp/2hzb51290850935.png",intern=TRUE))
character(0)
> try(system("convert tmp/3hzb51290850935.ps tmp/3hzb51290850935.png",intern=TRUE))
character(0)
> try(system("convert tmp/4r8t81290850935.ps tmp/4r8t81290850935.png",intern=TRUE))
character(0)
> try(system("convert tmp/5r8t81290850935.ps tmp/5r8t81290850935.png",intern=TRUE))
character(0)
> try(system("convert tmp/6r8t81290850935.ps tmp/6r8t81290850935.png",intern=TRUE))
character(0)
> try(system("convert tmp/720st1290850935.ps tmp/720st1290850935.png",intern=TRUE))
character(0)
> try(system("convert tmp/8dr9e1290850935.ps tmp/8dr9e1290850935.png",intern=TRUE))
character(0)
> try(system("convert tmp/9dr9e1290850935.ps tmp/9dr9e1290850935.png",intern=TRUE))
character(0)
> try(system("convert tmp/10dr9e1290850935.ps tmp/10dr9e1290850935.png",intern=TRUE))
character(0)
>
>
> proc.time()
user system elapsed
3.48 1.14 4.62