R version 2.9.0 (2009-04-17)
Copyright (C) 2009 The R Foundation for Statistical Computing
ISBN 3-900051-07-0
R is free software and comes with ABSOLUTELY NO WARRANTY.
You are welcome to redistribute it under certain conditions.
Type 'license()' or 'licence()' for distribution details.
R is a collaborative project with many contributors.
Type 'contributors()' for more information and
'citation()' on how to cite R or R packages in publications.
Type 'demo()' for some demos, 'help()' for on-line help, or
'help.start()' for an HTML browser interface to help.
Type 'q()' to quit R.
> x <- array(list(141
+ ,9.3
+ ,16
+ ,6
+ ,7
+ ,4
+ ,136
+ ,14.2
+ ,20
+ ,20
+ ,0
+ ,5
+ ,246
+ ,17.3
+ ,7
+ ,12
+ ,0
+ ,6
+ ,309
+ ,23
+ ,8
+ ,15
+ ,0
+ ,7
+ ,95
+ ,16.3
+ ,21
+ ,25
+ ,0
+ ,8
+ ,161
+ ,18.4
+ ,7
+ ,4
+ ,0
+ ,9
+ ,108
+ ,14.2
+ ,17
+ ,6
+ ,0
+ ,10
+ ,79
+ ,9.1
+ ,20
+ ,2
+ ,0
+ ,11
+ ,40
+ ,5.9
+ ,18
+ ,1
+ ,1
+ ,12
+ ,35
+ ,7.2
+ ,26
+ ,4
+ ,2
+ ,1
+ ,49
+ ,6.8
+ ,18
+ ,4
+ ,2
+ ,2
+ ,145
+ ,8
+ ,20
+ ,8
+ ,2
+ ,3
+ ,284
+ ,14.3
+ ,0
+ ,3
+ ,0
+ ,4
+ ,164
+ ,14.6
+ ,22
+ ,14
+ ,0
+ ,5
+ ,130
+ ,17.5
+ ,19
+ ,17
+ ,0
+ ,6
+ ,178
+ ,17.2
+ ,18
+ ,14
+ ,0
+ ,7
+ ,150
+ ,17.2
+ ,13
+ ,10
+ ,0
+ ,8
+ ,104
+ ,14.1
+ ,16
+ ,7
+ ,0
+ ,9
+ ,111
+ ,10.4
+ ,11
+ ,4
+ ,0
+ ,10
+ ,51
+ ,6.8
+ ,22
+ ,1
+ ,1
+ ,11
+ ,70
+ ,4.1
+ ,19
+ ,6
+ ,0
+ ,12
+ ,42
+ ,6.5
+ ,23
+ ,2
+ ,1
+ ,1
+ ,126
+ ,6.1
+ ,11
+ ,2
+ ,0
+ ,2
+ ,68
+ ,6.3
+ ,24
+ ,8
+ ,7
+ ,3
+ ,135
+ ,9.3
+ ,14
+ ,10
+ ,0
+ ,4
+ ,231
+ ,16.4
+ ,11
+ ,13
+ ,0
+ ,5
+ ,185
+ ,16.1
+ ,17
+ ,10
+ ,0
+ ,6
+ ,181
+ ,18
+ ,20
+ ,14
+ ,0
+ ,7
+ ,138
+ ,17.6
+ ,19
+ ,13
+ ,0
+ ,8
+ ,158
+ ,14
+ ,12
+ ,6
+ ,0
+ ,9
+ ,122
+ ,10.5
+ ,19
+ ,6
+ ,2
+ ,10
+ ,40
+ ,6.9
+ ,26
+ ,9
+ ,3
+ ,11
+ ,62
+ ,2.8
+ ,13
+ ,2
+ ,5
+ ,12
+ ,89
+ ,0.7
+ ,12
+ ,4
+ ,5
+ ,1
+ ,33
+ ,3.6
+ ,20
+ ,3
+ ,7
+ ,2
+ ,150
+ ,6.7
+ ,15
+ ,4
+ ,2
+ ,3
+ ,196
+ ,12.5
+ ,15
+ ,10
+ ,0
+ ,4
+ ,196
+ ,14.4
+ ,17
+ ,15
+ ,0
+ ,5
+ ,225
+ ,16.5
+ ,11
+ ,14
+ ,0
+ ,6
+ ,213
+ ,18.7
+ ,20
+ ,18
+ ,0
+ ,7
+ ,258
+ ,19.4
+ ,9
+ ,10
+ ,0
+ ,8
+ ,156
+ ,15.8
+ ,10
+ ,5
+ ,0
+ ,9
+ ,90
+ ,11.3
+ ,17
+ ,5
+ ,0
+ ,10
+ ,48
+ ,9.7
+ ,25
+ ,7
+ ,0
+ ,11
+ ,46
+ ,2.9
+ ,19
+ ,2
+ ,7
+ ,12
+ ,49
+ ,0.1
+ ,18
+ ,0
+ ,14
+ ,1
+ ,29
+ ,2.5
+ ,24
+ ,4
+ ,10
+ ,2
+ ,118
+ ,6.7
+ ,13
+ ,7
+ ,2
+ ,3
+ ,223
+ ,10.3
+ ,6
+ ,8
+ ,0
+ ,4
+ ,172
+ ,11.2
+ ,14
+ ,6
+ ,0
+ ,5
+ ,259
+ ,17.4
+ ,9
+ ,3
+ ,0
+ ,6
+ ,252
+ ,20.5
+ ,13
+ ,12
+ ,0
+ ,7
+ ,136
+ ,17
+ ,23
+ ,15
+ ,0
+ ,8
+ ,143
+ ,14.2
+ ,18
+ ,8
+ ,0
+ ,9
+ ,119
+ ,10.6
+ ,16
+ ,6
+ ,0
+ ,10
+ ,24
+ ,6.1
+ ,21
+ ,1
+ ,6
+ ,11)
+ ,dim=c(6
+ ,56)
+ ,dimnames=list(c('UrenZonneschijn'
+ ,'GemiddeldeTemperatuur'
+ ,'Neerslagdagen'
+ ,'Onweersdagen'
+ ,'Sneeuwdagen'
+ ,'Maand')
+ ,1:56))
> y <- array(NA,dim=c(6,56),dimnames=list(c('UrenZonneschijn','GemiddeldeTemperatuur','Neerslagdagen','Onweersdagen','Sneeuwdagen','Maand'),1:56))
> 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 = 'Do not include Seasonal Dummies'
> par1 = '2'
> #'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
GemiddeldeTemperatuur UrenZonneschijn Neerslagdagen Onweersdagen Sneeuwdagen
1 9.3 141 16 6 7
2 14.2 136 20 20 0
3 17.3 246 7 12 0
4 23.0 309 8 15 0
5 16.3 95 21 25 0
6 18.4 161 7 4 0
7 14.2 108 17 6 0
8 9.1 79 20 2 0
9 5.9 40 18 1 1
10 7.2 35 26 4 2
11 6.8 49 18 4 2
12 8.0 145 20 8 2
13 14.3 284 0 3 0
14 14.6 164 22 14 0
15 17.5 130 19 17 0
16 17.2 178 18 14 0
17 17.2 150 13 10 0
18 14.1 104 16 7 0
19 10.4 111 11 4 0
20 6.8 51 22 1 1
21 4.1 70 19 6 0
22 6.5 42 23 2 1
23 6.1 126 11 2 0
24 6.3 68 24 8 7
25 9.3 135 14 10 0
26 16.4 231 11 13 0
27 16.1 185 17 10 0
28 18.0 181 20 14 0
29 17.6 138 19 13 0
30 14.0 158 12 6 0
31 10.5 122 19 6 2
32 6.9 40 26 9 3
33 2.8 62 13 2 5
34 0.7 89 12 4 5
35 3.6 33 20 3 7
36 6.7 150 15 4 2
37 12.5 196 15 10 0
38 14.4 196 17 15 0
39 16.5 225 11 14 0
40 18.7 213 20 18 0
41 19.4 258 9 10 0
42 15.8 156 10 5 0
43 11.3 90 17 5 0
44 9.7 48 25 7 0
45 2.9 46 19 2 7
46 0.1 49 18 0 14
47 2.5 29 24 4 10
48 6.7 118 13 7 2
49 10.3 223 6 8 0
50 11.2 172 14 6 0
51 17.4 259 9 3 0
52 20.5 252 13 12 0
53 17.0 136 23 15 0
54 14.2 143 18 8 0
55 10.6 119 16 6 0
56 6.1 24 21 1 6
Maand
1 4
2 5
3 6
4 7
5 8
6 9
7 10
8 11
9 12
10 1
11 2
12 3
13 4
14 5
15 6
16 7
17 8
18 9
19 10
20 11
21 12
22 1
23 2
24 3
25 4
26 5
27 6
28 7
29 8
30 9
31 10
32 11
33 12
34 1
35 2
36 3
37 4
38 5
39 6
40 7
41 8
42 9
43 10
44 11
45 12
46 1
47 2
48 3
49 4
50 5
51 6
52 7
53 8
54 9
55 10
56 11
> k <- length(x[1,])
> df <- as.data.frame(x)
> (mylm <- lm(df))
Call:
lm(formula = df)
Coefficients:
(Intercept) UrenZonneschijn Neerslagdagen Onweersdagen
-1.68681 0.05166 0.15219 0.27900
Sneeuwdagen Maand
-0.39177 0.33085
> (mysum <- summary(mylm))
Call:
lm(formula = df)
Residuals:
Min 1Q Median 3Q Max
-6.3649 -1.4268 0.2579 1.5185 6.6110
Coefficients:
Estimate Std. Error t value Pr(>|t|)
(Intercept) -1.686811 2.733139 -0.617 0.53992
UrenZonneschijn 0.051658 0.009481 5.449 1.55e-06 ***
Neerslagdagen 0.152185 0.106599 1.428 0.15961
Onweersdagen 0.279004 0.089398 3.121 0.00299 **
Sneeuwdagen -0.391769 0.145934 -2.685 0.00983 **
Maand 0.330848 0.107591 3.075 0.00341 **
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
Residual standard error: 2.418 on 50 degrees of freedom
Multiple R-squared: 0.831, Adjusted R-squared: 0.8141
F-statistic: 49.18 on 5 and 50 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,] 0.7673816 0.46523688 0.23261844
[2,] 0.6969361 0.60612777 0.30306388
[3,] 0.6385470 0.72290607 0.36145304
[4,] 0.6953227 0.60935461 0.30467730
[5,] 0.7834694 0.43306130 0.21653065
[6,] 0.7054028 0.58919433 0.29459716
[7,] 0.7134701 0.57305973 0.28652987
[8,] 0.6385546 0.72289087 0.36144544
[9,] 0.6942800 0.61144004 0.30572002
[10,] 0.7110043 0.57799150 0.28899575
[11,] 0.7206938 0.55861237 0.27930619
[12,] 0.6633725 0.67325497 0.33662748
[13,] 0.9577133 0.08457345 0.04228673
[14,] 0.9438478 0.11230448 0.05615224
[15,] 0.9516645 0.09667106 0.04833553
[16,] 0.9254567 0.14908670 0.07454335
[17,] 0.9214598 0.15708043 0.07854022
[18,] 0.8878143 0.22437133 0.11218566
[19,] 0.8503321 0.29933584 0.14966792
[20,] 0.8104001 0.37919986 0.18959993
[21,] 0.8734356 0.25312885 0.12656442
[22,] 0.8462937 0.30741267 0.15370634
[23,] 0.8112608 0.37747844 0.18873922
[24,] 0.8100604 0.37987914 0.18993957
[25,] 0.8420560 0.31588799 0.15794399
[26,] 0.8443712 0.31125767 0.15562884
[27,] 0.8576789 0.28464229 0.14232115
[28,] 0.8715363 0.25692746 0.12846373
[29,] 0.8600808 0.27983834 0.13991917
[30,] 0.8407113 0.31857750 0.15928875
[31,] 0.7728858 0.45422832 0.22711416
[32,] 0.7142826 0.57143473 0.28571736
[33,] 0.6229680 0.75406407 0.37703204
[34,] 0.9233137 0.15337260 0.07668630
[35,] 0.9525422 0.09491551 0.04745776
[36,] 0.9209894 0.15802117 0.07901058
[37,] 0.9818569 0.03628628 0.01814314
[38,] 0.9510899 0.09782024 0.04891012
[39,] 0.9503153 0.09936950 0.04968475
> postscript(file="/var/www/html/rcomp/tmp/1lsi01293561836.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$resid)
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/2ekz31293561836.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> plot(mysum$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/html/rcomp/tmp/3ekz31293561836.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> hist(mysum$resid, main='Residual Histogram', xlab='values of Residuals')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/4ekz31293561836.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> densityplot(~mysum$resid,col='black',main='Residual Density Plot', xlab='values of Residuals')
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/56bh61293561836.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 = 56
Frequency = 1
1 2 3 4 5 6 7
1.0130966 -1.4166394 -0.1193804 1.0061484 0.2615722 6.6109990 2.7381417
8 9 10 11 12 13 14
-0.5351774 -1.0762374 2.4586538 2.2220819 -3.2882779 -0.8443405 -1.0933986
15 16 17 18 19 20 21
2.8516547 0.7304405 3.7229458 3.0488014 0.2542881 -1.0223635 -6.3649374
22 23 24 25 26 27 28
2.0198456 -1.6157835 0.3394570 -2.2309840 -0.8014138 0.8678861 1.0710973
29 30 31 32 33 34 35
2.9927136 1.0470378 -1.2058972 -2.4113646 -3.2637065 -3.5249550 1.7820799
36 37 38 39 40 41 42
-2.9696242 -2.3342805 -2.4645182 -1.0013202 -0.9979600 0.9526700 3.5337273
43 44 45 46 47 48 49
1.0469817 -0.4897383 -2.4667595 1.6701700 1.1762715 -1.8492232 -4.0013599
50 51 52 53 54 55 56
-1.4571465 1.5157353 1.5267148 1.3292800 0.5507821 -1.2779062 1.7834195
> postscript(file="/var/www/html/rcomp/tmp/66bh61293561836.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 = 56
Frequency = 1
lag(myerror, k = 1) myerror
0 1.0130966 NA
1 -1.4166394 1.0130966
2 -0.1193804 -1.4166394
3 1.0061484 -0.1193804
4 0.2615722 1.0061484
5 6.6109990 0.2615722
6 2.7381417 6.6109990
7 -0.5351774 2.7381417
8 -1.0762374 -0.5351774
9 2.4586538 -1.0762374
10 2.2220819 2.4586538
11 -3.2882779 2.2220819
12 -0.8443405 -3.2882779
13 -1.0933986 -0.8443405
14 2.8516547 -1.0933986
15 0.7304405 2.8516547
16 3.7229458 0.7304405
17 3.0488014 3.7229458
18 0.2542881 3.0488014
19 -1.0223635 0.2542881
20 -6.3649374 -1.0223635
21 2.0198456 -6.3649374
22 -1.6157835 2.0198456
23 0.3394570 -1.6157835
24 -2.2309840 0.3394570
25 -0.8014138 -2.2309840
26 0.8678861 -0.8014138
27 1.0710973 0.8678861
28 2.9927136 1.0710973
29 1.0470378 2.9927136
30 -1.2058972 1.0470378
31 -2.4113646 -1.2058972
32 -3.2637065 -2.4113646
33 -3.5249550 -3.2637065
34 1.7820799 -3.5249550
35 -2.9696242 1.7820799
36 -2.3342805 -2.9696242
37 -2.4645182 -2.3342805
38 -1.0013202 -2.4645182
39 -0.9979600 -1.0013202
40 0.9526700 -0.9979600
41 3.5337273 0.9526700
42 1.0469817 3.5337273
43 -0.4897383 1.0469817
44 -2.4667595 -0.4897383
45 1.6701700 -2.4667595
46 1.1762715 1.6701700
47 -1.8492232 1.1762715
48 -4.0013599 -1.8492232
49 -1.4571465 -4.0013599
50 1.5157353 -1.4571465
51 1.5267148 1.5157353
52 1.3292800 1.5267148
53 0.5507821 1.3292800
54 -1.2779062 0.5507821
55 1.7834195 -1.2779062
56 NA 1.7834195
> dum1 <- dum[2:length(myerror),]
> dum1
lag(myerror, k = 1) myerror
[1,] -1.4166394 1.0130966
[2,] -0.1193804 -1.4166394
[3,] 1.0061484 -0.1193804
[4,] 0.2615722 1.0061484
[5,] 6.6109990 0.2615722
[6,] 2.7381417 6.6109990
[7,] -0.5351774 2.7381417
[8,] -1.0762374 -0.5351774
[9,] 2.4586538 -1.0762374
[10,] 2.2220819 2.4586538
[11,] -3.2882779 2.2220819
[12,] -0.8443405 -3.2882779
[13,] -1.0933986 -0.8443405
[14,] 2.8516547 -1.0933986
[15,] 0.7304405 2.8516547
[16,] 3.7229458 0.7304405
[17,] 3.0488014 3.7229458
[18,] 0.2542881 3.0488014
[19,] -1.0223635 0.2542881
[20,] -6.3649374 -1.0223635
[21,] 2.0198456 -6.3649374
[22,] -1.6157835 2.0198456
[23,] 0.3394570 -1.6157835
[24,] -2.2309840 0.3394570
[25,] -0.8014138 -2.2309840
[26,] 0.8678861 -0.8014138
[27,] 1.0710973 0.8678861
[28,] 2.9927136 1.0710973
[29,] 1.0470378 2.9927136
[30,] -1.2058972 1.0470378
[31,] -2.4113646 -1.2058972
[32,] -3.2637065 -2.4113646
[33,] -3.5249550 -3.2637065
[34,] 1.7820799 -3.5249550
[35,] -2.9696242 1.7820799
[36,] -2.3342805 -2.9696242
[37,] -2.4645182 -2.3342805
[38,] -1.0013202 -2.4645182
[39,] -0.9979600 -1.0013202
[40,] 0.9526700 -0.9979600
[41,] 3.5337273 0.9526700
[42,] 1.0469817 3.5337273
[43,] -0.4897383 1.0469817
[44,] -2.4667595 -0.4897383
[45,] 1.6701700 -2.4667595
[46,] 1.1762715 1.6701700
[47,] -1.8492232 1.1762715
[48,] -4.0013599 -1.8492232
[49,] -1.4571465 -4.0013599
[50,] 1.5157353 -1.4571465
[51,] 1.5267148 1.5157353
[52,] 1.3292800 1.5267148
[53,] 0.5507821 1.3292800
[54,] -1.2779062 0.5507821
[55,] 1.7834195 -1.2779062
> z <- as.data.frame(dum1)
> z
lag(myerror, k = 1) myerror
1 -1.4166394 1.0130966
2 -0.1193804 -1.4166394
3 1.0061484 -0.1193804
4 0.2615722 1.0061484
5 6.6109990 0.2615722
6 2.7381417 6.6109990
7 -0.5351774 2.7381417
8 -1.0762374 -0.5351774
9 2.4586538 -1.0762374
10 2.2220819 2.4586538
11 -3.2882779 2.2220819
12 -0.8443405 -3.2882779
13 -1.0933986 -0.8443405
14 2.8516547 -1.0933986
15 0.7304405 2.8516547
16 3.7229458 0.7304405
17 3.0488014 3.7229458
18 0.2542881 3.0488014
19 -1.0223635 0.2542881
20 -6.3649374 -1.0223635
21 2.0198456 -6.3649374
22 -1.6157835 2.0198456
23 0.3394570 -1.6157835
24 -2.2309840 0.3394570
25 -0.8014138 -2.2309840
26 0.8678861 -0.8014138
27 1.0710973 0.8678861
28 2.9927136 1.0710973
29 1.0470378 2.9927136
30 -1.2058972 1.0470378
31 -2.4113646 -1.2058972
32 -3.2637065 -2.4113646
33 -3.5249550 -3.2637065
34 1.7820799 -3.5249550
35 -2.9696242 1.7820799
36 -2.3342805 -2.9696242
37 -2.4645182 -2.3342805
38 -1.0013202 -2.4645182
39 -0.9979600 -1.0013202
40 0.9526700 -0.9979600
41 3.5337273 0.9526700
42 1.0469817 3.5337273
43 -0.4897383 1.0469817
44 -2.4667595 -0.4897383
45 1.6701700 -2.4667595
46 1.1762715 1.6701700
47 -1.8492232 1.1762715
48 -4.0013599 -1.8492232
49 -1.4571465 -4.0013599
50 1.5157353 -1.4571465
51 1.5267148 1.5157353
52 1.3292800 1.5267148
53 0.5507821 1.3292800
54 -1.2779062 0.5507821
55 1.7834195 -1.2779062
> 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/7z2gr1293561836.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> acf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/8z2gr1293561836.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> pacf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Partial Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/9atxc1293561836.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> opar <- par(mfrow = c(2,2), oma = c(0, 0, 1.1, 0))
> plot(mylm, las = 1, sub='Residual Diagnostics')
> par(opar)
> dev.off()
null device
1
> if (n > n25) {
+ postscript(file="/var/www/html/rcomp/tmp/10atxc1293561836.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
+ plot(kp3:nmkm3,gqarr[,2], main='Goldfeld-Quandt test',ylab='2-sided p-value',xlab='breakpoint')
+ grid()
+ dev.off()
+ }
null device
1
>
> #Note: the /var/www/html/rcomp/createtable file can be downloaded at http://www.wessa.net/cretab
> load(file="/var/www/html/rcomp/createtable")
>
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a, 'Multiple Linear Regression - Estimated Regression Equation', 1, TRUE)
> a<-table.row.end(a)
> myeq <- colnames(x)[1]
> myeq <- paste(myeq, '[t] = ', sep='')
> for (i in 1:k){
+ if (mysum$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/11vue01293561836.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/12yuc51293561836.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/13tzyo1293561836.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/14yn8k1293561836.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/151n781293561836.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/16gfnh1293561836.tab")
+ }
>
> try(system("convert tmp/1lsi01293561836.ps tmp/1lsi01293561836.png",intern=TRUE))
character(0)
> try(system("convert tmp/2ekz31293561836.ps tmp/2ekz31293561836.png",intern=TRUE))
character(0)
> try(system("convert tmp/3ekz31293561836.ps tmp/3ekz31293561836.png",intern=TRUE))
character(0)
> try(system("convert tmp/4ekz31293561836.ps tmp/4ekz31293561836.png",intern=TRUE))
character(0)
> try(system("convert tmp/56bh61293561836.ps tmp/56bh61293561836.png",intern=TRUE))
character(0)
> try(system("convert tmp/66bh61293561836.ps tmp/66bh61293561836.png",intern=TRUE))
character(0)
> try(system("convert tmp/7z2gr1293561836.ps tmp/7z2gr1293561836.png",intern=TRUE))
character(0)
> try(system("convert tmp/8z2gr1293561836.ps tmp/8z2gr1293561836.png",intern=TRUE))
character(0)
> try(system("convert tmp/9atxc1293561836.ps tmp/9atxc1293561836.png",intern=TRUE))
character(0)
> try(system("convert tmp/10atxc1293561836.ps tmp/10atxc1293561836.png",intern=TRUE))
character(0)
>
>
> proc.time()
user system elapsed
2.460 1.627 9.820