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(100.0
+ ,114.1
+ ,141.7
+ ,100.0
+ ,93.5
+ ,110.3
+ ,153.4
+ ,117.8
+ ,88.2
+ ,103.9
+ ,145
+ ,95.7
+ ,89.2
+ ,101.6
+ ,137.7
+ ,100.5
+ ,91.4
+ ,94.6
+ ,148.3
+ ,105.1
+ ,92.5
+ ,95.9
+ ,152.2
+ ,116.2
+ ,91.4
+ ,104.7
+ ,169.4
+ ,125.3
+ ,88.2
+ ,102.8
+ ,168.6
+ ,130.2
+ ,87.1
+ ,98.1
+ ,161.1
+ ,137.1
+ ,84.9
+ ,113.9
+ ,174.1
+ ,136.3
+ ,92.5
+ ,80.9
+ ,179
+ ,107.8
+ ,93.5
+ ,95.7
+ ,190.6
+ ,118.1
+ ,93.5
+ ,113.2
+ ,190
+ ,119.5
+ ,91.4
+ ,105.9
+ ,181.6
+ ,124.1
+ ,90.3
+ ,108.8
+ ,174.8
+ ,114.0
+ ,91.4
+ ,102.3
+ ,180.5
+ ,132.2
+ ,93.5
+ ,99
+ ,196.8
+ ,160.0
+ ,93.5
+ ,100.7
+ ,193.8
+ ,124.6
+ ,92.5
+ ,115.5
+ ,197
+ ,138.7
+ ,91.4
+ ,100.7
+ ,216.3
+ ,105.1
+ ,89.2
+ ,109.9
+ ,221.4
+ ,132.3
+ ,86.0
+ ,114.6
+ ,217.9
+ ,118.4
+ ,88.2
+ ,85.4
+ ,229.7
+ ,114.2
+ ,87.1
+ ,100.5
+ ,227.4
+ ,106.7
+ ,87.1
+ ,114.8
+ ,204.2
+ ,110.7
+ ,86.0
+ ,116.5
+ ,196.6
+ ,115.3
+ ,84.9
+ ,112.9
+ ,198.8
+ ,95.7
+ ,84.9
+ ,102
+ ,207.5
+ ,106.0
+ ,86.0
+ ,106
+ ,190.7
+ ,109.3
+ ,86.0
+ ,105.3
+ ,201.6
+ ,105.9
+ ,84.9
+ ,118.8
+ ,210.5
+ ,118.5
+ ,86.0
+ ,106.1
+ ,223.5
+ ,107.5
+ ,82.8
+ ,109.3
+ ,223.8
+ ,102.4
+ ,77.4
+ ,117.2
+ ,231.2
+ ,126.7
+ ,80.6
+ ,92.5
+ ,244
+ ,112.0
+ ,78.5
+ ,104.2
+ ,234.7
+ ,99.5
+ ,75.3
+ ,112.5
+ ,250.2
+ ,88.3
+ ,75.3
+ ,122.4
+ ,265.7
+ ,118.0
+ ,75.3
+ ,113.3
+ ,287.6
+ ,96.2
+ ,77.4
+ ,100
+ ,283.3
+ ,96.0
+ ,78.5
+ ,110.7
+ ,295.4
+ ,117.5
+ ,76.3
+ ,112.8
+ ,312.3
+ ,113.5
+ ,73.1
+ ,109.8
+ ,333.8
+ ,101.9
+ ,68.8
+ ,117.3
+ ,347.7
+ ,130.1
+ ,65.6
+ ,109.1
+ ,383.2
+ ,96.5
+ ,69.9
+ ,115.9
+ ,407.1
+ ,122.2
+ ,82.8
+ ,96
+ ,413.6
+ ,106.4
+ ,84.9
+ ,99.8
+ ,362.7
+ ,99.8
+ ,80.6
+ ,116.8
+ ,321.9
+ ,113.0
+ ,74.2
+ ,115.7
+ ,239.4
+ ,99.6
+ ,71.0
+ ,99.4
+ ,191
+ ,85.0
+ ,74.2
+ ,94.3
+ ,159.7
+ ,96.8
+ ,82.8
+ ,91
+ ,163.4
+ ,83.2
+ ,86.0
+ ,93.2
+ ,157.6
+ ,81.1
+ ,86.0
+ ,103.1
+ ,166.2
+ ,104.4
+ ,82.8
+ ,94.1
+ ,176.7
+ ,91.3
+ ,78.5
+ ,91.8
+ ,198.3
+ ,85.0
+ ,79.6
+ ,102.7
+ ,226.2
+ ,117.5
+ ,87.1
+ ,82.6
+ ,216.2
+ ,98.3
+ ,89.2
+ ,89.1
+ ,235.9
+ ,112.7)
+ ,dim=c(4
+ ,60)
+ ,dimnames=list(c('WRKL'
+ ,'IND'
+ ,'GRON'
+ ,'BOUW')
+ ,1:60))
> y <- array(NA,dim=c(4,60),dimnames=list(c('WRKL','IND','GRON','BOUW'),1:60))
> 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 = '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
WRKL IND GRON BOUW
1 100.0 114.1 141.7 100.0
2 93.5 110.3 153.4 117.8
3 88.2 103.9 145.0 95.7
4 89.2 101.6 137.7 100.5
5 91.4 94.6 148.3 105.1
6 92.5 95.9 152.2 116.2
7 91.4 104.7 169.4 125.3
8 88.2 102.8 168.6 130.2
9 87.1 98.1 161.1 137.1
10 84.9 113.9 174.1 136.3
11 92.5 80.9 179.0 107.8
12 93.5 95.7 190.6 118.1
13 93.5 113.2 190.0 119.5
14 91.4 105.9 181.6 124.1
15 90.3 108.8 174.8 114.0
16 91.4 102.3 180.5 132.2
17 93.5 99.0 196.8 160.0
18 93.5 100.7 193.8 124.6
19 92.5 115.5 197.0 138.7
20 91.4 100.7 216.3 105.1
21 89.2 109.9 221.4 132.3
22 86.0 114.6 217.9 118.4
23 88.2 85.4 229.7 114.2
24 87.1 100.5 227.4 106.7
25 87.1 114.8 204.2 110.7
26 86.0 116.5 196.6 115.3
27 84.9 112.9 198.8 95.7
28 84.9 102.0 207.5 106.0
29 86.0 106.0 190.7 109.3
30 86.0 105.3 201.6 105.9
31 84.9 118.8 210.5 118.5
32 86.0 106.1 223.5 107.5
33 82.8 109.3 223.8 102.4
34 77.4 117.2 231.2 126.7
35 80.6 92.5 244.0 112.0
36 78.5 104.2 234.7 99.5
37 75.3 112.5 250.2 88.3
38 75.3 122.4 265.7 118.0
39 75.3 113.3 287.6 96.2
40 77.4 100.0 283.3 96.0
41 78.5 110.7 295.4 117.5
42 76.3 112.8 312.3 113.5
43 73.1 109.8 333.8 101.9
44 68.8 117.3 347.7 130.1
45 65.6 109.1 383.2 96.5
46 69.9 115.9 407.1 122.2
47 82.8 96.0 413.6 106.4
48 84.9 99.8 362.7 99.8
49 80.6 116.8 321.9 113.0
50 74.2 115.7 239.4 99.6
51 71.0 99.4 191.0 85.0
52 74.2 94.3 159.7 96.8
53 82.8 91.0 163.4 83.2
54 86.0 93.2 157.6 81.1
55 86.0 103.1 166.2 104.4
56 82.8 94.1 176.7 91.3
57 78.5 91.8 198.3 85.0
58 79.6 102.7 226.2 117.5
59 87.1 82.6 216.2 98.3
60 89.2 89.1 235.9 112.7
> k <- length(x[1,])
> df <- as.data.frame(x)
> (mylm <- lm(df))
Call:
lm(formula = df)
Coefficients:
(Intercept) IND GRON BOUW
96.01031 -0.16223 -0.06478 0.17759
> (mysum <- summary(mylm))
Call:
lm(formula = df)
Residuals:
Min 1Q Median 3Q Max
-13.3572 -2.6561 0.7497 2.6704 13.9207
Coefficients:
Estimate Std. Error t value Pr(>|t|)
(Intercept) 96.01031 7.72954 12.421 < 2e-16 ***
IND -0.16223 0.07370 -2.201 0.031843 *
GRON -0.06478 0.01029 -6.299 4.95e-08 ***
BOUW 0.17759 0.04453 3.989 0.000195 ***
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
Residual standard error: 5.033 on 56 degrees of freedom
Multiple R-squared: 0.5562, Adjusted R-squared: 0.5324
F-statistic: 23.39 on 3 and 56 DF, p-value: 6.054e-10
> 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,] 0.449112540 0.89822508 0.5508875
[2,] 0.357411146 0.71482229 0.6425889
[3,] 0.283862505 0.56772501 0.7161375
[4,] 0.375948786 0.75189757 0.6240512
[5,] 0.326009001 0.65201800 0.6739910
[6,] 0.244205408 0.48841082 0.7557946
[7,] 0.188107270 0.37621454 0.8118927
[8,] 0.124882794 0.24976559 0.8751172
[9,] 0.099137315 0.19827463 0.9008627
[10,] 0.067776902 0.13555380 0.9322231
[11,] 0.101251354 0.20250271 0.8987486
[12,] 0.070619144 0.14123829 0.9293809
[13,] 0.047526315 0.09505263 0.9524737
[14,] 0.052360140 0.10472028 0.9476399
[15,] 0.042032215 0.08406443 0.9579678
[16,] 0.057057553 0.11411511 0.9429424
[17,] 0.040561592 0.08112318 0.9594384
[18,] 0.034101270 0.06820254 0.9658987
[19,] 0.033633021 0.06726604 0.9663670
[20,] 0.034484139 0.06896828 0.9655159
[21,] 0.043929846 0.08785969 0.9560702
[22,] 0.040096367 0.08019273 0.9599036
[23,] 0.036242348 0.07248470 0.9637577
[24,] 0.032616689 0.06523338 0.9673833
[25,] 0.039022847 0.07804569 0.9609772
[26,] 0.040911277 0.08182255 0.9590887
[27,] 0.046292980 0.09258596 0.9537070
[28,] 0.081391568 0.16278314 0.9186084
[29,] 0.083776898 0.16755380 0.9162231
[30,] 0.077964163 0.15592833 0.9220358
[31,] 0.071337183 0.14267437 0.9286628
[32,] 0.059658780 0.11931756 0.9403412
[33,] 0.044272712 0.08854542 0.9557273
[34,] 0.028292059 0.05658412 0.9717079
[35,] 0.018982828 0.03796566 0.9810172
[36,] 0.012192955 0.02438591 0.9878070
[37,] 0.006992064 0.01398413 0.9930079
[38,] 0.009321063 0.01864213 0.9906789
[39,] 0.018779395 0.03755879 0.9812206
[40,] 0.055986375 0.11197275 0.9440136
[41,] 0.160755962 0.32151192 0.8392440
[42,] 0.176617806 0.35323561 0.8233822
[43,] 0.168629844 0.33725969 0.8313702
[44,] 0.155037428 0.31007486 0.8449626
[45,] 0.277625994 0.55525199 0.7223740
[46,] 0.937898604 0.12420279 0.0621014
[47,] 0.898166187 0.20366763 0.1018338
> postscript(file="/var/www/html/rcomp/tmp/17erz1261145124.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$resid)
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/2hgjy1261145124.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> plot(mysum$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/3ytnf1261145124.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> hist(mysum$resid, main='Residual Histogram', xlab='values of Residuals')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/4ml311261145124.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> densityplot(~mysum$resid,col='black',main='Residual Density Plot', xlab='values of Residuals')
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/513ht1261145124.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 = 60
Frequency = 1
1 2 3 4 5 6
13.92069087 4.40096215 1.44332927 0.74483904 1.67894135 1.27119823
7 8 9 10 11 12
1.09698654 -3.33329416 -6.90705078 -5.55951971 2.06559462 4.38890497
13 14 15 16 17 18
6.94050933 2.29510634 3.01877626 0.20129198 -2.11526757 4.25301536
19 20 21 22 23 24
3.35731002 7.07366549 1.86604922 1.67037499 0.64343448 3.17613495
25 26 27 28 29 30
3.28279870 1.14933117 3.08864640 0.05466489 0.12922572 1.32559162
31 32 33 34 35 36
0.75462282 2.58992811 0.83424212 -7.12026072 -4.48762833 -3.07202093
37 38 39 40 41 42
-1.93231962 -4.59663646 -0.78272295 -1.08348087 -1.28199420 -1.33613050
43 44 45 46 47 48
-1.56995714 -8.76089517 -5.02434303 -2.63705245 10.26154013 10.85280956
49 50 51 52 53 54
4.32350018 -5.21961346 -11.60655448 -13.35719809 -2.63760514 0.91652962
55 56 57 58 59 60
-1.05817324 -2.71160479 -4.86663722 -5.96270090 1.03838130 2.91173410
> postscript(file="/var/www/html/rcomp/tmp/6jwpt1261145124.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 = 60
Frequency = 1
lag(myerror, k = 1) myerror
0 13.92069087 NA
1 4.40096215 13.92069087
2 1.44332927 4.40096215
3 0.74483904 1.44332927
4 1.67894135 0.74483904
5 1.27119823 1.67894135
6 1.09698654 1.27119823
7 -3.33329416 1.09698654
8 -6.90705078 -3.33329416
9 -5.55951971 -6.90705078
10 2.06559462 -5.55951971
11 4.38890497 2.06559462
12 6.94050933 4.38890497
13 2.29510634 6.94050933
14 3.01877626 2.29510634
15 0.20129198 3.01877626
16 -2.11526757 0.20129198
17 4.25301536 -2.11526757
18 3.35731002 4.25301536
19 7.07366549 3.35731002
20 1.86604922 7.07366549
21 1.67037499 1.86604922
22 0.64343448 1.67037499
23 3.17613495 0.64343448
24 3.28279870 3.17613495
25 1.14933117 3.28279870
26 3.08864640 1.14933117
27 0.05466489 3.08864640
28 0.12922572 0.05466489
29 1.32559162 0.12922572
30 0.75462282 1.32559162
31 2.58992811 0.75462282
32 0.83424212 2.58992811
33 -7.12026072 0.83424212
34 -4.48762833 -7.12026072
35 -3.07202093 -4.48762833
36 -1.93231962 -3.07202093
37 -4.59663646 -1.93231962
38 -0.78272295 -4.59663646
39 -1.08348087 -0.78272295
40 -1.28199420 -1.08348087
41 -1.33613050 -1.28199420
42 -1.56995714 -1.33613050
43 -8.76089517 -1.56995714
44 -5.02434303 -8.76089517
45 -2.63705245 -5.02434303
46 10.26154013 -2.63705245
47 10.85280956 10.26154013
48 4.32350018 10.85280956
49 -5.21961346 4.32350018
50 -11.60655448 -5.21961346
51 -13.35719809 -11.60655448
52 -2.63760514 -13.35719809
53 0.91652962 -2.63760514
54 -1.05817324 0.91652962
55 -2.71160479 -1.05817324
56 -4.86663722 -2.71160479
57 -5.96270090 -4.86663722
58 1.03838130 -5.96270090
59 2.91173410 1.03838130
60 NA 2.91173410
> dum1 <- dum[2:length(myerror),]
> dum1
lag(myerror, k = 1) myerror
[1,] 4.40096215 13.92069087
[2,] 1.44332927 4.40096215
[3,] 0.74483904 1.44332927
[4,] 1.67894135 0.74483904
[5,] 1.27119823 1.67894135
[6,] 1.09698654 1.27119823
[7,] -3.33329416 1.09698654
[8,] -6.90705078 -3.33329416
[9,] -5.55951971 -6.90705078
[10,] 2.06559462 -5.55951971
[11,] 4.38890497 2.06559462
[12,] 6.94050933 4.38890497
[13,] 2.29510634 6.94050933
[14,] 3.01877626 2.29510634
[15,] 0.20129198 3.01877626
[16,] -2.11526757 0.20129198
[17,] 4.25301536 -2.11526757
[18,] 3.35731002 4.25301536
[19,] 7.07366549 3.35731002
[20,] 1.86604922 7.07366549
[21,] 1.67037499 1.86604922
[22,] 0.64343448 1.67037499
[23,] 3.17613495 0.64343448
[24,] 3.28279870 3.17613495
[25,] 1.14933117 3.28279870
[26,] 3.08864640 1.14933117
[27,] 0.05466489 3.08864640
[28,] 0.12922572 0.05466489
[29,] 1.32559162 0.12922572
[30,] 0.75462282 1.32559162
[31,] 2.58992811 0.75462282
[32,] 0.83424212 2.58992811
[33,] -7.12026072 0.83424212
[34,] -4.48762833 -7.12026072
[35,] -3.07202093 -4.48762833
[36,] -1.93231962 -3.07202093
[37,] -4.59663646 -1.93231962
[38,] -0.78272295 -4.59663646
[39,] -1.08348087 -0.78272295
[40,] -1.28199420 -1.08348087
[41,] -1.33613050 -1.28199420
[42,] -1.56995714 -1.33613050
[43,] -8.76089517 -1.56995714
[44,] -5.02434303 -8.76089517
[45,] -2.63705245 -5.02434303
[46,] 10.26154013 -2.63705245
[47,] 10.85280956 10.26154013
[48,] 4.32350018 10.85280956
[49,] -5.21961346 4.32350018
[50,] -11.60655448 -5.21961346
[51,] -13.35719809 -11.60655448
[52,] -2.63760514 -13.35719809
[53,] 0.91652962 -2.63760514
[54,] -1.05817324 0.91652962
[55,] -2.71160479 -1.05817324
[56,] -4.86663722 -2.71160479
[57,] -5.96270090 -4.86663722
[58,] 1.03838130 -5.96270090
[59,] 2.91173410 1.03838130
> z <- as.data.frame(dum1)
> z
lag(myerror, k = 1) myerror
1 4.40096215 13.92069087
2 1.44332927 4.40096215
3 0.74483904 1.44332927
4 1.67894135 0.74483904
5 1.27119823 1.67894135
6 1.09698654 1.27119823
7 -3.33329416 1.09698654
8 -6.90705078 -3.33329416
9 -5.55951971 -6.90705078
10 2.06559462 -5.55951971
11 4.38890497 2.06559462
12 6.94050933 4.38890497
13 2.29510634 6.94050933
14 3.01877626 2.29510634
15 0.20129198 3.01877626
16 -2.11526757 0.20129198
17 4.25301536 -2.11526757
18 3.35731002 4.25301536
19 7.07366549 3.35731002
20 1.86604922 7.07366549
21 1.67037499 1.86604922
22 0.64343448 1.67037499
23 3.17613495 0.64343448
24 3.28279870 3.17613495
25 1.14933117 3.28279870
26 3.08864640 1.14933117
27 0.05466489 3.08864640
28 0.12922572 0.05466489
29 1.32559162 0.12922572
30 0.75462282 1.32559162
31 2.58992811 0.75462282
32 0.83424212 2.58992811
33 -7.12026072 0.83424212
34 -4.48762833 -7.12026072
35 -3.07202093 -4.48762833
36 -1.93231962 -3.07202093
37 -4.59663646 -1.93231962
38 -0.78272295 -4.59663646
39 -1.08348087 -0.78272295
40 -1.28199420 -1.08348087
41 -1.33613050 -1.28199420
42 -1.56995714 -1.33613050
43 -8.76089517 -1.56995714
44 -5.02434303 -8.76089517
45 -2.63705245 -5.02434303
46 10.26154013 -2.63705245
47 10.85280956 10.26154013
48 4.32350018 10.85280956
49 -5.21961346 4.32350018
50 -11.60655448 -5.21961346
51 -13.35719809 -11.60655448
52 -2.63760514 -13.35719809
53 0.91652962 -2.63760514
54 -1.05817324 0.91652962
55 -2.71160479 -1.05817324
56 -4.86663722 -2.71160479
57 -5.96270090 -4.86663722
58 1.03838130 -5.96270090
59 2.91173410 1.03838130
> 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/7ulie1261145124.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> acf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/89mff1261145124.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> pacf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Partial Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/97cr11261145124.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> opar <- par(mfrow = c(2,2), oma = c(0, 0, 1.1, 0))
> plot(mylm, las = 1, sub='Residual Diagnostics')
> par(opar)
> dev.off()
null device
1
> if (n > n25) {
+ postscript(file="/var/www/html/rcomp/tmp/10br6s1261145124.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
+ plot(kp3:nmkm3,gqarr[,2], main='Goldfeld-Quandt test',ylab='2-sided p-value',xlab='breakpoint')
+ grid()
+ dev.off()
+ }
null device
1
>
> #Note: the /var/www/html/rcomp/createtable file can be downloaded at http://www.wessa.net/cretab
> load(file="/var/www/html/rcomp/createtable")
>
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a, 'Multiple Linear Regression - Estimated Regression Equation', 1, TRUE)
> a<-table.row.end(a)
> myeq <- colnames(x)[1]
> myeq <- paste(myeq, '[t] = ', sep='')
> for (i in 1:k){
+ if (mysum$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/11zpgq1261145124.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/12ag0g1261145124.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/13ueep1261145124.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/14o05l1261145124.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/1585m31261145125.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/16ddcr1261145125.tab")
+ }
>
> try(system("convert tmp/17erz1261145124.ps tmp/17erz1261145124.png",intern=TRUE))
character(0)
> try(system("convert tmp/2hgjy1261145124.ps tmp/2hgjy1261145124.png",intern=TRUE))
character(0)
> try(system("convert tmp/3ytnf1261145124.ps tmp/3ytnf1261145124.png",intern=TRUE))
character(0)
> try(system("convert tmp/4ml311261145124.ps tmp/4ml311261145124.png",intern=TRUE))
character(0)
> try(system("convert tmp/513ht1261145124.ps tmp/513ht1261145124.png",intern=TRUE))
character(0)
> try(system("convert tmp/6jwpt1261145124.ps tmp/6jwpt1261145124.png",intern=TRUE))
character(0)
> try(system("convert tmp/7ulie1261145124.ps tmp/7ulie1261145124.png",intern=TRUE))
character(0)
> try(system("convert tmp/89mff1261145124.ps tmp/89mff1261145124.png",intern=TRUE))
character(0)
> try(system("convert tmp/97cr11261145124.ps tmp/97cr11261145124.png",intern=TRUE))
character(0)
> try(system("convert tmp/10br6s1261145124.ps tmp/10br6s1261145124.png",intern=TRUE))
character(0)
>
>
> proc.time()
user system elapsed
2.549 1.616 8.421