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(10414.9
+ ,10723.8
+ ,12476.8
+ ,13938.9
+ ,12384.6
+ ,13979.8
+ ,12266.7
+ ,13807.4
+ ,12919.9
+ ,12973.9
+ ,11497.3
+ ,12509.8
+ ,12142
+ ,12934.1
+ ,13919.4
+ ,14908.3
+ ,12656.8
+ ,13772.1
+ ,12034.1
+ ,13012.6
+ ,13199.7
+ ,14049.9
+ ,10881.3
+ ,11816.5
+ ,11301.2
+ ,11593.2
+ ,13643.9
+ ,14466.2
+ ,12517
+ ,13615.9
+ ,13981.1
+ ,14733.9
+ ,14275.7
+ ,13880.7
+ ,13435
+ ,13527.5
+ ,13565.7
+ ,13584
+ ,16216.3
+ ,16170.2
+ ,12970
+ ,13260.6
+ ,14079.9
+ ,14741.9
+ ,14235
+ ,15486.5
+ ,12213.4
+ ,13154.5
+ ,12581
+ ,12621.2
+ ,14130.4
+ ,15031.6
+ ,14210.8
+ ,15452.4
+ ,14378.5
+ ,15428
+ ,13142.8
+ ,13105.9
+ ,13714.7
+ ,14716.8
+ ,13621.9
+ ,14180
+ ,15379.8
+ ,16202.2
+ ,13306.3
+ ,14392.4
+ ,14391.2
+ ,15140.6
+ ,14909.9
+ ,15960.1
+ ,14025.4
+ ,14351.3
+ ,12951.2
+ ,13230.2
+ ,14344.3
+ ,15202.1
+ ,16093.4
+ ,17056
+ ,15413.6
+ ,16077.7
+ ,14705.7
+ ,13348.2
+ ,15972.8
+ ,16402.4
+ ,16241.4
+ ,16559.1
+ ,16626.4
+ ,16579
+ ,17136.2
+ ,17561.2
+ ,15622.9
+ ,16129.6
+ ,18003.9
+ ,18484.3
+ ,16136.1
+ ,16402.6
+ ,14423.7
+ ,14032.3
+ ,16789.4
+ ,17109.1
+ ,16782.2
+ ,17157.2
+ ,14133.8
+ ,13879.8
+ ,12607
+ ,12362.4
+ ,12004.5
+ ,12683.5
+ ,12175.4
+ ,12608.8
+ ,13268
+ ,13583.7
+ ,12299.3
+ ,12846.3
+ ,11800.6
+ ,12347.1
+ ,13873.3
+ ,13967
+ ,12269.6
+ ,13114.3)
+ ,dim=c(2
+ ,60)
+ ,dimnames=list(c('In_IEU'
+ ,'Uit_IEU')
+ ,1:60))
> y <- array(NA,dim=c(2,60),dimnames=list(c('In_IEU','Uit_IEU'),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 = '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
In_IEU Uit_IEU M1 M2 M3 M4 M5 M6 M7 M8 M9 M10 M11 t
1 10414.9 10723.8 1 0 0 0 0 0 0 0 0 0 0 1
2 12476.8 13938.9 0 1 0 0 0 0 0 0 0 0 0 2
3 12384.6 13979.8 0 0 1 0 0 0 0 0 0 0 0 3
4 12266.7 13807.4 0 0 0 1 0 0 0 0 0 0 0 4
5 12919.9 12973.9 0 0 0 0 1 0 0 0 0 0 0 5
6 11497.3 12509.8 0 0 0 0 0 1 0 0 0 0 0 6
7 12142.0 12934.1 0 0 0 0 0 0 1 0 0 0 0 7
8 13919.4 14908.3 0 0 0 0 0 0 0 1 0 0 0 8
9 12656.8 13772.1 0 0 0 0 0 0 0 0 1 0 0 9
10 12034.1 13012.6 0 0 0 0 0 0 0 0 0 1 0 10
11 13199.7 14049.9 0 0 0 0 0 0 0 0 0 0 1 11
12 10881.3 11816.5 0 0 0 0 0 0 0 0 0 0 0 12
13 11301.2 11593.2 1 0 0 0 0 0 0 0 0 0 0 13
14 13643.9 14466.2 0 1 0 0 0 0 0 0 0 0 0 14
15 12517.0 13615.9 0 0 1 0 0 0 0 0 0 0 0 15
16 13981.1 14733.9 0 0 0 1 0 0 0 0 0 0 0 16
17 14275.7 13880.7 0 0 0 0 1 0 0 0 0 0 0 17
18 13435.0 13527.5 0 0 0 0 0 1 0 0 0 0 0 18
19 13565.7 13584.0 0 0 0 0 0 0 1 0 0 0 0 19
20 16216.3 16170.2 0 0 0 0 0 0 0 1 0 0 0 20
21 12970.0 13260.6 0 0 0 0 0 0 0 0 1 0 0 21
22 14079.9 14741.9 0 0 0 0 0 0 0 0 0 1 0 22
23 14235.0 15486.5 0 0 0 0 0 0 0 0 0 0 1 23
24 12213.4 13154.5 0 0 0 0 0 0 0 0 0 0 0 24
25 12581.0 12621.2 1 0 0 0 0 0 0 0 0 0 0 25
26 14130.4 15031.6 0 1 0 0 0 0 0 0 0 0 0 26
27 14210.8 15452.4 0 0 1 0 0 0 0 0 0 0 0 27
28 14378.5 15428.0 0 0 0 1 0 0 0 0 0 0 0 28
29 13142.8 13105.9 0 0 0 0 1 0 0 0 0 0 0 29
30 13714.7 14716.8 0 0 0 0 0 1 0 0 0 0 0 30
31 13621.9 14180.0 0 0 0 0 0 0 1 0 0 0 0 31
32 15379.8 16202.2 0 0 0 0 0 0 0 1 0 0 0 32
33 13306.3 14392.4 0 0 0 0 0 0 0 0 1 0 0 33
34 14391.2 15140.6 0 0 0 0 0 0 0 0 0 1 0 34
35 14909.9 15960.1 0 0 0 0 0 0 0 0 0 0 1 35
36 14025.4 14351.3 0 0 0 0 0 0 0 0 0 0 0 36
37 12951.2 13230.2 1 0 0 0 0 0 0 0 0 0 0 37
38 14344.3 15202.1 0 1 0 0 0 0 0 0 0 0 0 38
39 16093.4 17056.0 0 0 1 0 0 0 0 0 0 0 0 39
40 15413.6 16077.7 0 0 0 1 0 0 0 0 0 0 0 40
41 14705.7 13348.2 0 0 0 0 1 0 0 0 0 0 0 41
42 15972.8 16402.4 0 0 0 0 0 1 0 0 0 0 0 42
43 16241.4 16559.1 0 0 0 0 0 0 1 0 0 0 0 43
44 16626.4 16579.0 0 0 0 0 0 0 0 1 0 0 0 44
45 17136.2 17561.2 0 0 0 0 0 0 0 0 1 0 0 45
46 15622.9 16129.6 0 0 0 0 0 0 0 0 0 1 0 46
47 18003.9 18484.3 0 0 0 0 0 0 0 0 0 0 1 47
48 16136.1 16402.6 0 0 0 0 0 0 0 0 0 0 0 48
49 14423.7 14032.3 1 0 0 0 0 0 0 0 0 0 0 49
50 16789.4 17109.1 0 1 0 0 0 0 0 0 0 0 0 50
51 16782.2 17157.2 0 0 1 0 0 0 0 0 0 0 0 51
52 14133.8 13879.8 0 0 0 1 0 0 0 0 0 0 0 52
53 12607.0 12362.4 0 0 0 0 1 0 0 0 0 0 0 53
54 12004.5 12683.5 0 0 0 0 0 1 0 0 0 0 0 54
55 12175.4 12608.8 0 0 0 0 0 0 1 0 0 0 0 55
56 13268.0 13583.7 0 0 0 0 0 0 0 1 0 0 0 56
57 12299.3 12846.3 0 0 0 0 0 0 0 0 1 0 0 57
58 11800.6 12347.1 0 0 0 0 0 0 0 0 0 1 0 58
59 13873.3 13967.0 0 0 0 0 0 0 0 0 0 0 1 59
60 12269.6 13114.3 0 0 0 0 0 0 0 0 0 0 0 60
> k <- length(x[1,])
> df <- as.data.frame(x)
> (mylm <- lm(df))
Call:
lm(formula = df)
Coefficients:
(Intercept) Uit_IEU M1 M2 M3 M4
-1635.225 1.039 740.557 -145.111 -351.021 -32.611
M5 M6 M7 M8 M9 M10
1167.195 83.240 290.322 235.842 -17.934 -22.052
M11 t
-142.434 11.932
> (mysum <- summary(mylm))
Call:
lm(formula = df)
Residuals:
Min 1Q Median 3Q Max
-465.14 -207.58 -37.63 151.02 809.87
Coefficients:
Estimate Std. Error t value Pr(>|t|)
(Intercept) -1.635e+03 5.041e+02 -3.244 0.002201 **
Uit_IEU 1.039e+00 3.671e-02 28.315 < 2e-16 ***
M1 7.406e+02 2.272e+02 3.260 0.002101 **
M2 -1.451e+02 2.318e+02 -0.626 0.534373
M3 -3.510e+02 2.343e+02 -1.498 0.141004
M4 -3.261e+01 2.277e+02 -0.143 0.886729
M5 1.167e+03 2.235e+02 5.223 4.14e-06 ***
M6 8.324e+01 2.231e+02 0.373 0.710736
M7 2.903e+02 2.228e+02 1.303 0.199112
M8 2.358e+02 2.323e+02 1.015 0.315232
M9 -1.793e+01 2.236e+02 -0.080 0.936428
M10 -2.205e+01 2.231e+02 -0.099 0.921692
M11 -1.424e+02 2.322e+02 -0.613 0.542694
t 1.193e+01 2.853e+00 4.182 0.000128 ***
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
Residual standard error: 351.1 on 46 degrees of freedom
Multiple R-squared: 0.9656, Adjusted R-squared: 0.9558
F-statistic: 99.25 on 13 and 46 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,] 0.1956574 0.39131477 0.80434262
[2,] 0.1940637 0.38812731 0.80593635
[3,] 0.1388209 0.27764181 0.86117910
[4,] 0.1341194 0.26823875 0.86588063
[5,] 0.1599715 0.31994299 0.84002851
[6,] 0.1435904 0.28718077 0.85640962
[7,] 0.3830847 0.76616939 0.61691531
[8,] 0.3412487 0.68249734 0.65875133
[9,] 0.3303001 0.66060015 0.66969993
[10,] 0.3284624 0.65692477 0.67153761
[11,] 0.2777006 0.55540113 0.72229944
[12,] 0.2806985 0.56139700 0.71930150
[13,] 0.3850202 0.77004034 0.61497983
[14,] 0.4455917 0.89118334 0.55440833
[15,] 0.4083334 0.81666682 0.59166659
[16,] 0.4325669 0.86513377 0.56743311
[17,] 0.4077031 0.81540630 0.59229685
[18,] 0.3114666 0.62293320 0.68853340
[19,] 0.2815292 0.56305842 0.71847079
[20,] 0.2886040 0.57720799 0.71139601
[21,] 0.2382245 0.47644901 0.76177549
[22,] 0.1767884 0.35357673 0.82321164
[23,] 0.2420913 0.48418270 0.75790865
[24,] 0.9785361 0.04292771 0.02146385
[25,] 0.9637396 0.07252082 0.03626041
[26,] 0.9111595 0.17768101 0.08884051
[27,] 0.7992613 0.40147740 0.20073870
> postscript(file="/var/www/html/rcomp/tmp/1nen51258899186.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$resid)
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/269bv1258899186.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> plot(mysum$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/3hlf41258899186.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> hist(mysum$resid, main='Residual Histogram', xlab='values of Residuals')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/4qszc1258899186.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> densityplot(~mysum$resid,col='black',main='Residual Density Plot', xlab='values of Residuals')
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/5vqil1258899186.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
150.904094 -255.358412 -196.094184 -465.136555 -157.303106 -25.476578
7 8 9 10 11 12
-40.825281 -272.936541 -112.682824 46.256110 242.096088 90.812158
13 14 15 16 17 18
-9.670848 220.458580 171.370460 143.036560 112.746949 711.199741
19 20 21 22 23 24
564.156542 569.108879 589.002952 151.367943 -359.048410 -111.043697
25 26 27 28 29 30
58.399253 -23.927038 -186.945521 -324.224801 -357.983100 -388.491600
31 32 33 34 35 36
-142.335896 -443.840207 -394.320670 -94.943265 -319.613567 313.769173
37 38 39 40 41 42
-347.605886 -130.438365 -114.376260 -107.635090 809.873884 -25.656301
43 44 45 46 47 48
-138.951244 267.912289 -1.380655 -34.435060 7.448549 149.081788
49 50 51 52 53 54
147.973387 189.265235 326.045505 753.959887 -407.334627 -271.575262
55 56 57 58 59 60
-242.044121 -120.244420 -80.618803 -68.245729 429.117340 -442.619421
> postscript(file="/var/www/html/rcomp/tmp/6a5mi1258899186.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
0 150.904094 NA
1 -255.358412 150.904094
2 -196.094184 -255.358412
3 -465.136555 -196.094184
4 -157.303106 -465.136555
5 -25.476578 -157.303106
6 -40.825281 -25.476578
7 -272.936541 -40.825281
8 -112.682824 -272.936541
9 46.256110 -112.682824
10 242.096088 46.256110
11 90.812158 242.096088
12 -9.670848 90.812158
13 220.458580 -9.670848
14 171.370460 220.458580
15 143.036560 171.370460
16 112.746949 143.036560
17 711.199741 112.746949
18 564.156542 711.199741
19 569.108879 564.156542
20 589.002952 569.108879
21 151.367943 589.002952
22 -359.048410 151.367943
23 -111.043697 -359.048410
24 58.399253 -111.043697
25 -23.927038 58.399253
26 -186.945521 -23.927038
27 -324.224801 -186.945521
28 -357.983100 -324.224801
29 -388.491600 -357.983100
30 -142.335896 -388.491600
31 -443.840207 -142.335896
32 -394.320670 -443.840207
33 -94.943265 -394.320670
34 -319.613567 -94.943265
35 313.769173 -319.613567
36 -347.605886 313.769173
37 -130.438365 -347.605886
38 -114.376260 -130.438365
39 -107.635090 -114.376260
40 809.873884 -107.635090
41 -25.656301 809.873884
42 -138.951244 -25.656301
43 267.912289 -138.951244
44 -1.380655 267.912289
45 -34.435060 -1.380655
46 7.448549 -34.435060
47 149.081788 7.448549
48 147.973387 149.081788
49 189.265235 147.973387
50 326.045505 189.265235
51 753.959887 326.045505
52 -407.334627 753.959887
53 -271.575262 -407.334627
54 -242.044121 -271.575262
55 -120.244420 -242.044121
56 -80.618803 -120.244420
57 -68.245729 -80.618803
58 429.117340 -68.245729
59 -442.619421 429.117340
60 NA -442.619421
> dum1 <- dum[2:length(myerror),]
> dum1
lag(myerror, k = 1) myerror
[1,] -255.358412 150.904094
[2,] -196.094184 -255.358412
[3,] -465.136555 -196.094184
[4,] -157.303106 -465.136555
[5,] -25.476578 -157.303106
[6,] -40.825281 -25.476578
[7,] -272.936541 -40.825281
[8,] -112.682824 -272.936541
[9,] 46.256110 -112.682824
[10,] 242.096088 46.256110
[11,] 90.812158 242.096088
[12,] -9.670848 90.812158
[13,] 220.458580 -9.670848
[14,] 171.370460 220.458580
[15,] 143.036560 171.370460
[16,] 112.746949 143.036560
[17,] 711.199741 112.746949
[18,] 564.156542 711.199741
[19,] 569.108879 564.156542
[20,] 589.002952 569.108879
[21,] 151.367943 589.002952
[22,] -359.048410 151.367943
[23,] -111.043697 -359.048410
[24,] 58.399253 -111.043697
[25,] -23.927038 58.399253
[26,] -186.945521 -23.927038
[27,] -324.224801 -186.945521
[28,] -357.983100 -324.224801
[29,] -388.491600 -357.983100
[30,] -142.335896 -388.491600
[31,] -443.840207 -142.335896
[32,] -394.320670 -443.840207
[33,] -94.943265 -394.320670
[34,] -319.613567 -94.943265
[35,] 313.769173 -319.613567
[36,] -347.605886 313.769173
[37,] -130.438365 -347.605886
[38,] -114.376260 -130.438365
[39,] -107.635090 -114.376260
[40,] 809.873884 -107.635090
[41,] -25.656301 809.873884
[42,] -138.951244 -25.656301
[43,] 267.912289 -138.951244
[44,] -1.380655 267.912289
[45,] -34.435060 -1.380655
[46,] 7.448549 -34.435060
[47,] 149.081788 7.448549
[48,] 147.973387 149.081788
[49,] 189.265235 147.973387
[50,] 326.045505 189.265235
[51,] 753.959887 326.045505
[52,] -407.334627 753.959887
[53,] -271.575262 -407.334627
[54,] -242.044121 -271.575262
[55,] -120.244420 -242.044121
[56,] -80.618803 -120.244420
[57,] -68.245729 -80.618803
[58,] 429.117340 -68.245729
[59,] -442.619421 429.117340
> z <- as.data.frame(dum1)
> z
lag(myerror, k = 1) myerror
1 -255.358412 150.904094
2 -196.094184 -255.358412
3 -465.136555 -196.094184
4 -157.303106 -465.136555
5 -25.476578 -157.303106
6 -40.825281 -25.476578
7 -272.936541 -40.825281
8 -112.682824 -272.936541
9 46.256110 -112.682824
10 242.096088 46.256110
11 90.812158 242.096088
12 -9.670848 90.812158
13 220.458580 -9.670848
14 171.370460 220.458580
15 143.036560 171.370460
16 112.746949 143.036560
17 711.199741 112.746949
18 564.156542 711.199741
19 569.108879 564.156542
20 589.002952 569.108879
21 151.367943 589.002952
22 -359.048410 151.367943
23 -111.043697 -359.048410
24 58.399253 -111.043697
25 -23.927038 58.399253
26 -186.945521 -23.927038
27 -324.224801 -186.945521
28 -357.983100 -324.224801
29 -388.491600 -357.983100
30 -142.335896 -388.491600
31 -443.840207 -142.335896
32 -394.320670 -443.840207
33 -94.943265 -394.320670
34 -319.613567 -94.943265
35 313.769173 -319.613567
36 -347.605886 313.769173
37 -130.438365 -347.605886
38 -114.376260 -130.438365
39 -107.635090 -114.376260
40 809.873884 -107.635090
41 -25.656301 809.873884
42 -138.951244 -25.656301
43 267.912289 -138.951244
44 -1.380655 267.912289
45 -34.435060 -1.380655
46 7.448549 -34.435060
47 149.081788 7.448549
48 147.973387 149.081788
49 189.265235 147.973387
50 326.045505 189.265235
51 753.959887 326.045505
52 -407.334627 753.959887
53 -271.575262 -407.334627
54 -242.044121 -271.575262
55 -120.244420 -242.044121
56 -80.618803 -120.244420
57 -68.245729 -80.618803
58 429.117340 -68.245729
59 -442.619421 429.117340
> 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/765h71258899186.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> acf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/8scdj1258899186.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> pacf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Partial Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/9bmhq1258899186.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> opar <- par(mfrow = c(2,2), oma = c(0, 0, 1.1, 0))
> plot(mylm, las = 1, sub='Residual Diagnostics')
> par(opar)
> dev.off()
null device
1
> if (n > n25) {
+ postscript(file="/var/www/html/rcomp/tmp/10m7nd1258899186.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
+ plot(kp3:nmkm3,gqarr[,2], main='Goldfeld-Quandt test',ylab='2-sided p-value',xlab='breakpoint')
+ grid()
+ dev.off()
+ }
null device
1
>
> #Note: the /var/www/html/rcomp/createtable file can be downloaded at http://www.wessa.net/cretab
> load(file="/var/www/html/rcomp/createtable")
>
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a, 'Multiple Linear Regression - Estimated Regression Equation', 1, TRUE)
> a<-table.row.end(a)
> myeq <- colnames(x)[1]
> myeq <- paste(myeq, '[t] = ', sep='')
> for (i in 1:k){
+ if (mysum$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/11yq9v1258899186.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/1227xb1258899186.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/13cqty1258899186.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/14yqzc1258899186.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/15p30h1258899186.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/16j7b41258899186.tab")
+ }
>
> system("convert tmp/1nen51258899186.ps tmp/1nen51258899186.png")
> system("convert tmp/269bv1258899186.ps tmp/269bv1258899186.png")
> system("convert tmp/3hlf41258899186.ps tmp/3hlf41258899186.png")
> system("convert tmp/4qszc1258899186.ps tmp/4qszc1258899186.png")
> system("convert tmp/5vqil1258899186.ps tmp/5vqil1258899186.png")
> system("convert tmp/6a5mi1258899186.ps tmp/6a5mi1258899186.png")
> system("convert tmp/765h71258899186.ps tmp/765h71258899186.png")
> system("convert tmp/8scdj1258899186.ps tmp/8scdj1258899186.png")
> system("convert tmp/9bmhq1258899186.ps tmp/9bmhq1258899186.png")
> system("convert tmp/10m7nd1258899186.ps tmp/10m7nd1258899186.png")
>
>
> proc.time()
user system elapsed
2.407 1.587 3.286