R version 2.15.2 (2012-10-26) -- "Trick or Treat"
Copyright (C) 2012 The R Foundation for Statistical Computing
ISBN 3-900051-07-0
Platform: i686-pc-linux-gnu (32-bit)
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(-4
+ ,-16
+ ,3
+ ,0
+ ,3
+ ,-6
+ ,-18
+ ,5
+ ,-2
+ ,0
+ ,-3
+ ,-14
+ ,0
+ ,1
+ ,-1
+ ,-3
+ ,-12
+ ,-2
+ ,-2
+ ,-1
+ ,-7
+ ,-17
+ ,6
+ ,-2
+ ,-4
+ ,-9
+ ,-23
+ ,11
+ ,-2
+ ,1
+ ,-11
+ ,-28
+ ,9
+ ,-6
+ ,-1
+ ,-13
+ ,-31
+ ,17
+ ,-4
+ ,0
+ ,-11
+ ,-21
+ ,21
+ ,-2
+ ,-1
+ ,-9
+ ,-19
+ ,21
+ ,0
+ ,6
+ ,-17
+ ,-22
+ ,41
+ ,-5
+ ,0
+ ,-22
+ ,-22
+ ,57
+ ,-4
+ ,-3
+ ,-25
+ ,-25
+ ,65
+ ,-5
+ ,-3
+ ,-20
+ ,-16
+ ,68
+ ,-1
+ ,4
+ ,-24
+ ,-22
+ ,73
+ ,-2
+ ,1
+ ,-24
+ ,-21
+ ,71
+ ,-4
+ ,0
+ ,-22
+ ,-10
+ ,71
+ ,-1
+ ,-4
+ ,-19
+ ,-7
+ ,70
+ ,1
+ ,-2
+ ,-18
+ ,-5
+ ,69
+ ,1
+ ,3
+ ,-17
+ ,-4
+ ,65
+ ,-2
+ ,2
+ ,-11
+ ,7
+ ,57
+ ,1
+ ,5
+ ,-11
+ ,6
+ ,57
+ ,1
+ ,6
+ ,-12
+ ,3
+ ,57
+ ,3
+ ,6
+ ,-10
+ ,10
+ ,55
+ ,3
+ ,3
+ ,-15
+ ,0
+ ,65
+ ,1
+ ,4
+ ,-15
+ ,-2
+ ,65
+ ,1
+ ,7
+ ,-15
+ ,-1
+ ,64
+ ,0
+ ,5
+ ,-13
+ ,2
+ ,60
+ ,2
+ ,6
+ ,-8
+ ,8
+ ,43
+ ,2
+ ,1
+ ,-13
+ ,-6
+ ,47
+ ,-1
+ ,3
+ ,-9
+ ,-4
+ ,40
+ ,1
+ ,6
+ ,-7
+ ,4
+ ,31
+ ,0
+ ,0
+ ,-4
+ ,7
+ ,27
+ ,1
+ ,3
+ ,-4
+ ,3
+ ,24
+ ,1
+ ,4
+ ,-2
+ ,3
+ ,23
+ ,3
+ ,7
+ ,0
+ ,8
+ ,17
+ ,2
+ ,6
+ ,-2
+ ,3
+ ,16
+ ,0
+ ,6
+ ,-3
+ ,-3
+ ,15
+ ,0
+ ,6
+ ,1
+ ,4
+ ,8
+ ,3
+ ,6
+ ,-2
+ ,-5
+ ,5
+ ,-2
+ ,2
+ ,-1
+ ,-1
+ ,6
+ ,0
+ ,2
+ ,1
+ ,5
+ ,5
+ ,1
+ ,2
+ ,-3
+ ,0
+ ,12
+ ,-1
+ ,3
+ ,-4
+ ,-6
+ ,8
+ ,-2
+ ,-1
+ ,-9
+ ,-13
+ ,17
+ ,-1
+ ,-4
+ ,-9
+ ,-15
+ ,22
+ ,-1
+ ,4
+ ,-7
+ ,-8
+ ,24
+ ,1
+ ,5
+ ,-14
+ ,-20
+ ,36
+ ,-2
+ ,3
+ ,-12
+ ,-10
+ ,31
+ ,-5
+ ,-1
+ ,-16
+ ,-22
+ ,34
+ ,-5
+ ,-4
+ ,-20
+ ,-25
+ ,47
+ ,-6
+ ,0
+ ,-12
+ ,-10
+ ,33
+ ,-4
+ ,-1
+ ,-12
+ ,-8
+ ,35
+ ,-3
+ ,-1
+ ,-10
+ ,-9
+ ,31
+ ,-3
+ ,3
+ ,-10
+ ,-5
+ ,35
+ ,-1
+ ,2
+ ,-13
+ ,-7
+ ,39
+ ,-2
+ ,-4
+ ,-16
+ ,-11
+ ,46
+ ,-3
+ ,-3
+ ,-14
+ ,-11
+ ,40
+ ,-3
+ ,-1
+ ,-17
+ ,-16
+ ,50
+ ,-3
+ ,3
+ ,-24
+ ,-28
+ ,62
+ ,-5
+ ,-2)
+ ,dim=c(5
+ ,60)
+ ,dimnames=list(c('Consumer_confidence_indicator'
+ ,'General_economic_situation'
+ ,'Unemployment_in_Belgium'
+ ,'Financial_situation_of_households'
+ ,'Saving_capacity_of_households
')
+ ,1:60))
> y <- array(NA,dim=c(5,60),dimnames=list(c('Consumer_confidence_indicator','General_economic_situation','Unemployment_in_Belgium','Financial_situation_of_households','Saving_capacity_of_households
'),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'
> library(lattice)
> library(lmtest)
Loading required package: zoo
Attaching package: 'zoo'
The following object(s) are masked from 'package:base':
as.Date, 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
Consumer_confidence_indicator General_economic_situation
1 -4 -16
2 -6 -18
3 -3 -14
4 -3 -12
5 -7 -17
6 -9 -23
7 -11 -28
8 -13 -31
9 -11 -21
10 -9 -19
11 -17 -22
12 -22 -22
13 -25 -25
14 -20 -16
15 -24 -22
16 -24 -21
17 -22 -10
18 -19 -7
19 -18 -5
20 -17 -4
21 -11 7
22 -11 6
23 -12 3
24 -10 10
25 -15 0
26 -15 -2
27 -15 -1
28 -13 2
29 -8 8
30 -13 -6
31 -9 -4
32 -7 4
33 -4 7
34 -4 3
35 -2 3
36 0 8
37 -2 3
38 -3 -3
39 1 4
40 -2 -5
41 -1 -1
42 1 5
43 -3 0
44 -4 -6
45 -9 -13
46 -9 -15
47 -7 -8
48 -14 -20
49 -12 -10
50 -16 -22
51 -20 -25
52 -12 -10
53 -12 -8
54 -10 -9
55 -10 -5
56 -13 -7
57 -16 -11
58 -14 -11
59 -17 -16
60 -24 -28
Unemployment_in_Belgium Financial_situation_of_households
1 3 0
2 5 -2
3 0 1
4 -2 -2
5 6 -2
6 11 -2
7 9 -6
8 17 -4
9 21 -2
10 21 0
11 41 -5
12 57 -4
13 65 -5
14 68 -1
15 73 -2
16 71 -4
17 71 -1
18 70 1
19 69 1
20 65 -2
21 57 1
22 57 1
23 57 3
24 55 3
25 65 1
26 65 1
27 64 0
28 60 2
29 43 2
30 47 -1
31 40 1
32 31 0
33 27 1
34 24 1
35 23 3
36 17 2
37 16 0
38 15 0
39 8 3
40 5 -2
41 6 0
42 5 1
43 12 -1
44 8 -2
45 17 -1
46 22 -1
47 24 1
48 36 -2
49 31 -5
50 34 -5
51 47 -6
52 33 -4
53 35 -3
54 31 -3
55 35 -1
56 39 -2
57 46 -3
58 40 -3
59 50 -3
60 62 -5
Saving_capacity_of_households\r
1 3
2 0
3 -1
4 -1
5 -4
6 1
7 -1
8 0
9 -1
10 6
11 0
12 -3
13 -3
14 4
15 1
16 0
17 -4
18 -2
19 3
20 2
21 5
22 6
23 6
24 3
25 4
26 7
27 5
28 6
29 1
30 3
31 6
32 0
33 3
34 4
35 7
36 6
37 6
38 6
39 6
40 2
41 2
42 2
43 3
44 -1
45 -4
46 4
47 5
48 3
49 -1
50 -4
51 0
52 -1
53 -1
54 3
55 2
56 -4
57 -3
58 -1
59 3
60 -2
> k <- length(x[1,])
> df <- as.data.frame(x)
> (mylm <- lm(df))
Call:
lm(formula = df)
Coefficients:
(Intercept) General_economic_situation
0.1282 0.2515
Unemployment_in_Belgium Financial_situation_of_households
-0.2537 0.2683
`Saving_capacity_of_households\\r`
0.2275
> (mysum <- summary(mylm))
Call:
lm(formula = df)
Residuals:
Min 1Q Median 3Q Max
-0.58882 -0.24924 0.02032 0.19597 0.58164
Coefficients:
Estimate Std. Error t value Pr(>|t|)
(Intercept) 0.128163 0.090848 1.411 0.164
General_economic_situation 0.251519 0.006057 41.528 < 2e-16 ***
Unemployment_in_Belgium -0.253749 0.001736 -146.164 < 2e-16 ***
Financial_situation_of_households 0.268260 0.030223 8.876 3.34e-12 ***
`Saving_capacity_of_households\\r` 0.227502 0.016056 14.170 < 2e-16 ***
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
Residual standard error: 0.3022 on 55 degrees of freedom
Multiple R-squared: 0.9982, Adjusted R-squared: 0.9981
F-statistic: 7577 on 4 and 55 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,] 0.14962839 0.29925677 0.85037161
[2,] 0.17359018 0.34718036 0.82640982
[3,] 0.11410975 0.22821951 0.88589025
[4,] 0.06867674 0.13735348 0.93132326
[5,] 0.16439328 0.32878656 0.83560672
[6,] 0.10923565 0.21847131 0.89076435
[7,] 0.51144179 0.97711641 0.48855821
[8,] 0.47401934 0.94803868 0.52598066
[9,] 0.41102655 0.82205310 0.58897345
[10,] 0.56660059 0.86679882 0.43339941
[11,] 0.72078232 0.55843536 0.27921768
[12,] 0.77309379 0.45381243 0.22690621
[13,] 0.78790556 0.42418887 0.21209444
[14,] 0.73440822 0.53118356 0.26559178
[15,] 0.67331371 0.65337259 0.32668629
[16,] 0.85433878 0.29132244 0.14566122
[17,] 0.82491449 0.35017101 0.17508551
[18,] 0.78611444 0.42777111 0.21388556
[19,] 0.72173599 0.55652801 0.27826401
[20,] 0.68724157 0.62551686 0.31275843
[21,] 0.67607156 0.64785688 0.32392844
[22,] 0.60125333 0.79749334 0.39874667
[23,] 0.53485216 0.93029568 0.46514784
[24,] 0.59104995 0.81790010 0.40895005
[25,] 0.58012449 0.83975101 0.41987551
[26,] 0.49913254 0.99826508 0.50086746
[27,] 0.41843193 0.83686385 0.58156807
[28,] 0.66806050 0.66387900 0.33193950
[29,] 0.72779697 0.54440605 0.27220303
[30,] 0.67750008 0.64499984 0.32249992
[31,] 0.63242697 0.73514606 0.36757303
[32,] 0.58044530 0.83910941 0.41955470
[33,] 0.69409791 0.61180418 0.30590209
[34,] 0.71335206 0.57329588 0.28664794
[35,] 0.81738133 0.36523734 0.18261867
[36,] 0.82580455 0.34839091 0.17419545
[37,] 0.86804170 0.26391659 0.13195830
[38,] 0.86261117 0.27477765 0.13738883
[39,] 0.84536567 0.30926867 0.15463433
[40,] 0.82110644 0.35778712 0.17889356
[41,] 0.78654974 0.42690051 0.21345026
[42,] 0.68852579 0.62294843 0.31147421
[43,] 0.58153938 0.83692123 0.41846062
[44,] 0.96935492 0.06129015 0.03064508
[45,] 0.91180435 0.17639130 0.08819565
> postscript(file="/var/fisher/rcomp/tmp/1sr1z1355268344.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/fisher/rcomp/tmp/2u9vy1355268344.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> plot(mysum$resid, type='b', pch=19, main='Residuals', ylab='value of Residuals', xlab='time or index')
> grid()
> dev.off()
null device
1
> postscript(file="/var/fisher/rcomp/tmp/3welf1355268344.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> hist(mysum$resid, main='Residual Histogram', xlab='values of Residuals')
> grid()
> dev.off()
null device
1
> postscript(file="/var/fisher/rcomp/tmp/4hi0z1355268344.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> densityplot(~mysum$resid,col='black',main='Residual Density Plot', xlab='values of Residuals')
> dev.off()
null device
1
> postscript(file="/var/fisher/rcomp/tmp/58wk51355268344.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> qqnorm(mysum$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 = 60
Frequency = 1
1 2 3 4 5 6
-0.025124199 0.204438013 0.352340600 0.146585650 0.116677350 -0.242977239
7 8 9 10 11 12
0.035163128 0.055688238 0.246479391 -0.385593997 0.150254951 -0.375515242
13 14 15 16 17 18
-0.322707587 0.509314979 0.237938611 0.242944504 -0.418532083 0.581638245
19 20 21 22 23 24
-0.312659369 0.453108729 0.169124729 0.193141133 -0.588823041 -0.174444823
25 26 27 28 29 30
0.187249238 0.007779780 0.225776791 -0.307797447 0.006869816 -0.107097279
31 32 33 34 35 36
0.394595790 -0.268020378 0.011660945 0.028986528 0.556210601 0.271885945
37 38 39 40 41 42
-0.187749462 0.067613616 -0.274039961 0.479690767 0.190844845 0.159723786
43 44 45 46 47 48
-0.497422336 0.174963067 -0.366419041 -0.414655109 -0.431810365 -0.108814185
49 50 51 52 53 54
-0.177956265 0.284021408 -0.304435282 0.061281530 -0.202518015 0.123995816
55 56 57 58 59 60
-0.176101009 -0.024794205 -0.201719090 -0.179217285 -0.294143559 0.443099326
> postscript(file="/var/fisher/rcomp/tmp/6bczr1355268344.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 = 60
Frequency = 1
lag(myerror, k = 1) myerror
0 -0.025124199 NA
1 0.204438013 -0.025124199
2 0.352340600 0.204438013
3 0.146585650 0.352340600
4 0.116677350 0.146585650
5 -0.242977239 0.116677350
6 0.035163128 -0.242977239
7 0.055688238 0.035163128
8 0.246479391 0.055688238
9 -0.385593997 0.246479391
10 0.150254951 -0.385593997
11 -0.375515242 0.150254951
12 -0.322707587 -0.375515242
13 0.509314979 -0.322707587
14 0.237938611 0.509314979
15 0.242944504 0.237938611
16 -0.418532083 0.242944504
17 0.581638245 -0.418532083
18 -0.312659369 0.581638245
19 0.453108729 -0.312659369
20 0.169124729 0.453108729
21 0.193141133 0.169124729
22 -0.588823041 0.193141133
23 -0.174444823 -0.588823041
24 0.187249238 -0.174444823
25 0.007779780 0.187249238
26 0.225776791 0.007779780
27 -0.307797447 0.225776791
28 0.006869816 -0.307797447
29 -0.107097279 0.006869816
30 0.394595790 -0.107097279
31 -0.268020378 0.394595790
32 0.011660945 -0.268020378
33 0.028986528 0.011660945
34 0.556210601 0.028986528
35 0.271885945 0.556210601
36 -0.187749462 0.271885945
37 0.067613616 -0.187749462
38 -0.274039961 0.067613616
39 0.479690767 -0.274039961
40 0.190844845 0.479690767
41 0.159723786 0.190844845
42 -0.497422336 0.159723786
43 0.174963067 -0.497422336
44 -0.366419041 0.174963067
45 -0.414655109 -0.366419041
46 -0.431810365 -0.414655109
47 -0.108814185 -0.431810365
48 -0.177956265 -0.108814185
49 0.284021408 -0.177956265
50 -0.304435282 0.284021408
51 0.061281530 -0.304435282
52 -0.202518015 0.061281530
53 0.123995816 -0.202518015
54 -0.176101009 0.123995816
55 -0.024794205 -0.176101009
56 -0.201719090 -0.024794205
57 -0.179217285 -0.201719090
58 -0.294143559 -0.179217285
59 0.443099326 -0.294143559
60 NA 0.443099326
> dum1 <- dum[2:length(myerror),]
> dum1
lag(myerror, k = 1) myerror
[1,] 0.204438013 -0.025124199
[2,] 0.352340600 0.204438013
[3,] 0.146585650 0.352340600
[4,] 0.116677350 0.146585650
[5,] -0.242977239 0.116677350
[6,] 0.035163128 -0.242977239
[7,] 0.055688238 0.035163128
[8,] 0.246479391 0.055688238
[9,] -0.385593997 0.246479391
[10,] 0.150254951 -0.385593997
[11,] -0.375515242 0.150254951
[12,] -0.322707587 -0.375515242
[13,] 0.509314979 -0.322707587
[14,] 0.237938611 0.509314979
[15,] 0.242944504 0.237938611
[16,] -0.418532083 0.242944504
[17,] 0.581638245 -0.418532083
[18,] -0.312659369 0.581638245
[19,] 0.453108729 -0.312659369
[20,] 0.169124729 0.453108729
[21,] 0.193141133 0.169124729
[22,] -0.588823041 0.193141133
[23,] -0.174444823 -0.588823041
[24,] 0.187249238 -0.174444823
[25,] 0.007779780 0.187249238
[26,] 0.225776791 0.007779780
[27,] -0.307797447 0.225776791
[28,] 0.006869816 -0.307797447
[29,] -0.107097279 0.006869816
[30,] 0.394595790 -0.107097279
[31,] -0.268020378 0.394595790
[32,] 0.011660945 -0.268020378
[33,] 0.028986528 0.011660945
[34,] 0.556210601 0.028986528
[35,] 0.271885945 0.556210601
[36,] -0.187749462 0.271885945
[37,] 0.067613616 -0.187749462
[38,] -0.274039961 0.067613616
[39,] 0.479690767 -0.274039961
[40,] 0.190844845 0.479690767
[41,] 0.159723786 0.190844845
[42,] -0.497422336 0.159723786
[43,] 0.174963067 -0.497422336
[44,] -0.366419041 0.174963067
[45,] -0.414655109 -0.366419041
[46,] -0.431810365 -0.414655109
[47,] -0.108814185 -0.431810365
[48,] -0.177956265 -0.108814185
[49,] 0.284021408 -0.177956265
[50,] -0.304435282 0.284021408
[51,] 0.061281530 -0.304435282
[52,] -0.202518015 0.061281530
[53,] 0.123995816 -0.202518015
[54,] -0.176101009 0.123995816
[55,] -0.024794205 -0.176101009
[56,] -0.201719090 -0.024794205
[57,] -0.179217285 -0.201719090
[58,] -0.294143559 -0.179217285
[59,] 0.443099326 -0.294143559
> z <- as.data.frame(dum1)
> z
lag(myerror, k = 1) myerror
1 0.204438013 -0.025124199
2 0.352340600 0.204438013
3 0.146585650 0.352340600
4 0.116677350 0.146585650
5 -0.242977239 0.116677350
6 0.035163128 -0.242977239
7 0.055688238 0.035163128
8 0.246479391 0.055688238
9 -0.385593997 0.246479391
10 0.150254951 -0.385593997
11 -0.375515242 0.150254951
12 -0.322707587 -0.375515242
13 0.509314979 -0.322707587
14 0.237938611 0.509314979
15 0.242944504 0.237938611
16 -0.418532083 0.242944504
17 0.581638245 -0.418532083
18 -0.312659369 0.581638245
19 0.453108729 -0.312659369
20 0.169124729 0.453108729
21 0.193141133 0.169124729
22 -0.588823041 0.193141133
23 -0.174444823 -0.588823041
24 0.187249238 -0.174444823
25 0.007779780 0.187249238
26 0.225776791 0.007779780
27 -0.307797447 0.225776791
28 0.006869816 -0.307797447
29 -0.107097279 0.006869816
30 0.394595790 -0.107097279
31 -0.268020378 0.394595790
32 0.011660945 -0.268020378
33 0.028986528 0.011660945
34 0.556210601 0.028986528
35 0.271885945 0.556210601
36 -0.187749462 0.271885945
37 0.067613616 -0.187749462
38 -0.274039961 0.067613616
39 0.479690767 -0.274039961
40 0.190844845 0.479690767
41 0.159723786 0.190844845
42 -0.497422336 0.159723786
43 0.174963067 -0.497422336
44 -0.366419041 0.174963067
45 -0.414655109 -0.366419041
46 -0.431810365 -0.414655109
47 -0.108814185 -0.431810365
48 -0.177956265 -0.108814185
49 0.284021408 -0.177956265
50 -0.304435282 0.284021408
51 0.061281530 -0.304435282
52 -0.202518015 0.061281530
53 0.123995816 -0.202518015
54 -0.176101009 0.123995816
55 -0.024794205 -0.176101009
56 -0.201719090 -0.024794205
57 -0.179217285 -0.201719090
58 -0.294143559 -0.179217285
59 0.443099326 -0.294143559
> 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/fisher/rcomp/tmp/7ego21355268344.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/fisher/rcomp/tmp/8wum11355268344.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/fisher/rcomp/tmp/9ld521355268344.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/fisher/rcomp/tmp/10o5ce1355268344.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/fisher/rcomp/createtable file can be downloaded at http://www.wessa.net/cretab
> load(file="/var/fisher/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$coefficients)[i] != 't') myeq <- paste(myeq, '[t]', sep='')
+ }
+ }
> myeq <- paste(myeq, ' + e[t]')
> a<-table.row.start(a)
> a<-table.element(a, myeq)
> a<-table.row.end(a)
> a<-table.end(a)
> table.save(a,file="/var/fisher/rcomp/tmp/11qdyz1355268344.tab")
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a,hyperlink('http://www.xycoon.com/ols1.htm','Multiple Linear Regression - Ordinary Least Squares',''), 6, TRUE)
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a,'Variable',header=TRUE)
> a<-table.element(a,'Parameter',header=TRUE)
> a<-table.element(a,'S.D.',header=TRUE)
> a<-table.element(a,'T-STAT
H0: parameter = 0',header=TRUE)
> a<-table.element(a,'2-tail p-value',header=TRUE)
> a<-table.element(a,'1-tail p-value',header=TRUE)
> a<-table.row.end(a)
> for (i in 1:k){
+ a<-table.row.start(a)
+ a<-table.element(a,rownames(mysum$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$coefficients[i,4]/2,6))
+ a<-table.row.end(a)
+ }
> a<-table.end(a)
> table.save(a,file="/var/fisher/rcomp/tmp/120wf51355268344.tab")
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a, 'Multiple Linear Regression - Regression Statistics', 2, TRUE)
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a, 'Multiple R',1,TRUE)
> a<-table.element(a, sqrt(mysum$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$sigma)
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a, 'Sum Squared Residuals',1,TRUE)
> a<-table.element(a, sum(myerror*myerror))
> a<-table.row.end(a)
> a<-table.end(a)
> table.save(a,file="/var/fisher/rcomp/tmp/13mwc41355268344.tab")
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a, 'Multiple Linear Regression - Actuals, Interpolation, and Residuals', 4, TRUE)
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a, 'Time or Index', 1, TRUE)
> a<-table.element(a, 'Actuals', 1, TRUE)
> a<-table.element(a, 'Interpolation
Forecast', 1, TRUE)
> a<-table.element(a, 'Residuals
Prediction Error', 1, TRUE)
> a<-table.row.end(a)
> for (i in 1:n) {
+ a<-table.row.start(a)
+ a<-table.element(a,i, 1, TRUE)
+ a<-table.element(a,x[i])
+ a<-table.element(a,x[i]-mysum$resid[i])
+ a<-table.element(a,mysum$resid[i])
+ a<-table.row.end(a)
+ }
> a<-table.end(a)
> table.save(a,file="/var/fisher/rcomp/tmp/14dqqr1355268344.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/fisher/rcomp/tmp/15mgv91355268344.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/fisher/rcomp/tmp/16jng31355268344.tab")
+ }
>
> try(system("convert tmp/1sr1z1355268344.ps tmp/1sr1z1355268344.png",intern=TRUE))
character(0)
> try(system("convert tmp/2u9vy1355268344.ps tmp/2u9vy1355268344.png",intern=TRUE))
character(0)
> try(system("convert tmp/3welf1355268344.ps tmp/3welf1355268344.png",intern=TRUE))
character(0)
> try(system("convert tmp/4hi0z1355268344.ps tmp/4hi0z1355268344.png",intern=TRUE))
character(0)
> try(system("convert tmp/58wk51355268344.ps tmp/58wk51355268344.png",intern=TRUE))
character(0)
> try(system("convert tmp/6bczr1355268344.ps tmp/6bczr1355268344.png",intern=TRUE))
character(0)
> try(system("convert tmp/7ego21355268344.ps tmp/7ego21355268344.png",intern=TRUE))
character(0)
> try(system("convert tmp/8wum11355268344.ps tmp/8wum11355268344.png",intern=TRUE))
character(0)
> try(system("convert tmp/9ld521355268344.ps tmp/9ld521355268344.png",intern=TRUE))
character(0)
> try(system("convert tmp/10o5ce1355268344.ps tmp/10o5ce1355268344.png",intern=TRUE))
character(0)
>
>
> proc.time()
user system elapsed
6.051 1.571 7.673