R version 2.13.0 (2011-04-13)
Copyright (C) 2011 The R Foundation for Statistical Computing
ISBN 3-900051-07-0
Platform: i486-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.
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(7,14,5,18,5,11,8,16,6,18,5,14,6,14,5,15,4,15,5,19,6,16,7,18,6,17,7,16,5,11,7,14,7,12,4,9,6,14,5,15,5,16,6,17,5,15,5,17,7,16,7,12,7,11,5,15,5,15,4,17,4,16,7,12,5,15,6,16,4,15,6,12,6,11,8,14,7,15,6,11,5,15,5,16,4,15,6,12,6,17,7,13,5,15,8,15,8,14,5,14,6,13,4,7,5,17,5,13,5,15,5,14,6,13,6,16,5,12,6,14,5,17,6,16,4,15,5,16,9,10,6,15,6,11,5,13,5,18,7,14,5,14,7,14,6,14,6,12,9,14,7,15,6,15,5,15,5,13,6,17,7,19,5,15,6,15,7,16,7,11,6,15,8,15,5,14,6,16,4,16,6,16,7,13,6,12,8,9,4,13,5,13,6,14,7,19,7,13,6,12,6,13),dim=c(2,101),dimnames=list(c('Leeftijd','Happiness'),1:101))
> y <- array(NA,dim=c(2,101),dimnames=list(c('Leeftijd','Happiness'),1:101))
> 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
> 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
Happiness Leeftijd
1 14 7
2 18 5
3 11 5
4 16 8
5 18 6
6 14 5
7 14 6
8 15 5
9 15 4
10 19 5
11 16 6
12 18 7
13 17 6
14 16 7
15 11 5
16 14 7
17 12 7
18 9 4
19 14 6
20 15 5
21 16 5
22 17 6
23 15 5
24 17 5
25 16 7
26 12 7
27 11 7
28 15 5
29 15 5
30 17 4
31 16 4
32 12 7
33 15 5
34 16 6
35 15 4
36 12 6
37 11 6
38 14 8
39 15 7
40 11 6
41 15 5
42 16 5
43 15 4
44 12 6
45 17 6
46 13 7
47 15 5
48 15 8
49 14 8
50 14 5
51 13 6
52 7 4
53 17 5
54 13 5
55 15 5
56 14 5
57 13 6
58 16 6
59 12 5
60 14 6
61 17 5
62 16 6
63 15 4
64 16 5
65 10 9
66 15 6
67 11 6
68 13 5
69 18 5
70 14 7
71 14 5
72 14 7
73 14 6
74 12 6
75 14 9
76 15 7
77 15 6
78 15 5
79 13 5
80 17 6
81 19 7
82 15 5
83 15 6
84 16 7
85 11 7
86 15 6
87 15 8
88 14 5
89 16 6
90 16 4
91 16 6
92 13 7
93 12 6
94 9 8
95 13 4
96 13 5
97 14 6
98 19 7
99 13 7
100 12 6
101 13 6
> k <- length(x[1,])
> df <- as.data.frame(x)
> (mylm <- lm(df))
Call:
lm(formula = df)
Coefficients:
(Intercept) Leeftijd
15.4702 -0.1883
> (mysum <- summary(mylm))
Call:
lm(formula = df)
Residuals:
Min 1Q Median 3Q Max
-7.7169 -1.3402 0.2831 1.4714 4.8481
Coefficients:
Estimate Std. Error t value Pr(>|t|)
(Intercept) 15.4702 1.1688 13.236 <2e-16 ***
Leeftijd -0.1883 0.1957 -0.962 0.338
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
Residual standard error: 2.249 on 99 degrees of freedom
Multiple R-squared: 0.009267, Adjusted R-squared: -0.0007401
F-statistic: 0.926 on 1 and 99 DF, p-value: 0.3382
> 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,] 0.9255717 0.1488566 0.07442832
[2,] 0.8671037 0.2657926 0.13289630
[3,] 0.7966740 0.4066519 0.20332597
[4,] 0.6995560 0.6008880 0.30044399
[5,] 0.5953704 0.8092593 0.40462965
[6,] 0.7624735 0.4750530 0.23752650
[7,] 0.6868477 0.6263047 0.31315233
[8,] 0.6969021 0.6061958 0.30309789
[9,] 0.6490258 0.7019485 0.35097423
[10,] 0.5726203 0.8547594 0.42737971
[11,] 0.7535094 0.4929812 0.24649061
[12,] 0.7252769 0.5494463 0.27472313
[13,] 0.7887356 0.4225288 0.21126441
[14,] 0.9412584 0.1174831 0.05874157
[15,] 0.9194696 0.1610608 0.08053039
[16,] 0.8913887 0.2172225 0.10861126
[17,] 0.8719003 0.2561993 0.12809966
[18,] 0.8680487 0.2639026 0.13195130
[19,] 0.8293554 0.3412891 0.17064456
[20,] 0.8334276 0.3331447 0.16657237
[21,] 0.8013569 0.3972862 0.19864308
[22,] 0.8378123 0.3243754 0.16218772
[23,] 0.8956884 0.2086231 0.10431156
[24,] 0.8647147 0.2705706 0.13528532
[25,] 0.8282621 0.3434759 0.17173794
[26,] 0.8283121 0.3433758 0.17168791
[27,] 0.7981952 0.4036095 0.20180475
[28,] 0.8064988 0.3870025 0.19350123
[29,] 0.7630173 0.4739654 0.23698271
[30,] 0.7344012 0.5311976 0.26559880
[31,] 0.6834158 0.6331684 0.31658421
[32,] 0.6971773 0.6056454 0.30282272
[33,] 0.7624142 0.4751716 0.23758579
[34,] 0.7145645 0.5708711 0.28543555
[35,] 0.6680746 0.6638507 0.33192535
[36,] 0.7316705 0.5366589 0.26832947
[37,] 0.6830981 0.6338037 0.31690187
[38,] 0.6506982 0.6986036 0.34930181
[39,] 0.5965159 0.8069682 0.40348410
[40,] 0.6021450 0.7957099 0.39785497
[41,] 0.6203818 0.7592364 0.37961822
[42,] 0.5799469 0.8401062 0.42005308
[43,] 0.5255384 0.9489232 0.47446160
[44,] 0.4788600 0.9577199 0.52114004
[45,] 0.4218559 0.8437119 0.57814407
[46,] 0.3698457 0.7396914 0.63015430
[47,] 0.3354702 0.6709404 0.66452982
[48,] 0.8658191 0.2683617 0.13418087
[49,] 0.8711127 0.2577746 0.12888731
[50,] 0.8547374 0.2905253 0.14526263
[51,] 0.8202204 0.3595592 0.17977960
[52,] 0.7822590 0.4354819 0.21774097
[53,] 0.7535788 0.4928425 0.24642123
[54,] 0.7317074 0.5365852 0.26829260
[55,] 0.7485408 0.5029183 0.25145917
[56,] 0.7003856 0.5992287 0.29961435
[57,] 0.7064510 0.5870980 0.29354899
[58,] 0.6828469 0.6343062 0.31715312
[59,] 0.6284960 0.7430080 0.37150402
[60,] 0.5937779 0.8124441 0.40622206
[61,] 0.6868060 0.6263880 0.31319400
[62,] 0.6361661 0.7276678 0.36383391
[63,] 0.7008434 0.5983132 0.29915658
[64,] 0.6711092 0.6577815 0.32889077
[65,] 0.7489431 0.5021138 0.25105688
[66,] 0.6957265 0.6085471 0.30427353
[67,] 0.6394555 0.7210891 0.36054454
[68,] 0.5775604 0.8448791 0.42243956
[69,] 0.5139643 0.9720713 0.48603565
[70,] 0.5173016 0.9653969 0.48269843
[71,] 0.4511316 0.9022632 0.54886842
[72,] 0.3925284 0.7850569 0.60747156
[73,] 0.3335603 0.6671206 0.66643970
[74,] 0.2763118 0.5526237 0.72368817
[75,] 0.2424602 0.4849204 0.75753982
[76,] 0.2581920 0.5163840 0.74180802
[77,] 0.5119958 0.9760085 0.48800424
[78,] 0.4421277 0.8842554 0.55787229
[79,] 0.3801380 0.7602760 0.61986200
[80,] 0.3821851 0.7643702 0.61781489
[81,] 0.4084037 0.8168074 0.59159632
[82,] 0.3441247 0.6882494 0.65587532
[83,] 0.3124282 0.6248565 0.68757175
[84,] 0.2398887 0.4797775 0.76011126
[85,] 0.2298711 0.4597422 0.77012888
[86,] 0.1938488 0.3876975 0.80615125
[87,] 0.2035669 0.4071337 0.79643314
[88,] 0.1392288 0.2784577 0.86077116
[89,] 0.1004824 0.2009649 0.89951757
[90,] 0.4023724 0.8047449 0.59762757
[91,] 0.3352267 0.6704535 0.66477327
[92,] 0.2668300 0.5336600 0.73316999
> postscript(file="/var/wessaorg/rcomp/tmp/1p8wm1321995465.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$resid)
> grid()
> dev.off()
null device
1
> postscript(file="/var/wessaorg/rcomp/tmp/20nh61321995465.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> plot(mysum$resid, type='b', pch=19, main='Residuals', ylab='value of Residuals', xlab='time or index')
> grid()
> dev.off()
null device
1
> postscript(file="/var/wessaorg/rcomp/tmp/3zdg21321995465.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> hist(mysum$resid, main='Residual Histogram', xlab='values of Residuals')
> grid()
> dev.off()
null device
1
> postscript(file="/var/wessaorg/rcomp/tmp/4149j1321995465.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> densityplot(~mysum$resid,col='black',main='Residual Density Plot', xlab='values of Residuals')
> dev.off()
null device
1
> postscript(file="/var/wessaorg/rcomp/tmp/5sors1321995465.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 = 101
Frequency = 1
1 2 3 4 5 6
-0.15189684 3.47143500 -3.52856500 2.03643725 3.65976908 -0.52856500
7 8 9 10 11 12
-0.34023092 0.47143500 0.28310091 4.47143500 1.65976908 3.84810316
13 14 15 16 17 18
2.65976908 1.84810316 -3.52856500 -0.15189684 -2.15189684 -5.71689909
19 20 21 22 23 24
-0.34023092 0.47143500 1.47143500 2.65976908 0.47143500 2.47143500
25 26 27 28 29 30
1.84810316 -2.15189684 -3.15189684 0.47143500 0.47143500 2.28310091
31 32 33 34 35 36
1.28310091 -2.15189684 0.47143500 1.65976908 0.28310091 -2.34023092
37 38 39 40 41 42
-3.34023092 0.03643725 0.84810316 -3.34023092 0.47143500 1.47143500
43 44 45 46 47 48
0.28310091 -2.34023092 2.65976908 -1.15189684 0.47143500 1.03643725
49 50 51 52 53 54
0.03643725 -0.52856500 -1.34023092 -7.71689909 2.47143500 -1.52856500
55 56 57 58 59 60
0.47143500 -0.52856500 -1.34023092 1.65976908 -2.52856500 -0.34023092
61 62 63 64 65 66
2.47143500 1.65976908 0.28310091 1.47143500 -3.77522867 0.65976908
67 68 69 70 71 72
-3.34023092 -1.52856500 3.47143500 -0.15189684 -0.52856500 -0.15189684
73 74 75 76 77 78
-0.34023092 -2.34023092 0.22477133 0.84810316 0.65976908 0.47143500
79 80 81 82 83 84
-1.52856500 2.65976908 4.84810316 0.47143500 0.65976908 1.84810316
85 86 87 88 89 90
-3.15189684 0.65976908 1.03643725 -0.52856500 1.65976908 1.28310091
91 92 93 94 95 96
1.65976908 -1.15189684 -2.34023092 -4.96356275 -1.71689909 -1.52856500
97 98 99 100 101
-0.34023092 4.84810316 -1.15189684 -2.34023092 -1.34023092
> postscript(file="/var/wessaorg/rcomp/tmp/6b81l1321995465.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 = 101
Frequency = 1
lag(myerror, k = 1) myerror
0 -0.15189684 NA
1 3.47143500 -0.15189684
2 -3.52856500 3.47143500
3 2.03643725 -3.52856500
4 3.65976908 2.03643725
5 -0.52856500 3.65976908
6 -0.34023092 -0.52856500
7 0.47143500 -0.34023092
8 0.28310091 0.47143500
9 4.47143500 0.28310091
10 1.65976908 4.47143500
11 3.84810316 1.65976908
12 2.65976908 3.84810316
13 1.84810316 2.65976908
14 -3.52856500 1.84810316
15 -0.15189684 -3.52856500
16 -2.15189684 -0.15189684
17 -5.71689909 -2.15189684
18 -0.34023092 -5.71689909
19 0.47143500 -0.34023092
20 1.47143500 0.47143500
21 2.65976908 1.47143500
22 0.47143500 2.65976908
23 2.47143500 0.47143500
24 1.84810316 2.47143500
25 -2.15189684 1.84810316
26 -3.15189684 -2.15189684
27 0.47143500 -3.15189684
28 0.47143500 0.47143500
29 2.28310091 0.47143500
30 1.28310091 2.28310091
31 -2.15189684 1.28310091
32 0.47143500 -2.15189684
33 1.65976908 0.47143500
34 0.28310091 1.65976908
35 -2.34023092 0.28310091
36 -3.34023092 -2.34023092
37 0.03643725 -3.34023092
38 0.84810316 0.03643725
39 -3.34023092 0.84810316
40 0.47143500 -3.34023092
41 1.47143500 0.47143500
42 0.28310091 1.47143500
43 -2.34023092 0.28310091
44 2.65976908 -2.34023092
45 -1.15189684 2.65976908
46 0.47143500 -1.15189684
47 1.03643725 0.47143500
48 0.03643725 1.03643725
49 -0.52856500 0.03643725
50 -1.34023092 -0.52856500
51 -7.71689909 -1.34023092
52 2.47143500 -7.71689909
53 -1.52856500 2.47143500
54 0.47143500 -1.52856500
55 -0.52856500 0.47143500
56 -1.34023092 -0.52856500
57 1.65976908 -1.34023092
58 -2.52856500 1.65976908
59 -0.34023092 -2.52856500
60 2.47143500 -0.34023092
61 1.65976908 2.47143500
62 0.28310091 1.65976908
63 1.47143500 0.28310091
64 -3.77522867 1.47143500
65 0.65976908 -3.77522867
66 -3.34023092 0.65976908
67 -1.52856500 -3.34023092
68 3.47143500 -1.52856500
69 -0.15189684 3.47143500
70 -0.52856500 -0.15189684
71 -0.15189684 -0.52856500
72 -0.34023092 -0.15189684
73 -2.34023092 -0.34023092
74 0.22477133 -2.34023092
75 0.84810316 0.22477133
76 0.65976908 0.84810316
77 0.47143500 0.65976908
78 -1.52856500 0.47143500
79 2.65976908 -1.52856500
80 4.84810316 2.65976908
81 0.47143500 4.84810316
82 0.65976908 0.47143500
83 1.84810316 0.65976908
84 -3.15189684 1.84810316
85 0.65976908 -3.15189684
86 1.03643725 0.65976908
87 -0.52856500 1.03643725
88 1.65976908 -0.52856500
89 1.28310091 1.65976908
90 1.65976908 1.28310091
91 -1.15189684 1.65976908
92 -2.34023092 -1.15189684
93 -4.96356275 -2.34023092
94 -1.71689909 -4.96356275
95 -1.52856500 -1.71689909
96 -0.34023092 -1.52856500
97 4.84810316 -0.34023092
98 -1.15189684 4.84810316
99 -2.34023092 -1.15189684
100 -1.34023092 -2.34023092
101 NA -1.34023092
> dum1 <- dum[2:length(myerror),]
> dum1
lag(myerror, k = 1) myerror
[1,] 3.47143500 -0.15189684
[2,] -3.52856500 3.47143500
[3,] 2.03643725 -3.52856500
[4,] 3.65976908 2.03643725
[5,] -0.52856500 3.65976908
[6,] -0.34023092 -0.52856500
[7,] 0.47143500 -0.34023092
[8,] 0.28310091 0.47143500
[9,] 4.47143500 0.28310091
[10,] 1.65976908 4.47143500
[11,] 3.84810316 1.65976908
[12,] 2.65976908 3.84810316
[13,] 1.84810316 2.65976908
[14,] -3.52856500 1.84810316
[15,] -0.15189684 -3.52856500
[16,] -2.15189684 -0.15189684
[17,] -5.71689909 -2.15189684
[18,] -0.34023092 -5.71689909
[19,] 0.47143500 -0.34023092
[20,] 1.47143500 0.47143500
[21,] 2.65976908 1.47143500
[22,] 0.47143500 2.65976908
[23,] 2.47143500 0.47143500
[24,] 1.84810316 2.47143500
[25,] -2.15189684 1.84810316
[26,] -3.15189684 -2.15189684
[27,] 0.47143500 -3.15189684
[28,] 0.47143500 0.47143500
[29,] 2.28310091 0.47143500
[30,] 1.28310091 2.28310091
[31,] -2.15189684 1.28310091
[32,] 0.47143500 -2.15189684
[33,] 1.65976908 0.47143500
[34,] 0.28310091 1.65976908
[35,] -2.34023092 0.28310091
[36,] -3.34023092 -2.34023092
[37,] 0.03643725 -3.34023092
[38,] 0.84810316 0.03643725
[39,] -3.34023092 0.84810316
[40,] 0.47143500 -3.34023092
[41,] 1.47143500 0.47143500
[42,] 0.28310091 1.47143500
[43,] -2.34023092 0.28310091
[44,] 2.65976908 -2.34023092
[45,] -1.15189684 2.65976908
[46,] 0.47143500 -1.15189684
[47,] 1.03643725 0.47143500
[48,] 0.03643725 1.03643725
[49,] -0.52856500 0.03643725
[50,] -1.34023092 -0.52856500
[51,] -7.71689909 -1.34023092
[52,] 2.47143500 -7.71689909
[53,] -1.52856500 2.47143500
[54,] 0.47143500 -1.52856500
[55,] -0.52856500 0.47143500
[56,] -1.34023092 -0.52856500
[57,] 1.65976908 -1.34023092
[58,] -2.52856500 1.65976908
[59,] -0.34023092 -2.52856500
[60,] 2.47143500 -0.34023092
[61,] 1.65976908 2.47143500
[62,] 0.28310091 1.65976908
[63,] 1.47143500 0.28310091
[64,] -3.77522867 1.47143500
[65,] 0.65976908 -3.77522867
[66,] -3.34023092 0.65976908
[67,] -1.52856500 -3.34023092
[68,] 3.47143500 -1.52856500
[69,] -0.15189684 3.47143500
[70,] -0.52856500 -0.15189684
[71,] -0.15189684 -0.52856500
[72,] -0.34023092 -0.15189684
[73,] -2.34023092 -0.34023092
[74,] 0.22477133 -2.34023092
[75,] 0.84810316 0.22477133
[76,] 0.65976908 0.84810316
[77,] 0.47143500 0.65976908
[78,] -1.52856500 0.47143500
[79,] 2.65976908 -1.52856500
[80,] 4.84810316 2.65976908
[81,] 0.47143500 4.84810316
[82,] 0.65976908 0.47143500
[83,] 1.84810316 0.65976908
[84,] -3.15189684 1.84810316
[85,] 0.65976908 -3.15189684
[86,] 1.03643725 0.65976908
[87,] -0.52856500 1.03643725
[88,] 1.65976908 -0.52856500
[89,] 1.28310091 1.65976908
[90,] 1.65976908 1.28310091
[91,] -1.15189684 1.65976908
[92,] -2.34023092 -1.15189684
[93,] -4.96356275 -2.34023092
[94,] -1.71689909 -4.96356275
[95,] -1.52856500 -1.71689909
[96,] -0.34023092 -1.52856500
[97,] 4.84810316 -0.34023092
[98,] -1.15189684 4.84810316
[99,] -2.34023092 -1.15189684
[100,] -1.34023092 -2.34023092
> z <- as.data.frame(dum1)
> z
lag(myerror, k = 1) myerror
1 3.47143500 -0.15189684
2 -3.52856500 3.47143500
3 2.03643725 -3.52856500
4 3.65976908 2.03643725
5 -0.52856500 3.65976908
6 -0.34023092 -0.52856500
7 0.47143500 -0.34023092
8 0.28310091 0.47143500
9 4.47143500 0.28310091
10 1.65976908 4.47143500
11 3.84810316 1.65976908
12 2.65976908 3.84810316
13 1.84810316 2.65976908
14 -3.52856500 1.84810316
15 -0.15189684 -3.52856500
16 -2.15189684 -0.15189684
17 -5.71689909 -2.15189684
18 -0.34023092 -5.71689909
19 0.47143500 -0.34023092
20 1.47143500 0.47143500
21 2.65976908 1.47143500
22 0.47143500 2.65976908
23 2.47143500 0.47143500
24 1.84810316 2.47143500
25 -2.15189684 1.84810316
26 -3.15189684 -2.15189684
27 0.47143500 -3.15189684
28 0.47143500 0.47143500
29 2.28310091 0.47143500
30 1.28310091 2.28310091
31 -2.15189684 1.28310091
32 0.47143500 -2.15189684
33 1.65976908 0.47143500
34 0.28310091 1.65976908
35 -2.34023092 0.28310091
36 -3.34023092 -2.34023092
37 0.03643725 -3.34023092
38 0.84810316 0.03643725
39 -3.34023092 0.84810316
40 0.47143500 -3.34023092
41 1.47143500 0.47143500
42 0.28310091 1.47143500
43 -2.34023092 0.28310091
44 2.65976908 -2.34023092
45 -1.15189684 2.65976908
46 0.47143500 -1.15189684
47 1.03643725 0.47143500
48 0.03643725 1.03643725
49 -0.52856500 0.03643725
50 -1.34023092 -0.52856500
51 -7.71689909 -1.34023092
52 2.47143500 -7.71689909
53 -1.52856500 2.47143500
54 0.47143500 -1.52856500
55 -0.52856500 0.47143500
56 -1.34023092 -0.52856500
57 1.65976908 -1.34023092
58 -2.52856500 1.65976908
59 -0.34023092 -2.52856500
60 2.47143500 -0.34023092
61 1.65976908 2.47143500
62 0.28310091 1.65976908
63 1.47143500 0.28310091
64 -3.77522867 1.47143500
65 0.65976908 -3.77522867
66 -3.34023092 0.65976908
67 -1.52856500 -3.34023092
68 3.47143500 -1.52856500
69 -0.15189684 3.47143500
70 -0.52856500 -0.15189684
71 -0.15189684 -0.52856500
72 -0.34023092 -0.15189684
73 -2.34023092 -0.34023092
74 0.22477133 -2.34023092
75 0.84810316 0.22477133
76 0.65976908 0.84810316
77 0.47143500 0.65976908
78 -1.52856500 0.47143500
79 2.65976908 -1.52856500
80 4.84810316 2.65976908
81 0.47143500 4.84810316
82 0.65976908 0.47143500
83 1.84810316 0.65976908
84 -3.15189684 1.84810316
85 0.65976908 -3.15189684
86 1.03643725 0.65976908
87 -0.52856500 1.03643725
88 1.65976908 -0.52856500
89 1.28310091 1.65976908
90 1.65976908 1.28310091
91 -1.15189684 1.65976908
92 -2.34023092 -1.15189684
93 -4.96356275 -2.34023092
94 -1.71689909 -4.96356275
95 -1.52856500 -1.71689909
96 -0.34023092 -1.52856500
97 4.84810316 -0.34023092
98 -1.15189684 4.84810316
99 -2.34023092 -1.15189684
100 -1.34023092 -2.34023092
> 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/wessaorg/rcomp/tmp/77glc1321995465.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> acf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/wessaorg/rcomp/tmp/8ip181321995465.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> pacf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Partial Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/wessaorg/rcomp/tmp/9yyvz1321995465.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> opar <- par(mfrow = c(2,2), oma = c(0, 0, 1.1, 0))
> plot(mylm, las = 1, sub='Residual Diagnostics')
> par(opar)
> dev.off()
null device
1
> if (n > n25) {
+ postscript(file="/var/wessaorg/rcomp/tmp/10ld6l1321995465.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
+ plot(kp3:nmkm3,gqarr[,2], main='Goldfeld-Quandt test',ylab='2-sided p-value',xlab='breakpoint')
+ grid()
+ dev.off()
+ }
null device
1
>
> #Note: the /var/wessaorg/rcomp/createtable file can be downloaded at http://www.wessa.net/cretab
> load(file="/var/wessaorg/rcomp/createtable")
>
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a, 'Multiple Linear Regression - Estimated Regression Equation', 1, TRUE)
> a<-table.row.end(a)
> myeq <- colnames(x)[1]
> myeq <- paste(myeq, '[t] = ', sep='')
> for (i in 1:k){
+ if (mysum$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/wessaorg/rcomp/tmp/11qmnr1321995465.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/wessaorg/rcomp/tmp/12rxbk1321995466.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/wessaorg/rcomp/tmp/13l3cx1321995466.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/wessaorg/rcomp/tmp/14bejj1321995466.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/wessaorg/rcomp/tmp/15u4vd1321995466.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/wessaorg/rcomp/tmp/16uxmt1321995466.tab")
+ }
>
> try(system("convert tmp/1p8wm1321995465.ps tmp/1p8wm1321995465.png",intern=TRUE))
character(0)
> try(system("convert tmp/20nh61321995465.ps tmp/20nh61321995465.png",intern=TRUE))
character(0)
> try(system("convert tmp/3zdg21321995465.ps tmp/3zdg21321995465.png",intern=TRUE))
character(0)
> try(system("convert tmp/4149j1321995465.ps tmp/4149j1321995465.png",intern=TRUE))
character(0)
> try(system("convert tmp/5sors1321995465.ps tmp/5sors1321995465.png",intern=TRUE))
character(0)
> try(system("convert tmp/6b81l1321995465.ps tmp/6b81l1321995465.png",intern=TRUE))
character(0)
> try(system("convert tmp/77glc1321995465.ps tmp/77glc1321995465.png",intern=TRUE))
character(0)
> try(system("convert tmp/8ip181321995465.ps tmp/8ip181321995465.png",intern=TRUE))
character(0)
> try(system("convert tmp/9yyvz1321995465.ps tmp/9yyvz1321995465.png",intern=TRUE))
character(0)
> try(system("convert tmp/10ld6l1321995465.ps tmp/10ld6l1321995465.png",intern=TRUE))
character(0)
>
>
> proc.time()
user system elapsed
3.731 0.480 4.237