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(573
+ ,122
+ ,589
+ ,130
+ ,17.9
+ ,2849.27
+ ,567
+ ,117
+ ,584
+ ,127
+ ,17.4
+ ,2921.44
+ ,569
+ ,112
+ ,573
+ ,122
+ ,16.7
+ ,2981.85
+ ,621
+ ,113
+ ,567
+ ,117
+ ,16
+ ,3080.58
+ ,629
+ ,149
+ ,569
+ ,112
+ ,16.6
+ ,3106.22
+ ,628
+ ,157
+ ,621
+ ,113
+ ,19.1
+ ,3119.31
+ ,612
+ ,157
+ ,629
+ ,149
+ ,17.8
+ ,3061.26
+ ,595
+ ,147
+ ,628
+ ,157
+ ,17.2
+ ,3097.31
+ ,597
+ ,137
+ ,612
+ ,157
+ ,18.6
+ ,3161.69
+ ,593
+ ,132
+ ,595
+ ,147
+ ,16.3
+ ,3257.16
+ ,590
+ ,125
+ ,597
+ ,137
+ ,15.1
+ ,3277.01
+ ,580
+ ,123
+ ,593
+ ,132
+ ,19.2
+ ,3295.32
+ ,574
+ ,117
+ ,590
+ ,125
+ ,17.7
+ ,3363.99
+ ,573
+ ,114
+ ,580
+ ,123
+ ,19.1
+ ,3494.17
+ ,573
+ ,111
+ ,574
+ ,117
+ ,18
+ ,3667.03
+ ,620
+ ,112
+ ,573
+ ,114
+ ,17.5
+ ,3813.06
+ ,626
+ ,144
+ ,573
+ ,111
+ ,17.8
+ ,3917.96
+ ,620
+ ,150
+ ,620
+ ,112
+ ,21.1
+ ,3895.51
+ ,588
+ ,149
+ ,626
+ ,144
+ ,17.2
+ ,3801.06
+ ,566
+ ,134
+ ,620
+ ,150
+ ,19.4
+ ,3570.12
+ ,557
+ ,123
+ ,588
+ ,149
+ ,19.8
+ ,3701.61
+ ,561
+ ,116
+ ,566
+ ,134
+ ,17.6
+ ,3862.27
+ ,549
+ ,117
+ ,557
+ ,123
+ ,16.2
+ ,3970.1
+ ,532
+ ,111
+ ,561
+ ,116
+ ,19.5
+ ,4138.52
+ ,526
+ ,105
+ ,549
+ ,117
+ ,19.9
+ ,4199.75
+ ,511
+ ,102
+ ,532
+ ,111
+ ,20
+ ,4290.89
+ ,499
+ ,95
+ ,526
+ ,105
+ ,17.3
+ ,4443.91
+ ,555
+ ,93
+ ,511
+ ,102
+ ,18.9
+ ,4502.64
+ ,565
+ ,124
+ ,499
+ ,95
+ ,18.6
+ ,4356.98
+ ,542
+ ,130
+ ,555
+ ,93
+ ,21.4
+ ,4591.27
+ ,527
+ ,124
+ ,565
+ ,124
+ ,18.6
+ ,4696.96
+ ,510
+ ,115
+ ,542
+ ,130
+ ,19.8
+ ,4621.4
+ ,514
+ ,106
+ ,527
+ ,124
+ ,20.8
+ ,4562.84
+ ,517
+ ,105
+ ,510
+ ,115
+ ,19.6
+ ,4202.52
+ ,508
+ ,105
+ ,514
+ ,106
+ ,17.7
+ ,4296.49
+ ,493
+ ,101
+ ,517
+ ,105
+ ,19.8
+ ,4435.23
+ ,490
+ ,95
+ ,508
+ ,105
+ ,22.2
+ ,4105.18
+ ,469
+ ,93
+ ,493
+ ,101
+ ,20.7
+ ,4116.68
+ ,478
+ ,84
+ ,490
+ ,95
+ ,17.9
+ ,3844.49
+ ,528
+ ,87
+ ,469
+ ,93
+ ,20.9
+ ,3720.98
+ ,534
+ ,116
+ ,478
+ ,84
+ ,21.2
+ ,3674.4
+ ,518
+ ,120
+ ,528
+ ,87
+ ,21.4
+ ,3857.62
+ ,506
+ ,117
+ ,534
+ ,116
+ ,23
+ ,3801.06
+ ,502
+ ,109
+ ,518
+ ,120
+ ,21.3
+ ,3504.37
+ ,516
+ ,105
+ ,506
+ ,117
+ ,23.9
+ ,3032.6
+ ,528
+ ,107
+ ,502
+ ,109
+ ,22.4
+ ,3047.03
+ ,533
+ ,109
+ ,516
+ ,105
+ ,18.3
+ ,2962.34
+ ,536
+ ,109
+ ,528
+ ,107
+ ,22.8
+ ,2197.82
+ ,537
+ ,108
+ ,533
+ ,109
+ ,22.3
+ ,2014.45
+ ,524
+ ,107
+ ,536
+ ,109
+ ,17.8
+ ,1862.83
+ ,536
+ ,99
+ ,537
+ ,108
+ ,16.4
+ ,1905.41
+ ,587
+ ,103
+ ,524
+ ,107
+ ,16
+ ,1810.99
+ ,597
+ ,131
+ ,536
+ ,99
+ ,16.4
+ ,1670.07
+ ,581
+ ,137
+ ,587
+ ,103
+ ,17.7
+ ,1864.44
+ ,564
+ ,135
+ ,597
+ ,131
+ ,16.6
+ ,2052.02)
+ ,dim=c(6
+ ,55)
+ ,dimnames=list(c('Y'
+ ,'X'
+ ,'Y1'
+ ,'Y2'
+ ,'Y3'
+ ,'Y4')
+ ,1:55))
> y <- array(NA,dim=c(6,55),dimnames=list(c('Y','X','Y1','Y2','Y3','Y4'),1:55))
> 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
Y X Y1 Y2 Y3 Y4 M1 M2 M3 M4 M5 M6 M7 M8 M9 M10 M11 t
1 573 122 589 130 17.9 2849.27 1 0 0 0 0 0 0 0 0 0 0 1
2 567 117 584 127 17.4 2921.44 0 1 0 0 0 0 0 0 0 0 0 2
3 569 112 573 122 16.7 2981.85 0 0 1 0 0 0 0 0 0 0 0 3
4 621 113 567 117 16.0 3080.58 0 0 0 1 0 0 0 0 0 0 0 4
5 629 149 569 112 16.6 3106.22 0 0 0 0 1 0 0 0 0 0 0 5
6 628 157 621 113 19.1 3119.31 0 0 0 0 0 1 0 0 0 0 0 6
7 612 157 629 149 17.8 3061.26 0 0 0 0 0 0 1 0 0 0 0 7
8 595 147 628 157 17.2 3097.31 0 0 0 0 0 0 0 1 0 0 0 8
9 597 137 612 157 18.6 3161.69 0 0 0 0 0 0 0 0 1 0 0 9
10 593 132 595 147 16.3 3257.16 0 0 0 0 0 0 0 0 0 1 0 10
11 590 125 597 137 15.1 3277.01 0 0 0 0 0 0 0 0 0 0 1 11
12 580 123 593 132 19.2 3295.32 0 0 0 0 0 0 0 0 0 0 0 12
13 574 117 590 125 17.7 3363.99 1 0 0 0 0 0 0 0 0 0 0 13
14 573 114 580 123 19.1 3494.17 0 1 0 0 0 0 0 0 0 0 0 14
15 573 111 574 117 18.0 3667.03 0 0 1 0 0 0 0 0 0 0 0 15
16 620 112 573 114 17.5 3813.06 0 0 0 1 0 0 0 0 0 0 0 16
17 626 144 573 111 17.8 3917.96 0 0 0 0 1 0 0 0 0 0 0 17
18 620 150 620 112 21.1 3895.51 0 0 0 0 0 1 0 0 0 0 0 18
19 588 149 626 144 17.2 3801.06 0 0 0 0 0 0 1 0 0 0 0 19
20 566 134 620 150 19.4 3570.12 0 0 0 0 0 0 0 1 0 0 0 20
21 557 123 588 149 19.8 3701.61 0 0 0 0 0 0 0 0 1 0 0 21
22 561 116 566 134 17.6 3862.27 0 0 0 0 0 0 0 0 0 1 0 22
23 549 117 557 123 16.2 3970.10 0 0 0 0 0 0 0 0 0 0 1 23
24 532 111 561 116 19.5 4138.52 0 0 0 0 0 0 0 0 0 0 0 24
25 526 105 549 117 19.9 4199.75 1 0 0 0 0 0 0 0 0 0 0 25
26 511 102 532 111 20.0 4290.89 0 1 0 0 0 0 0 0 0 0 0 26
27 499 95 526 105 17.3 4443.91 0 0 1 0 0 0 0 0 0 0 0 27
28 555 93 511 102 18.9 4502.64 0 0 0 1 0 0 0 0 0 0 0 28
29 565 124 499 95 18.6 4356.98 0 0 0 0 1 0 0 0 0 0 0 29
30 542 130 555 93 21.4 4591.27 0 0 0 0 0 1 0 0 0 0 0 30
31 527 124 565 124 18.6 4696.96 0 0 0 0 0 0 1 0 0 0 0 31
32 510 115 542 130 19.8 4621.40 0 0 0 0 0 0 0 1 0 0 0 32
33 514 106 527 124 20.8 4562.84 0 0 0 0 0 0 0 0 1 0 0 33
34 517 105 510 115 19.6 4202.52 0 0 0 0 0 0 0 0 0 1 0 34
35 508 105 514 106 17.7 4296.49 0 0 0 0 0 0 0 0 0 0 1 35
36 493 101 517 105 19.8 4435.23 0 0 0 0 0 0 0 0 0 0 0 36
37 490 95 508 105 22.2 4105.18 1 0 0 0 0 0 0 0 0 0 0 37
38 469 93 493 101 20.7 4116.68 0 1 0 0 0 0 0 0 0 0 0 38
39 478 84 490 95 17.9 3844.49 0 0 1 0 0 0 0 0 0 0 0 39
40 528 87 469 93 20.9 3720.98 0 0 0 1 0 0 0 0 0 0 0 40
41 534 116 478 84 21.2 3674.40 0 0 0 0 1 0 0 0 0 0 0 41
42 518 120 528 87 21.4 3857.62 0 0 0 0 0 1 0 0 0 0 0 42
43 506 117 534 116 23.0 3801.06 0 0 0 0 0 0 1 0 0 0 0 43
44 502 109 518 120 21.3 3504.37 0 0 0 0 0 0 0 1 0 0 0 44
45 516 105 506 117 23.9 3032.60 0 0 0 0 0 0 0 0 1 0 0 45
46 528 107 502 109 22.4 3047.03 0 0 0 0 0 0 0 0 0 1 0 46
47 533 109 516 105 18.3 2962.34 0 0 0 0 0 0 0 0 0 0 1 47
48 536 109 528 107 22.8 2197.82 0 0 0 0 0 0 0 0 0 0 0 48
49 537 108 533 109 22.3 2014.45 1 0 0 0 0 0 0 0 0 0 0 49
50 524 107 536 109 17.8 1862.83 0 1 0 0 0 0 0 0 0 0 0 50
51 536 99 537 108 16.4 1905.41 0 0 1 0 0 0 0 0 0 0 0 51
52 587 103 524 107 16.0 1810.99 0 0 0 1 0 0 0 0 0 0 0 52
53 597 131 536 99 16.4 1670.07 0 0 0 0 1 0 0 0 0 0 0 53
54 581 137 587 103 17.7 1864.44 0 0 0 0 0 1 0 0 0 0 0 54
55 564 135 597 131 16.6 2052.02 0 0 0 0 0 0 1 0 0 0 0 55
> k <- length(x[1,])
> df <- as.data.frame(x)
> (mylm <- lm(df))
Call:
lm(formula = df)
Coefficients:
(Intercept) X Y1 Y2 Y3 Y4
63.241901 1.162320 0.780422 -0.792732 2.103896 -0.008417
M1 M2 M3 M4 M5 M6
2.766982 1.941191 15.869688 71.113325 35.438531 -25.750626
M7 M8 M9 M10 M11 t
-19.305463 -9.418760 12.586114 26.781387 19.389018 -0.268120
> (mysum <- summary(mylm))
Call:
lm(formula = df)
Residuals:
Min 1Q Median 3Q Max
-13.9293 -2.9571 -0.6877 3.2710 13.3866
Coefficients:
Estimate Std. Error t value Pr(>|t|)
(Intercept) 63.241901 52.569279 1.203 0.236610
X 1.162320 0.356310 3.262 0.002381 **
Y1 0.780422 0.130898 5.962 7.07e-07 ***
Y2 -0.792732 0.390900 -2.028 0.049810 *
Y3 2.103896 0.867991 2.424 0.020362 *
Y4 -0.008417 0.002094 -4.019 0.000276 ***
M1 2.766982 4.622443 0.599 0.553089
M2 1.941191 4.867364 0.399 0.692320
M3 15.869688 6.404088 2.478 0.017898 *
M4 71.113325 5.929281 11.994 2.59e-14 ***
M5 35.438531 12.032187 2.945 0.005551 **
M6 -25.750626 12.556784 -2.051 0.047426 *
M7 -19.305463 8.113687 -2.379 0.022612 *
M8 -9.418760 8.462380 -1.113 0.272881
M9 12.586114 8.935126 1.409 0.167299
M10 26.781387 6.758611 3.963 0.000325 ***
M11 19.389018 5.787196 3.350 0.001868 **
t -0.268120 0.157730 -1.700 0.097549 .
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
Residual standard error: 6.41 on 37 degrees of freedom
Multiple R-squared: 0.9838, Adjusted R-squared: 0.9763
F-statistic: 131.9 on 17 and 37 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,] 0.1985291 0.3970581881 0.8014709059
[2,] 0.7388147 0.5223705290 0.2611852645
[3,] 0.8370923 0.3258154218 0.1629077109
[4,] 0.8017419 0.3965161287 0.1982580643
[5,] 0.7198026 0.5603947473 0.2801973737
[6,] 0.6758136 0.6483728956 0.3241864478
[7,] 0.8403542 0.3192915724 0.1596457862
[8,] 0.8659546 0.2680907821 0.1340453911
[9,] 0.9356586 0.1286828722 0.0643414361
[10,] 0.8843436 0.2313127578 0.1156563789
[11,] 0.9872848 0.0254303312 0.0127151656
[12,] 0.9816604 0.0366792169 0.0183396085
[13,] 0.9997312 0.0005376863 0.0002688432
[14,] 0.9980809 0.0038381347 0.0019190673
> postscript(file="/var/www/html/rcomp/tmp/1z09i1258744278.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$resid)
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/2wvky1258744278.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> plot(mysum$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/300qf1258744278.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> hist(mysum$resid, main='Residual Histogram', xlab='values of Residuals')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/4lm2y1258744278.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> densityplot(~mysum$resid,col='black',main='Residual Density Plot', xlab='values of Residuals')
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/57r221258744278.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 = 55
Frequency = 1
1 2 3 4 5
-4.834528311 -0.745702861 0.007695224 -1.107538717 -5.579191414
6 7 8 9 10
0.640766617 3.005169018 -3.302160412 -1.332533532 -2.465709776
11 12 13 14 15
3.534609358 6.202554451 5.203592071 13.153483346 6.675447151
16 17 18 19 20
-1.779086947 0.843147991 6.307599122 -2.612011866 -13.929251813
21 22 23 24 25
-7.434531234 2.033693470 -1.311340500 -5.876362565 2.430302978
26 27 28 29 30
1.078683065 -9.550830520 0.254516428 13.386583427 -4.338035154
31 32 33 34 35
5.009824761 8.397555524 5.474822666 1.334438895 -5.473002889
36 37 38 39 40
-2.550991464 -1.879508484 -7.672921889 -0.687651256 -1.698008068
41 42 43 44 45
-8.644003104 -3.357515067 -3.583190652 8.833856701 3.292242100
46 47 48 49 50
-0.902422588 3.249734031 2.224799578 -0.919858255 -5.813541661
51 52 53 54 55
3.555339400 4.330117305 -0.006536900 0.747184482 -1.819791261
> postscript(file="/var/www/html/rcomp/tmp/648he1258744278.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 = 55
Frequency = 1
lag(myerror, k = 1) myerror
0 -4.834528311 NA
1 -0.745702861 -4.834528311
2 0.007695224 -0.745702861
3 -1.107538717 0.007695224
4 -5.579191414 -1.107538717
5 0.640766617 -5.579191414
6 3.005169018 0.640766617
7 -3.302160412 3.005169018
8 -1.332533532 -3.302160412
9 -2.465709776 -1.332533532
10 3.534609358 -2.465709776
11 6.202554451 3.534609358
12 5.203592071 6.202554451
13 13.153483346 5.203592071
14 6.675447151 13.153483346
15 -1.779086947 6.675447151
16 0.843147991 -1.779086947
17 6.307599122 0.843147991
18 -2.612011866 6.307599122
19 -13.929251813 -2.612011866
20 -7.434531234 -13.929251813
21 2.033693470 -7.434531234
22 -1.311340500 2.033693470
23 -5.876362565 -1.311340500
24 2.430302978 -5.876362565
25 1.078683065 2.430302978
26 -9.550830520 1.078683065
27 0.254516428 -9.550830520
28 13.386583427 0.254516428
29 -4.338035154 13.386583427
30 5.009824761 -4.338035154
31 8.397555524 5.009824761
32 5.474822666 8.397555524
33 1.334438895 5.474822666
34 -5.473002889 1.334438895
35 -2.550991464 -5.473002889
36 -1.879508484 -2.550991464
37 -7.672921889 -1.879508484
38 -0.687651256 -7.672921889
39 -1.698008068 -0.687651256
40 -8.644003104 -1.698008068
41 -3.357515067 -8.644003104
42 -3.583190652 -3.357515067
43 8.833856701 -3.583190652
44 3.292242100 8.833856701
45 -0.902422588 3.292242100
46 3.249734031 -0.902422588
47 2.224799578 3.249734031
48 -0.919858255 2.224799578
49 -5.813541661 -0.919858255
50 3.555339400 -5.813541661
51 4.330117305 3.555339400
52 -0.006536900 4.330117305
53 0.747184482 -0.006536900
54 -1.819791261 0.747184482
55 NA -1.819791261
> dum1 <- dum[2:length(myerror),]
> dum1
lag(myerror, k = 1) myerror
[1,] -0.745702861 -4.834528311
[2,] 0.007695224 -0.745702861
[3,] -1.107538717 0.007695224
[4,] -5.579191414 -1.107538717
[5,] 0.640766617 -5.579191414
[6,] 3.005169018 0.640766617
[7,] -3.302160412 3.005169018
[8,] -1.332533532 -3.302160412
[9,] -2.465709776 -1.332533532
[10,] 3.534609358 -2.465709776
[11,] 6.202554451 3.534609358
[12,] 5.203592071 6.202554451
[13,] 13.153483346 5.203592071
[14,] 6.675447151 13.153483346
[15,] -1.779086947 6.675447151
[16,] 0.843147991 -1.779086947
[17,] 6.307599122 0.843147991
[18,] -2.612011866 6.307599122
[19,] -13.929251813 -2.612011866
[20,] -7.434531234 -13.929251813
[21,] 2.033693470 -7.434531234
[22,] -1.311340500 2.033693470
[23,] -5.876362565 -1.311340500
[24,] 2.430302978 -5.876362565
[25,] 1.078683065 2.430302978
[26,] -9.550830520 1.078683065
[27,] 0.254516428 -9.550830520
[28,] 13.386583427 0.254516428
[29,] -4.338035154 13.386583427
[30,] 5.009824761 -4.338035154
[31,] 8.397555524 5.009824761
[32,] 5.474822666 8.397555524
[33,] 1.334438895 5.474822666
[34,] -5.473002889 1.334438895
[35,] -2.550991464 -5.473002889
[36,] -1.879508484 -2.550991464
[37,] -7.672921889 -1.879508484
[38,] -0.687651256 -7.672921889
[39,] -1.698008068 -0.687651256
[40,] -8.644003104 -1.698008068
[41,] -3.357515067 -8.644003104
[42,] -3.583190652 -3.357515067
[43,] 8.833856701 -3.583190652
[44,] 3.292242100 8.833856701
[45,] -0.902422588 3.292242100
[46,] 3.249734031 -0.902422588
[47,] 2.224799578 3.249734031
[48,] -0.919858255 2.224799578
[49,] -5.813541661 -0.919858255
[50,] 3.555339400 -5.813541661
[51,] 4.330117305 3.555339400
[52,] -0.006536900 4.330117305
[53,] 0.747184482 -0.006536900
[54,] -1.819791261 0.747184482
> z <- as.data.frame(dum1)
> z
lag(myerror, k = 1) myerror
1 -0.745702861 -4.834528311
2 0.007695224 -0.745702861
3 -1.107538717 0.007695224
4 -5.579191414 -1.107538717
5 0.640766617 -5.579191414
6 3.005169018 0.640766617
7 -3.302160412 3.005169018
8 -1.332533532 -3.302160412
9 -2.465709776 -1.332533532
10 3.534609358 -2.465709776
11 6.202554451 3.534609358
12 5.203592071 6.202554451
13 13.153483346 5.203592071
14 6.675447151 13.153483346
15 -1.779086947 6.675447151
16 0.843147991 -1.779086947
17 6.307599122 0.843147991
18 -2.612011866 6.307599122
19 -13.929251813 -2.612011866
20 -7.434531234 -13.929251813
21 2.033693470 -7.434531234
22 -1.311340500 2.033693470
23 -5.876362565 -1.311340500
24 2.430302978 -5.876362565
25 1.078683065 2.430302978
26 -9.550830520 1.078683065
27 0.254516428 -9.550830520
28 13.386583427 0.254516428
29 -4.338035154 13.386583427
30 5.009824761 -4.338035154
31 8.397555524 5.009824761
32 5.474822666 8.397555524
33 1.334438895 5.474822666
34 -5.473002889 1.334438895
35 -2.550991464 -5.473002889
36 -1.879508484 -2.550991464
37 -7.672921889 -1.879508484
38 -0.687651256 -7.672921889
39 -1.698008068 -0.687651256
40 -8.644003104 -1.698008068
41 -3.357515067 -8.644003104
42 -3.583190652 -3.357515067
43 8.833856701 -3.583190652
44 3.292242100 8.833856701
45 -0.902422588 3.292242100
46 3.249734031 -0.902422588
47 2.224799578 3.249734031
48 -0.919858255 2.224799578
49 -5.813541661 -0.919858255
50 3.555339400 -5.813541661
51 4.330117305 3.555339400
52 -0.006536900 4.330117305
53 0.747184482 -0.006536900
54 -1.819791261 0.747184482
> 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/7ulgz1258744278.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> acf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/816av1258744278.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> pacf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Partial Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/9n94e1258744278.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> opar <- par(mfrow = c(2,2), oma = c(0, 0, 1.1, 0))
> plot(mylm, las = 1, sub='Residual Diagnostics')
> par(opar)
> dev.off()
null device
1
> if (n > n25) {
+ postscript(file="/var/www/html/rcomp/tmp/104lro1258744278.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
+ plot(kp3:nmkm3,gqarr[,2], main='Goldfeld-Quandt test',ylab='2-sided p-value',xlab='breakpoint')
+ grid()
+ dev.off()
+ }
null device
1
>
> #Note: the /var/www/html/rcomp/createtable file can be downloaded at http://www.wessa.net/cretab
> load(file="/var/www/html/rcomp/createtable")
>
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a, 'Multiple Linear Regression - Estimated Regression Equation', 1, TRUE)
> a<-table.row.end(a)
> myeq <- colnames(x)[1]
> myeq <- paste(myeq, '[t] = ', sep='')
> for (i in 1:k){
+ if (mysum$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/117mkf1258744278.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/12h14m1258744278.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/13yuqb1258744278.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/146t9r1258744278.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/15z3ei1258744278.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/16x4nw1258744278.tab")
+ }
>
> system("convert tmp/1z09i1258744278.ps tmp/1z09i1258744278.png")
> system("convert tmp/2wvky1258744278.ps tmp/2wvky1258744278.png")
> system("convert tmp/300qf1258744278.ps tmp/300qf1258744278.png")
> system("convert tmp/4lm2y1258744278.ps tmp/4lm2y1258744278.png")
> system("convert tmp/57r221258744278.ps tmp/57r221258744278.png")
> system("convert tmp/648he1258744278.ps tmp/648he1258744278.png")
> system("convert tmp/7ulgz1258744278.ps tmp/7ulgz1258744278.png")
> system("convert tmp/816av1258744278.ps tmp/816av1258744278.png")
> system("convert tmp/9n94e1258744278.ps tmp/9n94e1258744278.png")
> system("convert tmp/104lro1258744278.ps tmp/104lro1258744278.png")
>
>
> proc.time()
user system elapsed
2.266 1.511 2.716