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(574
+ ,0
+ ,580
+ ,590
+ ,593
+ ,573
+ ,0
+ ,574
+ ,580
+ ,590
+ ,573
+ ,0
+ ,573
+ ,574
+ ,580
+ ,620
+ ,0
+ ,573
+ ,573
+ ,574
+ ,626
+ ,0
+ ,620
+ ,573
+ ,573
+ ,620
+ ,0
+ ,626
+ ,620
+ ,573
+ ,588
+ ,0
+ ,620
+ ,626
+ ,620
+ ,566
+ ,0
+ ,588
+ ,620
+ ,626
+ ,557
+ ,0
+ ,566
+ ,588
+ ,620
+ ,561
+ ,0
+ ,557
+ ,566
+ ,588
+ ,549
+ ,0
+ ,561
+ ,557
+ ,566
+ ,532
+ ,0
+ ,549
+ ,561
+ ,557
+ ,526
+ ,0
+ ,532
+ ,549
+ ,561
+ ,511
+ ,0
+ ,526
+ ,532
+ ,549
+ ,499
+ ,0
+ ,511
+ ,526
+ ,532
+ ,555
+ ,0
+ ,499
+ ,511
+ ,526
+ ,565
+ ,0
+ ,555
+ ,499
+ ,511
+ ,542
+ ,0
+ ,565
+ ,555
+ ,499
+ ,527
+ ,0
+ ,542
+ ,565
+ ,555
+ ,510
+ ,0
+ ,527
+ ,542
+ ,565
+ ,514
+ ,0
+ ,510
+ ,527
+ ,542
+ ,517
+ ,0
+ ,514
+ ,510
+ ,527
+ ,508
+ ,0
+ ,517
+ ,514
+ ,510
+ ,493
+ ,0
+ ,508
+ ,517
+ ,514
+ ,490
+ ,0
+ ,493
+ ,508
+ ,517
+ ,469
+ ,0
+ ,490
+ ,493
+ ,508
+ ,478
+ ,0
+ ,469
+ ,490
+ ,493
+ ,528
+ ,1
+ ,478
+ ,469
+ ,490
+ ,534
+ ,1
+ ,528
+ ,478
+ ,469
+ ,518
+ ,1
+ ,534
+ ,528
+ ,478
+ ,506
+ ,1
+ ,518
+ ,534
+ ,528
+ ,502
+ ,1
+ ,506
+ ,518
+ ,534
+ ,516
+ ,1
+ ,502
+ ,506
+ ,518
+ ,528
+ ,1
+ ,516
+ ,502
+ ,506
+ ,533
+ ,1
+ ,528
+ ,516
+ ,502
+ ,536
+ ,1
+ ,533
+ ,528
+ ,516
+ ,537
+ ,1
+ ,536
+ ,533
+ ,528
+ ,524
+ ,1
+ ,537
+ ,536
+ ,533
+ ,536
+ ,1
+ ,524
+ ,537
+ ,536
+ ,587
+ ,1
+ ,536
+ ,524
+ ,537
+ ,597
+ ,1
+ ,587
+ ,536
+ ,524
+ ,581
+ ,1
+ ,597
+ ,587
+ ,536
+ ,564
+ ,1
+ ,581
+ ,597
+ ,587
+ ,558
+ ,1
+ ,564
+ ,581
+ ,597
+ ,575
+ ,0
+ ,558
+ ,564
+ ,581
+ ,580
+ ,0
+ ,575
+ ,558
+ ,564
+ ,575
+ ,0
+ ,580
+ ,575
+ ,558
+ ,563
+ ,0
+ ,575
+ ,580
+ ,575
+ ,552
+ ,0
+ ,563
+ ,575
+ ,580
+ ,537
+ ,0
+ ,552
+ ,563
+ ,575
+ ,545
+ ,0
+ ,537
+ ,552
+ ,563
+ ,601
+ ,0
+ ,545
+ ,537
+ ,552)
+ ,dim=c(5
+ ,52)
+ ,dimnames=list(c('Y'
+ ,'X'
+ ,'Y1'
+ ,'Y2'
+ ,'Y3
')
+ ,1:52))
> y <- array(NA,dim=c(5,52),dimnames=list(c('Y','X','Y1','Y2','Y3
'),1:52))
> 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\r M1 M2 M3 M4 M5 M6 M7 M8 M9 M10 M11 t
1 574 0 580 590 593 1 0 0 0 0 0 0 0 0 0 0 1
2 573 0 574 580 590 0 1 0 0 0 0 0 0 0 0 0 2
3 573 0 573 574 580 0 0 1 0 0 0 0 0 0 0 0 3
4 620 0 573 573 574 0 0 0 1 0 0 0 0 0 0 0 4
5 626 0 620 573 573 0 0 0 0 1 0 0 0 0 0 0 5
6 620 0 626 620 573 0 0 0 0 0 1 0 0 0 0 0 6
7 588 0 620 626 620 0 0 0 0 0 0 1 0 0 0 0 7
8 566 0 588 620 626 0 0 0 0 0 0 0 1 0 0 0 8
9 557 0 566 588 620 0 0 0 0 0 0 0 0 1 0 0 9
10 561 0 557 566 588 0 0 0 0 0 0 0 0 0 1 0 10
11 549 0 561 557 566 0 0 0 0 0 0 0 0 0 0 1 11
12 532 0 549 561 557 0 0 0 0 0 0 0 0 0 0 0 12
13 526 0 532 549 561 1 0 0 0 0 0 0 0 0 0 0 13
14 511 0 526 532 549 0 1 0 0 0 0 0 0 0 0 0 14
15 499 0 511 526 532 0 0 1 0 0 0 0 0 0 0 0 15
16 555 0 499 511 526 0 0 0 1 0 0 0 0 0 0 0 16
17 565 0 555 499 511 0 0 0 0 1 0 0 0 0 0 0 17
18 542 0 565 555 499 0 0 0 0 0 1 0 0 0 0 0 18
19 527 0 542 565 555 0 0 0 0 0 0 1 0 0 0 0 19
20 510 0 527 542 565 0 0 0 0 0 0 0 1 0 0 0 20
21 514 0 510 527 542 0 0 0 0 0 0 0 0 1 0 0 21
22 517 0 514 510 527 0 0 0 0 0 0 0 0 0 1 0 22
23 508 0 517 514 510 0 0 0 0 0 0 0 0 0 0 1 23
24 493 0 508 517 514 0 0 0 0 0 0 0 0 0 0 0 24
25 490 0 493 508 517 1 0 0 0 0 0 0 0 0 0 0 25
26 469 0 490 493 508 0 1 0 0 0 0 0 0 0 0 0 26
27 478 0 469 490 493 0 0 1 0 0 0 0 0 0 0 0 27
28 528 1 478 469 490 0 0 0 1 0 0 0 0 0 0 0 28
29 534 1 528 478 469 0 0 0 0 1 0 0 0 0 0 0 29
30 518 1 534 528 478 0 0 0 0 0 1 0 0 0 0 0 30
31 506 1 518 534 528 0 0 0 0 0 0 1 0 0 0 0 31
32 502 1 506 518 534 0 0 0 0 0 0 0 1 0 0 0 32
33 516 1 502 506 518 0 0 0 0 0 0 0 0 1 0 0 33
34 528 1 516 502 506 0 0 0 0 0 0 0 0 0 1 0 34
35 533 1 528 516 502 0 0 0 0 0 0 0 0 0 0 1 35
36 536 1 533 528 516 0 0 0 0 0 0 0 0 0 0 0 36
37 537 1 536 533 528 1 0 0 0 0 0 0 0 0 0 0 37
38 524 1 537 536 533 0 1 0 0 0 0 0 0 0 0 0 38
39 536 1 524 537 536 0 0 1 0 0 0 0 0 0 0 0 39
40 587 1 536 524 537 0 0 0 1 0 0 0 0 0 0 0 40
41 597 1 587 536 524 0 0 0 0 1 0 0 0 0 0 0 41
42 581 1 597 587 536 0 0 0 0 0 1 0 0 0 0 0 42
43 564 1 581 597 587 0 0 0 0 0 0 1 0 0 0 0 43
44 558 1 564 581 597 0 0 0 0 0 0 0 1 0 0 0 44
45 575 0 558 564 581 0 0 0 0 0 0 0 0 1 0 0 45
46 580 0 575 558 564 0 0 0 0 0 0 0 0 0 1 0 46
47 575 0 580 575 558 0 0 0 0 0 0 0 0 0 0 1 47
48 563 0 575 580 575 0 0 0 0 0 0 0 0 0 0 0 48
49 552 0 563 575 580 1 0 0 0 0 0 0 0 0 0 0 49
50 537 0 552 563 575 0 1 0 0 0 0 0 0 0 0 0 50
51 545 0 537 552 563 0 0 1 0 0 0 0 0 0 0 0 51
52 601 0 545 537 552 0 0 0 1 0 0 0 0 0 0 0 52
> k <- length(x[1,])
> df <- as.data.frame(x)
> (mylm <- lm(df))
Call:
lm(formula = df)
Coefficients:
(Intercept) X Y1 Y2 `Y3\r` M1
-7.25131 4.22226 1.04737 0.03762 -0.09710 7.17062
M2 M3 M4 M5 M6 M7
-0.74924 15.38982 62.91357 15.11206 -10.29161 -8.74246
M8 M9 M10 M11 t
0.18370 19.72919 17.46291 4.42029 0.07437
> (mysum <- summary(mylm))
Call:
lm(formula = df)
Residuals:
Min 1Q Median 3Q Max
-13.5900 -3.6574 -0.9943 3.8343 15.1321
Coefficients:
Estimate Std. Error t value Pr(>|t|)
(Intercept) -7.25131 19.60220 -0.370 0.71367
X 4.22226 2.98636 1.414 0.16624
Y1 1.04737 0.16915 6.192 4.32e-07 ***
Y2 0.03762 0.24471 0.154 0.87869
`Y3\r` -0.09710 0.17043 -0.570 0.57249
M1 7.17062 5.01813 1.429 0.16189
M2 -0.74924 5.34584 -0.140 0.88934
M3 15.38982 5.08182 3.028 0.00460 **
M4 62.91357 5.89024 10.681 1.47e-12 ***
M5 15.11206 10.68921 1.414 0.16626
M6 -10.29161 8.96019 -1.149 0.25851
M7 -8.74246 5.49997 -1.590 0.12093
M8 0.18370 6.83226 0.027 0.97870
M9 19.72919 6.52228 3.025 0.00464 **
M10 17.46291 6.15825 2.836 0.00755 **
M11 4.42029 5.26044 0.840 0.40645
t 0.07437 0.07504 0.991 0.32848
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
Residual standard error: 6.921 on 35 degrees of freedom
Multiple R-squared: 0.9751, Adjusted R-squared: 0.9637
F-statistic: 85.53 on 16 and 35 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,] 0.9563308 0.087338458 0.043669229
[2,] 0.9963173 0.007365351 0.003682675
[3,] 0.9935527 0.012894570 0.006447285
[4,] 0.9874112 0.025177628 0.012588814
[5,] 0.9794744 0.041051237 0.020525618
[6,] 0.9893984 0.021203295 0.010601648
[7,] 0.9803382 0.039323688 0.019661844
[8,] 0.9852280 0.029543952 0.014771976
[9,] 0.9634982 0.073003643 0.036501821
[10,] 0.9339733 0.132053364 0.066026682
[11,] 0.8618578 0.276284435 0.138142217
[12,] 0.7922571 0.415485721 0.207742861
[13,] 0.6859334 0.628133291 0.314066645
> postscript(file="/var/www/html/rcomp/tmp/1hwlk1291056046.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$resid)
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/2hwlk1291056046.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> plot(mysum$resid, type='b', pch=19, main='Residuals', ylab='value of Residuals', xlab='time or index')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/3hwlk1291056046.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> hist(mysum$resid, main='Residual Histogram', xlab='values of Residuals')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/42xni1291056047.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> densityplot(~mysum$resid,col='black',main='Residual Density Plot', xlab='values of Residuals')
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/52xni1291056047.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 = 52
Frequency = 1
1 2 3 4 5 6
1.91743334 15.13205713 -0.77928045 -1.92238324 2.48149465 13.75824409
7 8 9 10 11 12
-9.24304272 -5.91952635 -10.87596851 2.46270685 -2.55612542 -3.66624117
13 14 15 16 17 18
1.73387784 0.33795632 -13.58998188 7.36204227 5.43170118 -5.98485495
19 20 21 22 23 24
6.54248599 -1.91118035 -1.39479979 -1.20926214 -2.18433924 -3.13660076
25 26 27 28 29 30
2.95881208 -7.36314844 6.07443474 -4.67342020 -5.69229822 -3.65450507
31 32 33 34 35 36
4.10916609 4.86162415 2.32909674 0.84316832 5.32788360 8.34490715
37 38 39 40 41 42
-0.06508073 -5.89431764 3.76168044 -4.81859613 -2.22089761 -4.11888408
43 44 45 46 47 48
-1.40860936 2.96908255 9.94167156 -2.09661303 -0.58741894 -1.54206523
49 50 51 52
-6.54504253 -2.21254736 4.53314715 4.05235730
> postscript(file="/var/www/html/rcomp/tmp/62xni1291056047.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 = 52
Frequency = 1
lag(myerror, k = 1) myerror
0 1.91743334 NA
1 15.13205713 1.91743334
2 -0.77928045 15.13205713
3 -1.92238324 -0.77928045
4 2.48149465 -1.92238324
5 13.75824409 2.48149465
6 -9.24304272 13.75824409
7 -5.91952635 -9.24304272
8 -10.87596851 -5.91952635
9 2.46270685 -10.87596851
10 -2.55612542 2.46270685
11 -3.66624117 -2.55612542
12 1.73387784 -3.66624117
13 0.33795632 1.73387784
14 -13.58998188 0.33795632
15 7.36204227 -13.58998188
16 5.43170118 7.36204227
17 -5.98485495 5.43170118
18 6.54248599 -5.98485495
19 -1.91118035 6.54248599
20 -1.39479979 -1.91118035
21 -1.20926214 -1.39479979
22 -2.18433924 -1.20926214
23 -3.13660076 -2.18433924
24 2.95881208 -3.13660076
25 -7.36314844 2.95881208
26 6.07443474 -7.36314844
27 -4.67342020 6.07443474
28 -5.69229822 -4.67342020
29 -3.65450507 -5.69229822
30 4.10916609 -3.65450507
31 4.86162415 4.10916609
32 2.32909674 4.86162415
33 0.84316832 2.32909674
34 5.32788360 0.84316832
35 8.34490715 5.32788360
36 -0.06508073 8.34490715
37 -5.89431764 -0.06508073
38 3.76168044 -5.89431764
39 -4.81859613 3.76168044
40 -2.22089761 -4.81859613
41 -4.11888408 -2.22089761
42 -1.40860936 -4.11888408
43 2.96908255 -1.40860936
44 9.94167156 2.96908255
45 -2.09661303 9.94167156
46 -0.58741894 -2.09661303
47 -1.54206523 -0.58741894
48 -6.54504253 -1.54206523
49 -2.21254736 -6.54504253
50 4.53314715 -2.21254736
51 4.05235730 4.53314715
52 NA 4.05235730
> dum1 <- dum[2:length(myerror),]
> dum1
lag(myerror, k = 1) myerror
[1,] 15.13205713 1.91743334
[2,] -0.77928045 15.13205713
[3,] -1.92238324 -0.77928045
[4,] 2.48149465 -1.92238324
[5,] 13.75824409 2.48149465
[6,] -9.24304272 13.75824409
[7,] -5.91952635 -9.24304272
[8,] -10.87596851 -5.91952635
[9,] 2.46270685 -10.87596851
[10,] -2.55612542 2.46270685
[11,] -3.66624117 -2.55612542
[12,] 1.73387784 -3.66624117
[13,] 0.33795632 1.73387784
[14,] -13.58998188 0.33795632
[15,] 7.36204227 -13.58998188
[16,] 5.43170118 7.36204227
[17,] -5.98485495 5.43170118
[18,] 6.54248599 -5.98485495
[19,] -1.91118035 6.54248599
[20,] -1.39479979 -1.91118035
[21,] -1.20926214 -1.39479979
[22,] -2.18433924 -1.20926214
[23,] -3.13660076 -2.18433924
[24,] 2.95881208 -3.13660076
[25,] -7.36314844 2.95881208
[26,] 6.07443474 -7.36314844
[27,] -4.67342020 6.07443474
[28,] -5.69229822 -4.67342020
[29,] -3.65450507 -5.69229822
[30,] 4.10916609 -3.65450507
[31,] 4.86162415 4.10916609
[32,] 2.32909674 4.86162415
[33,] 0.84316832 2.32909674
[34,] 5.32788360 0.84316832
[35,] 8.34490715 5.32788360
[36,] -0.06508073 8.34490715
[37,] -5.89431764 -0.06508073
[38,] 3.76168044 -5.89431764
[39,] -4.81859613 3.76168044
[40,] -2.22089761 -4.81859613
[41,] -4.11888408 -2.22089761
[42,] -1.40860936 -4.11888408
[43,] 2.96908255 -1.40860936
[44,] 9.94167156 2.96908255
[45,] -2.09661303 9.94167156
[46,] -0.58741894 -2.09661303
[47,] -1.54206523 -0.58741894
[48,] -6.54504253 -1.54206523
[49,] -2.21254736 -6.54504253
[50,] 4.53314715 -2.21254736
[51,] 4.05235730 4.53314715
> z <- as.data.frame(dum1)
> z
lag(myerror, k = 1) myerror
1 15.13205713 1.91743334
2 -0.77928045 15.13205713
3 -1.92238324 -0.77928045
4 2.48149465 -1.92238324
5 13.75824409 2.48149465
6 -9.24304272 13.75824409
7 -5.91952635 -9.24304272
8 -10.87596851 -5.91952635
9 2.46270685 -10.87596851
10 -2.55612542 2.46270685
11 -3.66624117 -2.55612542
12 1.73387784 -3.66624117
13 0.33795632 1.73387784
14 -13.58998188 0.33795632
15 7.36204227 -13.58998188
16 5.43170118 7.36204227
17 -5.98485495 5.43170118
18 6.54248599 -5.98485495
19 -1.91118035 6.54248599
20 -1.39479979 -1.91118035
21 -1.20926214 -1.39479979
22 -2.18433924 -1.20926214
23 -3.13660076 -2.18433924
24 2.95881208 -3.13660076
25 -7.36314844 2.95881208
26 6.07443474 -7.36314844
27 -4.67342020 6.07443474
28 -5.69229822 -4.67342020
29 -3.65450507 -5.69229822
30 4.10916609 -3.65450507
31 4.86162415 4.10916609
32 2.32909674 4.86162415
33 0.84316832 2.32909674
34 5.32788360 0.84316832
35 8.34490715 5.32788360
36 -0.06508073 8.34490715
37 -5.89431764 -0.06508073
38 3.76168044 -5.89431764
39 -4.81859613 3.76168044
40 -2.22089761 -4.81859613
41 -4.11888408 -2.22089761
42 -1.40860936 -4.11888408
43 2.96908255 -1.40860936
44 9.94167156 2.96908255
45 -2.09661303 9.94167156
46 -0.58741894 -2.09661303
47 -1.54206523 -0.58741894
48 -6.54504253 -1.54206523
49 -2.21254736 -6.54504253
50 4.53314715 -2.21254736
51 4.05235730 4.53314715
> 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/7cp4l1291056047.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> acf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/8nymo1291056047.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> pacf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Partial Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/9nymo1291056047.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> opar <- par(mfrow = c(2,2), oma = c(0, 0, 1.1, 0))
> plot(mylm, las = 1, sub='Residual Diagnostics')
> par(opar)
> dev.off()
null device
1
> if (n > n25) {
+ postscript(file="/var/www/html/rcomp/tmp/10nymo1291056047.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
+ plot(kp3:nmkm3,gqarr[,2], main='Goldfeld-Quandt test',ylab='2-sided p-value',xlab='breakpoint')
+ grid()
+ dev.off()
+ }
null device
1
>
> #Note: the /var/www/html/rcomp/createtable file can be downloaded at http://www.wessa.net/cretab
> load(file="/var/www/html/rcomp/createtable")
>
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a, 'Multiple Linear Regression - Estimated Regression Equation', 1, TRUE)
> a<-table.row.end(a)
> myeq <- colnames(x)[1]
> myeq <- paste(myeq, '[t] = ', sep='')
> for (i in 1:k){
+ if (mysum$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/119gkc1291056047.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/12uz0i1291056047.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/131ifc1291056047.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/14trxw1291056047.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/15xav21291056047.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/16tjbb1291056047.tab")
+ }
>
> try(system("convert tmp/1hwlk1291056046.ps tmp/1hwlk1291056046.png",intern=TRUE))
character(0)
> try(system("convert tmp/2hwlk1291056046.ps tmp/2hwlk1291056046.png",intern=TRUE))
character(0)
> try(system("convert tmp/3hwlk1291056046.ps tmp/3hwlk1291056046.png",intern=TRUE))
character(0)
> try(system("convert tmp/42xni1291056047.ps tmp/42xni1291056047.png",intern=TRUE))
character(0)
> try(system("convert tmp/52xni1291056047.ps tmp/52xni1291056047.png",intern=TRUE))
character(0)
> try(system("convert tmp/62xni1291056047.ps tmp/62xni1291056047.png",intern=TRUE))
character(0)
> try(system("convert tmp/7cp4l1291056047.ps tmp/7cp4l1291056047.png",intern=TRUE))
character(0)
> try(system("convert tmp/8nymo1291056047.ps tmp/8nymo1291056047.png",intern=TRUE))
character(0)
> try(system("convert tmp/9nymo1291056047.ps tmp/9nymo1291056047.png",intern=TRUE))
character(0)
> try(system("convert tmp/10nymo1291056047.ps tmp/10nymo1291056047.png",intern=TRUE))
character(0)
>
>
> proc.time()
user system elapsed
2.289 1.584 5.650