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(613
+ ,0
+ ,611
+ ,594
+ ,543
+ ,611
+ ,0
+ ,613
+ ,611
+ ,594
+ ,594
+ ,0
+ ,611
+ ,613
+ ,611
+ ,595
+ ,0
+ ,594
+ ,611
+ ,613
+ ,591
+ ,0
+ ,595
+ ,594
+ ,611
+ ,589
+ ,0
+ ,591
+ ,595
+ ,594
+ ,584
+ ,0
+ ,589
+ ,591
+ ,595
+ ,573
+ ,0
+ ,584
+ ,589
+ ,591
+ ,567
+ ,0
+ ,573
+ ,584
+ ,589
+ ,569
+ ,0
+ ,567
+ ,573
+ ,584
+ ,621
+ ,0
+ ,569
+ ,567
+ ,573
+ ,629
+ ,0
+ ,621
+ ,569
+ ,567
+ ,628
+ ,0
+ ,629
+ ,621
+ ,569
+ ,612
+ ,0
+ ,628
+ ,629
+ ,621
+ ,595
+ ,0
+ ,612
+ ,628
+ ,629
+ ,597
+ ,0
+ ,595
+ ,612
+ ,628
+ ,593
+ ,0
+ ,597
+ ,595
+ ,612
+ ,590
+ ,0
+ ,593
+ ,597
+ ,595
+ ,580
+ ,0
+ ,590
+ ,593
+ ,597
+ ,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
+ ,1
+ ,490
+ ,493
+ ,508
+ ,478
+ ,1
+ ,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)
+ ,dim=c(5
+ ,58)
+ ,dimnames=list(c('Y'
+ ,'X'
+ ,'Y1'
+ ,'Y2'
+ ,'Y3')
+ ,1:58))
> y <- array(NA,dim=c(5,58),dimnames=list(c('Y','X','Y1','Y2','Y3'),1:58))
> 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 M1 M2 M3 M4 M5 M6 M7 M8 M9 M10 M11 t
1 613 0 611 594 543 1 0 0 0 0 0 0 0 0 0 0 1
2 611 0 613 611 594 0 1 0 0 0 0 0 0 0 0 0 2
3 594 0 611 613 611 0 0 1 0 0 0 0 0 0 0 0 3
4 595 0 594 611 613 0 0 0 1 0 0 0 0 0 0 0 4
5 591 0 595 594 611 0 0 0 0 1 0 0 0 0 0 0 5
6 589 0 591 595 594 0 0 0 0 0 1 0 0 0 0 0 6
7 584 0 589 591 595 0 0 0 0 0 0 1 0 0 0 0 7
8 573 0 584 589 591 0 0 0 0 0 0 0 1 0 0 0 8
9 567 0 573 584 589 0 0 0 0 0 0 0 0 1 0 0 9
10 569 0 567 573 584 0 0 0 0 0 0 0 0 0 1 0 10
11 621 0 569 567 573 0 0 0 0 0 0 0 0 0 0 1 11
12 629 0 621 569 567 0 0 0 0 0 0 0 0 0 0 0 12
13 628 0 629 621 569 1 0 0 0 0 0 0 0 0 0 0 13
14 612 0 628 629 621 0 1 0 0 0 0 0 0 0 0 0 14
15 595 0 612 628 629 0 0 1 0 0 0 0 0 0 0 0 15
16 597 0 595 612 628 0 0 0 1 0 0 0 0 0 0 0 16
17 593 0 597 595 612 0 0 0 0 1 0 0 0 0 0 0 17
18 590 0 593 597 595 0 0 0 0 0 1 0 0 0 0 0 18
19 580 0 590 593 597 0 0 0 0 0 0 1 0 0 0 0 19
20 574 0 580 590 593 0 0 0 0 0 0 0 1 0 0 0 20
21 573 0 574 580 590 0 0 0 0 0 0 0 0 1 0 0 21
22 573 0 573 574 580 0 0 0 0 0 0 0 0 0 1 0 22
23 620 0 573 573 574 0 0 0 0 0 0 0 0 0 0 1 23
24 626 0 620 573 573 0 0 0 0 0 0 0 0 0 0 0 24
25 620 0 626 620 573 1 0 0 0 0 0 0 0 0 0 0 25
26 588 0 620 626 620 0 1 0 0 0 0 0 0 0 0 0 26
27 566 0 588 620 626 0 0 1 0 0 0 0 0 0 0 0 27
28 557 0 566 588 620 0 0 0 1 0 0 0 0 0 0 0 28
29 561 0 557 566 588 0 0 0 0 1 0 0 0 0 0 0 29
30 549 0 561 557 566 0 0 0 0 0 1 0 0 0 0 0 30
31 532 0 549 561 557 0 0 0 0 0 0 1 0 0 0 0 31
32 526 0 532 549 561 0 0 0 0 0 0 0 1 0 0 0 32
33 511 0 526 532 549 0 0 0 0 0 0 0 0 1 0 0 33
34 499 0 511 526 532 0 0 0 0 0 0 0 0 0 1 0 34
35 555 0 499 511 526 0 0 0 0 0 0 0 0 0 0 1 35
36 565 0 555 499 511 0 0 0 0 0 0 0 0 0 0 0 36
37 542 0 565 555 499 1 0 0 0 0 0 0 0 0 0 0 37
38 527 0 542 565 555 0 1 0 0 0 0 0 0 0 0 0 38
39 510 0 527 542 565 0 0 1 0 0 0 0 0 0 0 0 39
40 514 0 510 527 542 0 0 0 1 0 0 0 0 0 0 0 40
41 517 0 514 510 527 0 0 0 0 1 0 0 0 0 0 0 41
42 508 0 517 514 510 0 0 0 0 0 1 0 0 0 0 0 42
43 493 0 508 517 514 0 0 0 0 0 0 1 0 0 0 0 43
44 490 0 493 508 517 0 0 0 0 0 0 0 1 0 0 0 44
45 469 1 490 493 508 0 0 0 0 0 0 0 0 1 0 0 45
46 478 1 469 490 493 0 0 0 0 0 0 0 0 0 1 0 46
47 528 1 478 469 490 0 0 0 0 0 0 0 0 0 0 1 47
48 534 1 528 478 469 0 0 0 0 0 0 0 0 0 0 0 48
49 518 1 534 528 478 1 0 0 0 0 0 0 0 0 0 0 49
50 506 1 518 534 528 0 1 0 0 0 0 0 0 0 0 0 50
51 502 1 506 518 534 0 0 1 0 0 0 0 0 0 0 0 51
52 516 1 502 506 518 0 0 0 1 0 0 0 0 0 0 0 52
53 528 1 516 502 506 0 0 0 0 1 0 0 0 0 0 0 53
54 533 1 528 516 502 0 0 0 0 0 1 0 0 0 0 0 54
55 536 1 533 528 516 0 0 0 0 0 0 1 0 0 0 0 55
56 537 1 536 533 528 0 0 0 0 0 0 0 1 0 0 0 56
57 524 1 537 536 533 0 0 0 0 0 0 0 0 1 0 0 57
58 536 1 524 537 536 0 0 0 0 0 0 0 0 0 1 0 58
> k <- length(x[1,])
> df <- as.data.frame(x)
> (mylm <- lm(df))
Call:
lm(formula = df)
Coefficients:
(Intercept) X Y1 Y2 Y3 M1
27.28842 7.47896 1.07958 0.02197 -0.14008 -18.60968
M2 M3 M4 M5 M6 M7
-17.36755 -14.45561 3.85192 1.81842 -6.79023 -10.59179
M8 M9 M10 M11 t
-5.51469 -13.03123 0.31357 49.15241 -0.17636
> (mysum <- summary(mylm))
Call:
lm(formula = df)
Residuals:
Min 1Q Median 3Q Max
-13.5793 -4.4641 0.3791 3.9026 12.6715
Coefficients:
Estimate Std. Error t value Pr(>|t|)
(Intercept) 27.28842 32.45467 0.841 0.4053
X 7.47896 3.93239 1.902 0.0642 .
Y1 1.07958 0.15933 6.776 3.42e-08 ***
Y2 0.02197 0.23535 0.093 0.9261
Y3 -0.14008 0.16043 -0.873 0.3877
M1 -18.60968 12.04700 -1.545 0.1301
M2 -17.36755 10.95998 -1.585 0.1207
M3 -14.45561 11.53062 -1.254 0.2171
M4 3.85192 11.50256 0.335 0.7394
M5 1.81842 9.08304 0.200 0.8423
M6 -6.79023 9.11317 -0.745 0.4605
M7 -10.59179 9.95333 -1.064 0.2935
M8 -5.51469 10.45070 -0.528 0.6006
M9 -13.03123 10.16149 -1.282 0.2069
M10 0.31357 11.01034 0.028 0.9774
M11 49.15241 9.59320 5.124 7.53e-06 ***
t -0.17636 0.13019 -1.355 0.1830
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
Residual standard error: 7.225 on 41 degrees of freedom
Multiple R-squared: 0.9792, Adjusted R-squared: 0.9711
F-statistic: 120.8 on 16 and 41 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,] 0.12975804 0.25951608 0.8702420
[2,] 0.14517592 0.29035184 0.8548241
[3,] 0.07380359 0.14760718 0.9261964
[4,] 0.04199307 0.08398614 0.9580069
[5,] 0.02096008 0.04192016 0.9790399
[6,] 0.04525410 0.09050821 0.9547459
[7,] 0.51175023 0.97649954 0.4882498
[8,] 0.40477672 0.80955343 0.5952233
[9,] 0.43717513 0.87435025 0.5628249
[10,] 0.37036247 0.74072494 0.6296375
[11,] 0.37061239 0.74122479 0.6293876
[12,] 0.45781086 0.91562171 0.5421891
[13,] 0.47300102 0.94600204 0.5269990
[14,] 0.48826568 0.97653137 0.5117343
[15,] 0.62576052 0.74847896 0.3742395
[16,] 0.69914271 0.60171457 0.3008573
[17,] 0.83665505 0.32668990 0.1633450
[18,] 0.78419107 0.43161787 0.2158089
[19,] 0.75801536 0.48396928 0.2419846
> postscript(file="/var/www/html/rcomp/tmp/1zvjy1258742417.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$resid)
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/2pt2h1258742417.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> plot(mysum$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/313qc1258742417.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> hist(mysum$resid, main='Residual Histogram', xlab='values of Residuals')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/4824o1258742417.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> densityplot(~mysum$resid,col='black',main='Residual Density Plot', xlab='values of Residuals')
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/58jsw1258742417.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 = 58
Frequency = 1
1 2 3 4 5 6
7.88716946 9.43272993 -5.80630919 -4.26053814 -7.03692835 1.66309340
7 8 9 10 11 12
3.02812510 -7.99109317 5.40685702 0.25716466 0.02649102 0.33274545
13 14 15 16 17 18
8.61986197 -0.25803218 -1.57776098 0.85535681 -4.96170642 2.71634524
19 20 21 22 23 24
0.30103393 -0.29832016 12.67150820 -0.68631946 -3.16729512 1.28118437
25 26 27 28 29 30
6.55715264 -13.57929802 -2.79607159 -6.31392912 5.61297459 -4.80432414
31 32 33 34 35 36
-6.22004649 2.05600718 -0.08107727 -11.30534855 8.47620283 5.51101978
37 38 39 40 41 42
-12.40999588 3.97921646 2.34340704 3.67283530 2.83669258 -3.08624766
43 44 45 46 47 48
-3.89772034 5.01318727 -13.46529758 3.00215011 -5.33539873 -7.12494961
49 50 51 52 53 54
-10.65418819 0.42538382 7.83673472 6.04627515 3.54896760 3.51113316
55 56 57 58
6.78860780 1.22021887 -4.53199037 8.73235324
> postscript(file="/var/www/html/rcomp/tmp/64chy1258742417.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 = 58
Frequency = 1
lag(myerror, k = 1) myerror
0 7.88716946 NA
1 9.43272993 7.88716946
2 -5.80630919 9.43272993
3 -4.26053814 -5.80630919
4 -7.03692835 -4.26053814
5 1.66309340 -7.03692835
6 3.02812510 1.66309340
7 -7.99109317 3.02812510
8 5.40685702 -7.99109317
9 0.25716466 5.40685702
10 0.02649102 0.25716466
11 0.33274545 0.02649102
12 8.61986197 0.33274545
13 -0.25803218 8.61986197
14 -1.57776098 -0.25803218
15 0.85535681 -1.57776098
16 -4.96170642 0.85535681
17 2.71634524 -4.96170642
18 0.30103393 2.71634524
19 -0.29832016 0.30103393
20 12.67150820 -0.29832016
21 -0.68631946 12.67150820
22 -3.16729512 -0.68631946
23 1.28118437 -3.16729512
24 6.55715264 1.28118437
25 -13.57929802 6.55715264
26 -2.79607159 -13.57929802
27 -6.31392912 -2.79607159
28 5.61297459 -6.31392912
29 -4.80432414 5.61297459
30 -6.22004649 -4.80432414
31 2.05600718 -6.22004649
32 -0.08107727 2.05600718
33 -11.30534855 -0.08107727
34 8.47620283 -11.30534855
35 5.51101978 8.47620283
36 -12.40999588 5.51101978
37 3.97921646 -12.40999588
38 2.34340704 3.97921646
39 3.67283530 2.34340704
40 2.83669258 3.67283530
41 -3.08624766 2.83669258
42 -3.89772034 -3.08624766
43 5.01318727 -3.89772034
44 -13.46529758 5.01318727
45 3.00215011 -13.46529758
46 -5.33539873 3.00215011
47 -7.12494961 -5.33539873
48 -10.65418819 -7.12494961
49 0.42538382 -10.65418819
50 7.83673472 0.42538382
51 6.04627515 7.83673472
52 3.54896760 6.04627515
53 3.51113316 3.54896760
54 6.78860780 3.51113316
55 1.22021887 6.78860780
56 -4.53199037 1.22021887
57 8.73235324 -4.53199037
58 NA 8.73235324
> dum1 <- dum[2:length(myerror),]
> dum1
lag(myerror, k = 1) myerror
[1,] 9.43272993 7.88716946
[2,] -5.80630919 9.43272993
[3,] -4.26053814 -5.80630919
[4,] -7.03692835 -4.26053814
[5,] 1.66309340 -7.03692835
[6,] 3.02812510 1.66309340
[7,] -7.99109317 3.02812510
[8,] 5.40685702 -7.99109317
[9,] 0.25716466 5.40685702
[10,] 0.02649102 0.25716466
[11,] 0.33274545 0.02649102
[12,] 8.61986197 0.33274545
[13,] -0.25803218 8.61986197
[14,] -1.57776098 -0.25803218
[15,] 0.85535681 -1.57776098
[16,] -4.96170642 0.85535681
[17,] 2.71634524 -4.96170642
[18,] 0.30103393 2.71634524
[19,] -0.29832016 0.30103393
[20,] 12.67150820 -0.29832016
[21,] -0.68631946 12.67150820
[22,] -3.16729512 -0.68631946
[23,] 1.28118437 -3.16729512
[24,] 6.55715264 1.28118437
[25,] -13.57929802 6.55715264
[26,] -2.79607159 -13.57929802
[27,] -6.31392912 -2.79607159
[28,] 5.61297459 -6.31392912
[29,] -4.80432414 5.61297459
[30,] -6.22004649 -4.80432414
[31,] 2.05600718 -6.22004649
[32,] -0.08107727 2.05600718
[33,] -11.30534855 -0.08107727
[34,] 8.47620283 -11.30534855
[35,] 5.51101978 8.47620283
[36,] -12.40999588 5.51101978
[37,] 3.97921646 -12.40999588
[38,] 2.34340704 3.97921646
[39,] 3.67283530 2.34340704
[40,] 2.83669258 3.67283530
[41,] -3.08624766 2.83669258
[42,] -3.89772034 -3.08624766
[43,] 5.01318727 -3.89772034
[44,] -13.46529758 5.01318727
[45,] 3.00215011 -13.46529758
[46,] -5.33539873 3.00215011
[47,] -7.12494961 -5.33539873
[48,] -10.65418819 -7.12494961
[49,] 0.42538382 -10.65418819
[50,] 7.83673472 0.42538382
[51,] 6.04627515 7.83673472
[52,] 3.54896760 6.04627515
[53,] 3.51113316 3.54896760
[54,] 6.78860780 3.51113316
[55,] 1.22021887 6.78860780
[56,] -4.53199037 1.22021887
[57,] 8.73235324 -4.53199037
> z <- as.data.frame(dum1)
> z
lag(myerror, k = 1) myerror
1 9.43272993 7.88716946
2 -5.80630919 9.43272993
3 -4.26053814 -5.80630919
4 -7.03692835 -4.26053814
5 1.66309340 -7.03692835
6 3.02812510 1.66309340
7 -7.99109317 3.02812510
8 5.40685702 -7.99109317
9 0.25716466 5.40685702
10 0.02649102 0.25716466
11 0.33274545 0.02649102
12 8.61986197 0.33274545
13 -0.25803218 8.61986197
14 -1.57776098 -0.25803218
15 0.85535681 -1.57776098
16 -4.96170642 0.85535681
17 2.71634524 -4.96170642
18 0.30103393 2.71634524
19 -0.29832016 0.30103393
20 12.67150820 -0.29832016
21 -0.68631946 12.67150820
22 -3.16729512 -0.68631946
23 1.28118437 -3.16729512
24 6.55715264 1.28118437
25 -13.57929802 6.55715264
26 -2.79607159 -13.57929802
27 -6.31392912 -2.79607159
28 5.61297459 -6.31392912
29 -4.80432414 5.61297459
30 -6.22004649 -4.80432414
31 2.05600718 -6.22004649
32 -0.08107727 2.05600718
33 -11.30534855 -0.08107727
34 8.47620283 -11.30534855
35 5.51101978 8.47620283
36 -12.40999588 5.51101978
37 3.97921646 -12.40999588
38 2.34340704 3.97921646
39 3.67283530 2.34340704
40 2.83669258 3.67283530
41 -3.08624766 2.83669258
42 -3.89772034 -3.08624766
43 5.01318727 -3.89772034
44 -13.46529758 5.01318727
45 3.00215011 -13.46529758
46 -5.33539873 3.00215011
47 -7.12494961 -5.33539873
48 -10.65418819 -7.12494961
49 0.42538382 -10.65418819
50 7.83673472 0.42538382
51 6.04627515 7.83673472
52 3.54896760 6.04627515
53 3.51113316 3.54896760
54 6.78860780 3.51113316
55 1.22021887 6.78860780
56 -4.53199037 1.22021887
57 8.73235324 -4.53199037
> 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/71sty1258742417.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> acf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/8kzzl1258742417.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> pacf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Partial Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/95t9g1258742417.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> opar <- par(mfrow = c(2,2), oma = c(0, 0, 1.1, 0))
> plot(mylm, las = 1, sub='Residual Diagnostics')
> par(opar)
> dev.off()
null device
1
> if (n > n25) {
+ postscript(file="/var/www/html/rcomp/tmp/105iag1258742417.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
+ plot(kp3:nmkm3,gqarr[,2], main='Goldfeld-Quandt test',ylab='2-sided p-value',xlab='breakpoint')
+ grid()
+ dev.off()
+ }
null device
1
>
> #Note: the /var/www/html/rcomp/createtable file can be downloaded at http://www.wessa.net/cretab
> load(file="/var/www/html/rcomp/createtable")
>
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a, 'Multiple Linear Regression - Estimated Regression Equation', 1, TRUE)
> a<-table.row.end(a)
> myeq <- colnames(x)[1]
> myeq <- paste(myeq, '[t] = ', sep='')
> for (i in 1:k){
+ if (mysum$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/119ixn1258742417.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/12bqgx1258742417.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/13clsr1258742417.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/142kir1258742417.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/15kodw1258742417.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/16avt31258742417.tab")
+ }
>
> system("convert tmp/1zvjy1258742417.ps tmp/1zvjy1258742417.png")
> system("convert tmp/2pt2h1258742417.ps tmp/2pt2h1258742417.png")
> system("convert tmp/313qc1258742417.ps tmp/313qc1258742417.png")
> system("convert tmp/4824o1258742417.ps tmp/4824o1258742417.png")
> system("convert tmp/58jsw1258742417.ps tmp/58jsw1258742417.png")
> system("convert tmp/64chy1258742417.ps tmp/64chy1258742417.png")
> system("convert tmp/71sty1258742417.ps tmp/71sty1258742417.png")
> system("convert tmp/8kzzl1258742417.ps tmp/8kzzl1258742417.png")
> system("convert tmp/95t9g1258742417.ps tmp/95t9g1258742417.png")
> system("convert tmp/105iag1258742417.ps tmp/105iag1258742417.png")
>
>
> proc.time()
user system elapsed
2.292 1.511 2.788