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(423
+ ,114
+ ,449
+ ,441
+ ,427
+ ,423
+ ,427
+ ,116
+ ,452
+ ,449
+ ,441
+ ,427
+ ,441
+ ,153
+ ,462
+ ,452
+ ,449
+ ,441
+ ,449
+ ,162
+ ,455
+ ,462
+ ,452
+ ,449
+ ,452
+ ,161
+ ,461
+ ,455
+ ,462
+ ,452
+ ,462
+ ,149
+ ,461
+ ,461
+ ,455
+ ,462
+ ,455
+ ,139
+ ,463
+ ,461
+ ,461
+ ,455
+ ,461
+ ,135
+ ,462
+ ,463
+ ,461
+ ,461
+ ,461
+ ,130
+ ,456
+ ,462
+ ,463
+ ,461
+ ,463
+ ,127
+ ,455
+ ,456
+ ,462
+ ,463
+ ,462
+ ,122
+ ,456
+ ,455
+ ,456
+ ,462
+ ,456
+ ,117
+ ,472
+ ,456
+ ,455
+ ,456
+ ,455
+ ,112
+ ,472
+ ,472
+ ,456
+ ,455
+ ,456
+ ,113
+ ,471
+ ,472
+ ,472
+ ,456
+ ,472
+ ,149
+ ,465
+ ,471
+ ,472
+ ,472
+ ,472
+ ,157
+ ,459
+ ,465
+ ,471
+ ,472
+ ,471
+ ,157
+ ,465
+ ,459
+ ,465
+ ,471
+ ,465
+ ,147
+ ,468
+ ,465
+ ,459
+ ,465
+ ,459
+ ,137
+ ,467
+ ,468
+ ,465
+ ,459
+ ,465
+ ,132
+ ,463
+ ,467
+ ,468
+ ,465
+ ,468
+ ,125
+ ,460
+ ,463
+ ,467
+ ,468
+ ,467
+ ,123
+ ,462
+ ,460
+ ,463
+ ,467
+ ,463
+ ,117
+ ,461
+ ,462
+ ,460
+ ,463
+ ,460
+ ,114
+ ,476
+ ,461
+ ,462
+ ,460
+ ,462
+ ,111
+ ,476
+ ,476
+ ,461
+ ,462
+ ,461
+ ,112
+ ,471
+ ,476
+ ,476
+ ,461
+ ,476
+ ,144
+ ,453
+ ,471
+ ,476
+ ,476
+ ,476
+ ,150
+ ,443
+ ,453
+ ,471
+ ,476
+ ,471
+ ,149
+ ,442
+ ,443
+ ,453
+ ,471
+ ,453
+ ,134
+ ,444
+ ,442
+ ,443
+ ,453
+ ,443
+ ,123
+ ,438
+ ,444
+ ,442
+ ,443
+ ,442
+ ,116
+ ,427
+ ,438
+ ,444
+ ,442
+ ,444
+ ,117
+ ,424
+ ,427
+ ,438
+ ,444
+ ,438
+ ,111
+ ,416
+ ,424
+ ,427
+ ,438
+ ,427
+ ,105
+ ,406
+ ,416
+ ,424
+ ,427
+ ,424
+ ,102
+ ,431
+ ,406
+ ,416
+ ,424
+ ,416
+ ,95
+ ,434
+ ,431
+ ,406
+ ,416
+ ,406
+ ,93
+ ,418
+ ,434
+ ,431
+ ,406
+ ,431
+ ,124
+ ,412
+ ,418
+ ,434
+ ,431
+ ,434
+ ,130
+ ,404
+ ,412
+ ,418
+ ,434
+ ,418
+ ,124
+ ,409
+ ,404
+ ,412
+ ,418
+ ,412
+ ,115
+ ,412
+ ,409
+ ,404
+ ,412
+ ,404
+ ,106
+ ,406
+ ,412
+ ,409
+ ,404
+ ,409
+ ,105
+ ,398
+ ,406
+ ,412
+ ,409
+ ,412
+ ,105
+ ,397
+ ,398
+ ,406
+ ,412
+ ,406
+ ,101
+ ,385
+ ,397
+ ,398
+ ,406
+ ,398
+ ,95
+ ,390
+ ,385
+ ,397
+ ,398
+ ,397
+ ,93
+ ,413
+ ,390
+ ,385
+ ,397
+ ,385
+ ,84
+ ,413
+ ,413
+ ,390
+ ,385
+ ,390
+ ,87
+ ,401
+ ,413
+ ,413
+ ,390
+ ,413
+ ,116
+ ,397
+ ,401
+ ,413
+ ,413
+ ,413
+ ,120
+ ,397
+ ,397
+ ,401
+ ,413
+ ,401
+ ,117
+ ,409
+ ,397
+ ,397
+ ,401
+ ,397
+ ,109
+ ,419
+ ,409
+ ,397
+ ,397
+ ,397
+ ,105
+ ,424
+ ,419
+ ,409
+ ,397
+ ,409
+ ,107
+ ,428
+ ,424
+ ,419
+ ,409
+ ,419
+ ,109
+ ,430
+ ,428
+ ,424
+ ,419)
+ ,dim=c(6
+ ,57)
+ ,dimnames=list(c('Y'
+ ,'X'
+ ,'Y1'
+ ,'Y2'
+ ,'Y3'
+ ,'Y4')
+ ,1:57))
> y <- array(NA,dim=c(6,57),dimnames=list(c('Y','X','Y1','Y2','Y3','Y4'),1:57))
> 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
1 423 114 449 441 427 423 1 0 0 0 0 0 0 0 0 0 0 1
2 427 116 452 449 441 427 0 1 0 0 0 0 0 0 0 0 0 2
3 441 153 462 452 449 441 0 0 1 0 0 0 0 0 0 0 0 3
4 449 162 455 462 452 449 0 0 0 1 0 0 0 0 0 0 0 4
5 452 161 461 455 462 452 0 0 0 0 1 0 0 0 0 0 0 5
6 462 149 461 461 455 462 0 0 0 0 0 1 0 0 0 0 0 6
7 455 139 463 461 461 455 0 0 0 0 0 0 1 0 0 0 0 7
8 461 135 462 463 461 461 0 0 0 0 0 0 0 1 0 0 0 8
9 461 130 456 462 463 461 0 0 0 0 0 0 0 0 1 0 0 9
10 463 127 455 456 462 463 0 0 0 0 0 0 0 0 0 1 0 10
11 462 122 456 455 456 462 0 0 0 0 0 0 0 0 0 0 1 11
12 456 117 472 456 455 456 0 0 0 0 0 0 0 0 0 0 0 12
13 455 112 472 472 456 455 1 0 0 0 0 0 0 0 0 0 0 13
14 456 113 471 472 472 456 0 1 0 0 0 0 0 0 0 0 0 14
15 472 149 465 471 472 472 0 0 1 0 0 0 0 0 0 0 0 15
16 472 157 459 465 471 472 0 0 0 1 0 0 0 0 0 0 0 16
17 471 157 465 459 465 471 0 0 0 0 1 0 0 0 0 0 0 17
18 465 147 468 465 459 465 0 0 0 0 0 1 0 0 0 0 0 18
19 459 137 467 468 465 459 0 0 0 0 0 0 1 0 0 0 0 19
20 465 132 463 467 468 465 0 0 0 0 0 0 0 1 0 0 0 20
21 468 125 460 463 467 468 0 0 0 0 0 0 0 0 1 0 0 21
22 467 123 462 460 463 467 0 0 0 0 0 0 0 0 0 1 0 22
23 463 117 461 462 460 463 0 0 0 0 0 0 0 0 0 0 1 23
24 460 114 476 461 462 460 0 0 0 0 0 0 0 0 0 0 0 24
25 462 111 476 476 461 462 1 0 0 0 0 0 0 0 0 0 0 25
26 461 112 471 476 476 461 0 1 0 0 0 0 0 0 0 0 0 26
27 476 144 453 471 476 476 0 0 1 0 0 0 0 0 0 0 0 27
28 476 150 443 453 471 476 0 0 0 1 0 0 0 0 0 0 0 28
29 471 149 442 443 453 471 0 0 0 0 1 0 0 0 0 0 0 29
30 453 134 444 442 443 453 0 0 0 0 0 1 0 0 0 0 0 30
31 443 123 438 444 442 443 0 0 0 0 0 0 1 0 0 0 0 31
32 442 116 427 438 444 442 0 0 0 0 0 0 0 1 0 0 0 32
33 444 117 424 427 438 444 0 0 0 0 0 0 0 0 1 0 0 33
34 438 111 416 424 427 438 0 0 0 0 0 0 0 0 0 1 0 34
35 427 105 406 416 424 427 0 0 0 0 0 0 0 0 0 0 1 35
36 424 102 431 406 416 424 0 0 0 0 0 0 0 0 0 0 0 36
37 416 95 434 431 406 416 1 0 0 0 0 0 0 0 0 0 0 37
38 406 93 418 434 431 406 0 1 0 0 0 0 0 0 0 0 0 38
39 431 124 412 418 434 431 0 0 1 0 0 0 0 0 0 0 0 39
40 434 130 404 412 418 434 0 0 0 1 0 0 0 0 0 0 0 40
41 418 124 409 404 412 418 0 0 0 0 1 0 0 0 0 0 0 41
42 412 115 412 409 404 412 0 0 0 0 0 1 0 0 0 0 0 42
43 404 106 406 412 409 404 0 0 0 0 0 0 1 0 0 0 0 43
44 409 105 398 406 412 409 0 0 0 0 0 0 0 1 0 0 0 44
45 412 105 397 398 406 412 0 0 0 0 0 0 0 0 1 0 0 45
46 406 101 385 397 398 406 0 0 0 0 0 0 0 0 0 1 0 46
47 398 95 390 385 397 398 0 0 0 0 0 0 0 0 0 0 1 47
48 397 93 413 390 385 397 0 0 0 0 0 0 0 0 0 0 0 48
49 385 84 413 413 390 385 1 0 0 0 0 0 0 0 0 0 0 49
50 390 87 401 413 413 390 0 1 0 0 0 0 0 0 0 0 0 50
51 413 116 397 401 413 413 0 0 1 0 0 0 0 0 0 0 0 51
52 413 120 397 397 401 413 0 0 0 1 0 0 0 0 0 0 0 52
53 401 117 409 397 397 401 0 0 0 0 1 0 0 0 0 0 0 53
54 397 109 419 409 397 397 0 0 0 0 0 1 0 0 0 0 0 54
55 397 105 424 419 409 397 0 0 0 0 0 0 1 0 0 0 0 55
56 409 107 428 424 419 409 0 0 0 0 0 0 0 1 0 0 0 56
57 419 109 430 428 424 419 0 0 0 0 0 0 0 0 1 0 0 57
> k <- length(x[1,])
> df <- as.data.frame(x)
> (mylm <- lm(df))
Call:
lm(formula = df)
Coefficients:
(Intercept) X Y1 Y2 Y3 Y4
-1.269e-14 -2.224e-17 -5.738e-17 1.991e-16 -5.191e-16 1.000e+00
M1 M2 M3 M4 M5 M6
-1.362e-15 7.148e-16 -2.347e-15 -2.934e-15 -2.676e-15 1.685e-15
M7 M8 M9 M10 M11 t
-7.762e-16 -8.751e-16 -1.065e-15 -1.502e-15 -4.614e-16 -1.422e-17
> (mysum <- summary(mylm))
Call:
lm(formula = df)
Residuals:
Min 1Q Median 3Q Max
-4.318e-15 -6.647e-16 -2.145e-16 5.095e-16 1.476e-14
Coefficients:
Estimate Std. Error t value Pr(>|t|)
(Intercept) -1.269e-14 1.381e-14 -9.190e-01 0.363636
X -2.224e-17 1.437e-16 -1.550e-01 0.877805
Y1 -5.738e-17 8.417e-17 -6.820e-01 0.499444
Y2 1.991e-16 1.281e-16 1.555e+00 0.128093
Y3 -5.191e-16 1.256e-16 -4.133e+00 0.000184 ***
Y4 1.000e+00 8.113e-17 1.233e+16 < 2e-16 ***
M1 -1.362e-15 3.263e-15 -4.170e-01 0.678665
M2 7.148e-16 3.653e-15 1.960e-01 0.845873
M3 -2.347e-15 4.876e-15 -4.810e-01 0.632975
M4 -2.934e-15 5.859e-15 -5.010e-01 0.619318
M5 -2.676e-15 5.448e-15 -4.910e-01 0.626007
M6 1.685e-15 4.238e-15 3.980e-01 0.693012
M7 -7.762e-16 3.573e-15 -2.170e-01 0.829139
M8 -8.751e-16 3.390e-15 -2.580e-01 0.797678
M9 -1.065e-15 3.141e-15 -3.390e-01 0.736429
M10 -1.502e-15 3.090e-15 -4.860e-01 0.629576
M11 -4.614e-16 2.738e-15 -1.690e-01 0.867037
t -1.422e-17 7.861e-17 -1.810e-01 0.857411
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
Residual standard error: 2.914e-15 on 39 degrees of freedom
Multiple R-squared: 1, Adjusted R-squared: 1
F-statistic: 2.806e+32 on 17 and 39 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,] 2.204133e-02 4.408267e-02 0.9779586670
[2,] 5.544755e-02 1.108951e-01 0.9445524497
[3,] 6.972603e-01 6.054794e-01 0.3027397128
[4,] 4.561400e-01 9.122800e-01 0.5438599949
[5,] 2.108171e-04 4.216343e-04 0.9997891829
[6,] 9.482378e-02 1.896476e-01 0.9051762221
[7,] 1.514255e-05 3.028510e-05 0.9999848575
[8,] 9.783626e-01 4.327483e-02 0.0216374127
[9,] 1.580517e-01 3.161034e-01 0.8419482753
[10,] 9.110588e-01 1.778825e-01 0.0889412320
[11,] 9.997898e-01 4.203533e-04 0.0002101766
[12,] 2.122726e-09 4.245452e-09 0.9999999979
[13,] 9.835638e-01 3.287249e-02 0.0164362446
[14,] 3.319485e-01 6.638970e-01 0.6680515123
[15,] 9.373986e-01 1.252029e-01 0.0626014375
[16,] 1.000000e+00 0.000000e+00 0.0000000000
> postscript(file="/var/www/html/rcomp/tmp/1g2ww1258738505.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$resid)
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/2nokr1258738505.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> plot(mysum$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/3nrrc1258738505.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> hist(mysum$resid, main='Residual Histogram', xlab='values of Residuals')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/4rc3v1258738505.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> densityplot(~mysum$resid,col='black',main='Residual Density Plot', xlab='values of Residuals')
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/507db1258738505.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 = 57
Frequency = 1
1 2 3 4 5
-1.575666e-15 2.058264e-15 -1.378628e-15 -1.215801e-15 -2.024143e-15
6 7 8 9 10
1.475737e-14 -6.546414e-16 -1.101680e-15 -7.067898e-16 1.205175e-16
11 12 13 14 15
-1.828925e-15 -3.609952e-16 -1.840221e-16 -4.790245e-16 -2.419704e-16
16 17 18 19 20
2.506418e-16 -2.649469e-16 -4.055873e-15 -5.839829e-16 -5.978583e-16
21 22 23 24 25
-3.171493e-16 5.583475e-16 8.494762e-16 2.632884e-16 2.684977e-15
26 27 28 29 30
-3.305526e-16 -4.048223e-16 4.595329e-16 -4.758087e-16 -4.317600e-15
31 32 33 34 35
-4.625810e-16 -2.145303e-16 -1.138203e-16 1.968736e-16 -3.348855e-16
36 37 38 39 40
3.119648e-16 -1.903943e-15 5.094840e-16 4.111947e-16 -6.647440e-16
41 42 43 44 45
1.061551e-15 -4.057728e-15 1.418998e-16 5.254701e-17 2.815788e-16
46 47 48 49 50
-8.757386e-16 1.314335e-15 -2.142579e-16 9.786539e-16 -1.758171e-15
51 52 53 54 55
1.614226e-15 1.170370e-15 1.703347e-15 -2.326174e-15 1.559305e-15
56 57
1.861521e-15 8.561805e-16
> postscript(file="/var/www/html/rcomp/tmp/6b2sg1258738505.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 = 57
Frequency = 1
lag(myerror, k = 1) myerror
0 -1.575666e-15 NA
1 2.058264e-15 -1.575666e-15
2 -1.378628e-15 2.058264e-15
3 -1.215801e-15 -1.378628e-15
4 -2.024143e-15 -1.215801e-15
5 1.475737e-14 -2.024143e-15
6 -6.546414e-16 1.475737e-14
7 -1.101680e-15 -6.546414e-16
8 -7.067898e-16 -1.101680e-15
9 1.205175e-16 -7.067898e-16
10 -1.828925e-15 1.205175e-16
11 -3.609952e-16 -1.828925e-15
12 -1.840221e-16 -3.609952e-16
13 -4.790245e-16 -1.840221e-16
14 -2.419704e-16 -4.790245e-16
15 2.506418e-16 -2.419704e-16
16 -2.649469e-16 2.506418e-16
17 -4.055873e-15 -2.649469e-16
18 -5.839829e-16 -4.055873e-15
19 -5.978583e-16 -5.839829e-16
20 -3.171493e-16 -5.978583e-16
21 5.583475e-16 -3.171493e-16
22 8.494762e-16 5.583475e-16
23 2.632884e-16 8.494762e-16
24 2.684977e-15 2.632884e-16
25 -3.305526e-16 2.684977e-15
26 -4.048223e-16 -3.305526e-16
27 4.595329e-16 -4.048223e-16
28 -4.758087e-16 4.595329e-16
29 -4.317600e-15 -4.758087e-16
30 -4.625810e-16 -4.317600e-15
31 -2.145303e-16 -4.625810e-16
32 -1.138203e-16 -2.145303e-16
33 1.968736e-16 -1.138203e-16
34 -3.348855e-16 1.968736e-16
35 3.119648e-16 -3.348855e-16
36 -1.903943e-15 3.119648e-16
37 5.094840e-16 -1.903943e-15
38 4.111947e-16 5.094840e-16
39 -6.647440e-16 4.111947e-16
40 1.061551e-15 -6.647440e-16
41 -4.057728e-15 1.061551e-15
42 1.418998e-16 -4.057728e-15
43 5.254701e-17 1.418998e-16
44 2.815788e-16 5.254701e-17
45 -8.757386e-16 2.815788e-16
46 1.314335e-15 -8.757386e-16
47 -2.142579e-16 1.314335e-15
48 9.786539e-16 -2.142579e-16
49 -1.758171e-15 9.786539e-16
50 1.614226e-15 -1.758171e-15
51 1.170370e-15 1.614226e-15
52 1.703347e-15 1.170370e-15
53 -2.326174e-15 1.703347e-15
54 1.559305e-15 -2.326174e-15
55 1.861521e-15 1.559305e-15
56 8.561805e-16 1.861521e-15
57 NA 8.561805e-16
> dum1 <- dum[2:length(myerror),]
> dum1
lag(myerror, k = 1) myerror
[1,] 2.058264e-15 -1.575666e-15
[2,] -1.378628e-15 2.058264e-15
[3,] -1.215801e-15 -1.378628e-15
[4,] -2.024143e-15 -1.215801e-15
[5,] 1.475737e-14 -2.024143e-15
[6,] -6.546414e-16 1.475737e-14
[7,] -1.101680e-15 -6.546414e-16
[8,] -7.067898e-16 -1.101680e-15
[9,] 1.205175e-16 -7.067898e-16
[10,] -1.828925e-15 1.205175e-16
[11,] -3.609952e-16 -1.828925e-15
[12,] -1.840221e-16 -3.609952e-16
[13,] -4.790245e-16 -1.840221e-16
[14,] -2.419704e-16 -4.790245e-16
[15,] 2.506418e-16 -2.419704e-16
[16,] -2.649469e-16 2.506418e-16
[17,] -4.055873e-15 -2.649469e-16
[18,] -5.839829e-16 -4.055873e-15
[19,] -5.978583e-16 -5.839829e-16
[20,] -3.171493e-16 -5.978583e-16
[21,] 5.583475e-16 -3.171493e-16
[22,] 8.494762e-16 5.583475e-16
[23,] 2.632884e-16 8.494762e-16
[24,] 2.684977e-15 2.632884e-16
[25,] -3.305526e-16 2.684977e-15
[26,] -4.048223e-16 -3.305526e-16
[27,] 4.595329e-16 -4.048223e-16
[28,] -4.758087e-16 4.595329e-16
[29,] -4.317600e-15 -4.758087e-16
[30,] -4.625810e-16 -4.317600e-15
[31,] -2.145303e-16 -4.625810e-16
[32,] -1.138203e-16 -2.145303e-16
[33,] 1.968736e-16 -1.138203e-16
[34,] -3.348855e-16 1.968736e-16
[35,] 3.119648e-16 -3.348855e-16
[36,] -1.903943e-15 3.119648e-16
[37,] 5.094840e-16 -1.903943e-15
[38,] 4.111947e-16 5.094840e-16
[39,] -6.647440e-16 4.111947e-16
[40,] 1.061551e-15 -6.647440e-16
[41,] -4.057728e-15 1.061551e-15
[42,] 1.418998e-16 -4.057728e-15
[43,] 5.254701e-17 1.418998e-16
[44,] 2.815788e-16 5.254701e-17
[45,] -8.757386e-16 2.815788e-16
[46,] 1.314335e-15 -8.757386e-16
[47,] -2.142579e-16 1.314335e-15
[48,] 9.786539e-16 -2.142579e-16
[49,] -1.758171e-15 9.786539e-16
[50,] 1.614226e-15 -1.758171e-15
[51,] 1.170370e-15 1.614226e-15
[52,] 1.703347e-15 1.170370e-15
[53,] -2.326174e-15 1.703347e-15
[54,] 1.559305e-15 -2.326174e-15
[55,] 1.861521e-15 1.559305e-15
[56,] 8.561805e-16 1.861521e-15
> z <- as.data.frame(dum1)
> z
lag(myerror, k = 1) myerror
1 2.058264e-15 -1.575666e-15
2 -1.378628e-15 2.058264e-15
3 -1.215801e-15 -1.378628e-15
4 -2.024143e-15 -1.215801e-15
5 1.475737e-14 -2.024143e-15
6 -6.546414e-16 1.475737e-14
7 -1.101680e-15 -6.546414e-16
8 -7.067898e-16 -1.101680e-15
9 1.205175e-16 -7.067898e-16
10 -1.828925e-15 1.205175e-16
11 -3.609952e-16 -1.828925e-15
12 -1.840221e-16 -3.609952e-16
13 -4.790245e-16 -1.840221e-16
14 -2.419704e-16 -4.790245e-16
15 2.506418e-16 -2.419704e-16
16 -2.649469e-16 2.506418e-16
17 -4.055873e-15 -2.649469e-16
18 -5.839829e-16 -4.055873e-15
19 -5.978583e-16 -5.839829e-16
20 -3.171493e-16 -5.978583e-16
21 5.583475e-16 -3.171493e-16
22 8.494762e-16 5.583475e-16
23 2.632884e-16 8.494762e-16
24 2.684977e-15 2.632884e-16
25 -3.305526e-16 2.684977e-15
26 -4.048223e-16 -3.305526e-16
27 4.595329e-16 -4.048223e-16
28 -4.758087e-16 4.595329e-16
29 -4.317600e-15 -4.758087e-16
30 -4.625810e-16 -4.317600e-15
31 -2.145303e-16 -4.625810e-16
32 -1.138203e-16 -2.145303e-16
33 1.968736e-16 -1.138203e-16
34 -3.348855e-16 1.968736e-16
35 3.119648e-16 -3.348855e-16
36 -1.903943e-15 3.119648e-16
37 5.094840e-16 -1.903943e-15
38 4.111947e-16 5.094840e-16
39 -6.647440e-16 4.111947e-16
40 1.061551e-15 -6.647440e-16
41 -4.057728e-15 1.061551e-15
42 1.418998e-16 -4.057728e-15
43 5.254701e-17 1.418998e-16
44 2.815788e-16 5.254701e-17
45 -8.757386e-16 2.815788e-16
46 1.314335e-15 -8.757386e-16
47 -2.142579e-16 1.314335e-15
48 9.786539e-16 -2.142579e-16
49 -1.758171e-15 9.786539e-16
50 1.614226e-15 -1.758171e-15
51 1.170370e-15 1.614226e-15
52 1.703347e-15 1.170370e-15
53 -2.326174e-15 1.703347e-15
54 1.559305e-15 -2.326174e-15
55 1.861521e-15 1.559305e-15
56 8.561805e-16 1.861521e-15
> 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/70phn1258738505.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> acf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/8a3gx1258738505.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> pacf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Partial Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/903sz1258738505.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> opar <- par(mfrow = c(2,2), oma = c(0, 0, 1.1, 0))
> plot(mylm, las = 1, sub='Residual Diagnostics')
> par(opar)
> dev.off()
null device
1
> if (n > n25) {
+ postscript(file="/var/www/html/rcomp/tmp/10e9o61258738505.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
+ plot(kp3:nmkm3,gqarr[,2], main='Goldfeld-Quandt test',ylab='2-sided p-value',xlab='breakpoint')
+ grid()
+ dev.off()
+ }
null device
1
>
> #Note: the /var/www/html/rcomp/createtable file can be downloaded at http://www.wessa.net/cretab
> load(file="/var/www/html/rcomp/createtable")
>
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a, 'Multiple Linear Regression - Estimated Regression Equation', 1, TRUE)
> a<-table.row.end(a)
> myeq <- colnames(x)[1]
> myeq <- paste(myeq, '[t] = ', sep='')
> for (i in 1:k){
+ if (mysum$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/11jbt71258738505.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/1282pr1258738505.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/130gb41258738505.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/14vvix1258738505.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/15h4f51258738505.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/16dw9i1258738505.tab")
+ }
>
> system("convert tmp/1g2ww1258738505.ps tmp/1g2ww1258738505.png")
> system("convert tmp/2nokr1258738505.ps tmp/2nokr1258738505.png")
> system("convert tmp/3nrrc1258738505.ps tmp/3nrrc1258738505.png")
> system("convert tmp/4rc3v1258738505.ps tmp/4rc3v1258738505.png")
> system("convert tmp/507db1258738505.ps tmp/507db1258738505.png")
> system("convert tmp/6b2sg1258738505.ps tmp/6b2sg1258738505.png")
> system("convert tmp/70phn1258738505.ps tmp/70phn1258738505.png")
> system("convert tmp/8a3gx1258738505.ps tmp/8a3gx1258738505.png")
> system("convert tmp/903sz1258738505.ps tmp/903sz1258738505.png")
> system("convert tmp/10e9o61258738505.ps tmp/10e9o61258738505.png")
>
>
> proc.time()
user system elapsed
2.408 1.582 2.827