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(-999.00
+ ,38.60
+ ,6654.00
+ ,5712.00
+ ,645.00
+ ,3.30
+ ,3.00
+ ,5.00
+ ,3.00
+ ,6.30
+ ,4.50
+ ,1.00
+ ,6600.00
+ ,42.00
+ ,8.30
+ ,3.00
+ ,1.00
+ ,3.00
+ ,-999.00
+ ,14.00
+ ,3.39
+ ,44.50
+ ,60.00
+ ,12.50
+ ,1.00
+ ,1.00
+ ,1.00
+ ,-999.00
+ ,-999.00
+ ,0.92
+ ,5.70
+ ,25.00
+ ,16.50
+ ,5.00
+ ,2.00
+ ,3.00
+ ,2.10
+ ,69.00
+ ,2547.00
+ ,4603.00
+ ,624.00
+ ,3.90
+ ,3.00
+ ,5.00
+ ,4.00
+ ,9.10
+ ,27.00
+ ,10.55
+ ,179.50
+ ,180.00
+ ,9.80
+ ,4.00
+ ,4.00
+ ,4.00
+ ,15.80
+ ,19.00
+ ,0.02
+ ,0.30
+ ,35.00
+ ,19.70
+ ,1.00
+ ,1.00
+ ,1.00
+ ,5.20
+ ,30.40
+ ,160.00
+ ,169.00
+ ,392.00
+ ,6.20
+ ,4.00
+ ,5.00
+ ,4.00
+ ,10.90
+ ,28.00
+ ,3.30
+ ,25.60
+ ,63.00
+ ,14.50
+ ,1.00
+ ,2.00
+ ,1.00
+ ,8.30
+ ,50.00
+ ,52.16
+ ,440.00
+ ,230.00
+ ,9.70
+ ,1.00
+ ,1.00
+ ,1.00
+ ,11.00
+ ,7.00
+ ,0.43
+ ,6.40
+ ,112.00
+ ,12.50
+ ,5.00
+ ,4.00
+ ,4.00
+ ,3.20
+ ,30.00
+ ,465.00
+ ,423.00
+ ,281.00
+ ,3.90
+ ,5.00
+ ,5.00
+ ,5.00
+ ,7.60
+ ,-999.00
+ ,0.55
+ ,2.40
+ ,-999.00
+ ,10.30
+ ,2.00
+ ,1.00
+ ,2.00
+ ,-999.00
+ ,40.00
+ ,187.10
+ ,419.00
+ ,365.00
+ ,3.10
+ ,5.00
+ ,5.00
+ ,5.00
+ ,6.30
+ ,3.50
+ ,0.08
+ ,1.20
+ ,42.00
+ ,8.40
+ ,1.00
+ ,1.00
+ ,1.00
+ ,8.60
+ ,50.00
+ ,3.00
+ ,25.00
+ ,28.00
+ ,8.60
+ ,2.00
+ ,2.00
+ ,2.00
+ ,6.60
+ ,6.00
+ ,0.79
+ ,3500.00
+ ,42.00
+ ,10.70
+ ,2.00
+ ,2.00
+ ,2.00
+ ,9.50
+ ,10.40
+ ,0.20
+ ,5.00
+ ,120.00
+ ,10.70
+ ,2.00
+ ,2.00
+ ,2.00
+ ,4.80
+ ,34.00
+ ,1.41
+ ,17.50
+ ,-999.00
+ ,6.10
+ ,1.00
+ ,2.00
+ ,1.00
+ ,12.00
+ ,7.00
+ ,60.00
+ ,81.00
+ ,-999.00
+ ,18.10
+ ,1.00
+ ,1.00
+ ,1.00
+ ,-999.00
+ ,28.00
+ ,529.00
+ ,680.00
+ ,400.00
+ ,-999.00
+ ,5.00
+ ,5.00
+ ,5.00
+ ,3.30
+ ,20.00
+ ,27.66
+ ,115.00
+ ,148.00
+ ,3.80
+ ,5.00
+ ,5.00
+ ,5.00
+ ,11.00
+ ,3.90
+ ,0.12
+ ,1.00
+ ,16.00
+ ,14.40
+ ,3.00
+ ,1.00
+ ,2.00
+ ,-999.00
+ ,39.30
+ ,207.00
+ ,406.00
+ ,252.00
+ ,12.00
+ ,1.00
+ ,4.00
+ ,1.00
+ ,4.70
+ ,41.00
+ ,85.00
+ ,325.00
+ ,310.00
+ ,6.20
+ ,1.00
+ ,3.00
+ ,1.00
+ ,-999.00
+ ,16.20
+ ,36.33
+ ,119.50
+ ,63.00
+ ,13.00
+ ,1.00
+ ,1.00
+ ,1.00
+ ,10.40
+ ,9.00
+ ,0.10
+ ,4.00
+ ,28.00
+ ,13.80
+ ,5.00
+ ,1.00
+ ,3.00
+ ,7.40
+ ,7.60
+ ,1.04
+ ,5.50
+ ,68.00
+ ,8.20
+ ,5.00
+ ,3.00
+ ,4.00
+ ,2.10
+ ,46.00
+ ,521.00
+ ,655.00
+ ,336.00
+ ,2.90
+ ,5.00
+ ,5.00
+ ,5.00
+ ,-999.00
+ ,22.40
+ ,100.00
+ ,157.00
+ ,100.00
+ ,10.80
+ ,1.00
+ ,1.00
+ ,1.00
+ ,-999.00
+ ,16.30
+ ,35.00
+ ,56.00
+ ,33.00
+ ,-999.00
+ ,3.00
+ ,5.00
+ ,4.00
+ ,7.70
+ ,2.60
+ ,0.01
+ ,0.14
+ ,21.50
+ ,9.10
+ ,5.00
+ ,2.00
+ ,4.00
+ ,17.90
+ ,24.00
+ ,0.01
+ ,0.25
+ ,50.00
+ ,19.90
+ ,1.00
+ ,1.00
+ ,1.00
+ ,6.10
+ ,100.00
+ ,62.00
+ ,1320.00
+ ,267.00
+ ,8.00
+ ,1.00
+ ,1.00
+ ,1.00
+ ,8.20
+ ,-999.00
+ ,0.12
+ ,3.00
+ ,30.00
+ ,10.60
+ ,2.00
+ ,1.00
+ ,1.00
+ ,8.40
+ ,-999.00
+ ,1.35
+ ,8.10
+ ,45.00
+ ,11.20
+ ,3.00
+ ,1.00
+ ,3.00
+ ,11.90
+ ,3.20
+ ,0.02
+ ,0.40
+ ,19.00
+ ,13.20
+ ,4.00
+ ,1.00
+ ,3.00
+ ,10.80
+ ,2.00
+ ,0.05
+ ,0.33
+ ,30.00
+ ,12.80
+ ,4.00
+ ,1.00
+ ,3.00
+ ,13.80
+ ,5.00
+ ,1.70
+ ,6.30
+ ,12.00
+ ,19.40
+ ,2.00
+ ,1.00
+ ,1.00
+ ,14.30
+ ,6.50
+ ,3.50
+ ,10.80
+ ,120.00
+ ,17.40
+ ,2.00
+ ,1.00
+ ,1.00
+ ,-999.00
+ ,23.60
+ ,250.00
+ ,490.00
+ ,440.00
+ ,-999.00
+ ,5.00
+ ,5.00
+ ,5.00
+ ,15.20
+ ,12.00
+ ,0.48
+ ,15.50
+ ,140.00
+ ,17.00
+ ,2.00
+ ,2.00
+ ,2.00
+ ,10.00
+ ,20.20
+ ,10.00
+ ,115.00
+ ,170.00
+ ,10.90
+ ,4.00
+ ,4.00
+ ,4.00
+ ,11.90
+ ,13.00
+ ,1.62
+ ,11.40
+ ,17.00
+ ,13.70
+ ,2.00
+ ,1.00
+ ,2.00
+ ,6.50
+ ,27.00
+ ,192.00
+ ,180.00
+ ,115.00
+ ,8.40
+ ,4.00
+ ,4.00
+ ,4.00
+ ,7.50
+ ,18.00
+ ,2.50
+ ,12.10
+ ,31.00
+ ,8.40
+ ,5.00
+ ,5.00
+ ,5.00
+ ,-999.00
+ ,13.70
+ ,4.29
+ ,39.20
+ ,63.00
+ ,12.50
+ ,2.00
+ ,2.00
+ ,2.00
+ ,10.60
+ ,4.70
+ ,0.28
+ ,1.90
+ ,21.00
+ ,13.20
+ ,3.00
+ ,1.00
+ ,3.00
+ ,7.40
+ ,9.80
+ ,4.24
+ ,50.40
+ ,52.00
+ ,9.80
+ ,1.00
+ ,1.00
+ ,1.00
+ ,8.40
+ ,29.00
+ ,6.80
+ ,179.00
+ ,164.00
+ ,9.60
+ ,2.00
+ ,3.00
+ ,2.00
+ ,5.70
+ ,7.00
+ ,0.75
+ ,12.30
+ ,225.00
+ ,6.60
+ ,2.00
+ ,2.00
+ ,2.00
+ ,4.90
+ ,6.00
+ ,3.60
+ ,21.00
+ ,225.00
+ ,5.40
+ ,3.00
+ ,2.00
+ ,3.00
+ ,-999.00
+ ,17.00
+ ,14.83
+ ,98.20
+ ,150.00
+ ,2.60
+ ,5.00
+ ,5.00
+ ,5.00
+ ,3.20
+ ,20.00
+ ,55.50
+ ,175.00
+ ,151.00
+ ,3.80
+ ,5.00
+ ,5.00
+ ,5.00
+ ,-999.00
+ ,12.70
+ ,1.40
+ ,12.50
+ ,90.00
+ ,11.00
+ ,2.00
+ ,2.00
+ ,2.00
+ ,8.10
+ ,3.50
+ ,0.06
+ ,1.00
+ ,-999.00
+ ,10.30
+ ,3.00
+ ,1.00
+ ,2.00
+ ,11.00
+ ,4.50
+ ,0.90
+ ,2.60
+ ,60.00
+ ,13.30
+ ,2.00
+ ,1.00
+ ,2.00
+ ,4.90
+ ,7.50
+ ,2.00
+ ,12.30
+ ,200.00
+ ,5.40
+ ,3.00
+ ,1.00
+ ,3.00
+ ,13.20
+ ,2.30
+ ,0.10
+ ,2.50
+ ,46.00
+ ,15.80
+ ,3.00
+ ,2.00
+ ,2.00
+ ,9.70
+ ,24.00
+ ,4.19
+ ,58.00
+ ,210.00
+ ,10.30
+ ,4.00
+ ,3.00
+ ,4.00
+ ,12.80
+ ,3.00
+ ,3.50
+ ,3.90
+ ,14.00
+ ,19.40
+ ,2.00
+ ,1.00
+ ,1.00
+ ,-999.00
+ ,13.00
+ ,4.05
+ ,17.00
+ ,38.00
+ ,-999.00
+ ,3.00
+ ,1.00
+ ,1.00)
+ ,dim=c(9
+ ,62)
+ ,dimnames=list(c('SWS'
+ ,'L'
+ ,'Wb'
+ ,'Wbr'
+ ,'Tg'
+ ,'Ts'
+ ,'P'
+ ,'S'
+ ,'D')
+ ,1:62))
> y <- array(NA,dim=c(9,62),dimnames=list(c('SWS','L','Wb','Wbr','Tg','Ts','P','S','D'),1:62))
> for (i in 1:dim(x)[1])
+ {
+ for (j in 1:dim(x)[2])
+ {
+ y[i,j] <- as.numeric(x[i,j])
+ }
+ }
> par3 = 'No Linear Trend'
> par2 = 'Do not include Seasonal Dummies'
> par1 = '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
SWS L Wb Wbr Tg Ts P S D
1 -999.0 38.6 6654.00 5712.00 645.0 3.3 3 5 3
2 6.3 4.5 1.00 6600.00 42.0 8.3 3 1 3
3 -999.0 14.0 3.39 44.50 60.0 12.5 1 1 1
4 -999.0 -999.0 0.92 5.70 25.0 16.5 5 2 3
5 2.1 69.0 2547.00 4603.00 624.0 3.9 3 5 4
6 9.1 27.0 10.55 179.50 180.0 9.8 4 4 4
7 15.8 19.0 0.02 0.30 35.0 19.7 1 1 1
8 5.2 30.4 160.00 169.00 392.0 6.2 4 5 4
9 10.9 28.0 3.30 25.60 63.0 14.5 1 2 1
10 8.3 50.0 52.16 440.00 230.0 9.7 1 1 1
11 11.0 7.0 0.43 6.40 112.0 12.5 5 4 4
12 3.2 30.0 465.00 423.00 281.0 3.9 5 5 5
13 7.6 -999.0 0.55 2.40 -999.0 10.3 2 1 2
14 -999.0 40.0 187.10 419.00 365.0 3.1 5 5 5
15 6.3 3.5 0.08 1.20 42.0 8.4 1 1 1
16 8.6 50.0 3.00 25.00 28.0 8.6 2 2 2
17 6.6 6.0 0.79 3500.00 42.0 10.7 2 2 2
18 9.5 10.4 0.20 5.00 120.0 10.7 2 2 2
19 4.8 34.0 1.41 17.50 -999.0 6.1 1 2 1
20 12.0 7.0 60.00 81.00 -999.0 18.1 1 1 1
21 -999.0 28.0 529.00 680.00 400.0 -999.0 5 5 5
22 3.3 20.0 27.66 115.00 148.0 3.8 5 5 5
23 11.0 3.9 0.12 1.00 16.0 14.4 3 1 2
24 -999.0 39.3 207.00 406.00 252.0 12.0 1 4 1
25 4.7 41.0 85.00 325.00 310.0 6.2 1 3 1
26 -999.0 16.2 36.33 119.50 63.0 13.0 1 1 1
27 10.4 9.0 0.10 4.00 28.0 13.8 5 1 3
28 7.4 7.6 1.04 5.50 68.0 8.2 5 3 4
29 2.1 46.0 521.00 655.00 336.0 2.9 5 5 5
30 -999.0 22.4 100.00 157.00 100.0 10.8 1 1 1
31 -999.0 16.3 35.00 56.00 33.0 -999.0 3 5 4
32 7.7 2.6 0.01 0.14 21.5 9.1 5 2 4
33 17.9 24.0 0.01 0.25 50.0 19.9 1 1 1
34 6.1 100.0 62.00 1320.00 267.0 8.0 1 1 1
35 8.2 -999.0 0.12 3.00 30.0 10.6 2 1 1
36 8.4 -999.0 1.35 8.10 45.0 11.2 3 1 3
37 11.9 3.2 0.02 0.40 19.0 13.2 4 1 3
38 10.8 2.0 0.05 0.33 30.0 12.8 4 1 3
39 13.8 5.0 1.70 6.30 12.0 19.4 2 1 1
40 14.3 6.5 3.50 10.80 120.0 17.4 2 1 1
41 -999.0 23.6 250.00 490.00 440.0 -999.0 5 5 5
42 15.2 12.0 0.48 15.50 140.0 17.0 2 2 2
43 10.0 20.2 10.00 115.00 170.0 10.9 4 4 4
44 11.9 13.0 1.62 11.40 17.0 13.7 2 1 2
45 6.5 27.0 192.00 180.00 115.0 8.4 4 4 4
46 7.5 18.0 2.50 12.10 31.0 8.4 5 5 5
47 -999.0 13.7 4.29 39.20 63.0 12.5 2 2 2
48 10.6 4.7 0.28 1.90 21.0 13.2 3 1 3
49 7.4 9.8 4.24 50.40 52.0 9.8 1 1 1
50 8.4 29.0 6.80 179.00 164.0 9.6 2 3 2
51 5.7 7.0 0.75 12.30 225.0 6.6 2 2 2
52 4.9 6.0 3.60 21.00 225.0 5.4 3 2 3
53 -999.0 17.0 14.83 98.20 150.0 2.6 5 5 5
54 3.2 20.0 55.50 175.00 151.0 3.8 5 5 5
55 -999.0 12.7 1.40 12.50 90.0 11.0 2 2 2
56 8.1 3.5 0.06 1.00 -999.0 10.3 3 1 2
57 11.0 4.5 0.90 2.60 60.0 13.3 2 1 2
58 4.9 7.5 2.00 12.30 200.0 5.4 3 1 3
59 13.2 2.3 0.10 2.50 46.0 15.8 3 2 2
60 9.7 24.0 4.19 58.00 210.0 10.3 4 3 4
61 12.8 3.0 3.50 3.90 14.0 19.4 2 1 1
62 -999.0 13.0 4.05 17.00 38.0 -999.0 3 1 1
> k <- length(x[1,])
> df <- as.data.frame(x)
> (mylm <- lm(df))
Call:
lm(formula = df)
Coefficients:
(Intercept) L Wb Wbr Tg Ts
-192.39825 0.19698 -0.08943 0.02707 -0.16299 0.78501
P S D
-25.97234 -83.02757 121.61624
> (mysum <- summary(mylm))
Call:
lm(formula = df)
Residuals:
Min 1Q Median 3Q Max
-851.957 3.688 114.611 188.283 407.236
Coefficients:
Estimate Std. Error t value Pr(>|t|)
(Intercept) -192.39825 111.81220 -1.721 0.091134 .
L 0.19698 0.20084 0.981 0.331151
Wb -0.08943 0.07648 -1.169 0.247484
Wbr 0.02707 0.05041 0.537 0.593488
Tg -0.16299 0.17656 -0.923 0.360124
Ts 0.78501 0.19829 3.959 0.000226 ***
P -25.97234 91.79060 -0.283 0.778316
S -83.02757 60.60128 -1.370 0.176443
D 121.61624 120.37882 1.010 0.316952
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
Residual standard error: 368.8 on 53 degrees of freedom
Multiple R-squared: 0.3452, Adjusted R-squared: 0.2464
F-statistic: 3.493 on 8 and 53 DF, p-value: 0.002625
> 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,] 0.73461087 0.5307783 0.26538913
[2,] 0.75864345 0.4827131 0.24135655
[3,] 0.93230065 0.1353987 0.06769935
[4,] 0.92593842 0.1481232 0.07406158
[5,] 0.88872832 0.2225434 0.11127168
[6,] 0.84788168 0.3042366 0.15211832
[7,] 0.80122798 0.3975440 0.19877202
[8,] 0.76698337 0.4660333 0.23301663
[9,] 0.71415845 0.5716831 0.28584155
[10,] 0.65102201 0.6979560 0.34897799
[11,] 0.56829259 0.8634148 0.43170741
[12,] 0.54946647 0.9010671 0.45053353
[13,] 0.61993452 0.7601310 0.38006548
[14,] 0.64303910 0.7139218 0.35696090
[15,] 0.85981524 0.2803695 0.14018476
[16,] 0.82073360 0.3585328 0.17926640
[17,] 0.76004692 0.4799062 0.23995308
[18,] 0.70042461 0.5991508 0.29957539
[19,] 0.89105564 0.2178887 0.10894436
[20,] 0.86995915 0.2600817 0.13004085
[21,] 0.81856413 0.3628717 0.18143587
[22,] 0.78047471 0.4390506 0.21952529
[23,] 0.73897768 0.5220446 0.26102232
[24,] 0.74779711 0.5044058 0.25220289
[25,] 0.68196664 0.6360667 0.31803336
[26,] 0.61043179 0.7791364 0.38956821
[27,] 0.55275421 0.8944916 0.44724579
[28,] 0.47776692 0.9555338 0.52223308
[29,] 0.40347374 0.8069475 0.59652626
[30,] 0.31412605 0.6282521 0.68587395
[31,] 0.27469638 0.5493928 0.72530362
[32,] 0.21191109 0.4238222 0.78808891
[33,] 0.15040704 0.3008141 0.84959296
[34,] 0.09775267 0.1955053 0.90224733
[35,] 0.32907888 0.6581578 0.67092112
[36,] 0.52523455 0.9495309 0.47476545
[37,] 0.40316565 0.8063313 0.59683435
[38,] 0.27407763 0.5481553 0.72592237
[39,] 0.16656039 0.3331208 0.83343961
> postscript(file="/var/www/html/rcomp/tmp/12z3a1292961589.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$resid)
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/22z3a1292961589.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> plot(mysum$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/3dq2v1292961589.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> hist(mysum$resid, main='Residual Histogram', xlab='values of Residuals')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/4dq2v1292961589.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> densityplot(~mysum$resid,col='black',main='Residual Density Plot', xlab='values of Residuals')
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/5dq2v1292961589.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 = 62
Frequency = 1
1 2 3 4 5 6
-143.026588 -184.347521 -822.910460 -687.700039 389.308038 163.443835
7 8 9 10 11 12
182.073016 292.931392 266.681952 200.859302 185.833989 199.479734
13 14 15 16 17 18
117.592093 -815.115186 185.618723 163.320743 76.348657 185.658865
19 20 21 22 23 24
92.947900 16.539378 3.118505 149.176976 111.629548 -538.702198
25 26 27 28 29 30
386.924225 -822.331910 42.697271 95.371072 203.704965 -811.116682
31 32 33 34 35 36
-12.008608 5.395811 185.476437 173.232156 407.235910 192.121561
37 38 39 40 41 42
18.461811 19.709670 205.277597 224.694321 -9.302503 189.098763
43 44 45 46 47 48
164.886838 85.329784 167.562002 131.625594 -834.754761 -8.797368
49 50 51 52 53 54
185.048738 267.837432 202.712745 107.427179 -851.956674 150.431371
55 56 57 58 59 60
-828.515146 -53.414403 93.600578 20.121803 200.920610 88.824900
61 62
205.223487 20.482772
> postscript(file="/var/www/html/rcomp/tmp/6o0jy1292961589.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 = 62
Frequency = 1
lag(myerror, k = 1) myerror
0 -143.026588 NA
1 -184.347521 -143.026588
2 -822.910460 -184.347521
3 -687.700039 -822.910460
4 389.308038 -687.700039
5 163.443835 389.308038
6 182.073016 163.443835
7 292.931392 182.073016
8 266.681952 292.931392
9 200.859302 266.681952
10 185.833989 200.859302
11 199.479734 185.833989
12 117.592093 199.479734
13 -815.115186 117.592093
14 185.618723 -815.115186
15 163.320743 185.618723
16 76.348657 163.320743
17 185.658865 76.348657
18 92.947900 185.658865
19 16.539378 92.947900
20 3.118505 16.539378
21 149.176976 3.118505
22 111.629548 149.176976
23 -538.702198 111.629548
24 386.924225 -538.702198
25 -822.331910 386.924225
26 42.697271 -822.331910
27 95.371072 42.697271
28 203.704965 95.371072
29 -811.116682 203.704965
30 -12.008608 -811.116682
31 5.395811 -12.008608
32 185.476437 5.395811
33 173.232156 185.476437
34 407.235910 173.232156
35 192.121561 407.235910
36 18.461811 192.121561
37 19.709670 18.461811
38 205.277597 19.709670
39 224.694321 205.277597
40 -9.302503 224.694321
41 189.098763 -9.302503
42 164.886838 189.098763
43 85.329784 164.886838
44 167.562002 85.329784
45 131.625594 167.562002
46 -834.754761 131.625594
47 -8.797368 -834.754761
48 185.048738 -8.797368
49 267.837432 185.048738
50 202.712745 267.837432
51 107.427179 202.712745
52 -851.956674 107.427179
53 150.431371 -851.956674
54 -828.515146 150.431371
55 -53.414403 -828.515146
56 93.600578 -53.414403
57 20.121803 93.600578
58 200.920610 20.121803
59 88.824900 200.920610
60 205.223487 88.824900
61 20.482772 205.223487
62 NA 20.482772
> dum1 <- dum[2:length(myerror),]
> dum1
lag(myerror, k = 1) myerror
[1,] -184.347521 -143.026588
[2,] -822.910460 -184.347521
[3,] -687.700039 -822.910460
[4,] 389.308038 -687.700039
[5,] 163.443835 389.308038
[6,] 182.073016 163.443835
[7,] 292.931392 182.073016
[8,] 266.681952 292.931392
[9,] 200.859302 266.681952
[10,] 185.833989 200.859302
[11,] 199.479734 185.833989
[12,] 117.592093 199.479734
[13,] -815.115186 117.592093
[14,] 185.618723 -815.115186
[15,] 163.320743 185.618723
[16,] 76.348657 163.320743
[17,] 185.658865 76.348657
[18,] 92.947900 185.658865
[19,] 16.539378 92.947900
[20,] 3.118505 16.539378
[21,] 149.176976 3.118505
[22,] 111.629548 149.176976
[23,] -538.702198 111.629548
[24,] 386.924225 -538.702198
[25,] -822.331910 386.924225
[26,] 42.697271 -822.331910
[27,] 95.371072 42.697271
[28,] 203.704965 95.371072
[29,] -811.116682 203.704965
[30,] -12.008608 -811.116682
[31,] 5.395811 -12.008608
[32,] 185.476437 5.395811
[33,] 173.232156 185.476437
[34,] 407.235910 173.232156
[35,] 192.121561 407.235910
[36,] 18.461811 192.121561
[37,] 19.709670 18.461811
[38,] 205.277597 19.709670
[39,] 224.694321 205.277597
[40,] -9.302503 224.694321
[41,] 189.098763 -9.302503
[42,] 164.886838 189.098763
[43,] 85.329784 164.886838
[44,] 167.562002 85.329784
[45,] 131.625594 167.562002
[46,] -834.754761 131.625594
[47,] -8.797368 -834.754761
[48,] 185.048738 -8.797368
[49,] 267.837432 185.048738
[50,] 202.712745 267.837432
[51,] 107.427179 202.712745
[52,] -851.956674 107.427179
[53,] 150.431371 -851.956674
[54,] -828.515146 150.431371
[55,] -53.414403 -828.515146
[56,] 93.600578 -53.414403
[57,] 20.121803 93.600578
[58,] 200.920610 20.121803
[59,] 88.824900 200.920610
[60,] 205.223487 88.824900
[61,] 20.482772 205.223487
> z <- as.data.frame(dum1)
> z
lag(myerror, k = 1) myerror
1 -184.347521 -143.026588
2 -822.910460 -184.347521
3 -687.700039 -822.910460
4 389.308038 -687.700039
5 163.443835 389.308038
6 182.073016 163.443835
7 292.931392 182.073016
8 266.681952 292.931392
9 200.859302 266.681952
10 185.833989 200.859302
11 199.479734 185.833989
12 117.592093 199.479734
13 -815.115186 117.592093
14 185.618723 -815.115186
15 163.320743 185.618723
16 76.348657 163.320743
17 185.658865 76.348657
18 92.947900 185.658865
19 16.539378 92.947900
20 3.118505 16.539378
21 149.176976 3.118505
22 111.629548 149.176976
23 -538.702198 111.629548
24 386.924225 -538.702198
25 -822.331910 386.924225
26 42.697271 -822.331910
27 95.371072 42.697271
28 203.704965 95.371072
29 -811.116682 203.704965
30 -12.008608 -811.116682
31 5.395811 -12.008608
32 185.476437 5.395811
33 173.232156 185.476437
34 407.235910 173.232156
35 192.121561 407.235910
36 18.461811 192.121561
37 19.709670 18.461811
38 205.277597 19.709670
39 224.694321 205.277597
40 -9.302503 224.694321
41 189.098763 -9.302503
42 164.886838 189.098763
43 85.329784 164.886838
44 167.562002 85.329784
45 131.625594 167.562002
46 -834.754761 131.625594
47 -8.797368 -834.754761
48 185.048738 -8.797368
49 267.837432 185.048738
50 202.712745 267.837432
51 107.427179 202.712745
52 -851.956674 107.427179
53 150.431371 -851.956674
54 -828.515146 150.431371
55 -53.414403 -828.515146
56 93.600578 -53.414403
57 20.121803 93.600578
58 200.920610 20.121803
59 88.824900 200.920610
60 205.223487 88.824900
61 20.482772 205.223487
> 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/7yr111292961589.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> acf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/8yr111292961589.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> pacf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Partial Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/9yr111292961589.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> opar <- par(mfrow = c(2,2), oma = c(0, 0, 1.1, 0))
> plot(mylm, las = 1, sub='Residual Diagnostics')
> par(opar)
> dev.off()
null device
1
> if (n > n25) {
+ postscript(file="/var/www/html/rcomp/tmp/10r00m1292961589.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
+ plot(kp3:nmkm3,gqarr[,2], main='Goldfeld-Quandt test',ylab='2-sided p-value',xlab='breakpoint')
+ grid()
+ dev.off()
+ }
null device
1
>
> #Note: the /var/www/html/rcomp/createtable file can be downloaded at http://www.wessa.net/cretab
> load(file="/var/www/html/rcomp/createtable")
>
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a, 'Multiple Linear Regression - Estimated Regression Equation', 1, TRUE)
> a<-table.row.end(a)
> myeq <- colnames(x)[1]
> myeq <- paste(myeq, '[t] = ', sep='')
> for (i in 1:k){
+ if (mysum$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/11cjys1292961589.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/12yjff1292961589.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/13m2c91292961589.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/14xtbc1292961589.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/15jca01292961589.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/16mv861292961589.tab")
+ }
>
> try(system("convert tmp/12z3a1292961589.ps tmp/12z3a1292961589.png",intern=TRUE))
character(0)
> try(system("convert tmp/22z3a1292961589.ps tmp/22z3a1292961589.png",intern=TRUE))
character(0)
> try(system("convert tmp/3dq2v1292961589.ps tmp/3dq2v1292961589.png",intern=TRUE))
character(0)
> try(system("convert tmp/4dq2v1292961589.ps tmp/4dq2v1292961589.png",intern=TRUE))
character(0)
> try(system("convert tmp/5dq2v1292961589.ps tmp/5dq2v1292961589.png",intern=TRUE))
character(0)
> try(system("convert tmp/6o0jy1292961589.ps tmp/6o0jy1292961589.png",intern=TRUE))
character(0)
> try(system("convert tmp/7yr111292961589.ps tmp/7yr111292961589.png",intern=TRUE))
character(0)
> try(system("convert tmp/8yr111292961589.ps tmp/8yr111292961589.png",intern=TRUE))
character(0)
> try(system("convert tmp/9yr111292961589.ps tmp/9yr111292961589.png",intern=TRUE))
character(0)
> try(system("convert tmp/10r00m1292961589.ps tmp/10r00m1292961589.png",intern=TRUE))
character(0)
>
>
> proc.time()
user system elapsed
2.583 1.661 8.141