R version 2.9.0 (2009-04-17)
Copyright (C) 2009 The R Foundation for Statistical Computing
ISBN 3-900051-07-0
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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
+ ,-999.00
+ ,38.60
+ ,6654.00
+ ,5712.00
+ ,645.00
+ ,3.00
+ ,5.00
+ ,3.00
+ ,6.30
+ ,2.00
+ ,4.50
+ ,1.00
+ ,6600.00
+ ,42.00
+ ,3.00
+ ,1.00
+ ,3.00
+ ,-999.00
+ ,-999.00
+ ,14.00
+ ,3.39
+ ,44.50
+ ,60.00
+ ,1.00
+ ,1.00
+ ,1.00
+ ,-999.00
+ ,-999.00
+ ,-999.00
+ ,0.92
+ ,5.70
+ ,25.00
+ ,5.00
+ ,2.00
+ ,3.00
+ ,2.10
+ ,1.80
+ ,69.00
+ ,2547.00
+ ,4603.00
+ ,624.00
+ ,3.00
+ ,5.00
+ ,4.00
+ ,9.10
+ ,0.70
+ ,27.00
+ ,10.55
+ ,179.50
+ ,180.00
+ ,4.00
+ ,4.00
+ ,4.00
+ ,15.80
+ ,3.90
+ ,19.00
+ ,0.02
+ ,0.30
+ ,35.00
+ ,1.00
+ ,1.00
+ ,1.00
+ ,5.20
+ ,1.00
+ ,30.40
+ ,160.00
+ ,169.00
+ ,392.00
+ ,4.00
+ ,5.00
+ ,4.00
+ ,10.90
+ ,3.60
+ ,28.00
+ ,3.30
+ ,25.60
+ ,63.00
+ ,1.00
+ ,2.00
+ ,1.00
+ ,8.30
+ ,1.40
+ ,50.00
+ ,52.16
+ ,440.00
+ ,230.00
+ ,1.00
+ ,1.00
+ ,1.00
+ ,11.00
+ ,1.50
+ ,7.00
+ ,0.43
+ ,6.40
+ ,112.00
+ ,5.00
+ ,4.00
+ ,4.00
+ ,3.20
+ ,0.70
+ ,30.00
+ ,465.00
+ ,423.00
+ ,281.00
+ ,5.00
+ ,5.00
+ ,5.00
+ ,7.60
+ ,2.70
+ ,-999.00
+ ,0.55
+ ,2.40
+ ,-999.00
+ ,2.00
+ ,1.00
+ ,2.00
+ ,-999.00
+ ,-999.00
+ ,40.00
+ ,187.10
+ ,419.00
+ ,365.00
+ ,5.00
+ ,5.00
+ ,5.00
+ ,6.30
+ ,2.10
+ ,3.50
+ ,0.08
+ ,1.20
+ ,42.00
+ ,1.00
+ ,1.00
+ ,1.00
+ ,8.60
+ ,0.00
+ ,50.00
+ ,3.00
+ ,25.00
+ ,28.00
+ ,2.00
+ ,2.00
+ ,2.00
+ ,6.60
+ ,4.10
+ ,6.00
+ ,0.79
+ ,3500.00
+ ,42.00
+ ,2.00
+ ,2.00
+ ,2.00
+ ,9.50
+ ,1.20
+ ,10.40
+ ,0.20
+ ,5.00
+ ,120.00
+ ,2.00
+ ,2.00
+ ,2.00
+ ,4.80
+ ,1.30
+ ,34.00
+ ,1.41
+ ,17.50
+ ,-999.00
+ ,1.00
+ ,2.00
+ ,1.00
+ ,12.00
+ ,6.10
+ ,7.00
+ ,60.00
+ ,81.00
+ ,-999.00
+ ,1.00
+ ,1.00
+ ,1.00
+ ,-999.00
+ ,0.30
+ ,28.00
+ ,529.00
+ ,680.00
+ ,400.00
+ ,5.00
+ ,5.00
+ ,5.00
+ ,3.30
+ ,0.50
+ ,20.00
+ ,27.66
+ ,115.00
+ ,148.00
+ ,5.00
+ ,5.00
+ ,5.00
+ ,11.00
+ ,3.40
+ ,3.90
+ ,0.12
+ ,1.00
+ ,16.00
+ ,3.00
+ ,1.00
+ ,2.00
+ ,-999.00
+ ,-999.00
+ ,39.30
+ ,207.00
+ ,406.00
+ ,252.00
+ ,1.00
+ ,4.00
+ ,1.00
+ ,4.70
+ ,1.50
+ ,41.00
+ ,85.00
+ ,325.00
+ ,310.00
+ ,1.00
+ ,3.00
+ ,1.00
+ ,-999.00
+ ,-999.00
+ ,16.20
+ ,36.33
+ ,119.50
+ ,63.00
+ ,1.00
+ ,1.00
+ ,1.00
+ ,10.40
+ ,3.40
+ ,9.00
+ ,0.10
+ ,4.00
+ ,28.00
+ ,5.00
+ ,1.00
+ ,3.00
+ ,7.40
+ ,0.80
+ ,7.60
+ ,1.04
+ ,5.50
+ ,68.00
+ ,5.00
+ ,3.00
+ ,4.00
+ ,2.10
+ ,0.80
+ ,46.00
+ ,521.00
+ ,655.00
+ ,336.00
+ ,5.00
+ ,5.00
+ ,5.00
+ ,-999.00
+ ,-999.00
+ ,22.40
+ ,100.00
+ ,157.00
+ ,100.00
+ ,1.00
+ ,1.00
+ ,1.00
+ ,-999.00
+ ,-999.00
+ ,16.30
+ ,35.00
+ ,56.00
+ ,33.00
+ ,3.00
+ ,5.00
+ ,4.00
+ ,7.70
+ ,1.40
+ ,2.60
+ ,0.01
+ ,0.14
+ ,21.50
+ ,5.00
+ ,2.00
+ ,4.00
+ ,17.90
+ ,2.00
+ ,24.00
+ ,0.01
+ ,0.25
+ ,50.00
+ ,1.00
+ ,1.00
+ ,1.00
+ ,6.10
+ ,1.90
+ ,100.00
+ ,62.00
+ ,1320.00
+ ,267.00
+ ,1.00
+ ,1.00
+ ,1.00
+ ,8.20
+ ,2.40
+ ,-999.00
+ ,0.12
+ ,3.00
+ ,30.00
+ ,2.00
+ ,1.00
+ ,1.00
+ ,8.40
+ ,2.80
+ ,-999.00
+ ,1.35
+ ,8.10
+ ,45.00
+ ,3.00
+ ,1.00
+ ,3.00
+ ,11.90
+ ,1.30
+ ,3.20
+ ,0.02
+ ,0.40
+ ,19.00
+ ,4.00
+ ,1.00
+ ,3.00
+ ,10.80
+ ,2.00
+ ,2.00
+ ,0.05
+ ,0.33
+ ,30.00
+ ,4.00
+ ,1.00
+ ,3.00
+ ,13.80
+ ,5.60
+ ,5.00
+ ,1.70
+ ,6.30
+ ,12.00
+ ,2.00
+ ,1.00
+ ,1.00
+ ,14.30
+ ,3.10
+ ,6.50
+ ,3.50
+ ,10.80
+ ,120.00
+ ,2.00
+ ,1.00
+ ,1.00
+ ,-999.00
+ ,1.00
+ ,23.60
+ ,250.00
+ ,490.00
+ ,440.00
+ ,5.00
+ ,5.00
+ ,5.00
+ ,15.20
+ ,1.80
+ ,12.00
+ ,0.48
+ ,15.50
+ ,140.00
+ ,2.00
+ ,2.00
+ ,2.00
+ ,10.00
+ ,0.90
+ ,20.20
+ ,10.00
+ ,115.00
+ ,170.00
+ ,4.00
+ ,4.00
+ ,4.00
+ ,11.90
+ ,1.80
+ ,13.00
+ ,1.62
+ ,11.40
+ ,17.00
+ ,2.00
+ ,1.00
+ ,2.00
+ ,6.50
+ ,1.90
+ ,27.00
+ ,192.00
+ ,180.00
+ ,115.00
+ ,4.00
+ ,4.00
+ ,4.00
+ ,7.50
+ ,0.90
+ ,18.00
+ ,2.50
+ ,12.10
+ ,31.00
+ ,5.00
+ ,5.00
+ ,5.00
+ ,-999.00
+ ,-999.00
+ ,13.70
+ ,4.29
+ ,39.20
+ ,63.00
+ ,2.00
+ ,2.00
+ ,2.00
+ ,10.60
+ ,2.60
+ ,4.70
+ ,0.28
+ ,1.90
+ ,21.00
+ ,3.00
+ ,1.00
+ ,3.00
+ ,7.40
+ ,2.40
+ ,9.80
+ ,4.24
+ ,50.40
+ ,52.00
+ ,1.00
+ ,1.00
+ ,1.00
+ ,8.40
+ ,1.20
+ ,29.00
+ ,6.80
+ ,179.00
+ ,164.00
+ ,2.00
+ ,3.00
+ ,2.00
+ ,5.70
+ ,0.90
+ ,7.00
+ ,0.75
+ ,12.30
+ ,225.00
+ ,2.00
+ ,2.00
+ ,2.00
+ ,4.90
+ ,0.50
+ ,6.00
+ ,3.60
+ ,21.00
+ ,225.00
+ ,3.00
+ ,2.00
+ ,3.00
+ ,-999.00
+ ,-999.00
+ ,17.00
+ ,14.83
+ ,98.20
+ ,150.00
+ ,5.00
+ ,5.00
+ ,5.00
+ ,3.20
+ ,0.60
+ ,20.00
+ ,55.50
+ ,175.00
+ ,151.00
+ ,5.00
+ ,5.00
+ ,5.00
+ ,-999.00
+ ,-999.00
+ ,12.70
+ ,1.40
+ ,12.50
+ ,90.00
+ ,2.00
+ ,2.00
+ ,2.00
+ ,8.10
+ ,2.20
+ ,3.50
+ ,0.06
+ ,1.00
+ ,-999.00
+ ,3.00
+ ,1.00
+ ,2.00
+ ,11.00
+ ,2.30
+ ,4.50
+ ,0.90
+ ,2.60
+ ,60.00
+ ,2.00
+ ,1.00
+ ,2.00
+ ,4.90
+ ,0.50
+ ,7.50
+ ,2.00
+ ,12.30
+ ,200.00
+ ,3.00
+ ,1.00
+ ,3.00
+ ,13.20
+ ,2.60
+ ,2.30
+ ,0.10
+ ,2.50
+ ,46.00
+ ,3.00
+ ,2.00
+ ,2.00
+ ,9.70
+ ,0.60
+ ,24.00
+ ,4.19
+ ,58.00
+ ,210.00
+ ,4.00
+ ,3.00
+ ,4.00
+ ,12.80
+ ,6.60
+ ,3.00
+ ,3.50
+ ,3.90
+ ,14.00
+ ,2.00
+ ,1.00
+ ,1.00
+ ,-999.00
+ ,-999.00
+ ,13.00
+ ,4.05
+ ,17.00
+ ,38.00
+ ,3.00
+ ,1.00
+ ,1.00)
+ ,dim=c(9
+ ,62)
+ ,dimnames=list(c('SWS'
+ ,'PS'
+ ,'L'
+ ,'Wb'
+ ,'Wbr'
+ ,'Tg'
+ ,'P'
+ ,'S'
+ ,'D
')
+ ,1:62))
> y <- array(NA,dim=c(9,62),dimnames=list(c('SWS','PS','L','Wb','Wbr','Tg','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 PS L Wb Wbr Tg P S D\r
1 -999.0 -999.0 38.6 6654.00 5712.00 645.0 3 5 3
2 6.3 2.0 4.5 1.00 6600.00 42.0 3 1 3
3 -999.0 -999.0 14.0 3.39 44.50 60.0 1 1 1
4 -999.0 -999.0 -999.0 0.92 5.70 25.0 5 2 3
5 2.1 1.8 69.0 2547.00 4603.00 624.0 3 5 4
6 9.1 0.7 27.0 10.55 179.50 180.0 4 4 4
7 15.8 3.9 19.0 0.02 0.30 35.0 1 1 1
8 5.2 1.0 30.4 160.00 169.00 392.0 4 5 4
9 10.9 3.6 28.0 3.30 25.60 63.0 1 2 1
10 8.3 1.4 50.0 52.16 440.00 230.0 1 1 1
11 11.0 1.5 7.0 0.43 6.40 112.0 5 4 4
12 3.2 0.7 30.0 465.00 423.00 281.0 5 5 5
13 7.6 2.7 -999.0 0.55 2.40 -999.0 2 1 2
14 -999.0 -999.0 40.0 187.10 419.00 365.0 5 5 5
15 6.3 2.1 3.5 0.08 1.20 42.0 1 1 1
16 8.6 0.0 50.0 3.00 25.00 28.0 2 2 2
17 6.6 4.1 6.0 0.79 3500.00 42.0 2 2 2
18 9.5 1.2 10.4 0.20 5.00 120.0 2 2 2
19 4.8 1.3 34.0 1.41 17.50 -999.0 1 2 1
20 12.0 6.1 7.0 60.00 81.00 -999.0 1 1 1
21 -999.0 0.3 28.0 529.00 680.00 400.0 5 5 5
22 3.3 0.5 20.0 27.66 115.00 148.0 5 5 5
23 11.0 3.4 3.9 0.12 1.00 16.0 3 1 2
24 -999.0 -999.0 39.3 207.00 406.00 252.0 1 4 1
25 4.7 1.5 41.0 85.00 325.00 310.0 1 3 1
26 -999.0 -999.0 16.2 36.33 119.50 63.0 1 1 1
27 10.4 3.4 9.0 0.10 4.00 28.0 5 1 3
28 7.4 0.8 7.6 1.04 5.50 68.0 5 3 4
29 2.1 0.8 46.0 521.00 655.00 336.0 5 5 5
30 -999.0 -999.0 22.4 100.00 157.00 100.0 1 1 1
31 -999.0 -999.0 16.3 35.00 56.00 33.0 3 5 4
32 7.7 1.4 2.6 0.01 0.14 21.5 5 2 4
33 17.9 2.0 24.0 0.01 0.25 50.0 1 1 1
34 6.1 1.9 100.0 62.00 1320.00 267.0 1 1 1
35 8.2 2.4 -999.0 0.12 3.00 30.0 2 1 1
36 8.4 2.8 -999.0 1.35 8.10 45.0 3 1 3
37 11.9 1.3 3.2 0.02 0.40 19.0 4 1 3
38 10.8 2.0 2.0 0.05 0.33 30.0 4 1 3
39 13.8 5.6 5.0 1.70 6.30 12.0 2 1 1
40 14.3 3.1 6.5 3.50 10.80 120.0 2 1 1
41 -999.0 1.0 23.6 250.00 490.00 440.0 5 5 5
42 15.2 1.8 12.0 0.48 15.50 140.0 2 2 2
43 10.0 0.9 20.2 10.00 115.00 170.0 4 4 4
44 11.9 1.8 13.0 1.62 11.40 17.0 2 1 2
45 6.5 1.9 27.0 192.00 180.00 115.0 4 4 4
46 7.5 0.9 18.0 2.50 12.10 31.0 5 5 5
47 -999.0 -999.0 13.7 4.29 39.20 63.0 2 2 2
48 10.6 2.6 4.7 0.28 1.90 21.0 3 1 3
49 7.4 2.4 9.8 4.24 50.40 52.0 1 1 1
50 8.4 1.2 29.0 6.80 179.00 164.0 2 3 2
51 5.7 0.9 7.0 0.75 12.30 225.0 2 2 2
52 4.9 0.5 6.0 3.60 21.00 225.0 3 2 3
53 -999.0 -999.0 17.0 14.83 98.20 150.0 5 5 5
54 3.2 0.6 20.0 55.50 175.00 151.0 5 5 5
55 -999.0 -999.0 12.7 1.40 12.50 90.0 2 2 2
56 8.1 2.2 3.5 0.06 1.00 -999.0 3 1 2
57 11.0 2.3 4.5 0.90 2.60 60.0 2 1 2
58 4.9 0.5 7.5 2.00 12.30 200.0 3 1 3
59 13.2 2.6 2.3 0.10 2.50 46.0 3 2 2
60 9.7 0.6 24.0 4.19 58.00 210.0 4 3 4
61 12.8 6.6 3.0 3.50 3.90 14.0 2 1 1
62 -999.0 -999.0 13.0 4.05 17.00 38.0 3 1 1
> k <- length(x[1,])
> df <- as.data.frame(x)
> (mylm <- lm(df))
Call:
lm(formula = df)
Coefficients:
(Intercept) PS L Wb Wbr Tg
58.596203 0.955259 0.019899 0.007974 0.002622 -0.067620
P S `D\r`
-2.794662 -22.090214 -11.483472
> (mysum <- summary(mylm))
Call:
lm(formula = df)
Residuals:
Min 1Q Median 3Q Max
-855.551 -9.767 17.882 60.586 140.515
Coefficients:
Estimate Std. Error t value Pr(>|t|)
(Intercept) 58.596203 55.685707 1.052 0.297
PS 0.955259 0.062235 15.349 <2e-16 ***
L 0.019899 0.098519 0.202 0.841
Wb 0.007974 0.037502 0.213 0.832
Wbr 0.002622 0.024641 0.106 0.916
Tg -0.067620 0.086431 -0.782 0.437
P -2.794662 44.714931 -0.062 0.950
S -22.090214 29.839333 -0.740 0.462
`D\r` -11.483472 59.599358 -0.193 0.848
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
Residual standard error: 179.9 on 53 degrees of freedom
Multiple R-squared: 0.8442, Adjusted R-squared: 0.8207
F-statistic: 35.89 on 8 and 53 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,] 4.996589e-06 9.993178e-06 9.999950e-01
[2,] 9.034865e-08 1.806973e-07 9.999999e-01
[3,] 2.454728e-09 4.909457e-09 1.000000e+00
[4,] 1.020820e-10 2.041640e-10 1.000000e+00
[5,] 1.556277e-12 3.112553e-12 1.000000e+00
[6,] 3.091300e-14 6.182601e-14 1.000000e+00
[7,] 4.426300e-16 8.852600e-16 1.000000e+00
[8,] 1.184976e-17 2.369952e-17 1.000000e+00
[9,] 1.752603e-19 3.505207e-19 1.000000e+00
[10,] 9.838936e-01 3.221287e-02 1.610644e-02
[11,] 9.794727e-01 4.105451e-02 2.052726e-02
[12,] 9.668577e-01 6.628460e-02 3.314230e-02
[13,] 9.526235e-01 9.475300e-02 4.737650e-02
[14,] 9.281155e-01 1.437691e-01 7.188453e-02
[15,] 8.943758e-01 2.112483e-01 1.056242e-01
[16,] 8.500860e-01 2.998280e-01 1.499140e-01
[17,] 8.025176e-01 3.949649e-01 1.974824e-01
[18,] 9.822010e-01 3.559808e-02 1.779904e-02
[19,] 9.800692e-01 3.986164e-02 1.993082e-02
[20,] 9.682550e-01 6.349006e-02 3.174503e-02
[21,] 9.502853e-01 9.942941e-02 4.971471e-02
[22,] 9.238990e-01 1.522020e-01 7.610099e-02
[23,] 9.946817e-01 1.063655e-02 5.318277e-03
[24,] 9.901487e-01 1.970250e-02 9.851252e-03
[25,] 9.979375e-01 4.125074e-03 2.062537e-03
[26,] 9.959463e-01 8.107345e-03 4.053672e-03
[27,] 9.932876e-01 1.342479e-02 6.712395e-03
[28,] 9.867930e-01 2.641393e-02 1.320697e-02
[29,] 9.751566e-01 4.968673e-02 2.484336e-02
[30,] 1.000000e+00 3.452881e-21 1.726440e-21
[31,] 1.000000e+00 3.811945e-20 1.905972e-20
[32,] 1.000000e+00 1.764170e-18 8.820850e-19
[33,] 1.000000e+00 9.632183e-17 4.816091e-17
[34,] 1.000000e+00 3.420674e-15 1.710337e-15
[35,] 1.000000e+00 2.196635e-13 1.098317e-13
[36,] 1.000000e+00 1.997124e-11 9.985620e-12
[37,] 1.000000e+00 1.193116e-09 5.965581e-10
[38,] 9.999999e-01 1.117211e-07 5.586054e-08
[39,] 9.999958e-01 8.469404e-06 4.234702e-06
> postscript(file="/var/www/html/rcomp/tmp/1ikap1292933509.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$resid)
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/2ikap1292933509.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> plot(mysum$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/3bcrs1292933509.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> hist(mysum$resid, main='Residual Histogram', xlab='values of Residuals')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/4bcrs1292933509.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> densityplot(~mysum$resid,col='black',main='Residual Density Plot', xlab='values of Residuals')
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/5bcrs1292933509.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
24.8021573 -3.8434031 -63.2896141 10.8583831 114.9964386 106.3881807
7 8 9 10 11 12
-8.1656706 137.3954447 10.9329167 -2.2769916 106.6529565 139.3641137
13 14 15 16 17 18
-50.6135112 99.8438030 -15.1672689 23.5494592 10.3620213 30.3869854
19 20 21 22 23 24
-64.8659739 -84.4378671 -855.5513179 135.1556826 3.5978070 12.8892615
25 26 27 28 29 30
43.8362612 -63.5898423 20.7728598 78.6416801 140.5145070 -61.8173076
31 32 33 34 35 36
62.9572441 53.2557209 -3.3356560 -5.8332517 8.3728762 34.9435070
37 38 39 40 41 42
21.0011458 20.0001125 -10.3007623 -0.1656093 -850.7046218 36.8046392
43 44 45 46 47 48
106.7297281 3.0788713 96.7982722 131.5722051 -26.7057155 15.7640339
49 50 51 52 53 54
-13.9651704 53.4735578 34.0178394 47.8524398 87.9779075 134.7837025
55 56 57 58 59 60
-24.7670170 -66.7821851 4.8068738 24.0774352 30.7089060 87.4510670
61 62
-12.0890440 -59.1012037
> postscript(file="/var/www/html/rcomp/tmp/6l39v1292933509.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 24.8021573 NA
1 -3.8434031 24.8021573
2 -63.2896141 -3.8434031
3 10.8583831 -63.2896141
4 114.9964386 10.8583831
5 106.3881807 114.9964386
6 -8.1656706 106.3881807
7 137.3954447 -8.1656706
8 10.9329167 137.3954447
9 -2.2769916 10.9329167
10 106.6529565 -2.2769916
11 139.3641137 106.6529565
12 -50.6135112 139.3641137
13 99.8438030 -50.6135112
14 -15.1672689 99.8438030
15 23.5494592 -15.1672689
16 10.3620213 23.5494592
17 30.3869854 10.3620213
18 -64.8659739 30.3869854
19 -84.4378671 -64.8659739
20 -855.5513179 -84.4378671
21 135.1556826 -855.5513179
22 3.5978070 135.1556826
23 12.8892615 3.5978070
24 43.8362612 12.8892615
25 -63.5898423 43.8362612
26 20.7728598 -63.5898423
27 78.6416801 20.7728598
28 140.5145070 78.6416801
29 -61.8173076 140.5145070
30 62.9572441 -61.8173076
31 53.2557209 62.9572441
32 -3.3356560 53.2557209
33 -5.8332517 -3.3356560
34 8.3728762 -5.8332517
35 34.9435070 8.3728762
36 21.0011458 34.9435070
37 20.0001125 21.0011458
38 -10.3007623 20.0001125
39 -0.1656093 -10.3007623
40 -850.7046218 -0.1656093
41 36.8046392 -850.7046218
42 106.7297281 36.8046392
43 3.0788713 106.7297281
44 96.7982722 3.0788713
45 131.5722051 96.7982722
46 -26.7057155 131.5722051
47 15.7640339 -26.7057155
48 -13.9651704 15.7640339
49 53.4735578 -13.9651704
50 34.0178394 53.4735578
51 47.8524398 34.0178394
52 87.9779075 47.8524398
53 134.7837025 87.9779075
54 -24.7670170 134.7837025
55 -66.7821851 -24.7670170
56 4.8068738 -66.7821851
57 24.0774352 4.8068738
58 30.7089060 24.0774352
59 87.4510670 30.7089060
60 -12.0890440 87.4510670
61 -59.1012037 -12.0890440
62 NA -59.1012037
> dum1 <- dum[2:length(myerror),]
> dum1
lag(myerror, k = 1) myerror
[1,] -3.8434031 24.8021573
[2,] -63.2896141 -3.8434031
[3,] 10.8583831 -63.2896141
[4,] 114.9964386 10.8583831
[5,] 106.3881807 114.9964386
[6,] -8.1656706 106.3881807
[7,] 137.3954447 -8.1656706
[8,] 10.9329167 137.3954447
[9,] -2.2769916 10.9329167
[10,] 106.6529565 -2.2769916
[11,] 139.3641137 106.6529565
[12,] -50.6135112 139.3641137
[13,] 99.8438030 -50.6135112
[14,] -15.1672689 99.8438030
[15,] 23.5494592 -15.1672689
[16,] 10.3620213 23.5494592
[17,] 30.3869854 10.3620213
[18,] -64.8659739 30.3869854
[19,] -84.4378671 -64.8659739
[20,] -855.5513179 -84.4378671
[21,] 135.1556826 -855.5513179
[22,] 3.5978070 135.1556826
[23,] 12.8892615 3.5978070
[24,] 43.8362612 12.8892615
[25,] -63.5898423 43.8362612
[26,] 20.7728598 -63.5898423
[27,] 78.6416801 20.7728598
[28,] 140.5145070 78.6416801
[29,] -61.8173076 140.5145070
[30,] 62.9572441 -61.8173076
[31,] 53.2557209 62.9572441
[32,] -3.3356560 53.2557209
[33,] -5.8332517 -3.3356560
[34,] 8.3728762 -5.8332517
[35,] 34.9435070 8.3728762
[36,] 21.0011458 34.9435070
[37,] 20.0001125 21.0011458
[38,] -10.3007623 20.0001125
[39,] -0.1656093 -10.3007623
[40,] -850.7046218 -0.1656093
[41,] 36.8046392 -850.7046218
[42,] 106.7297281 36.8046392
[43,] 3.0788713 106.7297281
[44,] 96.7982722 3.0788713
[45,] 131.5722051 96.7982722
[46,] -26.7057155 131.5722051
[47,] 15.7640339 -26.7057155
[48,] -13.9651704 15.7640339
[49,] 53.4735578 -13.9651704
[50,] 34.0178394 53.4735578
[51,] 47.8524398 34.0178394
[52,] 87.9779075 47.8524398
[53,] 134.7837025 87.9779075
[54,] -24.7670170 134.7837025
[55,] -66.7821851 -24.7670170
[56,] 4.8068738 -66.7821851
[57,] 24.0774352 4.8068738
[58,] 30.7089060 24.0774352
[59,] 87.4510670 30.7089060
[60,] -12.0890440 87.4510670
[61,] -59.1012037 -12.0890440
> z <- as.data.frame(dum1)
> z
lag(myerror, k = 1) myerror
1 -3.8434031 24.8021573
2 -63.2896141 -3.8434031
3 10.8583831 -63.2896141
4 114.9964386 10.8583831
5 106.3881807 114.9964386
6 -8.1656706 106.3881807
7 137.3954447 -8.1656706
8 10.9329167 137.3954447
9 -2.2769916 10.9329167
10 106.6529565 -2.2769916
11 139.3641137 106.6529565
12 -50.6135112 139.3641137
13 99.8438030 -50.6135112
14 -15.1672689 99.8438030
15 23.5494592 -15.1672689
16 10.3620213 23.5494592
17 30.3869854 10.3620213
18 -64.8659739 30.3869854
19 -84.4378671 -64.8659739
20 -855.5513179 -84.4378671
21 135.1556826 -855.5513179
22 3.5978070 135.1556826
23 12.8892615 3.5978070
24 43.8362612 12.8892615
25 -63.5898423 43.8362612
26 20.7728598 -63.5898423
27 78.6416801 20.7728598
28 140.5145070 78.6416801
29 -61.8173076 140.5145070
30 62.9572441 -61.8173076
31 53.2557209 62.9572441
32 -3.3356560 53.2557209
33 -5.8332517 -3.3356560
34 8.3728762 -5.8332517
35 34.9435070 8.3728762
36 21.0011458 34.9435070
37 20.0001125 21.0011458
38 -10.3007623 20.0001125
39 -0.1656093 -10.3007623
40 -850.7046218 -0.1656093
41 36.8046392 -850.7046218
42 106.7297281 36.8046392
43 3.0788713 106.7297281
44 96.7982722 3.0788713
45 131.5722051 96.7982722
46 -26.7057155 131.5722051
47 15.7640339 -26.7057155
48 -13.9651704 15.7640339
49 53.4735578 -13.9651704
50 34.0178394 53.4735578
51 47.8524398 34.0178394
52 87.9779075 47.8524398
53 134.7837025 87.9779075
54 -24.7670170 134.7837025
55 -66.7821851 -24.7670170
56 4.8068738 -66.7821851
57 24.0774352 4.8068738
58 30.7089060 24.0774352
59 87.4510670 30.7089060
60 -12.0890440 87.4510670
61 -59.1012037 -12.0890440
> 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/7wc8g1292933509.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> acf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/8plp11292933509.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> pacf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Partial Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/9plp11292933509.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> opar <- par(mfrow = c(2,2), oma = c(0, 0, 1.1, 0))
> plot(mylm, las = 1, sub='Residual Diagnostics')
> par(opar)
> dev.off()
null device
1
> if (n > n25) {
+ postscript(file="/var/www/html/rcomp/tmp/10hd6m1292933509.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
+ plot(kp3:nmkm3,gqarr[,2], main='Goldfeld-Quandt test',ylab='2-sided p-value',xlab='breakpoint')
+ grid()
+ dev.off()
+ }
null device
1
>
> #Note: the /var/www/html/rcomp/createtable file can be downloaded at http://www.wessa.net/cretab
> load(file="/var/www/html/rcomp/createtable")
>
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a, 'Multiple Linear Regression - Estimated Regression Equation', 1, TRUE)
> a<-table.row.end(a)
> myeq <- colnames(x)[1]
> myeq <- paste(myeq, '[t] = ', sep='')
> for (i in 1:k){
+ if (mysum$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/11lv5a1292933509.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/126w3x1292933509.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/13k5j61292933509.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/1466hu1292933509.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/1597y01292933509.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/16iamc1292933509.tab")
+ }
>
> try(system("convert tmp/1ikap1292933509.ps tmp/1ikap1292933509.png",intern=TRUE))
character(0)
> try(system("convert tmp/2ikap1292933509.ps tmp/2ikap1292933509.png",intern=TRUE))
character(0)
> try(system("convert tmp/3bcrs1292933509.ps tmp/3bcrs1292933509.png",intern=TRUE))
character(0)
> try(system("convert tmp/4bcrs1292933509.ps tmp/4bcrs1292933509.png",intern=TRUE))
character(0)
> try(system("convert tmp/5bcrs1292933509.ps tmp/5bcrs1292933509.png",intern=TRUE))
character(0)
> try(system("convert tmp/6l39v1292933509.ps tmp/6l39v1292933509.png",intern=TRUE))
character(0)
> try(system("convert tmp/7wc8g1292933509.ps tmp/7wc8g1292933509.png",intern=TRUE))
character(0)
> try(system("convert tmp/8plp11292933509.ps tmp/8plp11292933509.png",intern=TRUE))
character(0)
> try(system("convert tmp/9plp11292933509.ps tmp/9plp11292933509.png",intern=TRUE))
character(0)
> try(system("convert tmp/10hd6m1292933509.ps tmp/10hd6m1292933509.png",intern=TRUE))
character(0)
>
>
> proc.time()
user system elapsed
2.607 1.628 8.033