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.
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Type 'license()' or 'licence()' for distribution details.
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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
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> x <- array(list(3016,0,2155,0,2172,0,2150,0,2533,0,2058,0,2160,0,2260,0,2498,0,2695,0,2799,0,2946,0,2930,0,2318,0,2540,0,2570,0,2669,0,2450,0,2842,0,3440,0,2678,0,2981,0,2260,0,2844,0,2546,0,2456,0,2295,0,2379,0,2479,0,2057,0,2280,0,2351,0,2276,0,2548,1,2311,1,2201,1,2725,1,2408,1,2139,1,1898,1,2537,1,2068,1,2063,1,2520,1,2434,1,2190,1,2794,1,2070,1,2615,1,2265,1,2139,1,2428,1,2137,1,1823,1,2063,1,1806,1,1758,1,2243,1,1993,1,1932,1,2465,1),dim=c(2,61),dimnames=list(c('y','x'),1:61))
> y <- array(NA,dim=c(2,61),dimnames=list(c('y','x'),1:61))
> 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 = '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 M1 M2 M3 M4 M5 M6 M7 M8 M9 M10 M11
1 3016 0 1 0 0 0 0 0 0 0 0 0 0
2 2155 0 0 1 0 0 0 0 0 0 0 0 0
3 2172 0 0 0 1 0 0 0 0 0 0 0 0
4 2150 0 0 0 0 1 0 0 0 0 0 0 0
5 2533 0 0 0 0 0 1 0 0 0 0 0 0
6 2058 0 0 0 0 0 0 1 0 0 0 0 0
7 2160 0 0 0 0 0 0 0 1 0 0 0 0
8 2260 0 0 0 0 0 0 0 0 1 0 0 0
9 2498 0 0 0 0 0 0 0 0 0 1 0 0
10 2695 0 0 0 0 0 0 0 0 0 0 1 0
11 2799 0 0 0 0 0 0 0 0 0 0 0 1
12 2946 0 0 0 0 0 0 0 0 0 0 0 0
13 2930 0 1 0 0 0 0 0 0 0 0 0 0
14 2318 0 0 1 0 0 0 0 0 0 0 0 0
15 2540 0 0 0 1 0 0 0 0 0 0 0 0
16 2570 0 0 0 0 1 0 0 0 0 0 0 0
17 2669 0 0 0 0 0 1 0 0 0 0 0 0
18 2450 0 0 0 0 0 0 1 0 0 0 0 0
19 2842 0 0 0 0 0 0 0 1 0 0 0 0
20 3440 0 0 0 0 0 0 0 0 1 0 0 0
21 2678 0 0 0 0 0 0 0 0 0 1 0 0
22 2981 0 0 0 0 0 0 0 0 0 0 1 0
23 2260 0 0 0 0 0 0 0 0 0 0 0 1
24 2844 0 0 0 0 0 0 0 0 0 0 0 0
25 2546 0 1 0 0 0 0 0 0 0 0 0 0
26 2456 0 0 1 0 0 0 0 0 0 0 0 0
27 2295 0 0 0 1 0 0 0 0 0 0 0 0
28 2379 0 0 0 0 1 0 0 0 0 0 0 0
29 2479 0 0 0 0 0 1 0 0 0 0 0 0
30 2057 0 0 0 0 0 0 1 0 0 0 0 0
31 2280 0 0 0 0 0 0 0 1 0 0 0 0
32 2351 0 0 0 0 0 0 0 0 1 0 0 0
33 2276 0 0 0 0 0 0 0 0 0 1 0 0
34 2548 1 0 0 0 0 0 0 0 0 0 1 0
35 2311 1 0 0 0 0 0 0 0 0 0 0 1
36 2201 1 0 0 0 0 0 0 0 0 0 0 0
37 2725 1 1 0 0 0 0 0 0 0 0 0 0
38 2408 1 0 1 0 0 0 0 0 0 0 0 0
39 2139 1 0 0 1 0 0 0 0 0 0 0 0
40 1898 1 0 0 0 1 0 0 0 0 0 0 0
41 2537 1 0 0 0 0 1 0 0 0 0 0 0
42 2068 1 0 0 0 0 0 1 0 0 0 0 0
43 2063 1 0 0 0 0 0 0 1 0 0 0 0
44 2520 1 0 0 0 0 0 0 0 1 0 0 0
45 2434 1 0 0 0 0 0 0 0 0 1 0 0
46 2190 1 0 0 0 0 0 0 0 0 0 1 0
47 2794 1 0 0 0 0 0 0 0 0 0 0 1
48 2070 1 0 0 0 0 0 0 0 0 0 0 0
49 2615 1 1 0 0 0 0 0 0 0 0 0 0
50 2265 1 0 1 0 0 0 0 0 0 0 0 0
51 2139 1 0 0 1 0 0 0 0 0 0 0 0
52 2428 1 0 0 0 1 0 0 0 0 0 0 0
53 2137 1 0 0 0 0 1 0 0 0 0 0 0
54 1823 1 0 0 0 0 0 1 0 0 0 0 0
55 2063 1 0 0 0 0 0 0 1 0 0 0 0
56 1806 1 0 0 0 0 0 0 0 1 0 0 0
57 1758 1 0 0 0 0 0 0 0 0 1 0 0
58 2243 1 0 0 0 0 0 0 0 0 0 1 0
59 1993 1 0 0 0 0 0 0 0 0 0 0 1
60 1932 1 0 0 0 0 0 0 0 0 0 0 0
61 2465 1 1 0 0 0 0 0 0 0 0 0 0
> k <- length(x[1,])
> df <- as.data.frame(x)
> (mylm <- lm(df))
Call:
lm(formula = df)
Coefficients:
(Intercept) x M1 M2 M3 M4
2589.64 -318.40 285.73 -141.88 -205.28 -177.28
M5 M6 M7 M8 M9 M10
8.72 -371.08 -180.68 13.12 -133.48 132.80
M11
32.80
> (mysum <- summary(mylm))
Call:
lm(formula = df)
Residuals:
Min 1Q Median 3Q Max
-478.36 -180.16 -27.56 167.84 837.24
Coefficients:
Estimate Std. Error t value Pr(>|t|)
(Intercept) 2589.64 131.78 19.651 < 2e-16 ***
x -318.40 72.54 -4.389 6.22e-05 ***
M1 285.73 168.57 1.695 0.0966 .
M2 -141.88 176.50 -0.804 0.4255
M3 -205.28 176.50 -1.163 0.2506
M4 -177.28 176.50 -1.004 0.3202
M5 8.72 176.50 0.049 0.9608
M6 -371.08 176.50 -2.102 0.0408 *
M7 -180.68 176.50 -1.024 0.3111
M8 13.12 176.50 0.074 0.9411
M9 -133.48 176.50 -0.756 0.4532
M10 132.80 175.91 0.755 0.4540
M11 32.80 175.91 0.186 0.8529
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
Residual standard error: 278.1 on 48 degrees of freedom
Multiple R-squared: 0.4467, Adjusted R-squared: 0.3084
F-statistic: 3.23 on 12 and 48 DF, p-value: 0.001862
> 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,] 0.40507128 0.81014256 0.59492872
[2,] 0.25712878 0.51425756 0.74287122
[3,] 0.26158678 0.52317355 0.73841322
[4,] 0.48950129 0.97900258 0.51049871
[5,] 0.96464766 0.07070467 0.03535234
[6,] 0.95169375 0.09661250 0.04830625
[7,] 0.94930925 0.10138149 0.05069075
[8,] 0.95368845 0.09262309 0.04631155
[9,] 0.96636283 0.06727434 0.03363717
[10,] 0.96421040 0.07157921 0.03578960
[11,] 0.94498124 0.11003751 0.05501876
[12,] 0.91214147 0.17571705 0.08785853
[13,] 0.86655913 0.26688175 0.13344087
[14,] 0.81026123 0.37947755 0.18973877
[15,] 0.74966240 0.50067520 0.25033760
[16,] 0.68106183 0.63787635 0.31893817
[17,] 0.66421274 0.67157452 0.33578726
[18,] 0.59829030 0.80341939 0.40170970
[19,] 0.54968142 0.90063715 0.45031858
[20,] 0.45323796 0.90647592 0.54676204
[21,] 0.40682603 0.81365206 0.59317397
[22,] 0.34191722 0.68383444 0.65808278
[23,] 0.28915425 0.57830849 0.71084575
[24,] 0.20427621 0.40855242 0.79572379
[25,] 0.20880990 0.41761979 0.79119010
[26,] 0.18175060 0.36350120 0.81824940
[27,] 0.12633226 0.25266452 0.87366774
[28,] 0.07318348 0.14636696 0.92681652
[29,] 0.11576435 0.23152870 0.88423565
[30,] 0.19652468 0.39304936 0.80347532
> postscript(file="/var/www/html/rcomp/tmp/1z7av1261270796.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$resid)
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/2rkcq1261270796.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> plot(mysum$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/3wa2f1261270796.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> hist(mysum$resid, main='Residual Histogram', xlab='values of Residuals')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/41o4y1261270796.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> densityplot(~mysum$resid,col='black',main='Residual Density Plot', xlab='values of Residuals')
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/56znt1261270796.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 = 61
Frequency = 1
1 2 3 4 5 6
140.632653 -292.760544 -212.360544 -262.360544 -65.360544 -160.560544
7 8 9 10 11 12
-248.960544 -342.760544 41.839456 -27.440816 176.559184 356.359184
13 14 15 16 17 18
54.632653 -129.760544 155.639456 157.639456 70.639456 231.439456
19 20 21 22 23 24
433.039456 837.239456 221.839456 258.559184 -362.440816 254.359184
25 26 27 28 29 30
-329.367347 8.239456 -89.360544 -33.360544 -119.360544 -161.560544
31 32 33 34 35 36
-128.960544 -251.760544 -180.160544 143.960544 6.960544 -70.239456
37 38 39 40 41 42
168.034014 278.640816 73.040816 -195.959184 257.040816 167.840816
43 44 45 46 47 48
-27.559184 235.640816 296.240816 -214.039456 489.960544 -201.239456
49 50 51 52 53 54
58.034014 135.640816 73.040816 334.040816 -142.959184 -77.159184
55 56 57 58 59 60
-27.559184 -478.359184 -379.759184 -161.039456 -311.039456 -339.239456
61
-91.965986
> postscript(file="/var/www/html/rcomp/tmp/6argw1261270796.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 = 61
Frequency = 1
lag(myerror, k = 1) myerror
0 140.632653 NA
1 -292.760544 140.632653
2 -212.360544 -292.760544
3 -262.360544 -212.360544
4 -65.360544 -262.360544
5 -160.560544 -65.360544
6 -248.960544 -160.560544
7 -342.760544 -248.960544
8 41.839456 -342.760544
9 -27.440816 41.839456
10 176.559184 -27.440816
11 356.359184 176.559184
12 54.632653 356.359184
13 -129.760544 54.632653
14 155.639456 -129.760544
15 157.639456 155.639456
16 70.639456 157.639456
17 231.439456 70.639456
18 433.039456 231.439456
19 837.239456 433.039456
20 221.839456 837.239456
21 258.559184 221.839456
22 -362.440816 258.559184
23 254.359184 -362.440816
24 -329.367347 254.359184
25 8.239456 -329.367347
26 -89.360544 8.239456
27 -33.360544 -89.360544
28 -119.360544 -33.360544
29 -161.560544 -119.360544
30 -128.960544 -161.560544
31 -251.760544 -128.960544
32 -180.160544 -251.760544
33 143.960544 -180.160544
34 6.960544 143.960544
35 -70.239456 6.960544
36 168.034014 -70.239456
37 278.640816 168.034014
38 73.040816 278.640816
39 -195.959184 73.040816
40 257.040816 -195.959184
41 167.840816 257.040816
42 -27.559184 167.840816
43 235.640816 -27.559184
44 296.240816 235.640816
45 -214.039456 296.240816
46 489.960544 -214.039456
47 -201.239456 489.960544
48 58.034014 -201.239456
49 135.640816 58.034014
50 73.040816 135.640816
51 334.040816 73.040816
52 -142.959184 334.040816
53 -77.159184 -142.959184
54 -27.559184 -77.159184
55 -478.359184 -27.559184
56 -379.759184 -478.359184
57 -161.039456 -379.759184
58 -311.039456 -161.039456
59 -339.239456 -311.039456
60 -91.965986 -339.239456
61 NA -91.965986
> dum1 <- dum[2:length(myerror),]
> dum1
lag(myerror, k = 1) myerror
[1,] -292.760544 140.632653
[2,] -212.360544 -292.760544
[3,] -262.360544 -212.360544
[4,] -65.360544 -262.360544
[5,] -160.560544 -65.360544
[6,] -248.960544 -160.560544
[7,] -342.760544 -248.960544
[8,] 41.839456 -342.760544
[9,] -27.440816 41.839456
[10,] 176.559184 -27.440816
[11,] 356.359184 176.559184
[12,] 54.632653 356.359184
[13,] -129.760544 54.632653
[14,] 155.639456 -129.760544
[15,] 157.639456 155.639456
[16,] 70.639456 157.639456
[17,] 231.439456 70.639456
[18,] 433.039456 231.439456
[19,] 837.239456 433.039456
[20,] 221.839456 837.239456
[21,] 258.559184 221.839456
[22,] -362.440816 258.559184
[23,] 254.359184 -362.440816
[24,] -329.367347 254.359184
[25,] 8.239456 -329.367347
[26,] -89.360544 8.239456
[27,] -33.360544 -89.360544
[28,] -119.360544 -33.360544
[29,] -161.560544 -119.360544
[30,] -128.960544 -161.560544
[31,] -251.760544 -128.960544
[32,] -180.160544 -251.760544
[33,] 143.960544 -180.160544
[34,] 6.960544 143.960544
[35,] -70.239456 6.960544
[36,] 168.034014 -70.239456
[37,] 278.640816 168.034014
[38,] 73.040816 278.640816
[39,] -195.959184 73.040816
[40,] 257.040816 -195.959184
[41,] 167.840816 257.040816
[42,] -27.559184 167.840816
[43,] 235.640816 -27.559184
[44,] 296.240816 235.640816
[45,] -214.039456 296.240816
[46,] 489.960544 -214.039456
[47,] -201.239456 489.960544
[48,] 58.034014 -201.239456
[49,] 135.640816 58.034014
[50,] 73.040816 135.640816
[51,] 334.040816 73.040816
[52,] -142.959184 334.040816
[53,] -77.159184 -142.959184
[54,] -27.559184 -77.159184
[55,] -478.359184 -27.559184
[56,] -379.759184 -478.359184
[57,] -161.039456 -379.759184
[58,] -311.039456 -161.039456
[59,] -339.239456 -311.039456
[60,] -91.965986 -339.239456
> z <- as.data.frame(dum1)
> z
lag(myerror, k = 1) myerror
1 -292.760544 140.632653
2 -212.360544 -292.760544
3 -262.360544 -212.360544
4 -65.360544 -262.360544
5 -160.560544 -65.360544
6 -248.960544 -160.560544
7 -342.760544 -248.960544
8 41.839456 -342.760544
9 -27.440816 41.839456
10 176.559184 -27.440816
11 356.359184 176.559184
12 54.632653 356.359184
13 -129.760544 54.632653
14 155.639456 -129.760544
15 157.639456 155.639456
16 70.639456 157.639456
17 231.439456 70.639456
18 433.039456 231.439456
19 837.239456 433.039456
20 221.839456 837.239456
21 258.559184 221.839456
22 -362.440816 258.559184
23 254.359184 -362.440816
24 -329.367347 254.359184
25 8.239456 -329.367347
26 -89.360544 8.239456
27 -33.360544 -89.360544
28 -119.360544 -33.360544
29 -161.560544 -119.360544
30 -128.960544 -161.560544
31 -251.760544 -128.960544
32 -180.160544 -251.760544
33 143.960544 -180.160544
34 6.960544 143.960544
35 -70.239456 6.960544
36 168.034014 -70.239456
37 278.640816 168.034014
38 73.040816 278.640816
39 -195.959184 73.040816
40 257.040816 -195.959184
41 167.840816 257.040816
42 -27.559184 167.840816
43 235.640816 -27.559184
44 296.240816 235.640816
45 -214.039456 296.240816
46 489.960544 -214.039456
47 -201.239456 489.960544
48 58.034014 -201.239456
49 135.640816 58.034014
50 73.040816 135.640816
51 334.040816 73.040816
52 -142.959184 334.040816
53 -77.159184 -142.959184
54 -27.559184 -77.159184
55 -478.359184 -27.559184
56 -379.759184 -478.359184
57 -161.039456 -379.759184
58 -311.039456 -161.039456
59 -339.239456 -311.039456
60 -91.965986 -339.239456
> 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/7s9gi1261270796.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> acf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/8dsev1261270796.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> pacf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Partial Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/92xnx1261270796.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> opar <- par(mfrow = c(2,2), oma = c(0, 0, 1.1, 0))
> plot(mylm, las = 1, sub='Residual Diagnostics')
> par(opar)
> dev.off()
null device
1
> if (n > n25) {
+ postscript(file="/var/www/html/rcomp/tmp/10ewfb1261270796.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
+ plot(kp3:nmkm3,gqarr[,2], main='Goldfeld-Quandt test',ylab='2-sided p-value',xlab='breakpoint')
+ grid()
+ dev.off()
+ }
null device
1
>
> #Note: the /var/www/html/rcomp/createtable file can be downloaded at http://www.wessa.net/cretab
> load(file="/var/www/html/rcomp/createtable")
>
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a, 'Multiple Linear Regression - Estimated Regression Equation', 1, TRUE)
> a<-table.row.end(a)
> myeq <- colnames(x)[1]
> myeq <- paste(myeq, '[t] = ', sep='')
> for (i in 1:k){
+ if (mysum$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/11oqy71261270796.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/12sn931261270797.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/13bg0k1261270797.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/14pucg1261270797.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/154vd31261270797.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/16fbzx1261270797.tab")
+ }
>
> try(system("convert tmp/1z7av1261270796.ps tmp/1z7av1261270796.png",intern=TRUE))
character(0)
> try(system("convert tmp/2rkcq1261270796.ps tmp/2rkcq1261270796.png",intern=TRUE))
character(0)
> try(system("convert tmp/3wa2f1261270796.ps tmp/3wa2f1261270796.png",intern=TRUE))
character(0)
> try(system("convert tmp/41o4y1261270796.ps tmp/41o4y1261270796.png",intern=TRUE))
character(0)
> try(system("convert tmp/56znt1261270796.ps tmp/56znt1261270796.png",intern=TRUE))
character(0)
> try(system("convert tmp/6argw1261270796.ps tmp/6argw1261270796.png",intern=TRUE))
character(0)
> try(system("convert tmp/7s9gi1261270796.ps tmp/7s9gi1261270796.png",intern=TRUE))
character(0)
> try(system("convert tmp/8dsev1261270796.ps tmp/8dsev1261270796.png",intern=TRUE))
character(0)
> try(system("convert tmp/92xnx1261270796.ps tmp/92xnx1261270796.png",intern=TRUE))
character(0)
> try(system("convert tmp/10ewfb1261270796.ps tmp/10ewfb1261270796.png",intern=TRUE))
character(0)
>
>
> proc.time()
user system elapsed
2.451 1.586 3.039