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.
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'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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Type 'q()' to quit R.
> x <- array(list(20366,0,22782,0,19169,0,13807,0,29743,0,25591,0,29096,0,26482,0,22405,0,27044,0,17970,0,18730,0,19684,0,19785,0,18479,0,10698,0,31956,0,29506,0,34506,0,27165,0,26736,0,23691,0,18157,0,17328,0,18205,0,20995,0,17382,0,9367,0,31124,0,26551,0,30651,0,25859,0,25100,0,25778,0,20418,0,18688,0,20424,0,24776,0,19814,0,12738,0,31566,0,30111,0,30019,0,31934,1,25826,1,26835,1,20205,1,17789,1,20520,1,22518,1,15572,1,11509,1,25447,1,24090,1,27786,1,26195,1,20516,1,22759,1,19028,1,16971,1,20036,1),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 20366 0 1 0 0 0 0 0 0 0 0 0 0
2 22782 0 0 1 0 0 0 0 0 0 0 0 0
3 19169 0 0 0 1 0 0 0 0 0 0 0 0
4 13807 0 0 0 0 1 0 0 0 0 0 0 0
5 29743 0 0 0 0 0 1 0 0 0 0 0 0
6 25591 0 0 0 0 0 0 1 0 0 0 0 0
7 29096 0 0 0 0 0 0 0 1 0 0 0 0
8 26482 0 0 0 0 0 0 0 0 1 0 0 0
9 22405 0 0 0 0 0 0 0 0 0 1 0 0
10 27044 0 0 0 0 0 0 0 0 0 0 1 0
11 17970 0 0 0 0 0 0 0 0 0 0 0 1
12 18730 0 0 0 0 0 0 0 0 0 0 0 0
13 19684 0 1 0 0 0 0 0 0 0 0 0 0
14 19785 0 0 1 0 0 0 0 0 0 0 0 0
15 18479 0 0 0 1 0 0 0 0 0 0 0 0
16 10698 0 0 0 0 1 0 0 0 0 0 0 0
17 31956 0 0 0 0 0 1 0 0 0 0 0 0
18 29506 0 0 0 0 0 0 1 0 0 0 0 0
19 34506 0 0 0 0 0 0 0 1 0 0 0 0
20 27165 0 0 0 0 0 0 0 0 1 0 0 0
21 26736 0 0 0 0 0 0 0 0 0 1 0 0
22 23691 0 0 0 0 0 0 0 0 0 0 1 0
23 18157 0 0 0 0 0 0 0 0 0 0 0 1
24 17328 0 0 0 0 0 0 0 0 0 0 0 0
25 18205 0 1 0 0 0 0 0 0 0 0 0 0
26 20995 0 0 1 0 0 0 0 0 0 0 0 0
27 17382 0 0 0 1 0 0 0 0 0 0 0 0
28 9367 0 0 0 0 1 0 0 0 0 0 0 0
29 31124 0 0 0 0 0 1 0 0 0 0 0 0
30 26551 0 0 0 0 0 0 1 0 0 0 0 0
31 30651 0 0 0 0 0 0 0 1 0 0 0 0
32 25859 0 0 0 0 0 0 0 0 1 0 0 0
33 25100 0 0 0 0 0 0 0 0 0 1 0 0
34 25778 0 0 0 0 0 0 0 0 0 0 1 0
35 20418 0 0 0 0 0 0 0 0 0 0 0 1
36 18688 0 0 0 0 0 0 0 0 0 0 0 0
37 20424 0 1 0 0 0 0 0 0 0 0 0 0
38 24776 0 0 1 0 0 0 0 0 0 0 0 0
39 19814 0 0 0 1 0 0 0 0 0 0 0 0
40 12738 0 0 0 0 1 0 0 0 0 0 0 0
41 31566 0 0 0 0 0 1 0 0 0 0 0 0
42 30111 0 0 0 0 0 0 1 0 0 0 0 0
43 30019 0 0 0 0 0 0 0 1 0 0 0 0
44 31934 1 0 0 0 0 0 0 0 1 0 0 0
45 25826 1 0 0 0 0 0 0 0 0 1 0 0
46 26835 1 0 0 0 0 0 0 0 0 0 1 0
47 20205 1 0 0 0 0 0 0 0 0 0 0 1
48 17789 1 0 0 0 0 0 0 0 0 0 0 0
49 20520 1 1 0 0 0 0 0 0 0 0 0 0
50 22518 1 0 1 0 0 0 0 0 0 0 0 0
51 15572 1 0 0 1 0 0 0 0 0 0 0 0
52 11509 1 0 0 0 1 0 0 0 0 0 0 0
53 25447 1 0 0 0 0 1 0 0 0 0 0 0
54 24090 1 0 0 0 0 0 1 0 0 0 0 0
55 27786 1 0 0 0 0 0 0 1 0 0 0 0
56 26195 1 0 0 0 0 0 0 0 1 0 0 0
57 20516 1 0 0 0 0 0 0 0 0 1 0 0
58 22759 1 0 0 0 0 0 0 0 0 0 1 0
59 19028 1 0 0 0 0 0 0 0 0 0 0 1
60 16971 1 0 0 0 0 0 0 0 0 0 0 0
61 20036 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
18279.642 -946.104 1908.226 4080.779 -7.221 -6466.621
M5 M6 M7 M8 M9 M10
11876.779 9079.379 12321.179 9625.800 6215.400 7320.200
M11
1254.400
> (mysum <- summary(mylm))
Call:
lm(formula = df)
Residuals:
Min 1Q Median 3Q Max
-3763.3 -1423.4 178.2 1103.7 4974.7
Coefficients:
Estimate Std. Error t value Pr(>|t|)
(Intercept) 18279.642 906.256 20.171 < 2e-16 ***
X -946.104 563.483 -1.679 0.09965 .
M1 1908.226 1189.113 1.605 0.11511
M2 4080.779 1246.473 3.274 0.00197 **
M3 -7.221 1246.473 -0.006 0.99540
M4 -6466.621 1246.473 -5.188 4.24e-06 ***
M5 11876.779 1246.473 9.528 1.20e-12 ***
M6 9079.379 1246.473 7.284 2.70e-09 ***
M7 12321.179 1246.473 9.885 3.70e-13 ***
M8 9625.800 1241.368 7.754 5.19e-10 ***
M9 6215.400 1241.368 5.007 7.87e-06 ***
M10 7320.200 1241.368 5.897 3.60e-07 ***
M11 1254.400 1241.368 1.010 0.31732
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
Residual standard error: 1963 on 48 degrees of freedom
Multiple R-squared: 0.9058, Adjusted R-squared: 0.8822
F-statistic: 38.45 on 12 and 48 DF, p-value: < 2.2e-16
> if (n > n25) {
+ kp3 <- k + 3
+ nmkm3 <- n - k - 3
+ gqarr <- array(NA, dim=c(nmkm3-kp3+1,3))
+ numgqtests <- 0
+ numsignificant1 <- 0
+ numsignificant5 <- 0
+ numsignificant10 <- 0
+ for (mypoint in kp3:nmkm3) {
+ j <- 0
+ numgqtests <- numgqtests + 1
+ for (myalt in c('greater', 'two.sided', 'less')) {
+ j <- j + 1
+ gqarr[mypoint-kp3+1,j] <- gqtest(mylm, point=mypoint, alternative=myalt)$p.value
+ }
+ if (gqarr[mypoint-kp3+1,2] < 0.01) numsignificant1 <- numsignificant1 + 1
+ if (gqarr[mypoint-kp3+1,2] < 0.05) numsignificant5 <- numsignificant5 + 1
+ if (gqarr[mypoint-kp3+1,2] < 0.10) numsignificant10 <- numsignificant10 + 1
+ }
+ gqarr
+ }
[,1] [,2] [,3]
[1,] 0.44464673 0.8892935 0.5553533
[2,] 0.37373413 0.7474683 0.6262659
[3,] 0.47376582 0.9475316 0.5262342
[4,] 0.72944545 0.5411091 0.2705545
[5,] 0.62962314 0.7407537 0.3703769
[6,] 0.69260473 0.6147905 0.3073953
[7,] 0.68811130 0.6237774 0.3118887
[8,] 0.61538788 0.7692242 0.3846121
[9,] 0.53397316 0.9320537 0.4660268
[10,] 0.51273658 0.9745268 0.4872634
[11,] 0.47323394 0.9464679 0.5267661
[12,] 0.40095322 0.8019064 0.5990468
[13,] 0.45731230 0.9146246 0.5426877
[14,] 0.38037631 0.7607526 0.6196237
[15,] 0.31068455 0.6213691 0.6893155
[16,] 0.24279724 0.4855945 0.7572028
[17,] 0.34442439 0.6888488 0.6555756
[18,] 0.26212423 0.5242485 0.7378758
[19,] 0.20196213 0.4039243 0.7980379
[20,] 0.18680291 0.3736058 0.8131971
[21,] 0.14150778 0.2830156 0.8584922
[22,] 0.14640207 0.2928041 0.8535979
[23,] 0.15915313 0.3183063 0.8408469
[24,] 0.11071634 0.2214327 0.8892837
[25,] 0.10279771 0.2055954 0.8972023
[26,] 0.06846976 0.1369395 0.9315302
[27,] 0.06831084 0.1366217 0.9316892
[28,] 0.03816110 0.0763222 0.9618389
[29,] 0.10867570 0.2173514 0.8913243
[30,] 0.38034111 0.7606822 0.6196589
> postscript(file="/var/www/html/rcomp/tmp/1ae1o1258729336.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$resid)
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/21k451258729336.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> plot(mysum$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/364jw1258729336.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> hist(mysum$resid, main='Residual Histogram', xlab='values of Residuals')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/4jbgv1258729336.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> densityplot(~mysum$resid,col='black',main='Residual Density Plot', xlab='values of Residuals')
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/5thol1258729336.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
178.13187 421.57912 896.57912 1993.97912 -413.42088 -1768.02088
7 8 9 10 11 12
-1504.82088 -1423.44176 -2090.04176 1444.15824 -1564.04176 450.35824
13 14 15 16 17 18
-503.86813 -2575.42088 206.57912 -1115.02088 1799.57912 2146.97912
19 20 21 22 23 24
3905.17912 -740.44176 2240.95824 -1908.84176 -1377.04176 -951.64176
25 26 27 28 29 30
-1982.86813 -1365.42088 -890.42088 -2446.02088 967.57912 -808.02088
31 32 33 34 35 36
50.17912 -2046.44176 604.95824 178.15824 883.95824 408.35824
37 38 39 40 41 42
236.13187 2415.57912 1541.57912 924.97912 1409.57912 2751.97912
43 44 45 46 47 48
-581.82088 4974.66264 2277.06264 2181.26264 1617.06264 455.46264
49 50 51 52 53 54
1278.23626 1103.68352 -1754.31648 642.08352 -3763.31648 -2322.91648
55 56 57 58 59 60
-1868.71648 -764.33736 -3032.93736 -1894.73736 440.06264 -362.53736
61
794.23626
> postscript(file="/var/www/html/rcomp/tmp/62u4t1258729336.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
0 178.13187 NA
1 421.57912 178.13187
2 896.57912 421.57912
3 1993.97912 896.57912
4 -413.42088 1993.97912
5 -1768.02088 -413.42088
6 -1504.82088 -1768.02088
7 -1423.44176 -1504.82088
8 -2090.04176 -1423.44176
9 1444.15824 -2090.04176
10 -1564.04176 1444.15824
11 450.35824 -1564.04176
12 -503.86813 450.35824
13 -2575.42088 -503.86813
14 206.57912 -2575.42088
15 -1115.02088 206.57912
16 1799.57912 -1115.02088
17 2146.97912 1799.57912
18 3905.17912 2146.97912
19 -740.44176 3905.17912
20 2240.95824 -740.44176
21 -1908.84176 2240.95824
22 -1377.04176 -1908.84176
23 -951.64176 -1377.04176
24 -1982.86813 -951.64176
25 -1365.42088 -1982.86813
26 -890.42088 -1365.42088
27 -2446.02088 -890.42088
28 967.57912 -2446.02088
29 -808.02088 967.57912
30 50.17912 -808.02088
31 -2046.44176 50.17912
32 604.95824 -2046.44176
33 178.15824 604.95824
34 883.95824 178.15824
35 408.35824 883.95824
36 236.13187 408.35824
37 2415.57912 236.13187
38 1541.57912 2415.57912
39 924.97912 1541.57912
40 1409.57912 924.97912
41 2751.97912 1409.57912
42 -581.82088 2751.97912
43 4974.66264 -581.82088
44 2277.06264 4974.66264
45 2181.26264 2277.06264
46 1617.06264 2181.26264
47 455.46264 1617.06264
48 1278.23626 455.46264
49 1103.68352 1278.23626
50 -1754.31648 1103.68352
51 642.08352 -1754.31648
52 -3763.31648 642.08352
53 -2322.91648 -3763.31648
54 -1868.71648 -2322.91648
55 -764.33736 -1868.71648
56 -3032.93736 -764.33736
57 -1894.73736 -3032.93736
58 440.06264 -1894.73736
59 -362.53736 440.06264
60 794.23626 -362.53736
61 NA 794.23626
> dum1 <- dum[2:length(myerror),]
> dum1
lag(myerror, k = 1) myerror
[1,] 421.57912 178.13187
[2,] 896.57912 421.57912
[3,] 1993.97912 896.57912
[4,] -413.42088 1993.97912
[5,] -1768.02088 -413.42088
[6,] -1504.82088 -1768.02088
[7,] -1423.44176 -1504.82088
[8,] -2090.04176 -1423.44176
[9,] 1444.15824 -2090.04176
[10,] -1564.04176 1444.15824
[11,] 450.35824 -1564.04176
[12,] -503.86813 450.35824
[13,] -2575.42088 -503.86813
[14,] 206.57912 -2575.42088
[15,] -1115.02088 206.57912
[16,] 1799.57912 -1115.02088
[17,] 2146.97912 1799.57912
[18,] 3905.17912 2146.97912
[19,] -740.44176 3905.17912
[20,] 2240.95824 -740.44176
[21,] -1908.84176 2240.95824
[22,] -1377.04176 -1908.84176
[23,] -951.64176 -1377.04176
[24,] -1982.86813 -951.64176
[25,] -1365.42088 -1982.86813
[26,] -890.42088 -1365.42088
[27,] -2446.02088 -890.42088
[28,] 967.57912 -2446.02088
[29,] -808.02088 967.57912
[30,] 50.17912 -808.02088
[31,] -2046.44176 50.17912
[32,] 604.95824 -2046.44176
[33,] 178.15824 604.95824
[34,] 883.95824 178.15824
[35,] 408.35824 883.95824
[36,] 236.13187 408.35824
[37,] 2415.57912 236.13187
[38,] 1541.57912 2415.57912
[39,] 924.97912 1541.57912
[40,] 1409.57912 924.97912
[41,] 2751.97912 1409.57912
[42,] -581.82088 2751.97912
[43,] 4974.66264 -581.82088
[44,] 2277.06264 4974.66264
[45,] 2181.26264 2277.06264
[46,] 1617.06264 2181.26264
[47,] 455.46264 1617.06264
[48,] 1278.23626 455.46264
[49,] 1103.68352 1278.23626
[50,] -1754.31648 1103.68352
[51,] 642.08352 -1754.31648
[52,] -3763.31648 642.08352
[53,] -2322.91648 -3763.31648
[54,] -1868.71648 -2322.91648
[55,] -764.33736 -1868.71648
[56,] -3032.93736 -764.33736
[57,] -1894.73736 -3032.93736
[58,] 440.06264 -1894.73736
[59,] -362.53736 440.06264
[60,] 794.23626 -362.53736
> z <- as.data.frame(dum1)
> z
lag(myerror, k = 1) myerror
1 421.57912 178.13187
2 896.57912 421.57912
3 1993.97912 896.57912
4 -413.42088 1993.97912
5 -1768.02088 -413.42088
6 -1504.82088 -1768.02088
7 -1423.44176 -1504.82088
8 -2090.04176 -1423.44176
9 1444.15824 -2090.04176
10 -1564.04176 1444.15824
11 450.35824 -1564.04176
12 -503.86813 450.35824
13 -2575.42088 -503.86813
14 206.57912 -2575.42088
15 -1115.02088 206.57912
16 1799.57912 -1115.02088
17 2146.97912 1799.57912
18 3905.17912 2146.97912
19 -740.44176 3905.17912
20 2240.95824 -740.44176
21 -1908.84176 2240.95824
22 -1377.04176 -1908.84176
23 -951.64176 -1377.04176
24 -1982.86813 -951.64176
25 -1365.42088 -1982.86813
26 -890.42088 -1365.42088
27 -2446.02088 -890.42088
28 967.57912 -2446.02088
29 -808.02088 967.57912
30 50.17912 -808.02088
31 -2046.44176 50.17912
32 604.95824 -2046.44176
33 178.15824 604.95824
34 883.95824 178.15824
35 408.35824 883.95824
36 236.13187 408.35824
37 2415.57912 236.13187
38 1541.57912 2415.57912
39 924.97912 1541.57912
40 1409.57912 924.97912
41 2751.97912 1409.57912
42 -581.82088 2751.97912
43 4974.66264 -581.82088
44 2277.06264 4974.66264
45 2181.26264 2277.06264
46 1617.06264 2181.26264
47 455.46264 1617.06264
48 1278.23626 455.46264
49 1103.68352 1278.23626
50 -1754.31648 1103.68352
51 642.08352 -1754.31648
52 -3763.31648 642.08352
53 -2322.91648 -3763.31648
54 -1868.71648 -2322.91648
55 -764.33736 -1868.71648
56 -3032.93736 -764.33736
57 -1894.73736 -3032.93736
58 440.06264 -1894.73736
59 -362.53736 440.06264
60 794.23626 -362.53736
> 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/74edg1258729336.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> acf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/8gl141258729336.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> pacf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Partial Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/9y0qc1258729336.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> opar <- par(mfrow = c(2,2), oma = c(0, 0, 1.1, 0))
> plot(mylm, las = 1, sub='Residual Diagnostics')
> par(opar)
> dev.off()
null device
1
> if (n > n25) {
+ postscript(file="/var/www/html/rcomp/tmp/10fldp1258729336.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
+ plot(kp3:nmkm3,gqarr[,2], main='Goldfeld-Quandt test',ylab='2-sided p-value',xlab='breakpoint')
+ grid()
+ dev.off()
+ }
null device
1
>
> #Note: the /var/www/html/rcomp/createtable file can be downloaded at http://www.wessa.net/cretab
> load(file="/var/www/html/rcomp/createtable")
>
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a, 'Multiple Linear Regression - Estimated Regression Equation', 1, TRUE)
> a<-table.row.end(a)
> myeq <- colnames(x)[1]
> myeq <- paste(myeq, '[t] = ', sep='')
> for (i in 1:k){
+ if (mysum$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/11ougt1258729336.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/12aoys1258729336.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/13hnb31258729336.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/14fwp11258729336.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/15q9cf1258729336.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/16fp3n1258729336.tab")
+ }
>
> system("convert tmp/1ae1o1258729336.ps tmp/1ae1o1258729336.png")
> system("convert tmp/21k451258729336.ps tmp/21k451258729336.png")
> system("convert tmp/364jw1258729336.ps tmp/364jw1258729336.png")
> system("convert tmp/4jbgv1258729336.ps tmp/4jbgv1258729336.png")
> system("convert tmp/5thol1258729336.ps tmp/5thol1258729336.png")
> system("convert tmp/62u4t1258729336.ps tmp/62u4t1258729336.png")
> system("convert tmp/74edg1258729336.ps tmp/74edg1258729336.png")
> system("convert tmp/8gl141258729336.ps tmp/8gl141258729336.png")
> system("convert tmp/9y0qc1258729336.ps tmp/9y0qc1258729336.png")
> system("convert tmp/10fldp1258729336.ps tmp/10fldp1258729336.png")
>
>
> proc.time()
user system elapsed
2.494 1.607 4.549