R version 2.8.0 (2008-10-20)
Copyright (C) 2008 The R Foundation for Statistical Computing
ISBN 3-900051-07-0
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> x <- array(list(127059,0,122860,0,117702,0,113537,0,108366,0,111078,0,150739,1,159129,0,157928,0,147768,0,137507,0,136919,0,136151,0,133001,0,125554,0,119647,0,114158,0,116193,0,152803,1,161761,0,160942,0,149470,0,139208,0,134588,0,130322,0,126611,0,122401,0,117352,0,112135,0,112879,0,148729,1,157230,0,157221,0,146681,0,136524,0,132111,0,125326,0,122716,0,116615,0,113719,0,110737,0,112093,0,143565,1,149946,0,149147,0,134339,0,122683,0,115614,0,116566,0,111272,0,104609,0,101802,0,94542,0,93051,0,124129,1,130374,0,123946,0,114971,0,105531,0,104919,0),dim=c(2,60),dimnames=list(c('X','Y'),1:60))
> y <- array(NA,dim=c(2,60),dimnames=list(c('X','Y'),1:60))
> for (i in 1:dim(x)[1])
+ {
+ for (j in 1:dim(x)[2])
+ {
+ y[i,j] <- as.numeric(x[i,j])
+ }
+ }
> par3 = 'Linear Trend'
> par2 = 'Include Quarterly 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
X Y Q1 Q2 Q3 t
1 127059 0 1 0 0 1
2 122860 0 0 1 0 2
3 117702 0 0 0 1 3
4 113537 0 0 0 0 4
5 108366 0 1 0 0 5
6 111078 0 0 1 0 6
7 150739 1 0 0 1 7
8 159129 0 0 0 0 8
9 157928 0 1 0 0 9
10 147768 0 0 1 0 10
11 137507 0 0 0 1 11
12 136919 0 0 0 0 12
13 136151 0 1 0 0 13
14 133001 0 0 1 0 14
15 125554 0 0 0 1 15
16 119647 0 0 0 0 16
17 114158 0 1 0 0 17
18 116193 0 0 1 0 18
19 152803 1 0 0 1 19
20 161761 0 0 0 0 20
21 160942 0 1 0 0 21
22 149470 0 0 1 0 22
23 139208 0 0 0 1 23
24 134588 0 0 0 0 24
25 130322 0 1 0 0 25
26 126611 0 0 1 0 26
27 122401 0 0 0 1 27
28 117352 0 0 0 0 28
29 112135 0 1 0 0 29
30 112879 0 0 1 0 30
31 148729 1 0 0 1 31
32 157230 0 0 0 0 32
33 157221 0 1 0 0 33
34 146681 0 0 1 0 34
35 136524 0 0 0 1 35
36 132111 0 0 0 0 36
37 125326 0 1 0 0 37
38 122716 0 0 1 0 38
39 116615 0 0 0 1 39
40 113719 0 0 0 0 40
41 110737 0 1 0 0 41
42 112093 0 0 1 0 42
43 143565 1 0 0 1 43
44 149946 0 0 0 0 44
45 149147 0 1 0 0 45
46 134339 0 0 1 0 46
47 122683 0 0 0 1 47
48 115614 0 0 0 0 48
49 116566 0 1 0 0 49
50 111272 0 0 1 0 50
51 104609 0 0 0 1 51
52 101802 0 0 0 0 52
53 94542 0 1 0 0 53
54 93051 0 0 1 0 54
55 124129 1 0 0 1 55
56 130374 0 0 0 0 56
57 123946 0 1 0 0 57
58 114971 0 0 1 0 58
59 105531 0 0 0 1 59
60 104919 0 0 0 0 60
> k <- length(x[1,])
> df <- as.data.frame(x)
> (mylm <- lm(df))
Call:
lm(formula = df)
Coefficients:
(Intercept) Y Q1 Q2 Q3 t
141817.1 21159.6 -2723.1 -6988.5 -7448.6 -372.1
> (mysum <- summary(mylm))
Call:
lm(formula = df)
Residuals:
Min 1Q Median 3Q Max
-28867.5 -11731.6 -216.6 7772.3 30406.3
Coefficients:
Estimate Std. Error t value Pr(>|t|)
(Intercept) 141817.1 5728.2 24.758 < 2e-16 ***
Y 21159.6 8916.6 2.373 0.02123 *
Q1 -2723.1 5955.6 -0.457 0.64934
Q2 -6988.5 5949.4 -1.175 0.24528
Q3 -7448.6 6647.2 -1.121 0.26743
t -372.1 121.6 -3.060 0.00345 **
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
Residual standard error: 16280 on 54 degrees of freedom
Multiple R-squared: 0.2337, Adjusted R-squared: 0.1628
F-statistic: 3.294 on 5 and 54 DF, p-value: 0.01144
> 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,] 0.9158129 0.1683743 0.08418713
[2,] 0.8475356 0.3049287 0.15246437
[3,] 0.7737514 0.4524971 0.22624857
[4,] 0.7505466 0.4989068 0.24945338
[5,] 0.7118566 0.5762868 0.28814340
[6,] 0.6420290 0.7159420 0.35797101
[7,] 0.6038171 0.7923658 0.39618289
[8,] 0.7088128 0.5823743 0.29118715
[9,] 0.8032233 0.3935534 0.19677670
[10,] 0.8128823 0.3742354 0.18711769
[11,] 0.7481175 0.5037651 0.25188253
[12,] 0.7893322 0.4213356 0.21066781
[13,] 0.8228676 0.3542647 0.17713236
[14,] 0.7962567 0.4074866 0.20374328
[15,] 0.7345891 0.5308218 0.26541092
[16,] 0.6943511 0.6112979 0.30564893
[17,] 0.6549399 0.6901202 0.34506012
[18,] 0.6030887 0.7938227 0.39691134
[19,] 0.5655448 0.8689103 0.43445517
[20,] 0.6517944 0.6964112 0.34820561
[21,] 0.7614374 0.4771252 0.23856260
[22,] 0.8075259 0.3849481 0.19247406
[23,] 0.7539813 0.4920374 0.24601871
[24,] 0.7638842 0.4722316 0.23611581
[25,] 0.8042363 0.3915274 0.19576370
[26,] 0.8029846 0.3940309 0.19701545
[27,] 0.7597067 0.4805865 0.24029327
[28,] 0.6984618 0.6030764 0.30153822
[29,] 0.6381973 0.7236055 0.36180275
[30,] 0.5643161 0.8713677 0.43568387
[31,] 0.5055222 0.9889556 0.49447781
[32,] 0.5453307 0.9093385 0.45466926
[33,] 0.6108069 0.7783863 0.38919313
[34,] 0.6068098 0.7863803 0.39319017
[35,] 0.5116452 0.9767096 0.48835480
[36,] 0.5288614 0.9422773 0.47113863
[37,] 0.6506393 0.6987213 0.34936067
[38,] 0.7060580 0.5878840 0.29394199
[39,] 0.6861128 0.6277743 0.31388715
[40,] 0.5967603 0.8064794 0.40323970
[41,] 0.5113683 0.9772634 0.48863170
[42,] 0.4388548 0.8777097 0.56114516
[43,] 0.3416268 0.6832536 0.65837321
> postscript(file="/var/www/html/rcomp/tmp/1jxvu1227466158.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$resid)
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/2o8um1227466158.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> plot(mysum$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/3wlu91227466158.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> hist(mysum$resid, main='Residual Histogram', xlab='values of Residuals')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/4subn1227466158.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> densityplot(~mysum$resid,col='black',main='Residual Density Plot', xlab='values of Residuals')
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/5pei81227466158.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 = 60
Frequency = 1
1 2 3 4 5
-1.166290e+04 -1.122436e+04 -1.555023e+04 -2.679170e+04 -2.886749e+04
6 7 8 9 10
-2.151796e+04 -2.184427e+03 2.028871e+04 2.218291e+04 1.666044e+04
11 12 13 14 15
7.231578e+03 -4.328890e+02 1.894315e+03 3.381849e+03 -3.233018e+03
16 17 18 19 20
-1.621648e+04 -1.861028e+04 -1.193775e+04 4.344787e+03 2.738592e+04
21 22 23 24 25
2.966212e+04 2.282766e+04 1.339779e+04 1.701324e+03 5.305289e+02
26 27 28 29 30
1.457062e+03 -1.920804e+03 -1.404627e+04 -1.616807e+04 -1.078653e+04
31 32 33 34 35
4.736000e+03 2.732013e+04 3.040634e+04 2.450387e+04 1.517900e+04
36 37 38 39 40
3.689538e+03 -2.577381e-01 2.027276e+03 -3.241591e+03 -1.321406e+04
41 42 43 44 45
-1.310085e+04 -7.107320e+03 4.037213e+03 2.450135e+04 2.679755e+04
46 47 48 49 50
1.662708e+04 5.803218e+03 -8.342249e+03 -4.295044e+03 -4.951511e+03
51 52 53 54 55
-1.078238e+04 -2.066584e+04 -2.483064e+04 -2.168411e+04 -1.093357e+04
56 57 58 59 60
9.394560e+03 6.061765e+03 1.724298e+03 -6.883569e+03 -1.457204e+04
> postscript(file="/var/www/html/rcomp/tmp/6aqdf1227466158.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 = 60
Frequency = 1
lag(myerror, k = 1) myerror
0 -1.166290e+04 NA
1 -1.122436e+04 -1.166290e+04
2 -1.555023e+04 -1.122436e+04
3 -2.679170e+04 -1.555023e+04
4 -2.886749e+04 -2.679170e+04
5 -2.151796e+04 -2.886749e+04
6 -2.184427e+03 -2.151796e+04
7 2.028871e+04 -2.184427e+03
8 2.218291e+04 2.028871e+04
9 1.666044e+04 2.218291e+04
10 7.231578e+03 1.666044e+04
11 -4.328890e+02 7.231578e+03
12 1.894315e+03 -4.328890e+02
13 3.381849e+03 1.894315e+03
14 -3.233018e+03 3.381849e+03
15 -1.621648e+04 -3.233018e+03
16 -1.861028e+04 -1.621648e+04
17 -1.193775e+04 -1.861028e+04
18 4.344787e+03 -1.193775e+04
19 2.738592e+04 4.344787e+03
20 2.966212e+04 2.738592e+04
21 2.282766e+04 2.966212e+04
22 1.339779e+04 2.282766e+04
23 1.701324e+03 1.339779e+04
24 5.305289e+02 1.701324e+03
25 1.457062e+03 5.305289e+02
26 -1.920804e+03 1.457062e+03
27 -1.404627e+04 -1.920804e+03
28 -1.616807e+04 -1.404627e+04
29 -1.078653e+04 -1.616807e+04
30 4.736000e+03 -1.078653e+04
31 2.732013e+04 4.736000e+03
32 3.040634e+04 2.732013e+04
33 2.450387e+04 3.040634e+04
34 1.517900e+04 2.450387e+04
35 3.689538e+03 1.517900e+04
36 -2.577381e-01 3.689538e+03
37 2.027276e+03 -2.577381e-01
38 -3.241591e+03 2.027276e+03
39 -1.321406e+04 -3.241591e+03
40 -1.310085e+04 -1.321406e+04
41 -7.107320e+03 -1.310085e+04
42 4.037213e+03 -7.107320e+03
43 2.450135e+04 4.037213e+03
44 2.679755e+04 2.450135e+04
45 1.662708e+04 2.679755e+04
46 5.803218e+03 1.662708e+04
47 -8.342249e+03 5.803218e+03
48 -4.295044e+03 -8.342249e+03
49 -4.951511e+03 -4.295044e+03
50 -1.078238e+04 -4.951511e+03
51 -2.066584e+04 -1.078238e+04
52 -2.483064e+04 -2.066584e+04
53 -2.168411e+04 -2.483064e+04
54 -1.093357e+04 -2.168411e+04
55 9.394560e+03 -1.093357e+04
56 6.061765e+03 9.394560e+03
57 1.724298e+03 6.061765e+03
58 -6.883569e+03 1.724298e+03
59 -1.457204e+04 -6.883569e+03
60 NA -1.457204e+04
> dum1 <- dum[2:length(myerror),]
> dum1
lag(myerror, k = 1) myerror
[1,] -1.122436e+04 -1.166290e+04
[2,] -1.555023e+04 -1.122436e+04
[3,] -2.679170e+04 -1.555023e+04
[4,] -2.886749e+04 -2.679170e+04
[5,] -2.151796e+04 -2.886749e+04
[6,] -2.184427e+03 -2.151796e+04
[7,] 2.028871e+04 -2.184427e+03
[8,] 2.218291e+04 2.028871e+04
[9,] 1.666044e+04 2.218291e+04
[10,] 7.231578e+03 1.666044e+04
[11,] -4.328890e+02 7.231578e+03
[12,] 1.894315e+03 -4.328890e+02
[13,] 3.381849e+03 1.894315e+03
[14,] -3.233018e+03 3.381849e+03
[15,] -1.621648e+04 -3.233018e+03
[16,] -1.861028e+04 -1.621648e+04
[17,] -1.193775e+04 -1.861028e+04
[18,] 4.344787e+03 -1.193775e+04
[19,] 2.738592e+04 4.344787e+03
[20,] 2.966212e+04 2.738592e+04
[21,] 2.282766e+04 2.966212e+04
[22,] 1.339779e+04 2.282766e+04
[23,] 1.701324e+03 1.339779e+04
[24,] 5.305289e+02 1.701324e+03
[25,] 1.457062e+03 5.305289e+02
[26,] -1.920804e+03 1.457062e+03
[27,] -1.404627e+04 -1.920804e+03
[28,] -1.616807e+04 -1.404627e+04
[29,] -1.078653e+04 -1.616807e+04
[30,] 4.736000e+03 -1.078653e+04
[31,] 2.732013e+04 4.736000e+03
[32,] 3.040634e+04 2.732013e+04
[33,] 2.450387e+04 3.040634e+04
[34,] 1.517900e+04 2.450387e+04
[35,] 3.689538e+03 1.517900e+04
[36,] -2.577381e-01 3.689538e+03
[37,] 2.027276e+03 -2.577381e-01
[38,] -3.241591e+03 2.027276e+03
[39,] -1.321406e+04 -3.241591e+03
[40,] -1.310085e+04 -1.321406e+04
[41,] -7.107320e+03 -1.310085e+04
[42,] 4.037213e+03 -7.107320e+03
[43,] 2.450135e+04 4.037213e+03
[44,] 2.679755e+04 2.450135e+04
[45,] 1.662708e+04 2.679755e+04
[46,] 5.803218e+03 1.662708e+04
[47,] -8.342249e+03 5.803218e+03
[48,] -4.295044e+03 -8.342249e+03
[49,] -4.951511e+03 -4.295044e+03
[50,] -1.078238e+04 -4.951511e+03
[51,] -2.066584e+04 -1.078238e+04
[52,] -2.483064e+04 -2.066584e+04
[53,] -2.168411e+04 -2.483064e+04
[54,] -1.093357e+04 -2.168411e+04
[55,] 9.394560e+03 -1.093357e+04
[56,] 6.061765e+03 9.394560e+03
[57,] 1.724298e+03 6.061765e+03
[58,] -6.883569e+03 1.724298e+03
[59,] -1.457204e+04 -6.883569e+03
> z <- as.data.frame(dum1)
> z
lag(myerror, k = 1) myerror
1 -1.122436e+04 -1.166290e+04
2 -1.555023e+04 -1.122436e+04
3 -2.679170e+04 -1.555023e+04
4 -2.886749e+04 -2.679170e+04
5 -2.151796e+04 -2.886749e+04
6 -2.184427e+03 -2.151796e+04
7 2.028871e+04 -2.184427e+03
8 2.218291e+04 2.028871e+04
9 1.666044e+04 2.218291e+04
10 7.231578e+03 1.666044e+04
11 -4.328890e+02 7.231578e+03
12 1.894315e+03 -4.328890e+02
13 3.381849e+03 1.894315e+03
14 -3.233018e+03 3.381849e+03
15 -1.621648e+04 -3.233018e+03
16 -1.861028e+04 -1.621648e+04
17 -1.193775e+04 -1.861028e+04
18 4.344787e+03 -1.193775e+04
19 2.738592e+04 4.344787e+03
20 2.966212e+04 2.738592e+04
21 2.282766e+04 2.966212e+04
22 1.339779e+04 2.282766e+04
23 1.701324e+03 1.339779e+04
24 5.305289e+02 1.701324e+03
25 1.457062e+03 5.305289e+02
26 -1.920804e+03 1.457062e+03
27 -1.404627e+04 -1.920804e+03
28 -1.616807e+04 -1.404627e+04
29 -1.078653e+04 -1.616807e+04
30 4.736000e+03 -1.078653e+04
31 2.732013e+04 4.736000e+03
32 3.040634e+04 2.732013e+04
33 2.450387e+04 3.040634e+04
34 1.517900e+04 2.450387e+04
35 3.689538e+03 1.517900e+04
36 -2.577381e-01 3.689538e+03
37 2.027276e+03 -2.577381e-01
38 -3.241591e+03 2.027276e+03
39 -1.321406e+04 -3.241591e+03
40 -1.310085e+04 -1.321406e+04
41 -7.107320e+03 -1.310085e+04
42 4.037213e+03 -7.107320e+03
43 2.450135e+04 4.037213e+03
44 2.679755e+04 2.450135e+04
45 1.662708e+04 2.679755e+04
46 5.803218e+03 1.662708e+04
47 -8.342249e+03 5.803218e+03
48 -4.295044e+03 -8.342249e+03
49 -4.951511e+03 -4.295044e+03
50 -1.078238e+04 -4.951511e+03
51 -2.066584e+04 -1.078238e+04
52 -2.483064e+04 -2.066584e+04
53 -2.168411e+04 -2.483064e+04
54 -1.093357e+04 -2.168411e+04
55 9.394560e+03 -1.093357e+04
56 6.061765e+03 9.394560e+03
57 1.724298e+03 6.061765e+03
58 -6.883569e+03 1.724298e+03
59 -1.457204e+04 -6.883569e+03
> 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/7btff1227466158.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> acf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/817fs1227466158.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> pacf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Partial Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/9k8ji1227466158.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> opar <- par(mfrow = c(2,2), oma = c(0, 0, 1.1, 0))
> plot(mylm, las = 1, sub='Residual Diagnostics')
> par(opar)
> dev.off()
null device
1
> if (n > n25) {
+ postscript(file="/var/www/html/rcomp/tmp/104ybw1227466158.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
+ plot(kp3:nmkm3,gqarr[,2], main='Goldfeld-Quandt test',ylab='2-sided p-value',xlab='breakpoint')
+ grid()
+ dev.off()
+ }
null device
1
>
> #Note: the /var/www/html/rcomp/createtable file can be downloaded at http://www.wessa.net/cretab
> load(file="/var/www/html/rcomp/createtable")
>
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a, 'Multiple Linear Regression - Estimated Regression Equation', 1, TRUE)
> a<-table.row.end(a)
> myeq <- colnames(x)[1]
> myeq <- paste(myeq, '[t] = ', sep='')
> for (i in 1:k){
+ if (mysum$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/1193ub1227466158.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/12mcr31227466158.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/13m3ui1227466158.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/14dyz51227466158.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/15qahg1227466158.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/16vr2h1227466158.tab")
+ }
>
> system("convert tmp/1jxvu1227466158.ps tmp/1jxvu1227466158.png")
> system("convert tmp/2o8um1227466158.ps tmp/2o8um1227466158.png")
> system("convert tmp/3wlu91227466158.ps tmp/3wlu91227466158.png")
> system("convert tmp/4subn1227466158.ps tmp/4subn1227466158.png")
> system("convert tmp/5pei81227466158.ps tmp/5pei81227466158.png")
> system("convert tmp/6aqdf1227466158.ps tmp/6aqdf1227466158.png")
> system("convert tmp/7btff1227466158.ps tmp/7btff1227466158.png")
> system("convert tmp/817fs1227466158.ps tmp/817fs1227466158.png")
> system("convert tmp/9k8ji1227466158.ps tmp/9k8ji1227466158.png")
> system("convert tmp/104ybw1227466158.ps tmp/104ybw1227466158.png")
>
>
> proc.time()
user system elapsed
2.432 1.551 2.849