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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'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(2.11,0,2.09,0,2.05,0,2.08,0,2.06,0,2.06,0,2.08,0,2.07,0,2.06,0,2.07,0,2.06,0,2.09,0,2.07,0,2.09,0,2.28,0,2.33,0,2.35,0,2.52,0,2.63,0,2.58,0,2.70,0,2.81,0,2.97,0,3.04,0,3.28,0,3.33,0,3.50,0,3.56,0,3.57,0,3.69,0,3.82,0,3.79,0,3.96,0,4.06,0,4.05,0,4.03,0,3.94,0,4.02,0,3.88,0,4.02,0,4.03,0,4.09,0,3.99,0,4.01,0,4.01,0,4.19,0,4.30,0,4.27,0,3.82,0,3.15,1,2.49,1,1.81,1,1.26,1,1.06,1,0.84,1,0.78,1,0.70,1,0.36,1,0.35,1,0.36,1),dim=c(2,60),dimnames=list(c('Y','X'),1:60))
> y <- array(NA,dim=c(2,60),dimnames=list(c('Y','X'),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 = '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
Y X t
1 2.11 0 1
2 2.09 0 2
3 2.05 0 3
4 2.08 0 4
5 2.06 0 5
6 2.06 0 6
7 2.08 0 7
8 2.07 0 8
9 2.06 0 9
10 2.07 0 10
11 2.06 0 11
12 2.09 0 12
13 2.07 0 13
14 2.09 0 14
15 2.28 0 15
16 2.33 0 16
17 2.35 0 17
18 2.52 0 18
19 2.63 0 19
20 2.58 0 20
21 2.70 0 21
22 2.81 0 22
23 2.97 0 23
24 3.04 0 24
25 3.28 0 25
26 3.33 0 26
27 3.50 0 27
28 3.56 0 28
29 3.57 0 29
30 3.69 0 30
31 3.82 0 31
32 3.79 0 32
33 3.96 0 33
34 4.06 0 34
35 4.05 0 35
36 4.03 0 36
37 3.94 0 37
38 4.02 0 38
39 3.88 0 39
40 4.02 0 40
41 4.03 0 41
42 4.09 0 42
43 3.99 0 43
44 4.01 0 44
45 4.01 0 45
46 4.19 0 46
47 4.30 0 47
48 4.27 0 48
49 3.82 0 49
50 3.15 1 50
51 2.49 1 51
52 1.81 1 52
53 1.26 1 53
54 1.06 1 54
55 0.84 1 55
56 0.78 1 56
57 0.70 1 57
58 0.36 1 58
59 0.35 1 59
60 0.36 1 60
> k <- length(x[1,])
> df <- as.data.frame(x)
> (mylm <- lm(df))
Call:
lm(formula = df)
Coefficients:
(Intercept) X t
1.77079 -3.52383 0.05363
> (mysum <- summary(mylm))
Call:
lm(formula = df)
Residuals:
Min 1Q Median 3Q Max
-1.10449 -0.24361 -0.03336 0.21157 2.22176
Coefficients:
Estimate Std. Error t value Pr(>|t|)
(Intercept) 1.770788 0.148037 11.96 < 2e-16 ***
X -3.523834 0.230361 -15.30 < 2e-16 ***
t 0.053626 0.005147 10.42 8.18e-15 ***
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
Residual standard error: 0.5124 on 57 degrees of freedom
Multiple R-squared: 0.8042, Adjusted R-squared: 0.7973
F-statistic: 117 on 2 and 57 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,] 6.996183e-05 1.399237e-04 0.99993004
[2,] 5.218053e-06 1.043611e-05 0.99999478
[3,] 2.032749e-07 4.065498e-07 0.99999980
[4,] 6.425831e-09 1.285166e-08 0.99999999
[5,] 2.408092e-10 4.816183e-10 1.00000000
[6,] 6.936663e-12 1.387333e-11 1.00000000
[7,] 8.352048e-13 1.670410e-12 1.00000000
[8,] 2.733242e-14 5.466484e-14 1.00000000
[9,] 1.926231e-15 3.852462e-15 1.00000000
[10,] 7.799268e-11 1.559854e-10 1.00000000
[11,] 4.436752e-10 8.873503e-10 1.00000000
[12,] 4.272472e-10 8.544945e-10 1.00000000
[13,] 3.580733e-09 7.161467e-09 1.00000000
[14,] 1.828673e-08 3.657347e-08 0.99999998
[15,] 1.216937e-08 2.433874e-08 0.99999999
[16,] 1.480026e-08 2.960053e-08 0.99999999
[17,] 2.531661e-08 5.063322e-08 0.99999997
[18,] 8.422557e-08 1.684511e-07 0.99999992
[19,] 1.786464e-07 3.572927e-07 0.99999982
[20,] 1.057100e-06 2.114199e-06 0.99999894
[21,] 2.495072e-06 4.990144e-06 0.99999750
[22,] 6.953782e-06 1.390756e-05 0.99999305
[23,] 1.168170e-05 2.336339e-05 0.99998832
[24,] 1.300936e-05 2.601872e-05 0.99998699
[25,] 1.518203e-05 3.036406e-05 0.99998482
[26,] 1.828708e-05 3.657416e-05 0.99998171
[27,] 1.650921e-05 3.301841e-05 0.99998349
[28,] 1.640440e-05 3.280879e-05 0.99998360
[29,] 1.513219e-05 3.026437e-05 0.99998487
[30,] 1.125466e-05 2.250933e-05 0.99998875
[31,] 8.002511e-06 1.600502e-05 0.99999200
[32,] 7.943539e-06 1.588708e-05 0.99999206
[33,] 7.835298e-06 1.567060e-05 0.99999216
[34,] 2.245562e-05 4.491123e-05 0.99997754
[35,] 4.526783e-05 9.053565e-05 0.99995473
[36,] 1.215537e-04 2.431074e-04 0.99987845
[37,] 2.884674e-04 5.769348e-04 0.99971153
[38,] 1.567091e-03 3.134181e-03 0.99843291
[39,] 7.537081e-03 1.507416e-02 0.99246292
[40,] 3.094913e-02 6.189826e-02 0.96905087
[41,] 3.654097e-02 7.308195e-02 0.96345903
[42,] 2.367494e-02 4.734988e-02 0.97632506
[43,] 1.607262e-02 3.214524e-02 0.98392738
[44,] 2.313480e-02 4.626961e-02 0.97686520
[45,] 2.099065e-01 4.198130e-01 0.79009348
[46,] 8.064559e-01 3.870882e-01 0.19354408
[47,] 9.856014e-01 2.879727e-02 0.01439863
[48,] 9.818674e-01 3.626528e-02 0.01813264
[49,] 9.604630e-01 7.907403e-02 0.03953701
> postscript(file="/var/www/html/rcomp/tmp/1fudp1258653125.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$resid)
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/2wbor1258653125.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> plot(mysum$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/3r2nw1258653125.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> hist(mysum$resid, main='Residual Histogram', xlab='values of Residuals')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/4wv2m1258653125.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> densityplot(~mysum$resid,col='black',main='Residual Density Plot', xlab='values of Residuals')
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/5vgod1258653125.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 6
0.285586565 0.211960934 0.118335303 0.094709673 0.021084042 -0.032541589
7 8 9 10 11 12
-0.066167219 -0.129792850 -0.193418481 -0.237044111 -0.300669742 -0.324295373
13 14 15 16 17 18
-0.397921003 -0.431546634 -0.295172265 -0.298797895 -0.332423526 -0.216049157
19 20 21 22 23 24
-0.159674787 -0.263300418 -0.196926049 -0.140551679 -0.034177310 -0.017802941
25 26 27 28 29 30
0.168571429 0.164945798 0.281320167 0.287694537 0.244068906 0.310443275
31 32 33 34 35 36
0.386817645 0.303192014 0.419566383 0.465940752 0.402315122 0.328689491
37 38 39 40 41 42
0.185063860 0.211438230 0.017812599 0.104186968 0.060561338 0.066935707
43 44 45 46 47 48
-0.086689924 -0.120315554 -0.173941185 -0.047566816 0.008807554 -0.074818077
49 50 51 52 53 54
-0.578443708 2.221764517 1.508138886 0.774513256 0.170887625 -0.082738006
55 56 57 58 59 60
-0.356363636 -0.469989267 -0.603614898 -0.997240528 -1.060866159 -1.104491790
> postscript(file="/var/www/html/rcomp/tmp/6dhse1258653125.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 0.285586565 NA
1 0.211960934 0.285586565
2 0.118335303 0.211960934
3 0.094709673 0.118335303
4 0.021084042 0.094709673
5 -0.032541589 0.021084042
6 -0.066167219 -0.032541589
7 -0.129792850 -0.066167219
8 -0.193418481 -0.129792850
9 -0.237044111 -0.193418481
10 -0.300669742 -0.237044111
11 -0.324295373 -0.300669742
12 -0.397921003 -0.324295373
13 -0.431546634 -0.397921003
14 -0.295172265 -0.431546634
15 -0.298797895 -0.295172265
16 -0.332423526 -0.298797895
17 -0.216049157 -0.332423526
18 -0.159674787 -0.216049157
19 -0.263300418 -0.159674787
20 -0.196926049 -0.263300418
21 -0.140551679 -0.196926049
22 -0.034177310 -0.140551679
23 -0.017802941 -0.034177310
24 0.168571429 -0.017802941
25 0.164945798 0.168571429
26 0.281320167 0.164945798
27 0.287694537 0.281320167
28 0.244068906 0.287694537
29 0.310443275 0.244068906
30 0.386817645 0.310443275
31 0.303192014 0.386817645
32 0.419566383 0.303192014
33 0.465940752 0.419566383
34 0.402315122 0.465940752
35 0.328689491 0.402315122
36 0.185063860 0.328689491
37 0.211438230 0.185063860
38 0.017812599 0.211438230
39 0.104186968 0.017812599
40 0.060561338 0.104186968
41 0.066935707 0.060561338
42 -0.086689924 0.066935707
43 -0.120315554 -0.086689924
44 -0.173941185 -0.120315554
45 -0.047566816 -0.173941185
46 0.008807554 -0.047566816
47 -0.074818077 0.008807554
48 -0.578443708 -0.074818077
49 2.221764517 -0.578443708
50 1.508138886 2.221764517
51 0.774513256 1.508138886
52 0.170887625 0.774513256
53 -0.082738006 0.170887625
54 -0.356363636 -0.082738006
55 -0.469989267 -0.356363636
56 -0.603614898 -0.469989267
57 -0.997240528 -0.603614898
58 -1.060866159 -0.997240528
59 -1.104491790 -1.060866159
60 NA -1.104491790
> dum1 <- dum[2:length(myerror),]
> dum1
lag(myerror, k = 1) myerror
[1,] 0.211960934 0.285586565
[2,] 0.118335303 0.211960934
[3,] 0.094709673 0.118335303
[4,] 0.021084042 0.094709673
[5,] -0.032541589 0.021084042
[6,] -0.066167219 -0.032541589
[7,] -0.129792850 -0.066167219
[8,] -0.193418481 -0.129792850
[9,] -0.237044111 -0.193418481
[10,] -0.300669742 -0.237044111
[11,] -0.324295373 -0.300669742
[12,] -0.397921003 -0.324295373
[13,] -0.431546634 -0.397921003
[14,] -0.295172265 -0.431546634
[15,] -0.298797895 -0.295172265
[16,] -0.332423526 -0.298797895
[17,] -0.216049157 -0.332423526
[18,] -0.159674787 -0.216049157
[19,] -0.263300418 -0.159674787
[20,] -0.196926049 -0.263300418
[21,] -0.140551679 -0.196926049
[22,] -0.034177310 -0.140551679
[23,] -0.017802941 -0.034177310
[24,] 0.168571429 -0.017802941
[25,] 0.164945798 0.168571429
[26,] 0.281320167 0.164945798
[27,] 0.287694537 0.281320167
[28,] 0.244068906 0.287694537
[29,] 0.310443275 0.244068906
[30,] 0.386817645 0.310443275
[31,] 0.303192014 0.386817645
[32,] 0.419566383 0.303192014
[33,] 0.465940752 0.419566383
[34,] 0.402315122 0.465940752
[35,] 0.328689491 0.402315122
[36,] 0.185063860 0.328689491
[37,] 0.211438230 0.185063860
[38,] 0.017812599 0.211438230
[39,] 0.104186968 0.017812599
[40,] 0.060561338 0.104186968
[41,] 0.066935707 0.060561338
[42,] -0.086689924 0.066935707
[43,] -0.120315554 -0.086689924
[44,] -0.173941185 -0.120315554
[45,] -0.047566816 -0.173941185
[46,] 0.008807554 -0.047566816
[47,] -0.074818077 0.008807554
[48,] -0.578443708 -0.074818077
[49,] 2.221764517 -0.578443708
[50,] 1.508138886 2.221764517
[51,] 0.774513256 1.508138886
[52,] 0.170887625 0.774513256
[53,] -0.082738006 0.170887625
[54,] -0.356363636 -0.082738006
[55,] -0.469989267 -0.356363636
[56,] -0.603614898 -0.469989267
[57,] -0.997240528 -0.603614898
[58,] -1.060866159 -0.997240528
[59,] -1.104491790 -1.060866159
> z <- as.data.frame(dum1)
> z
lag(myerror, k = 1) myerror
1 0.211960934 0.285586565
2 0.118335303 0.211960934
3 0.094709673 0.118335303
4 0.021084042 0.094709673
5 -0.032541589 0.021084042
6 -0.066167219 -0.032541589
7 -0.129792850 -0.066167219
8 -0.193418481 -0.129792850
9 -0.237044111 -0.193418481
10 -0.300669742 -0.237044111
11 -0.324295373 -0.300669742
12 -0.397921003 -0.324295373
13 -0.431546634 -0.397921003
14 -0.295172265 -0.431546634
15 -0.298797895 -0.295172265
16 -0.332423526 -0.298797895
17 -0.216049157 -0.332423526
18 -0.159674787 -0.216049157
19 -0.263300418 -0.159674787
20 -0.196926049 -0.263300418
21 -0.140551679 -0.196926049
22 -0.034177310 -0.140551679
23 -0.017802941 -0.034177310
24 0.168571429 -0.017802941
25 0.164945798 0.168571429
26 0.281320167 0.164945798
27 0.287694537 0.281320167
28 0.244068906 0.287694537
29 0.310443275 0.244068906
30 0.386817645 0.310443275
31 0.303192014 0.386817645
32 0.419566383 0.303192014
33 0.465940752 0.419566383
34 0.402315122 0.465940752
35 0.328689491 0.402315122
36 0.185063860 0.328689491
37 0.211438230 0.185063860
38 0.017812599 0.211438230
39 0.104186968 0.017812599
40 0.060561338 0.104186968
41 0.066935707 0.060561338
42 -0.086689924 0.066935707
43 -0.120315554 -0.086689924
44 -0.173941185 -0.120315554
45 -0.047566816 -0.173941185
46 0.008807554 -0.047566816
47 -0.074818077 0.008807554
48 -0.578443708 -0.074818077
49 2.221764517 -0.578443708
50 1.508138886 2.221764517
51 0.774513256 1.508138886
52 0.170887625 0.774513256
53 -0.082738006 0.170887625
54 -0.356363636 -0.082738006
55 -0.469989267 -0.356363636
56 -0.603614898 -0.469989267
57 -0.997240528 -0.603614898
58 -1.060866159 -0.997240528
59 -1.104491790 -1.060866159
> 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/7oj101258653125.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> acf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/8crqp1258653125.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> pacf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Partial Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/9lfnb1258653125.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> opar <- par(mfrow = c(2,2), oma = c(0, 0, 1.1, 0))
> plot(mylm, las = 1, sub='Residual Diagnostics')
> par(opar)
> dev.off()
null device
1
> if (n > n25) {
+ postscript(file="/var/www/html/rcomp/tmp/10w0lp1258653125.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
+ plot(kp3:nmkm3,gqarr[,2], main='Goldfeld-Quandt test',ylab='2-sided p-value',xlab='breakpoint')
+ grid()
+ dev.off()
+ }
null device
1
>
> #Note: the /var/www/html/rcomp/createtable file can be downloaded at http://www.wessa.net/cretab
> load(file="/var/www/html/rcomp/createtable")
>
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a, 'Multiple Linear Regression - Estimated Regression Equation', 1, TRUE)
> a<-table.row.end(a)
> myeq <- colnames(x)[1]
> myeq <- paste(myeq, '[t] = ', sep='')
> for (i in 1:k){
+ if (mysum$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/11aokx1258653125.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/122uu51258653126.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/13lto41258653126.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/146hpa1258653126.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/15ydcz1258653126.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/163iqt1258653126.tab")
+ }
>
> system("convert tmp/1fudp1258653125.ps tmp/1fudp1258653125.png")
> system("convert tmp/2wbor1258653125.ps tmp/2wbor1258653125.png")
> system("convert tmp/3r2nw1258653125.ps tmp/3r2nw1258653125.png")
> system("convert tmp/4wv2m1258653125.ps tmp/4wv2m1258653125.png")
> system("convert tmp/5vgod1258653125.ps tmp/5vgod1258653125.png")
> system("convert tmp/6dhse1258653125.ps tmp/6dhse1258653125.png")
> system("convert tmp/7oj101258653125.ps tmp/7oj101258653125.png")
> system("convert tmp/8crqp1258653125.ps tmp/8crqp1258653125.png")
> system("convert tmp/9lfnb1258653125.ps tmp/9lfnb1258653125.png")
> system("convert tmp/10w0lp1258653125.ps tmp/10w0lp1258653125.png")
>
>
> proc.time()
user system elapsed
2.417 1.513 2.867