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
'help.start()' for an HTML browser interface to help.
Type 'q()' to quit R.
> x <- array(list(5.7,97.33,6.1,97.89,6,98.69,5.9,99.01,5.8,99.18,5.7,98.45,5.6,98.13,5.4,98.29,5.4,99.1,5.5,99.26,5.6,98.85,5.7,98.05,5.9,98.53,6.1,99.34,6,100.14,5.8,100.3,5.8,100.22,5.7,99.9,5.5,99.58,5.3,99.9,5.2,100.78,5.2,100.78,5,100.46,5.1,100.06,5.1,100.28,5.2,100.78,4.9,101.58,4.8,102.06,4.5,102.02,4.5,101.68,4.4,101.32,4.4,101.81,4.2,102.3,4.1,102.12,3.9,102.1,3.8,101.75,3.9,101.5,4.2,102.16,4.1,103.47,3.8,104.05,3.6,104.09,3.7,103.55,3.5,102.77,3.4,102.89,3.1,103.6,3.1,103.76,3.1,103.92,3.2,103.35,3.3,103.32,3.5,104.2,3.6,105.44,3.5,105.81,3.3,106.25,3.2,105.94,3.1,105.82,3.2,105.96,3,106.49,3,106.32,3.1,105.88,3.4,105.07),dim=c(2,60),dimnames=list(c('manwerk','infl'),1:60))
> y <- array(NA,dim=c(2,60),dimnames=list(c('manwerk','infl'),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 = 'No Linear Trend'
> par2 = 'Do not include Seasonal Dummies'
> par1 = '1'
> #'GNU S' R Code compiled by R2WASP v. 1.0.44 ()
> #Author: Prof. Dr. P. Wessa
> #To cite this work: AUTHOR(S), (YEAR), YOUR SOFTWARE TITLE (vNUMBER) in Free Statistics Software (v$_version), Office for Research Development and Education, URL http://www.wessa.net/rwasp_YOURPAGE.wasp/
> #Source of accompanying publication: Office for Research, Development, and Education
> #Technical description: Write here your technical program description (don't use hard returns!)
> library(lattice)
> library(lmtest)
Loading required package: zoo
Attaching package: 'zoo'
The following object(s) are masked from package:base :
as.Date.numeric
> n25 <- 25 #minimum number of obs. for Goldfeld-Quandt test
> par1 <- as.numeric(par1)
> x <- t(y)
> k <- length(x[1,])
> n <- length(x[,1])
> x1 <- cbind(x[,par1], x[,1:k!=par1])
> mycolnames <- c(colnames(x)[par1], colnames(x)[1:k!=par1])
> colnames(x1) <- mycolnames #colnames(x)[par1]
> x <- x1
> if (par3 == 'First Differences'){
+ x2 <- array(0, dim=c(n-1,k), dimnames=list(1:(n-1), paste('(1-B)',colnames(x),sep='')))
+ for (i in 1:n-1) {
+ for (j in 1:k) {
+ x2[i,j] <- x[i+1,j] - x[i,j]
+ }
+ }
+ x <- x2
+ }
> if (par2 == 'Include Monthly Dummies'){
+ x2 <- array(0, dim=c(n,11), dimnames=list(1:n, paste('M', seq(1:11), sep ='')))
+ for (i in 1:11){
+ x2[seq(i,n,12),i] <- 1
+ }
+ x <- cbind(x, x2)
+ }
> if (par2 == 'Include Quarterly Dummies'){
+ x2 <- array(0, dim=c(n,3), dimnames=list(1:n, paste('Q', seq(1:3), sep ='')))
+ for (i in 1:3){
+ x2[seq(i,n,4),i] <- 1
+ }
+ x <- cbind(x, x2)
+ }
> k <- length(x[1,])
> if (par3 == 'Linear Trend'){
+ x <- cbind(x, c(1:n))
+ colnames(x)[k+1] <- 't'
+ }
> x
manwerk infl
1 5.7 97.33
2 6.1 97.89
3 6.0 98.69
4 5.9 99.01
5 5.8 99.18
6 5.7 98.45
7 5.6 98.13
8 5.4 98.29
9 5.4 99.10
10 5.5 99.26
11 5.6 98.85
12 5.7 98.05
13 5.9 98.53
14 6.1 99.34
15 6.0 100.14
16 5.8 100.30
17 5.8 100.22
18 5.7 99.90
19 5.5 99.58
20 5.3 99.90
21 5.2 100.78
22 5.2 100.78
23 5.0 100.46
24 5.1 100.06
25 5.1 100.28
26 5.2 100.78
27 4.9 101.58
28 4.8 102.06
29 4.5 102.02
30 4.5 101.68
31 4.4 101.32
32 4.4 101.81
33 4.2 102.30
34 4.1 102.12
35 3.9 102.10
36 3.8 101.75
37 3.9 101.50
38 4.2 102.16
39 4.1 103.47
40 3.8 104.05
41 3.6 104.09
42 3.7 103.55
43 3.5 102.77
44 3.4 102.89
45 3.1 103.60
46 3.1 103.76
47 3.1 103.92
48 3.2 103.35
49 3.3 103.32
50 3.5 104.20
51 3.6 105.44
52 3.5 105.81
53 3.3 106.25
54 3.2 105.94
55 3.1 105.82
56 3.2 105.96
57 3.0 106.49
58 3.0 106.32
59 3.1 105.88
60 3.4 105.07
> k <- length(x[1,])
> df <- as.data.frame(x)
> (mylm <- lm(df))
Call:
lm(formula = df)
Coefficients:
(Intercept) infl
43.1130 -0.3792
> (mysum <- summary(mylm))
Call:
lm(formula = df)
Residuals:
Min 1Q Median 3Q Max
-0.72829 -0.24552 0.04882 0.29882 0.86118
Coefficients:
Estimate Std. Error t value Pr(>|t|)
(Intercept) 43.11299 2.10718 20.46 <2e-16 ***
infl -0.37921 0.02069 -18.32 <2e-16 ***
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
Residual standard error: 0.409 on 58 degrees of freedom
Multiple R-squared: 0.8527, Adjusted R-squared: 0.8502
F-statistic: 335.8 on 1 and 58 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,] 0.097470049 0.1949400981 0.9025299509
[2,] 0.056338289 0.1126765782 0.9436617109
[3,] 0.044176119 0.0883522384 0.9558238808
[4,] 0.079482599 0.1589651978 0.9205174011
[5,] 0.090292777 0.1805855533 0.9097072233
[6,] 0.058116392 0.1162327836 0.9418836082
[7,] 0.031349449 0.0626988980 0.9686505510
[8,] 0.016169327 0.0323386539 0.9838306730
[9,] 0.010137033 0.0202740658 0.9898629671
[10,] 0.017015719 0.0340314382 0.9829842809
[11,] 0.017047411 0.0340948221 0.9829525889
[12,] 0.013438248 0.0268764964 0.9865617518
[13,] 0.011481455 0.0229629095 0.9885185453
[14,] 0.009258935 0.0185178709 0.9907410645
[15,] 0.009241817 0.0184836330 0.9907581835
[16,] 0.017218962 0.0344379232 0.9827810384
[17,] 0.033261593 0.0665231851 0.9667384075
[18,] 0.046450473 0.0929009462 0.9535495269
[19,] 0.078125473 0.1562509461 0.9218745270
[20,] 0.094008646 0.1880172923 0.9059913539
[21,] 0.106324859 0.2126497187 0.8936751406
[22,] 0.136920964 0.2738419281 0.8630790359
[23,] 0.197809917 0.3956198347 0.8021900826
[24,] 0.311940481 0.6238809615 0.6880595193
[25,] 0.428713867 0.8574277350 0.5712861325
[26,] 0.544521496 0.9109570080 0.4554785040
[27,] 0.663161129 0.6736777411 0.3368388706
[28,] 0.751214302 0.4975713968 0.2487856984
[29,] 0.806394579 0.3872108424 0.1936054212
[30,] 0.847688303 0.3046233949 0.1523116974
[31,] 0.877008880 0.2459822407 0.1229911203
[32,] 0.911804766 0.1763904681 0.0881952340
[33,] 0.926765089 0.1464698227 0.0732349114
[34,] 0.956768084 0.0864638312 0.0432319156
[35,] 0.990496297 0.0190074066 0.0095037033
[36,] 0.995481507 0.0090369864 0.0045184932
[37,] 0.995196935 0.0096061294 0.0048030647
[38,] 0.997373169 0.0052536615 0.0026268308
[39,] 0.997401346 0.0051973083 0.0025986542
[40,] 0.996727184 0.0065456312 0.0032728156
[41,] 0.995949331 0.0081013376 0.0040506688
[42,] 0.994880214 0.0102395711 0.0051197855
[43,] 0.994014321 0.0119713581 0.0059856791
[44,] 0.993753066 0.0124938681 0.0062469340
[45,] 0.996467694 0.0070646126 0.0035323063
[46,] 0.994737679 0.0105246420 0.0052623210
[47,] 0.995882748 0.0082345039 0.0041172519
[48,] 0.998789633 0.0024207341 0.0012103670
[49,] 0.999824347 0.0003513058 0.0001756529
[50,] 0.999262427 0.0014751457 0.0007375729
[51,] 0.996990607 0.0060187862 0.0030093931
> postscript(file="/var/www/html/rcomp/tmp/1trp21258653813.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$resid)
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/2usio1258653813.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> plot(mysum$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/3ur8q1258653813.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> hist(mysum$resid, main='Residual Histogram', xlab='values of Residuals')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/4caaq1258653813.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> densityplot(~mysum$resid,col='black',main='Residual Density Plot', xlab='values of Residuals')
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/5xbzg1258653813.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
-0.50440047 0.10795757 0.31132621 0.33267367 0.29713950 -0.07968438
7 8 9 10 11 12
-0.30103183 -0.44035811 -0.13319736 0.02747637 -0.02800006 -0.23136870
13 14 15 16 17 18
0.15065248 0.65781323 0.86118187 0.72185560 0.69151874 0.47017128
19 20 21 22 23 24
0.14882382 0.07017128 0.30387678 0.30387678 -0.01747067 -0.06915499
25 26 27 28 29 30
0.01427138 0.30387678 0.30724542 0.38926661 0.07409818 -0.05483350
31 32 33 34 35 36
-0.29134938 -0.10553609 -0.11972280 -0.28798074 -0.49556496 -0.72828874
37 38 39 40 41 42
-0.72309144 -0.17281231 0.22395384 0.14389610 -0.04093547 -0.14570930
43 44 45 46 47 48
-0.64149372 -0.69598843 -0.72674876 -0.66607503 -0.60540130 -0.72155146
49 50 51 52 53 54
-0.63292778 -0.09922228 0.47099911 0.51130711 0.47815986 0.26060451
55 56 57 58 59 60
0.11509921 0.26818873 0.26917045 0.20470461 0.13785186 0.13069111
> postscript(file="/var/www/html/rcomp/tmp/60bpo1258653813.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 -0.50440047 NA
1 0.10795757 -0.50440047
2 0.31132621 0.10795757
3 0.33267367 0.31132621
4 0.29713950 0.33267367
5 -0.07968438 0.29713950
6 -0.30103183 -0.07968438
7 -0.44035811 -0.30103183
8 -0.13319736 -0.44035811
9 0.02747637 -0.13319736
10 -0.02800006 0.02747637
11 -0.23136870 -0.02800006
12 0.15065248 -0.23136870
13 0.65781323 0.15065248
14 0.86118187 0.65781323
15 0.72185560 0.86118187
16 0.69151874 0.72185560
17 0.47017128 0.69151874
18 0.14882382 0.47017128
19 0.07017128 0.14882382
20 0.30387678 0.07017128
21 0.30387678 0.30387678
22 -0.01747067 0.30387678
23 -0.06915499 -0.01747067
24 0.01427138 -0.06915499
25 0.30387678 0.01427138
26 0.30724542 0.30387678
27 0.38926661 0.30724542
28 0.07409818 0.38926661
29 -0.05483350 0.07409818
30 -0.29134938 -0.05483350
31 -0.10553609 -0.29134938
32 -0.11972280 -0.10553609
33 -0.28798074 -0.11972280
34 -0.49556496 -0.28798074
35 -0.72828874 -0.49556496
36 -0.72309144 -0.72828874
37 -0.17281231 -0.72309144
38 0.22395384 -0.17281231
39 0.14389610 0.22395384
40 -0.04093547 0.14389610
41 -0.14570930 -0.04093547
42 -0.64149372 -0.14570930
43 -0.69598843 -0.64149372
44 -0.72674876 -0.69598843
45 -0.66607503 -0.72674876
46 -0.60540130 -0.66607503
47 -0.72155146 -0.60540130
48 -0.63292778 -0.72155146
49 -0.09922228 -0.63292778
50 0.47099911 -0.09922228
51 0.51130711 0.47099911
52 0.47815986 0.51130711
53 0.26060451 0.47815986
54 0.11509921 0.26060451
55 0.26818873 0.11509921
56 0.26917045 0.26818873
57 0.20470461 0.26917045
58 0.13785186 0.20470461
59 0.13069111 0.13785186
60 NA 0.13069111
> dum1 <- dum[2:length(myerror),]
> dum1
lag(myerror, k = 1) myerror
[1,] 0.10795757 -0.50440047
[2,] 0.31132621 0.10795757
[3,] 0.33267367 0.31132621
[4,] 0.29713950 0.33267367
[5,] -0.07968438 0.29713950
[6,] -0.30103183 -0.07968438
[7,] -0.44035811 -0.30103183
[8,] -0.13319736 -0.44035811
[9,] 0.02747637 -0.13319736
[10,] -0.02800006 0.02747637
[11,] -0.23136870 -0.02800006
[12,] 0.15065248 -0.23136870
[13,] 0.65781323 0.15065248
[14,] 0.86118187 0.65781323
[15,] 0.72185560 0.86118187
[16,] 0.69151874 0.72185560
[17,] 0.47017128 0.69151874
[18,] 0.14882382 0.47017128
[19,] 0.07017128 0.14882382
[20,] 0.30387678 0.07017128
[21,] 0.30387678 0.30387678
[22,] -0.01747067 0.30387678
[23,] -0.06915499 -0.01747067
[24,] 0.01427138 -0.06915499
[25,] 0.30387678 0.01427138
[26,] 0.30724542 0.30387678
[27,] 0.38926661 0.30724542
[28,] 0.07409818 0.38926661
[29,] -0.05483350 0.07409818
[30,] -0.29134938 -0.05483350
[31,] -0.10553609 -0.29134938
[32,] -0.11972280 -0.10553609
[33,] -0.28798074 -0.11972280
[34,] -0.49556496 -0.28798074
[35,] -0.72828874 -0.49556496
[36,] -0.72309144 -0.72828874
[37,] -0.17281231 -0.72309144
[38,] 0.22395384 -0.17281231
[39,] 0.14389610 0.22395384
[40,] -0.04093547 0.14389610
[41,] -0.14570930 -0.04093547
[42,] -0.64149372 -0.14570930
[43,] -0.69598843 -0.64149372
[44,] -0.72674876 -0.69598843
[45,] -0.66607503 -0.72674876
[46,] -0.60540130 -0.66607503
[47,] -0.72155146 -0.60540130
[48,] -0.63292778 -0.72155146
[49,] -0.09922228 -0.63292778
[50,] 0.47099911 -0.09922228
[51,] 0.51130711 0.47099911
[52,] 0.47815986 0.51130711
[53,] 0.26060451 0.47815986
[54,] 0.11509921 0.26060451
[55,] 0.26818873 0.11509921
[56,] 0.26917045 0.26818873
[57,] 0.20470461 0.26917045
[58,] 0.13785186 0.20470461
[59,] 0.13069111 0.13785186
> z <- as.data.frame(dum1)
> z
lag(myerror, k = 1) myerror
1 0.10795757 -0.50440047
2 0.31132621 0.10795757
3 0.33267367 0.31132621
4 0.29713950 0.33267367
5 -0.07968438 0.29713950
6 -0.30103183 -0.07968438
7 -0.44035811 -0.30103183
8 -0.13319736 -0.44035811
9 0.02747637 -0.13319736
10 -0.02800006 0.02747637
11 -0.23136870 -0.02800006
12 0.15065248 -0.23136870
13 0.65781323 0.15065248
14 0.86118187 0.65781323
15 0.72185560 0.86118187
16 0.69151874 0.72185560
17 0.47017128 0.69151874
18 0.14882382 0.47017128
19 0.07017128 0.14882382
20 0.30387678 0.07017128
21 0.30387678 0.30387678
22 -0.01747067 0.30387678
23 -0.06915499 -0.01747067
24 0.01427138 -0.06915499
25 0.30387678 0.01427138
26 0.30724542 0.30387678
27 0.38926661 0.30724542
28 0.07409818 0.38926661
29 -0.05483350 0.07409818
30 -0.29134938 -0.05483350
31 -0.10553609 -0.29134938
32 -0.11972280 -0.10553609
33 -0.28798074 -0.11972280
34 -0.49556496 -0.28798074
35 -0.72828874 -0.49556496
36 -0.72309144 -0.72828874
37 -0.17281231 -0.72309144
38 0.22395384 -0.17281231
39 0.14389610 0.22395384
40 -0.04093547 0.14389610
41 -0.14570930 -0.04093547
42 -0.64149372 -0.14570930
43 -0.69598843 -0.64149372
44 -0.72674876 -0.69598843
45 -0.66607503 -0.72674876
46 -0.60540130 -0.66607503
47 -0.72155146 -0.60540130
48 -0.63292778 -0.72155146
49 -0.09922228 -0.63292778
50 0.47099911 -0.09922228
51 0.51130711 0.47099911
52 0.47815986 0.51130711
53 0.26060451 0.47815986
54 0.11509921 0.26060451
55 0.26818873 0.11509921
56 0.26917045 0.26818873
57 0.20470461 0.26917045
58 0.13785186 0.20470461
59 0.13069111 0.13785186
> 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/7s0831258653813.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> acf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/8f5yb1258653813.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> pacf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Partial Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/9x4an1258653813.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> opar <- par(mfrow = c(2,2), oma = c(0, 0, 1.1, 0))
> plot(mylm, las = 1, sub='Residual Diagnostics')
> par(opar)
> dev.off()
null device
1
> if (n > n25) {
+ postscript(file="/var/www/html/rcomp/tmp/1060ur1258653813.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
+ plot(kp3:nmkm3,gqarr[,2], main='Goldfeld-Quandt test',ylab='2-sided p-value',xlab='breakpoint')
+ grid()
+ dev.off()
+ }
null device
1
>
> #Note: the /var/www/html/rcomp/createtable file can be downloaded at http://www.wessa.net/cretab
> load(file="/var/www/html/rcomp/createtable")
>
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a, 'Multiple Linear Regression - Estimated Regression Equation', 1, TRUE)
> a<-table.row.end(a)
> myeq <- colnames(x)[1]
> myeq <- paste(myeq, '[t] = ', sep='')
> for (i in 1:k){
+ if (mysum$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/11ydic1258653813.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/12uhgi1258653813.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/13mivc1258653813.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/14qwxg1258653813.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/15127y1258653813.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/168ety1258653813.tab")
+ }
>
> system("convert tmp/1trp21258653813.ps tmp/1trp21258653813.png")
> system("convert tmp/2usio1258653813.ps tmp/2usio1258653813.png")
> system("convert tmp/3ur8q1258653813.ps tmp/3ur8q1258653813.png")
> system("convert tmp/4caaq1258653813.ps tmp/4caaq1258653813.png")
> system("convert tmp/5xbzg1258653813.ps tmp/5xbzg1258653813.png")
> system("convert tmp/60bpo1258653813.ps tmp/60bpo1258653813.png")
> system("convert tmp/7s0831258653813.ps tmp/7s0831258653813.png")
> system("convert tmp/8f5yb1258653813.ps tmp/8f5yb1258653813.png")
> system("convert tmp/9x4an1258653813.ps tmp/9x4an1258653813.png")
> system("convert tmp/1060ur1258653813.ps tmp/1060ur1258653813.png")
>
>
> proc.time()
user system elapsed
2.453 1.548 2.856