R version 2.13.0 (2011-04-13)
Copyright (C) 2011 The R Foundation for Statistical Computing
ISBN 3-900051-07-0
Platform: i486-pc-linux-gnu (32-bit)
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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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(119.3,143.7,104.1,124.1,97.1,129.2,97.3,121.9,104.5,124.8,111,129.6,113,125.2,95.4,124.8,86.2,128.3,111.7,129.4,97.5,127.6,99.7,123.7,111.5,129,91.8,118.4,86.3,104.9,88.7,101,95.1,99.5,105.1,106.7,104.5,101.6,89.1,103.2,82.6,104.6,102.7,105.7,91.8,101.1,94.1,98.8,103.1,107.6,93.2,96.9,91,106.4,94.3,102,99.4,105.7,115.7,117,116.8,116,99.8,125.5,96,120.2,115.9,124.1,109.1,111.4,117.3,120.8,109.8,120.2,112.8,124.6,110.7,125.4,100,114.2,113.3,113.6,122.4,110.5,112.5,106.4,104.2,117,92.5,121.9,117.2,114.9,109.3,117.6,106.1,117.6,118.8,125.8,105.3,114.9,106,119.4,102,117.3,112.9,115,116.5,120.9,114.8,117,100.5,117.8,85.4,114,114.6,114.4,109.9,119.6,100.7,113.1,115.5,125.1),dim=c(2,61),dimnames=list(c('TIP','IPCN'),1:61))
> y <- array(NA,dim=c(2,61),dimnames=list(c('TIP','IPCN'),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 = 'Do not include Seasonal Dummies'
> par1 = '2'
> #'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
> 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
IPCN TIP
1 143.7 119.3
2 124.1 104.1
3 129.2 97.1
4 121.9 97.3
5 124.8 104.5
6 129.6 111.0
7 125.2 113.0
8 124.8 95.4
9 128.3 86.2
10 129.4 111.7
11 127.6 97.5
12 123.7 99.7
13 129.0 111.5
14 118.4 91.8
15 104.9 86.3
16 101.0 88.7
17 99.5 95.1
18 106.7 105.1
19 101.6 104.5
20 103.2 89.1
21 104.6 82.6
22 105.7 102.7
23 101.1 91.8
24 98.8 94.1
25 107.6 103.1
26 96.9 93.2
27 106.4 91.0
28 102.0 94.3
29 105.7 99.4
30 117.0 115.7
31 116.0 116.8
32 125.5 99.8
33 120.2 96.0
34 124.1 115.9
35 111.4 109.1
36 120.8 117.3
37 120.2 109.8
38 124.6 112.8
39 125.4 110.7
40 114.2 100.0
41 113.6 113.3
42 110.5 122.4
43 106.4 112.5
44 117.0 104.2
45 121.9 92.5
46 114.9 117.2
47 117.6 109.3
48 117.6 106.1
49 125.8 118.8
50 114.9 105.3
51 119.4 106.0
52 117.3 102.0
53 115.0 112.9
54 120.9 116.5
55 117.0 114.8
56 117.8 100.5
57 114.0 85.4
58 114.4 114.6
59 119.6 109.9
60 113.1 100.7
61 125.1 115.5
> k <- length(x[1,])
> df <- as.data.frame(x)
> (mylm <- lm(df))
Call:
lm(formula = df)
Coefficients:
(Intercept) TIP
74.5328 0.4022
> (mysum <- summary(mylm))
Call:
lm(formula = df)
Residuals:
Min 1Q Median 3Q Max
-15.1175 -6.7703 -0.4887 6.9455 21.1851
Coefficients:
Estimate Std. Error t value Pr(>|t|)
(Intercept) 74.5328 11.8903 6.268 4.62e-08 ***
TIP 0.4022 0.1138 3.535 0.000801 ***
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
Residual standard error: 8.883 on 59 degrees of freedom
Multiple R-squared: 0.1748, Adjusted R-squared: 0.1608
F-statistic: 12.5 on 1 and 59 DF, p-value: 0.0008008
> 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,] 0.25821028 5.164206e-01 7.417897e-01
[2,] 0.17564651 3.512930e-01 8.243535e-01
[3,] 0.22159517 4.431903e-01 7.784048e-01
[4,] 0.15458111 3.091622e-01 8.454189e-01
[5,] 0.23829473 4.765895e-01 7.617053e-01
[6,] 0.17550487 3.510097e-01 8.244951e-01
[7,] 0.14816446 2.963289e-01 8.518355e-01
[8,] 0.12318023 2.463605e-01 8.768198e-01
[9,] 0.09715074 1.943015e-01 9.028493e-01
[10,] 0.10119953 2.023991e-01 8.988005e-01
[11,] 0.32837429 6.567486e-01 6.716257e-01
[12,] 0.62410233 7.517953e-01 3.758977e-01
[13,] 0.89328735 2.134253e-01 1.067126e-01
[14,] 0.96285736 7.428527e-02 3.714264e-02
[15,] 0.99437912 1.124177e-02 5.620885e-03
[16,] 0.99341450 1.317100e-02 6.585499e-03
[17,] 0.98902634 2.194732e-02 1.097366e-02
[18,] 0.99339996 1.320008e-02 6.600039e-03
[19,] 0.99473639 1.052722e-02 5.263609e-03
[20,] 0.99800524 3.989523e-03 1.994762e-03
[21,] 0.99830914 3.381726e-03 1.690863e-03
[22,] 0.99974982 5.003600e-04 2.501800e-04
[23,] 0.99970154 5.969298e-04 2.984649e-04
[24,] 0.99993312 1.337672e-04 6.688360e-05
[25,] 0.99998088 3.824223e-05 1.912112e-05
[26,] 0.99996976 6.047825e-05 3.023913e-05
[27,] 0.99995457 9.085475e-05 4.542737e-05
[28,] 0.99996883 6.234215e-05 3.117107e-05
[29,] 0.99994731 1.053886e-04 5.269431e-05
[30,] 0.99993036 1.392709e-04 6.963545e-05
[31,] 0.99992858 1.428382e-04 7.141908e-05
[32,] 0.99986228 2.754355e-04 1.377178e-04
[33,] 0.99972307 5.538624e-04 2.769312e-04
[34,] 0.99971895 5.620970e-04 2.810485e-04
[35,] 0.99981114 3.777296e-04 1.888648e-04
[36,] 0.99961197 7.760558e-04 3.880279e-04
[37,] 0.99938773 1.224532e-03 6.122659e-04
[38,] 0.99966424 6.715183e-04 3.357592e-04
[39,] 0.99998112 3.775499e-05 1.887750e-05
[40,] 0.99994435 1.113087e-04 5.565434e-05
[41,] 0.99996782 6.436936e-05 3.218468e-05
[42,] 0.99996530 6.939562e-05 3.469781e-05
[43,] 0.99988950 2.210011e-04 1.105005e-04
[44,] 0.99965610 6.878039e-04 3.439019e-04
[45,] 0.99969576 6.084808e-04 3.042404e-04
[46,] 0.99921146 1.577075e-03 7.885377e-04
[47,] 0.99794070 4.118609e-03 2.059305e-03
[48,] 0.99404568 1.190864e-02 5.954322e-03
[49,] 0.98918418 2.163164e-02 1.081582e-02
[50,] 0.97133053 5.733895e-02 2.866947e-02
[51,] 0.93471036 1.305793e-01 6.528964e-02
[52,] 0.84775433 3.044913e-01 1.522457e-01
> postscript(file="/var/wessaorg/rcomp/tmp/1wuz41322156990.ps",horizontal=F,onefile=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$resid)
> grid()
> dev.off()
null device
1
> postscript(file="/var/wessaorg/rcomp/tmp/211if1322156990.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> plot(mysum$resid, type='b', pch=19, main='Residuals', ylab='value of Residuals', xlab='time or index')
> grid()
> dev.off()
null device
1
> postscript(file="/var/wessaorg/rcomp/tmp/3saci1322156990.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> hist(mysum$resid, main='Residual Histogram', xlab='values of Residuals')
> grid()
> dev.off()
null device
1
> postscript(file="/var/wessaorg/rcomp/tmp/4lyez1322156990.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> densityplot(~mysum$resid,col='black',main='Residual Density Plot', xlab='values of Residuals')
> dev.off()
null device
1
> postscript(file="/var/wessaorg/rcomp/tmp/55uob1322156990.ps",horizontal=F,onefile=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
21.1851291 7.6985193 15.6138963 8.2334570 8.2376406 10.4233619
7 8 9 10 11 12
5.2189685 11.8976307 19.0978405 9.9418242 13.8530176 9.0681848
13 14 15 16 17 18
9.6222635 6.9455389 -4.3423791 -9.2076513 -13.2817103 -10.1036775
19 20 21 22 23 24
-14.9623594 -7.1685299 -3.1542513 -10.1384053 -10.3544611 -13.5795135
25 26 27 28 29 30
-8.3992840 -15.1175365 -4.7327037 -10.4599529 -8.8111561 -4.0669627
31 32 33 34 35 36
-5.5093791 10.8279652 7.0563127 2.9525980 -7.0124643 -0.9104774
37 38 39 40 41 42
1.5059980 4.6994078 6.3440209 -0.5524742 -6.5016905 -13.2616807
43 44 45 46 47 48
-13.3799332 0.5582996 10.1640012 -6.7702578 -0.8929037 0.3941258
49 50 51 52 53 54
3.4862275 -1.9841168 2.2343455 1.7431324 -4.9408119 -0.4887201
55 56 57 58 59 60
-3.7049856 2.8464275 5.1195979 -6.2245463 0.8657783 -1.9340119
61
4.1134767
> postscript(file="/var/wessaorg/rcomp/tmp/6w11b1322156990.ps",horizontal=F,onefile=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 21.1851291 NA
1 7.6985193 21.1851291
2 15.6138963 7.6985193
3 8.2334570 15.6138963
4 8.2376406 8.2334570
5 10.4233619 8.2376406
6 5.2189685 10.4233619
7 11.8976307 5.2189685
8 19.0978405 11.8976307
9 9.9418242 19.0978405
10 13.8530176 9.9418242
11 9.0681848 13.8530176
12 9.6222635 9.0681848
13 6.9455389 9.6222635
14 -4.3423791 6.9455389
15 -9.2076513 -4.3423791
16 -13.2817103 -9.2076513
17 -10.1036775 -13.2817103
18 -14.9623594 -10.1036775
19 -7.1685299 -14.9623594
20 -3.1542513 -7.1685299
21 -10.1384053 -3.1542513
22 -10.3544611 -10.1384053
23 -13.5795135 -10.3544611
24 -8.3992840 -13.5795135
25 -15.1175365 -8.3992840
26 -4.7327037 -15.1175365
27 -10.4599529 -4.7327037
28 -8.8111561 -10.4599529
29 -4.0669627 -8.8111561
30 -5.5093791 -4.0669627
31 10.8279652 -5.5093791
32 7.0563127 10.8279652
33 2.9525980 7.0563127
34 -7.0124643 2.9525980
35 -0.9104774 -7.0124643
36 1.5059980 -0.9104774
37 4.6994078 1.5059980
38 6.3440209 4.6994078
39 -0.5524742 6.3440209
40 -6.5016905 -0.5524742
41 -13.2616807 -6.5016905
42 -13.3799332 -13.2616807
43 0.5582996 -13.3799332
44 10.1640012 0.5582996
45 -6.7702578 10.1640012
46 -0.8929037 -6.7702578
47 0.3941258 -0.8929037
48 3.4862275 0.3941258
49 -1.9841168 3.4862275
50 2.2343455 -1.9841168
51 1.7431324 2.2343455
52 -4.9408119 1.7431324
53 -0.4887201 -4.9408119
54 -3.7049856 -0.4887201
55 2.8464275 -3.7049856
56 5.1195979 2.8464275
57 -6.2245463 5.1195979
58 0.8657783 -6.2245463
59 -1.9340119 0.8657783
60 4.1134767 -1.9340119
61 NA 4.1134767
> dum1 <- dum[2:length(myerror),]
> dum1
lag(myerror, k = 1) myerror
[1,] 7.6985193 21.1851291
[2,] 15.6138963 7.6985193
[3,] 8.2334570 15.6138963
[4,] 8.2376406 8.2334570
[5,] 10.4233619 8.2376406
[6,] 5.2189685 10.4233619
[7,] 11.8976307 5.2189685
[8,] 19.0978405 11.8976307
[9,] 9.9418242 19.0978405
[10,] 13.8530176 9.9418242
[11,] 9.0681848 13.8530176
[12,] 9.6222635 9.0681848
[13,] 6.9455389 9.6222635
[14,] -4.3423791 6.9455389
[15,] -9.2076513 -4.3423791
[16,] -13.2817103 -9.2076513
[17,] -10.1036775 -13.2817103
[18,] -14.9623594 -10.1036775
[19,] -7.1685299 -14.9623594
[20,] -3.1542513 -7.1685299
[21,] -10.1384053 -3.1542513
[22,] -10.3544611 -10.1384053
[23,] -13.5795135 -10.3544611
[24,] -8.3992840 -13.5795135
[25,] -15.1175365 -8.3992840
[26,] -4.7327037 -15.1175365
[27,] -10.4599529 -4.7327037
[28,] -8.8111561 -10.4599529
[29,] -4.0669627 -8.8111561
[30,] -5.5093791 -4.0669627
[31,] 10.8279652 -5.5093791
[32,] 7.0563127 10.8279652
[33,] 2.9525980 7.0563127
[34,] -7.0124643 2.9525980
[35,] -0.9104774 -7.0124643
[36,] 1.5059980 -0.9104774
[37,] 4.6994078 1.5059980
[38,] 6.3440209 4.6994078
[39,] -0.5524742 6.3440209
[40,] -6.5016905 -0.5524742
[41,] -13.2616807 -6.5016905
[42,] -13.3799332 -13.2616807
[43,] 0.5582996 -13.3799332
[44,] 10.1640012 0.5582996
[45,] -6.7702578 10.1640012
[46,] -0.8929037 -6.7702578
[47,] 0.3941258 -0.8929037
[48,] 3.4862275 0.3941258
[49,] -1.9841168 3.4862275
[50,] 2.2343455 -1.9841168
[51,] 1.7431324 2.2343455
[52,] -4.9408119 1.7431324
[53,] -0.4887201 -4.9408119
[54,] -3.7049856 -0.4887201
[55,] 2.8464275 -3.7049856
[56,] 5.1195979 2.8464275
[57,] -6.2245463 5.1195979
[58,] 0.8657783 -6.2245463
[59,] -1.9340119 0.8657783
[60,] 4.1134767 -1.9340119
> z <- as.data.frame(dum1)
> z
lag(myerror, k = 1) myerror
1 7.6985193 21.1851291
2 15.6138963 7.6985193
3 8.2334570 15.6138963
4 8.2376406 8.2334570
5 10.4233619 8.2376406
6 5.2189685 10.4233619
7 11.8976307 5.2189685
8 19.0978405 11.8976307
9 9.9418242 19.0978405
10 13.8530176 9.9418242
11 9.0681848 13.8530176
12 9.6222635 9.0681848
13 6.9455389 9.6222635
14 -4.3423791 6.9455389
15 -9.2076513 -4.3423791
16 -13.2817103 -9.2076513
17 -10.1036775 -13.2817103
18 -14.9623594 -10.1036775
19 -7.1685299 -14.9623594
20 -3.1542513 -7.1685299
21 -10.1384053 -3.1542513
22 -10.3544611 -10.1384053
23 -13.5795135 -10.3544611
24 -8.3992840 -13.5795135
25 -15.1175365 -8.3992840
26 -4.7327037 -15.1175365
27 -10.4599529 -4.7327037
28 -8.8111561 -10.4599529
29 -4.0669627 -8.8111561
30 -5.5093791 -4.0669627
31 10.8279652 -5.5093791
32 7.0563127 10.8279652
33 2.9525980 7.0563127
34 -7.0124643 2.9525980
35 -0.9104774 -7.0124643
36 1.5059980 -0.9104774
37 4.6994078 1.5059980
38 6.3440209 4.6994078
39 -0.5524742 6.3440209
40 -6.5016905 -0.5524742
41 -13.2616807 -6.5016905
42 -13.3799332 -13.2616807
43 0.5582996 -13.3799332
44 10.1640012 0.5582996
45 -6.7702578 10.1640012
46 -0.8929037 -6.7702578
47 0.3941258 -0.8929037
48 3.4862275 0.3941258
49 -1.9841168 3.4862275
50 2.2343455 -1.9841168
51 1.7431324 2.2343455
52 -4.9408119 1.7431324
53 -0.4887201 -4.9408119
54 -3.7049856 -0.4887201
55 2.8464275 -3.7049856
56 5.1195979 2.8464275
57 -6.2245463 5.1195979
58 0.8657783 -6.2245463
59 -1.9340119 0.8657783
60 4.1134767 -1.9340119
> 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/wessaorg/rcomp/tmp/7zw4q1322156990.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> acf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/wessaorg/rcomp/tmp/8byd81322156990.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> pacf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Partial Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/wessaorg/rcomp/tmp/9sccu1322156990.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> opar <- par(mfrow = c(2,2), oma = c(0, 0, 1.1, 0))
> plot(mylm, las = 1, sub='Residual Diagnostics')
> par(opar)
> dev.off()
null device
1
> if (n > n25) {
+ postscript(file="/var/wessaorg/rcomp/tmp/10ev961322156990.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
+ plot(kp3:nmkm3,gqarr[,2], main='Goldfeld-Quandt test',ylab='2-sided p-value',xlab='breakpoint')
+ grid()
+ dev.off()
+ }
null device
1
>
> #Note: the /var/wessaorg/rcomp/createtable file can be downloaded at http://www.wessa.net/cretab
> load(file="/var/wessaorg/rcomp/createtable")
>
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a, 'Multiple Linear Regression - Estimated Regression Equation', 1, TRUE)
> a<-table.row.end(a)
> myeq <- colnames(x)[1]
> myeq <- paste(myeq, '[t] = ', sep='')
> for (i in 1:k){
+ if (mysum$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/wessaorg/rcomp/tmp/115mpr1322156990.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/wessaorg/rcomp/tmp/12k3qp1322156990.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/wessaorg/rcomp/tmp/13yf1u1322156990.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/wessaorg/rcomp/tmp/14g35g1322156990.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/wessaorg/rcomp/tmp/15za7b1322156990.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/wessaorg/rcomp/tmp/168kj01322156990.tab")
+ }
>
> try(system("convert tmp/1wuz41322156990.ps tmp/1wuz41322156990.png",intern=TRUE))
character(0)
> try(system("convert tmp/211if1322156990.ps tmp/211if1322156990.png",intern=TRUE))
character(0)
> try(system("convert tmp/3saci1322156990.ps tmp/3saci1322156990.png",intern=TRUE))
character(0)
> try(system("convert tmp/4lyez1322156990.ps tmp/4lyez1322156990.png",intern=TRUE))
character(0)
> try(system("convert tmp/55uob1322156990.ps tmp/55uob1322156990.png",intern=TRUE))
character(0)
> try(system("convert tmp/6w11b1322156990.ps tmp/6w11b1322156990.png",intern=TRUE))
character(0)
> try(system("convert tmp/7zw4q1322156990.ps tmp/7zw4q1322156990.png",intern=TRUE))
character(0)
> try(system("convert tmp/8byd81322156990.ps tmp/8byd81322156990.png",intern=TRUE))
character(0)
> try(system("convert tmp/9sccu1322156990.ps tmp/9sccu1322156990.png",intern=TRUE))
character(0)
> try(system("convert tmp/10ev961322156990.ps tmp/10ev961322156990.png",intern=TRUE))
character(0)
>
>
> proc.time()
user system elapsed
3.550 0.521 4.160