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.
R is a collaborative project with many contributors.
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(72772,26073,22274,45104,18103,14819,44525,15100,15136,41169,14738,13704,31118,22259,19638,28435,10277,7551,22162,6225,8019,20202,7663,6509,17773,6618,6634,17094,9945,11166,15153,7590,7508,11218,4293,4275,10796,4656,4944,9594,5145,5441,9309,2001,1689,8556,1779,1522,8041,1609,1416,7639,2191,1594,6884,1617,1909,6642,2554,2599,6321,2198,1262,6216,1578,1199,5865,3446,4404,5799,1380,1166,5695,1249,1122,5644,1223,886,5446,834,778,5395,3754,4436,5363,2283,1890,5338,3028,3107,5160,1100,1038,5091,457,300,5057,1201,988,5039,2192,2008,4880,1508,1522,4735,1393,1336,4693,952,976,4653,1032,798,4586,1279,869,4398,1370,1260,3974,649,578,3858,1900,2359,3826,666,736,3819,1313,1690,3556,1353,1201,3372,1500,813,3193,877,778,3126,874,687,3104,1133,1270,2967,754,671,2848,695,1559,2748,609,489,2649,696,773,2625,756,629,2572,670,637,2548,301,277,2477,630,776,2442,798,1651,2392,436,377,2372,388,222),dim=c(3,60),dimnames=list(c('weekdag','zaterdag','zondag'),1:60))
> y <- array(NA,dim=c(3,60),dimnames=list(c('weekdag','zaterdag','zondag'),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 = '3'
> #'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
zondag weekdag zaterdag
1 22274 72772 26073
2 14819 45104 18103
3 15136 44525 15100
4 13704 41169 14738
5 19638 31118 22259
6 7551 28435 10277
7 8019 22162 6225
8 6509 20202 7663
9 6634 17773 6618
10 11166 17094 9945
11 7508 15153 7590
12 4275 11218 4293
13 4944 10796 4656
14 5441 9594 5145
15 1689 9309 2001
16 1522 8556 1779
17 1416 8041 1609
18 1594 7639 2191
19 1909 6884 1617
20 2599 6642 2554
21 1262 6321 2198
22 1199 6216 1578
23 4404 5865 3446
24 1166 5799 1380
25 1122 5695 1249
26 886 5644 1223
27 778 5446 834
28 4436 5395 3754
29 1890 5363 2283
30 3107 5338 3028
31 1038 5160 1100
32 300 5091 457
33 988 5057 1201
34 2008 5039 2192
35 1522 4880 1508
36 1336 4735 1393
37 976 4693 952
38 798 4653 1032
39 869 4586 1279
40 1260 4398 1370
41 578 3974 649
42 2359 3858 1900
43 736 3826 666
44 1690 3819 1313
45 1201 3556 1353
46 813 3372 1500
47 778 3193 877
48 687 3126 874
49 1270 3104 1133
50 671 2967 754
51 1559 2848 695
52 489 2748 609
53 773 2649 696
54 629 2625 756
55 637 2572 670
56 277 2548 301
57 776 2477 630
58 1651 2442 798
59 377 2392 436
60 222 2372 388
> k <- length(x[1,])
> df <- as.data.frame(x)
> (mylm <- lm(df))
Call:
lm(formula = df)
Coefficients:
(Intercept) weekdag zaterdag
235.69559 -0.02089 0.93376
> (mysum <- summary(mylm))
Call:
lm(formula = df)
Residuals:
Min 1Q Median 3Q Max
-1686.9 -272.5 -166.1 275.6 2433.7
Coefficients:
Estimate Std. Error t value Pr(>|t|)
(Intercept) 235.69559 114.20941 2.064 0.0436 *
weekdag -0.02089 0.02250 -0.929 0.3570
zaterdag 0.93376 0.05425 17.213 <2e-16 ***
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
Residual standard error: 693.6 on 57 degrees of freedom
Multiple R-squared: 0.9801, Adjusted R-squared: 0.9794
F-statistic: 1401 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,] 0.9999937 1.265520e-05 6.327599e-06
[2,] 1.0000000 3.266071e-10 1.633035e-10
[3,] 1.0000000 3.980734e-11 1.990367e-11
[4,] 1.0000000 1.824411e-10 9.122055e-11
[5,] 1.0000000 7.563065e-12 3.781532e-12
[6,] 1.0000000 2.623499e-11 1.311749e-11
[7,] 1.0000000 6.768895e-11 3.384447e-11
[8,] 1.0000000 2.092318e-10 1.046159e-10
[9,] 1.0000000 7.832930e-10 3.916465e-10
[10,] 1.0000000 8.080168e-10 4.040084e-10
[11,] 1.0000000 1.239273e-09 6.196367e-10
[12,] 1.0000000 2.171036e-09 1.085518e-09
[13,] 1.0000000 2.608688e-09 1.304344e-09
[14,] 1.0000000 2.587123e-09 1.293562e-09
[15,] 1.0000000 7.811758e-09 3.905879e-09
[16,] 1.0000000 8.495625e-10 4.247813e-10
[17,] 1.0000000 2.031760e-09 1.015880e-09
[18,] 1.0000000 5.223796e-10 2.611898e-10
[19,] 1.0000000 1.614399e-09 8.071994e-10
[20,] 1.0000000 4.939895e-09 2.469947e-09
[21,] 1.0000000 1.309776e-08 6.548878e-09
[22,] 1.0000000 3.381821e-08 1.690911e-08
[23,] 1.0000000 2.566581e-08 1.283290e-08
[24,] 1.0000000 5.040835e-08 2.520418e-08
[25,] 0.9999999 1.545237e-07 7.726183e-08
[26,] 0.9999998 4.424683e-07 2.212341e-07
[27,] 0.9999994 1.216543e-06 6.082715e-07
[28,] 0.9999983 3.320478e-06 1.660239e-06
[29,] 0.9999957 8.616822e-06 4.308411e-06
[30,] 0.9999889 2.225198e-05 1.112599e-05
[31,] 0.9999714 5.728890e-05 2.864445e-05
[32,] 0.9999379 1.242958e-04 6.214791e-05
[33,] 0.9998527 2.945819e-04 1.472910e-04
[34,] 0.9997447 5.105349e-04 2.552675e-04
[35,] 0.9994200 1.160014e-03 5.800069e-04
[36,] 0.9987046 2.590842e-03 1.295421e-03
[37,] 0.9983948 3.210488e-03 1.605244e-03
[38,] 0.9965020 6.995973e-03 3.497987e-03
[39,] 0.9968980 6.203986e-03 3.101993e-03
[40,] 0.9935751 1.284979e-02 6.424897e-03
[41,] 0.9973237 5.352692e-03 2.676346e-03
[42,] 0.9936843 1.263144e-02 6.315721e-03
[43,] 0.9877696 2.446078e-02 1.223039e-02
[44,] 0.9782684 4.346323e-02 2.173161e-02
[45,] 0.9658540 6.829206e-02 3.414603e-02
[46,] 0.9929938 1.401247e-02 7.006235e-03
[47,] 0.9797782 4.044366e-02 2.022183e-02
[48,] 0.9446923 1.106153e-01 5.530767e-02
[49,] 0.9070204 1.859592e-01 9.297961e-02
> postscript(file="/var/wessaorg/rcomp/tmp/1gv7i1322130290.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$resid)
> grid()
> dev.off()
null device
1
> postscript(file="/var/wessaorg/rcomp/tmp/27hdy1322130290.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> plot(mysum$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/3tekw1322130290.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> hist(mysum$resid, main='Residual Histogram', xlab='values of Residuals')
> grid()
> dev.off()
null device
1
> postscript(file="/var/wessaorg/rcomp/tmp/416dq1322130290.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> densityplot(~mysum$resid,col='black',main='Residual Density Plot', xlab='values of Residuals')
> dev.off()
null device
1
> postscript(file="/var/wessaorg/rcomp/tmp/50a001322130290.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 = 60
Frequency = 1
1 2 3 4 5 6
-787.248457 -1378.236826 1730.760054 566.663073 -732.182613 -1686.876062
7 8 9 10 11 12
2433.670192 -460.034874 589.997788 2001.176818 501.636993 265.040914
13 14 15 16 17 18
586.267253 601.542095 -220.657464 -196.094825 -154.115203 -527.965385
19 20 21 22 23 24
307.240524 117.247003 -894.039800 -380.299742 1073.094681 -237.127122
25 26 27 28 29 30
-160.976948 -373.764659 -122.667297 807.675156 -365.426057 155.397141
31 32 33 34 35 36
-117.024254 -256.055438 -263.486519 -169.223100 -19.850389 -101.497091
37 38 39 40 41 42
-50.584544 -304.121447 -465.161133 -163.061730 -180.676601 429.760487
43 44 45 46 47 48
-41.642882 308.065313 -223.780338 -752.888165 -209.892957 -299.491550
49 50 51 52 53 54
41.203814 -206.761944 733.843788 -257.941858 -57.247847 -257.775162
55 56 57 58 59 60
-170.578798 -186.521198 3.786863 721.183165 -215.838825 -326.436011
> postscript(file="/var/wessaorg/rcomp/tmp/6rtmx1322130290.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 = 60
Frequency = 1
lag(myerror, k = 1) myerror
0 -787.248457 NA
1 -1378.236826 -787.248457
2 1730.760054 -1378.236826
3 566.663073 1730.760054
4 -732.182613 566.663073
5 -1686.876062 -732.182613
6 2433.670192 -1686.876062
7 -460.034874 2433.670192
8 589.997788 -460.034874
9 2001.176818 589.997788
10 501.636993 2001.176818
11 265.040914 501.636993
12 586.267253 265.040914
13 601.542095 586.267253
14 -220.657464 601.542095
15 -196.094825 -220.657464
16 -154.115203 -196.094825
17 -527.965385 -154.115203
18 307.240524 -527.965385
19 117.247003 307.240524
20 -894.039800 117.247003
21 -380.299742 -894.039800
22 1073.094681 -380.299742
23 -237.127122 1073.094681
24 -160.976948 -237.127122
25 -373.764659 -160.976948
26 -122.667297 -373.764659
27 807.675156 -122.667297
28 -365.426057 807.675156
29 155.397141 -365.426057
30 -117.024254 155.397141
31 -256.055438 -117.024254
32 -263.486519 -256.055438
33 -169.223100 -263.486519
34 -19.850389 -169.223100
35 -101.497091 -19.850389
36 -50.584544 -101.497091
37 -304.121447 -50.584544
38 -465.161133 -304.121447
39 -163.061730 -465.161133
40 -180.676601 -163.061730
41 429.760487 -180.676601
42 -41.642882 429.760487
43 308.065313 -41.642882
44 -223.780338 308.065313
45 -752.888165 -223.780338
46 -209.892957 -752.888165
47 -299.491550 -209.892957
48 41.203814 -299.491550
49 -206.761944 41.203814
50 733.843788 -206.761944
51 -257.941858 733.843788
52 -57.247847 -257.941858
53 -257.775162 -57.247847
54 -170.578798 -257.775162
55 -186.521198 -170.578798
56 3.786863 -186.521198
57 721.183165 3.786863
58 -215.838825 721.183165
59 -326.436011 -215.838825
60 NA -326.436011
> dum1 <- dum[2:length(myerror),]
> dum1
lag(myerror, k = 1) myerror
[1,] -1378.236826 -787.248457
[2,] 1730.760054 -1378.236826
[3,] 566.663073 1730.760054
[4,] -732.182613 566.663073
[5,] -1686.876062 -732.182613
[6,] 2433.670192 -1686.876062
[7,] -460.034874 2433.670192
[8,] 589.997788 -460.034874
[9,] 2001.176818 589.997788
[10,] 501.636993 2001.176818
[11,] 265.040914 501.636993
[12,] 586.267253 265.040914
[13,] 601.542095 586.267253
[14,] -220.657464 601.542095
[15,] -196.094825 -220.657464
[16,] -154.115203 -196.094825
[17,] -527.965385 -154.115203
[18,] 307.240524 -527.965385
[19,] 117.247003 307.240524
[20,] -894.039800 117.247003
[21,] -380.299742 -894.039800
[22,] 1073.094681 -380.299742
[23,] -237.127122 1073.094681
[24,] -160.976948 -237.127122
[25,] -373.764659 -160.976948
[26,] -122.667297 -373.764659
[27,] 807.675156 -122.667297
[28,] -365.426057 807.675156
[29,] 155.397141 -365.426057
[30,] -117.024254 155.397141
[31,] -256.055438 -117.024254
[32,] -263.486519 -256.055438
[33,] -169.223100 -263.486519
[34,] -19.850389 -169.223100
[35,] -101.497091 -19.850389
[36,] -50.584544 -101.497091
[37,] -304.121447 -50.584544
[38,] -465.161133 -304.121447
[39,] -163.061730 -465.161133
[40,] -180.676601 -163.061730
[41,] 429.760487 -180.676601
[42,] -41.642882 429.760487
[43,] 308.065313 -41.642882
[44,] -223.780338 308.065313
[45,] -752.888165 -223.780338
[46,] -209.892957 -752.888165
[47,] -299.491550 -209.892957
[48,] 41.203814 -299.491550
[49,] -206.761944 41.203814
[50,] 733.843788 -206.761944
[51,] -257.941858 733.843788
[52,] -57.247847 -257.941858
[53,] -257.775162 -57.247847
[54,] -170.578798 -257.775162
[55,] -186.521198 -170.578798
[56,] 3.786863 -186.521198
[57,] 721.183165 3.786863
[58,] -215.838825 721.183165
[59,] -326.436011 -215.838825
> z <- as.data.frame(dum1)
> z
lag(myerror, k = 1) myerror
1 -1378.236826 -787.248457
2 1730.760054 -1378.236826
3 566.663073 1730.760054
4 -732.182613 566.663073
5 -1686.876062 -732.182613
6 2433.670192 -1686.876062
7 -460.034874 2433.670192
8 589.997788 -460.034874
9 2001.176818 589.997788
10 501.636993 2001.176818
11 265.040914 501.636993
12 586.267253 265.040914
13 601.542095 586.267253
14 -220.657464 601.542095
15 -196.094825 -220.657464
16 -154.115203 -196.094825
17 -527.965385 -154.115203
18 307.240524 -527.965385
19 117.247003 307.240524
20 -894.039800 117.247003
21 -380.299742 -894.039800
22 1073.094681 -380.299742
23 -237.127122 1073.094681
24 -160.976948 -237.127122
25 -373.764659 -160.976948
26 -122.667297 -373.764659
27 807.675156 -122.667297
28 -365.426057 807.675156
29 155.397141 -365.426057
30 -117.024254 155.397141
31 -256.055438 -117.024254
32 -263.486519 -256.055438
33 -169.223100 -263.486519
34 -19.850389 -169.223100
35 -101.497091 -19.850389
36 -50.584544 -101.497091
37 -304.121447 -50.584544
38 -465.161133 -304.121447
39 -163.061730 -465.161133
40 -180.676601 -163.061730
41 429.760487 -180.676601
42 -41.642882 429.760487
43 308.065313 -41.642882
44 -223.780338 308.065313
45 -752.888165 -223.780338
46 -209.892957 -752.888165
47 -299.491550 -209.892957
48 41.203814 -299.491550
49 -206.761944 41.203814
50 733.843788 -206.761944
51 -257.941858 733.843788
52 -57.247847 -257.941858
53 -257.775162 -57.247847
54 -170.578798 -257.775162
55 -186.521198 -170.578798
56 3.786863 -186.521198
57 721.183165 3.786863
58 -215.838825 721.183165
59 -326.436011 -215.838825
> 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/77pbz1322130290.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> acf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/wessaorg/rcomp/tmp/8hmvy1322130290.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> pacf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Partial Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/wessaorg/rcomp/tmp/9i2gp1322130290.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> opar <- par(mfrow = c(2,2), oma = c(0, 0, 1.1, 0))
> plot(mylm, las = 1, sub='Residual Diagnostics')
> par(opar)
> dev.off()
null device
1
> if (n > n25) {
+ postscript(file="/var/wessaorg/rcomp/tmp/10ktoe1322130290.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
+ plot(kp3:nmkm3,gqarr[,2], main='Goldfeld-Quandt test',ylab='2-sided p-value',xlab='breakpoint')
+ grid()
+ dev.off()
+ }
null device
1
>
> #Note: the /var/wessaorg/rcomp/createtable file can be downloaded at http://www.wessa.net/cretab
> load(file="/var/wessaorg/rcomp/createtable")
>
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a, 'Multiple Linear Regression - Estimated Regression Equation', 1, TRUE)
> a<-table.row.end(a)
> myeq <- colnames(x)[1]
> myeq <- paste(myeq, '[t] = ', sep='')
> for (i in 1:k){
+ if (mysum$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/1178b91322130290.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/12fo0g1322130290.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/13z1gq1322130290.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/14u3o21322130290.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/15s02a1322130290.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/16mx841322130290.tab")
+ }
>
> try(system("convert tmp/1gv7i1322130290.ps tmp/1gv7i1322130290.png",intern=TRUE))
character(0)
> try(system("convert tmp/27hdy1322130290.ps tmp/27hdy1322130290.png",intern=TRUE))
character(0)
> try(system("convert tmp/3tekw1322130290.ps tmp/3tekw1322130290.png",intern=TRUE))
character(0)
> try(system("convert tmp/416dq1322130290.ps tmp/416dq1322130290.png",intern=TRUE))
character(0)
> try(system("convert tmp/50a001322130290.ps tmp/50a001322130290.png",intern=TRUE))
character(0)
> try(system("convert tmp/6rtmx1322130290.ps tmp/6rtmx1322130290.png",intern=TRUE))
character(0)
> try(system("convert tmp/77pbz1322130290.ps tmp/77pbz1322130290.png",intern=TRUE))
character(0)
> try(system("convert tmp/8hmvy1322130290.ps tmp/8hmvy1322130290.png",intern=TRUE))
character(0)
> try(system("convert tmp/9i2gp1322130290.ps tmp/9i2gp1322130290.png",intern=TRUE))
character(0)
> try(system("convert tmp/10ktoe1322130290.ps tmp/10ktoe1322130290.png",intern=TRUE))
character(0)
>
>
> proc.time()
user system elapsed
3.164 0.450 3.634