R version 2.8.0 (2008-10-20)
Copyright (C) 2008 The R Foundation for Statistical Computing
ISBN 3-900051-07-0
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(54156,53661,52441,50648,48141,46127,45623,56527,60205,61321,58088,54623,53495,51824,50518,49050,47111,45264,44357,54862,57871,59070,56273,52837,51702,49447,48965,46922,46256,45200,44471,53119,55016,56641,51847,47990,45744,46390,44461,41582,40813,38096,35461,44375,46255,45610,43375,40167,40628,40590,39473,36735,36634,32806,32907,41076,42254,43215,41116,40373),dim=c(1,60),dimnames=list(c('R(1)'),1:60))
> y <- array(NA,dim=c(1,60),dimnames=list(c('R(1)'),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
R(1) t
1 54156 1
2 53661 2
3 52441 3
4 50648 4
5 48141 5
6 46127 6
7 45623 7
8 56527 8
9 60205 9
10 61321 10
11 58088 11
12 54623 12
13 53495 13
14 51824 14
15 50518 15
16 49050 16
17 47111 17
18 45264 18
19 44357 19
20 54862 20
21 57871 21
22 59070 22
23 56273 23
24 52837 24
25 51702 25
26 49447 26
27 48965 27
28 46922 28
29 46256 29
30 45200 30
31 44471 31
32 53119 32
33 55016 33
34 56641 34
35 51847 35
36 47990 36
37 45744 37
38 46390 38
39 44461 39
40 41582 40
41 40813 41
42 38096 42
43 35461 43
44 44375 44
45 46255 45
46 45610 46
47 43375 47
48 40167 48
49 40628 49
50 40590 50
51 39473 51
52 36735 52
53 36634 53
54 32806 54
55 32907 55
56 41076 56
57 42254 57
58 43215 58
59 41116 59
60 40373 60
> k <- length(x[1,])
> df <- as.data.frame(x)
> (mylm <- lm(df))
Call:
lm(formula = df)
Coefficients:
(Intercept) t
56288.3 -292.6
> (mysum <- summary(mylm))
Call:
lm(formula = df)
Residuals:
Min 1Q Median 3Q Max
-8617.00 -2977.49 -42.52 2742.43 10301.76
Coefficients:
Estimate Std. Error t value Pr(>|t|)
(Intercept) 56288.34 1239.46 45.41 < 2e-16 ***
t -292.62 35.34 -8.28 2.08e-11 ***
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
Residual standard error: 4741 on 58 degrees of freedom
Multiple R-squared: 0.5417, Adjusted R-squared: 0.5338
F-statistic: 68.57 on 1 and 58 DF, p-value: 2.078e-11
> 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,] 0.0045717391 0.0091434781 0.99542826
[2,] 0.0013217592 0.0026435183 0.99867824
[3,] 0.0002947039 0.0005894079 0.99970530
[4,] 0.4584780626 0.9169561252 0.54152194
[5,] 0.7504295866 0.4991408269 0.24957041
[6,] 0.8104181241 0.3791637518 0.18958188
[7,] 0.7433636878 0.5132726244 0.25663631
[8,] 0.6796823721 0.6406352559 0.32031763
[9,] 0.6274900809 0.7450198382 0.37250992
[10,] 0.6014381674 0.7971236652 0.39856183
[11,] 0.5896796176 0.8206407649 0.41032038
[12,] 0.5979303966 0.8041392067 0.40206960
[13,] 0.6474451778 0.7051096445 0.35255482
[14,] 0.7394021685 0.5211956630 0.26059783
[15,] 0.8367799052 0.3264401896 0.16322009
[16,] 0.8253337716 0.3493324569 0.17466623
[17,] 0.8595751530 0.2808496940 0.14042485
[18,] 0.9018389576 0.1963220848 0.09816104
[19,] 0.8917190035 0.2165619931 0.10828100
[20,] 0.8544618179 0.2910763641 0.14553818
[21,] 0.8100039197 0.3799921605 0.18999608
[22,] 0.7698948389 0.4602103222 0.23010516
[23,] 0.7254656382 0.5490687236 0.27453436
[24,] 0.7053454831 0.5893090338 0.29465452
[25,] 0.6890265164 0.6219469672 0.31097348
[26,] 0.6909771159 0.6180457682 0.30902288
[27,] 0.7082585873 0.5834828254 0.29174141
[28,] 0.6850489750 0.6299020500 0.31495103
[29,] 0.7385141207 0.5229717586 0.26148588
[30,] 0.8870746244 0.2258507511 0.11292538
[31,] 0.9131737095 0.1736525809 0.08682629
[32,] 0.9050899632 0.1898200737 0.09491004
[33,] 0.8885731347 0.2228537306 0.11142687
[34,] 0.8804902385 0.2390195230 0.11950976
[35,] 0.8639031154 0.2721937692 0.13609688
[36,] 0.8442610849 0.3114778301 0.15573892
[37,] 0.8194472590 0.3611054821 0.18055274
[38,] 0.8318231398 0.3363537204 0.16817686
[39,] 0.9188606021 0.1622787959 0.08113940
[40,] 0.8835087956 0.2329824089 0.11649120
[41,] 0.8811363960 0.2377272080 0.11886360
[42,] 0.8995533231 0.2008933538 0.10044668
[43,] 0.9037401802 0.1925196395 0.09625982
[44,] 0.8713699050 0.2572601899 0.12863009
[45,] 0.8523331909 0.2953336182 0.14766681
[46,] 0.8630036303 0.2739927393 0.13699637
[47,] 0.8839142619 0.2321714762 0.11608574
[48,] 0.8470926629 0.3058146742 0.15290734
[49,] 0.7956323655 0.4087352691 0.20436763
[50,] 0.7341629902 0.5316740196 0.26583701
[51,] 0.9797644270 0.0404711460 0.02023557
> postscript(file="/var/www/html/freestat/rcomp/tmp/1qsog1230127605.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$resid)
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/freestat/rcomp/tmp/2gvpj1230127605.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> plot(mysum$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/freestat/rcomp/tmp/3qqrg1230127605.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> hist(mysum$resid, main='Residual Histogram', xlab='values of Residuals')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/freestat/rcomp/tmp/4xad01230127605.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> densityplot(~mysum$resid,col='black',main='Residual Density Plot', xlab='values of Residuals')
> dev.off()
null device
1
> postscript(file="/var/www/html/freestat/rcomp/tmp/5qaw31230127605.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 7
-1839.7240 -2042.1035 -2969.4829 -4469.8623 -6684.2417 -8405.6211 -8617.0005
8 9 10 11 12 13 14
2579.6201 6550.2407 7958.8613 5018.4818 1846.1024 1010.7230 -367.6564
15 16 17 18 19 20 21
-1381.0358 -2556.4152 -4202.7946 -5757.1740 -6371.5534 4426.0671 7727.6877
22 23 24 25 26 27 28
9219.3083 6714.9289 3571.5495 2729.1701 766.7907 577.4113 -1172.9681
29 30 31 32 33 34 35
-1546.3476 -2309.7270 -2746.1064 6194.5142 8384.1348 10301.7554 5800.3760
36 37 38 39 40 41 42
2235.9966 282.6172 1221.2378 -415.1417 -3001.5211 -3477.9005 -5902.2799
43 44 45 46 47 48 49
-8244.6593 961.9613 3134.5819 2782.2025 839.8231 -2075.5564 -1321.9358
50 51 52 53 54 55 56
-1067.3152 -1891.6946 -4337.0740 -4145.4534 -7680.8328 -7287.2122 1174.4084
57 58 59 60
2645.0289 3898.6495 2092.2701 1641.8907
> postscript(file="/var/www/html/freestat/rcomp/tmp/6c62y1230127605.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 -1839.7240 NA
1 -2042.1035 -1839.7240
2 -2969.4829 -2042.1035
3 -4469.8623 -2969.4829
4 -6684.2417 -4469.8623
5 -8405.6211 -6684.2417
6 -8617.0005 -8405.6211
7 2579.6201 -8617.0005
8 6550.2407 2579.6201
9 7958.8613 6550.2407
10 5018.4818 7958.8613
11 1846.1024 5018.4818
12 1010.7230 1846.1024
13 -367.6564 1010.7230
14 -1381.0358 -367.6564
15 -2556.4152 -1381.0358
16 -4202.7946 -2556.4152
17 -5757.1740 -4202.7946
18 -6371.5534 -5757.1740
19 4426.0671 -6371.5534
20 7727.6877 4426.0671
21 9219.3083 7727.6877
22 6714.9289 9219.3083
23 3571.5495 6714.9289
24 2729.1701 3571.5495
25 766.7907 2729.1701
26 577.4113 766.7907
27 -1172.9681 577.4113
28 -1546.3476 -1172.9681
29 -2309.7270 -1546.3476
30 -2746.1064 -2309.7270
31 6194.5142 -2746.1064
32 8384.1348 6194.5142
33 10301.7554 8384.1348
34 5800.3760 10301.7554
35 2235.9966 5800.3760
36 282.6172 2235.9966
37 1221.2378 282.6172
38 -415.1417 1221.2378
39 -3001.5211 -415.1417
40 -3477.9005 -3001.5211
41 -5902.2799 -3477.9005
42 -8244.6593 -5902.2799
43 961.9613 -8244.6593
44 3134.5819 961.9613
45 2782.2025 3134.5819
46 839.8231 2782.2025
47 -2075.5564 839.8231
48 -1321.9358 -2075.5564
49 -1067.3152 -1321.9358
50 -1891.6946 -1067.3152
51 -4337.0740 -1891.6946
52 -4145.4534 -4337.0740
53 -7680.8328 -4145.4534
54 -7287.2122 -7680.8328
55 1174.4084 -7287.2122
56 2645.0289 1174.4084
57 3898.6495 2645.0289
58 2092.2701 3898.6495
59 1641.8907 2092.2701
60 NA 1641.8907
> dum1 <- dum[2:length(myerror),]
> dum1
lag(myerror, k = 1) myerror
[1,] -2042.1035 -1839.7240
[2,] -2969.4829 -2042.1035
[3,] -4469.8623 -2969.4829
[4,] -6684.2417 -4469.8623
[5,] -8405.6211 -6684.2417
[6,] -8617.0005 -8405.6211
[7,] 2579.6201 -8617.0005
[8,] 6550.2407 2579.6201
[9,] 7958.8613 6550.2407
[10,] 5018.4818 7958.8613
[11,] 1846.1024 5018.4818
[12,] 1010.7230 1846.1024
[13,] -367.6564 1010.7230
[14,] -1381.0358 -367.6564
[15,] -2556.4152 -1381.0358
[16,] -4202.7946 -2556.4152
[17,] -5757.1740 -4202.7946
[18,] -6371.5534 -5757.1740
[19,] 4426.0671 -6371.5534
[20,] 7727.6877 4426.0671
[21,] 9219.3083 7727.6877
[22,] 6714.9289 9219.3083
[23,] 3571.5495 6714.9289
[24,] 2729.1701 3571.5495
[25,] 766.7907 2729.1701
[26,] 577.4113 766.7907
[27,] -1172.9681 577.4113
[28,] -1546.3476 -1172.9681
[29,] -2309.7270 -1546.3476
[30,] -2746.1064 -2309.7270
[31,] 6194.5142 -2746.1064
[32,] 8384.1348 6194.5142
[33,] 10301.7554 8384.1348
[34,] 5800.3760 10301.7554
[35,] 2235.9966 5800.3760
[36,] 282.6172 2235.9966
[37,] 1221.2378 282.6172
[38,] -415.1417 1221.2378
[39,] -3001.5211 -415.1417
[40,] -3477.9005 -3001.5211
[41,] -5902.2799 -3477.9005
[42,] -8244.6593 -5902.2799
[43,] 961.9613 -8244.6593
[44,] 3134.5819 961.9613
[45,] 2782.2025 3134.5819
[46,] 839.8231 2782.2025
[47,] -2075.5564 839.8231
[48,] -1321.9358 -2075.5564
[49,] -1067.3152 -1321.9358
[50,] -1891.6946 -1067.3152
[51,] -4337.0740 -1891.6946
[52,] -4145.4534 -4337.0740
[53,] -7680.8328 -4145.4534
[54,] -7287.2122 -7680.8328
[55,] 1174.4084 -7287.2122
[56,] 2645.0289 1174.4084
[57,] 3898.6495 2645.0289
[58,] 2092.2701 3898.6495
[59,] 1641.8907 2092.2701
> z <- as.data.frame(dum1)
> z
lag(myerror, k = 1) myerror
1 -2042.1035 -1839.7240
2 -2969.4829 -2042.1035
3 -4469.8623 -2969.4829
4 -6684.2417 -4469.8623
5 -8405.6211 -6684.2417
6 -8617.0005 -8405.6211
7 2579.6201 -8617.0005
8 6550.2407 2579.6201
9 7958.8613 6550.2407
10 5018.4818 7958.8613
11 1846.1024 5018.4818
12 1010.7230 1846.1024
13 -367.6564 1010.7230
14 -1381.0358 -367.6564
15 -2556.4152 -1381.0358
16 -4202.7946 -2556.4152
17 -5757.1740 -4202.7946
18 -6371.5534 -5757.1740
19 4426.0671 -6371.5534
20 7727.6877 4426.0671
21 9219.3083 7727.6877
22 6714.9289 9219.3083
23 3571.5495 6714.9289
24 2729.1701 3571.5495
25 766.7907 2729.1701
26 577.4113 766.7907
27 -1172.9681 577.4113
28 -1546.3476 -1172.9681
29 -2309.7270 -1546.3476
30 -2746.1064 -2309.7270
31 6194.5142 -2746.1064
32 8384.1348 6194.5142
33 10301.7554 8384.1348
34 5800.3760 10301.7554
35 2235.9966 5800.3760
36 282.6172 2235.9966
37 1221.2378 282.6172
38 -415.1417 1221.2378
39 -3001.5211 -415.1417
40 -3477.9005 -3001.5211
41 -5902.2799 -3477.9005
42 -8244.6593 -5902.2799
43 961.9613 -8244.6593
44 3134.5819 961.9613
45 2782.2025 3134.5819
46 839.8231 2782.2025
47 -2075.5564 839.8231
48 -1321.9358 -2075.5564
49 -1067.3152 -1321.9358
50 -1891.6946 -1067.3152
51 -4337.0740 -1891.6946
52 -4145.4534 -4337.0740
53 -7680.8328 -4145.4534
54 -7287.2122 -7680.8328
55 1174.4084 -7287.2122
56 2645.0289 1174.4084
57 3898.6495 2645.0289
58 2092.2701 3898.6495
59 1641.8907 2092.2701
> 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/freestat/rcomp/tmp/7iv381230127605.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> acf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/freestat/rcomp/tmp/87d351230127605.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> pacf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Partial Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/freestat/rcomp/tmp/90z1x1230127605.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> opar <- par(mfrow = c(2,2), oma = c(0, 0, 1.1, 0))
> plot(mylm, las = 1, sub='Residual Diagnostics')
> par(opar)
> dev.off()
null device
1
> if (n > n25) {
+ postscript(file="/var/www/html/freestat/rcomp/tmp/10r9o31230127605.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
+ plot(kp3:nmkm3,gqarr[,2], main='Goldfeld-Quandt test',ylab='2-sided p-value',xlab='breakpoint')
+ grid()
+ dev.off()
+ }
null device
1
>
> #Note: the /var/www/html/freestat/rcomp/createtable file can be downloaded at http://www.wessa.net/cretab
> load(file="/var/www/html/freestat/rcomp/createtable")
>
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a, 'Multiple Linear Regression - Estimated Regression Equation', 1, TRUE)
> a<-table.row.end(a)
> myeq <- colnames(x)[1]
> myeq <- paste(myeq, '[t] = ', sep='')
> for (i in 1:k){
+ if (mysum$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/freestat/rcomp/tmp/11b49f1230127605.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/freestat/rcomp/tmp/12kxoz1230127605.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/freestat/rcomp/tmp/13kq6m1230127605.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/freestat/rcomp/tmp/14l7851230127605.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/freestat/rcomp/tmp/15jhbc1230127605.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/freestat/rcomp/tmp/16g9jg1230127605.tab")
+ }
>
> system("convert tmp/1qsog1230127605.ps tmp/1qsog1230127605.png")
> system("convert tmp/2gvpj1230127605.ps tmp/2gvpj1230127605.png")
> system("convert tmp/3qqrg1230127605.ps tmp/3qqrg1230127605.png")
> system("convert tmp/4xad01230127605.ps tmp/4xad01230127605.png")
> system("convert tmp/5qaw31230127605.ps tmp/5qaw31230127605.png")
> system("convert tmp/6c62y1230127605.ps tmp/6c62y1230127605.png")
> system("convert tmp/7iv381230127605.ps tmp/7iv381230127605.png")
> system("convert tmp/87d351230127605.ps tmp/87d351230127605.png")
> system("convert tmp/90z1x1230127605.ps tmp/90z1x1230127605.png")
> system("convert tmp/10r9o31230127605.ps tmp/10r9o31230127605.png")
>
>
> proc.time()
user system elapsed
3.649 2.450 4.084