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.
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(21,2472.81,19,2407.6,25,2454.62,21,2448.05,23,2497.84,23,2645.64,19,2756.76,18,2849.27,19,2921.44,19,2981.85,22,3080.58,23,3106.22,20,3119.31,14,3061.26,14,3097.31,14,3161.69,15,3257.16,11,3277.01,17,3295.32,16,3363.99,20,3494.17,24,3667.03,23,3813.06,20,3917.96,21,3895.51,19,3801.06,23,3570.12,23,3701.61,23,3862.27,23,3970.1,27,4138.52,26,4199.75,17,4290.89,24,4443.91,26,4502.64,24,4356.98,27,4591.27,27,4696.96,26,4621.4,24,4562.84,23,4202.52,23,4296.49,24,4435.23,17,4105.18,21,4116.68,19,3844.49,22,3720.98,22,3674.4,18,3857.62,16,3801.06,14,3504.37,12,3032.6,14,3047.03,16,2962.34,8,2197.82,3,2014.45,0,1862.83,5,1905.41,1,1810.99,1,1670.07,3,1864.44),dim=c(2,61),dimnames=list(c('Consvertr','Aand'),1:61))
> y <- array(NA,dim=c(2,61),dimnames=list(c('Consvertr','Aand'),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 = '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
Consvertr Aand
1 21 2472.81
2 19 2407.60
3 25 2454.62
4 21 2448.05
5 23 2497.84
6 23 2645.64
7 19 2756.76
8 18 2849.27
9 19 2921.44
10 19 2981.85
11 22 3080.58
12 23 3106.22
13 20 3119.31
14 14 3061.26
15 14 3097.31
16 14 3161.69
17 15 3257.16
18 11 3277.01
19 17 3295.32
20 16 3363.99
21 20 3494.17
22 24 3667.03
23 23 3813.06
24 20 3917.96
25 21 3895.51
26 19 3801.06
27 23 3570.12
28 23 3701.61
29 23 3862.27
30 23 3970.10
31 27 4138.52
32 26 4199.75
33 17 4290.89
34 24 4443.91
35 26 4502.64
36 24 4356.98
37 27 4591.27
38 27 4696.96
39 26 4621.40
40 24 4562.84
41 23 4202.52
42 23 4296.49
43 24 4435.23
44 17 4105.18
45 21 4116.68
46 19 3844.49
47 22 3720.98
48 22 3674.40
49 18 3857.62
50 16 3801.06
51 14 3504.37
52 12 3032.60
53 14 3047.03
54 16 2962.34
55 8 2197.82
56 3 2014.45
57 0 1862.83
58 5 1905.41
59 1 1810.99
60 1 1670.07
61 3 1864.44
> k <- length(x[1,])
> df <- as.data.frame(x)
> (mylm <- lm(df))
Call:
lm(formula = df)
Coefficients:
(Intercept) Aand
-2.489121 0.006175
> (mysum <- summary(mylm))
Call:
lm(formula = df)
Residuals:
Min 1Q Median 3Q Max
-9.0143 -2.6376 -0.4625 2.8942 12.3312
Coefficients:
Estimate Std. Error t value Pr(>|t|)
(Intercept) -2.4891208 2.5712903 -0.968 0.337
Aand 0.0061753 0.0007395 8.351 1.40e-11 ***
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
Residual standard error: 4.677 on 59 degrees of freedom
Multiple R-squared: 0.5417, Adjusted R-squared: 0.5339
F-statistic: 69.74 on 1 and 59 DF, p-value: 1.398e-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,] 0.19706308 0.394126161 0.802936920
[2,] 0.17796047 0.355920949 0.822039525
[3,] 0.22935624 0.458712488 0.770643756
[4,] 0.17586752 0.351735035 0.824132483
[5,] 0.11788960 0.235779205 0.882110397
[6,] 0.07866443 0.157328864 0.921335568
[7,] 0.14160082 0.283201630 0.858399185
[8,] 0.25904900 0.518097992 0.740951004
[9,] 0.23782757 0.475655145 0.762172428
[10,] 0.52784371 0.944312578 0.472156289
[11,] 0.64404370 0.711912591 0.355956295
[12,] 0.66649147 0.667017053 0.333508526
[13,] 0.60513953 0.789720939 0.394860469
[14,] 0.73516645 0.529667106 0.264833553
[15,] 0.68179514 0.636409713 0.318204856
[16,] 0.61011951 0.779760981 0.389880490
[17,] 0.70945839 0.581083213 0.290541606
[18,] 0.93582264 0.128354722 0.064177361
[19,] 0.96545414 0.069091719 0.034545859
[20,] 0.95374838 0.092503247 0.046251623
[21,] 0.94119170 0.117616591 0.058808295
[22,] 0.91606898 0.167862032 0.083931016
[23,] 0.95019584 0.099608328 0.049804164
[24,] 0.96499299 0.070014026 0.035007013
[25,] 0.96764525 0.064709497 0.032354749
[26,] 0.96434945 0.071301097 0.035650548
[27,] 0.98828040 0.023439196 0.011719598
[28,] 0.99254998 0.014900042 0.007450021
[29,] 0.99869920 0.002601600 0.001300800
[30,] 0.99775742 0.004485158 0.002242579
[31,] 0.99692878 0.006142446 0.003071223
[32,] 0.99468388 0.010632241 0.005316120
[33,] 0.99330965 0.013380708 0.006690354
[34,] 0.99002925 0.019941492 0.009970746
[35,] 0.98394180 0.032116404 0.016058202
[36,] 0.97445402 0.051091964 0.025545982
[37,] 0.96020760 0.079584809 0.039792404
[38,] 0.93772970 0.124540594 0.062270297
[39,] 0.90587507 0.188249854 0.094124927
[40,] 0.95159172 0.096816555 0.048408278
[41,] 0.92819934 0.143601321 0.071800661
[42,] 0.89807935 0.203841304 0.101920652
[43,] 0.90219246 0.195615073 0.097807537
[44,] 0.94603905 0.107921897 0.053960949
[45,] 0.91744234 0.165115324 0.082557662
[46,] 0.92749722 0.145005556 0.072502778
[47,] 0.96896515 0.062069692 0.031034846
[48,] 0.97913769 0.041724618 0.020862309
[49,] 0.97860978 0.042780448 0.021390224
[50,] 0.95003300 0.099934001 0.049967000
[51,] 0.93058123 0.138837548 0.069418774
[52,] 0.87114434 0.257711326 0.128855663
> postscript(file="/var/www/html/rcomp/tmp/1rhaf1258526123.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$resid)
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/2mrin1258526123.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> plot(mysum$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/3lh4r1258526123.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> hist(mysum$resid, main='Residual Histogram', xlab='values of Residuals')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/4vf1h1258526123.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> densityplot(~mysum$resid,col='black',main='Residual Density Plot', xlab='values of Residuals')
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/5sk8s1258526123.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 = 61
Frequency = 1
1 2 3 4 5 6
8.21888908 6.62157745 12.33121697 8.37178839 10.06432245 9.15161980
7 8 9 10 11 12
4.46542549 2.89415267 3.44848453 3.07543739 5.46575449 6.30742096
13 14 15 16 17 18
3.22658687 -2.41493959 -2.63755752 -3.03512042 -2.62467200 -6.74725080
19 20 21 22 23 24
-0.86031972 -2.28437446 0.91173087 3.84427633 1.94250388 -1.70528035
25 26 27 28 29 30
-0.56664588 -1.98339307 3.44272027 2.63073602 1.63861959 0.97274187
31 32 33 34 35 36
3.93270546 2.55459461 -7.00821811 -0.95315559 0.68417169 -0.41634070
37 38 39 40 41 42
1.13685886 0.48419619 -0.04920156 -1.68757864 -0.46251084 -1.04279954
43 44 45 46 47 48
-0.89955438 -5.86141155 -1.93242698 -2.25158438 1.51112134 1.79876470
49 50 51 52 53 54
-3.33266548 -4.98339307 -5.15125673 -4.23795679 -2.32706571 0.19591661
55 56 57 58 59 60
-3.08297761 -6.95062114 -9.01432901 -4.27727136 -7.69420381 -6.82398690
61
-6.02427117
> postscript(file="/var/www/html/rcomp/tmp/68q6e1258526123.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 = 61
Frequency = 1
lag(myerror, k = 1) myerror
0 8.21888908 NA
1 6.62157745 8.21888908
2 12.33121697 6.62157745
3 8.37178839 12.33121697
4 10.06432245 8.37178839
5 9.15161980 10.06432245
6 4.46542549 9.15161980
7 2.89415267 4.46542549
8 3.44848453 2.89415267
9 3.07543739 3.44848453
10 5.46575449 3.07543739
11 6.30742096 5.46575449
12 3.22658687 6.30742096
13 -2.41493959 3.22658687
14 -2.63755752 -2.41493959
15 -3.03512042 -2.63755752
16 -2.62467200 -3.03512042
17 -6.74725080 -2.62467200
18 -0.86031972 -6.74725080
19 -2.28437446 -0.86031972
20 0.91173087 -2.28437446
21 3.84427633 0.91173087
22 1.94250388 3.84427633
23 -1.70528035 1.94250388
24 -0.56664588 -1.70528035
25 -1.98339307 -0.56664588
26 3.44272027 -1.98339307
27 2.63073602 3.44272027
28 1.63861959 2.63073602
29 0.97274187 1.63861959
30 3.93270546 0.97274187
31 2.55459461 3.93270546
32 -7.00821811 2.55459461
33 -0.95315559 -7.00821811
34 0.68417169 -0.95315559
35 -0.41634070 0.68417169
36 1.13685886 -0.41634070
37 0.48419619 1.13685886
38 -0.04920156 0.48419619
39 -1.68757864 -0.04920156
40 -0.46251084 -1.68757864
41 -1.04279954 -0.46251084
42 -0.89955438 -1.04279954
43 -5.86141155 -0.89955438
44 -1.93242698 -5.86141155
45 -2.25158438 -1.93242698
46 1.51112134 -2.25158438
47 1.79876470 1.51112134
48 -3.33266548 1.79876470
49 -4.98339307 -3.33266548
50 -5.15125673 -4.98339307
51 -4.23795679 -5.15125673
52 -2.32706571 -4.23795679
53 0.19591661 -2.32706571
54 -3.08297761 0.19591661
55 -6.95062114 -3.08297761
56 -9.01432901 -6.95062114
57 -4.27727136 -9.01432901
58 -7.69420381 -4.27727136
59 -6.82398690 -7.69420381
60 -6.02427117 -6.82398690
61 NA -6.02427117
> dum1 <- dum[2:length(myerror),]
> dum1
lag(myerror, k = 1) myerror
[1,] 6.62157745 8.21888908
[2,] 12.33121697 6.62157745
[3,] 8.37178839 12.33121697
[4,] 10.06432245 8.37178839
[5,] 9.15161980 10.06432245
[6,] 4.46542549 9.15161980
[7,] 2.89415267 4.46542549
[8,] 3.44848453 2.89415267
[9,] 3.07543739 3.44848453
[10,] 5.46575449 3.07543739
[11,] 6.30742096 5.46575449
[12,] 3.22658687 6.30742096
[13,] -2.41493959 3.22658687
[14,] -2.63755752 -2.41493959
[15,] -3.03512042 -2.63755752
[16,] -2.62467200 -3.03512042
[17,] -6.74725080 -2.62467200
[18,] -0.86031972 -6.74725080
[19,] -2.28437446 -0.86031972
[20,] 0.91173087 -2.28437446
[21,] 3.84427633 0.91173087
[22,] 1.94250388 3.84427633
[23,] -1.70528035 1.94250388
[24,] -0.56664588 -1.70528035
[25,] -1.98339307 -0.56664588
[26,] 3.44272027 -1.98339307
[27,] 2.63073602 3.44272027
[28,] 1.63861959 2.63073602
[29,] 0.97274187 1.63861959
[30,] 3.93270546 0.97274187
[31,] 2.55459461 3.93270546
[32,] -7.00821811 2.55459461
[33,] -0.95315559 -7.00821811
[34,] 0.68417169 -0.95315559
[35,] -0.41634070 0.68417169
[36,] 1.13685886 -0.41634070
[37,] 0.48419619 1.13685886
[38,] -0.04920156 0.48419619
[39,] -1.68757864 -0.04920156
[40,] -0.46251084 -1.68757864
[41,] -1.04279954 -0.46251084
[42,] -0.89955438 -1.04279954
[43,] -5.86141155 -0.89955438
[44,] -1.93242698 -5.86141155
[45,] -2.25158438 -1.93242698
[46,] 1.51112134 -2.25158438
[47,] 1.79876470 1.51112134
[48,] -3.33266548 1.79876470
[49,] -4.98339307 -3.33266548
[50,] -5.15125673 -4.98339307
[51,] -4.23795679 -5.15125673
[52,] -2.32706571 -4.23795679
[53,] 0.19591661 -2.32706571
[54,] -3.08297761 0.19591661
[55,] -6.95062114 -3.08297761
[56,] -9.01432901 -6.95062114
[57,] -4.27727136 -9.01432901
[58,] -7.69420381 -4.27727136
[59,] -6.82398690 -7.69420381
[60,] -6.02427117 -6.82398690
> z <- as.data.frame(dum1)
> z
lag(myerror, k = 1) myerror
1 6.62157745 8.21888908
2 12.33121697 6.62157745
3 8.37178839 12.33121697
4 10.06432245 8.37178839
5 9.15161980 10.06432245
6 4.46542549 9.15161980
7 2.89415267 4.46542549
8 3.44848453 2.89415267
9 3.07543739 3.44848453
10 5.46575449 3.07543739
11 6.30742096 5.46575449
12 3.22658687 6.30742096
13 -2.41493959 3.22658687
14 -2.63755752 -2.41493959
15 -3.03512042 -2.63755752
16 -2.62467200 -3.03512042
17 -6.74725080 -2.62467200
18 -0.86031972 -6.74725080
19 -2.28437446 -0.86031972
20 0.91173087 -2.28437446
21 3.84427633 0.91173087
22 1.94250388 3.84427633
23 -1.70528035 1.94250388
24 -0.56664588 -1.70528035
25 -1.98339307 -0.56664588
26 3.44272027 -1.98339307
27 2.63073602 3.44272027
28 1.63861959 2.63073602
29 0.97274187 1.63861959
30 3.93270546 0.97274187
31 2.55459461 3.93270546
32 -7.00821811 2.55459461
33 -0.95315559 -7.00821811
34 0.68417169 -0.95315559
35 -0.41634070 0.68417169
36 1.13685886 -0.41634070
37 0.48419619 1.13685886
38 -0.04920156 0.48419619
39 -1.68757864 -0.04920156
40 -0.46251084 -1.68757864
41 -1.04279954 -0.46251084
42 -0.89955438 -1.04279954
43 -5.86141155 -0.89955438
44 -1.93242698 -5.86141155
45 -2.25158438 -1.93242698
46 1.51112134 -2.25158438
47 1.79876470 1.51112134
48 -3.33266548 1.79876470
49 -4.98339307 -3.33266548
50 -5.15125673 -4.98339307
51 -4.23795679 -5.15125673
52 -2.32706571 -4.23795679
53 0.19591661 -2.32706571
54 -3.08297761 0.19591661
55 -6.95062114 -3.08297761
56 -9.01432901 -6.95062114
57 -4.27727136 -9.01432901
58 -7.69420381 -4.27727136
59 -6.82398690 -7.69420381
60 -6.02427117 -6.82398690
> 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/78nyf1258526123.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> acf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/8kxy01258526123.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> pacf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Partial Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/9ffvo1258526123.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> opar <- par(mfrow = c(2,2), oma = c(0, 0, 1.1, 0))
> plot(mylm, las = 1, sub='Residual Diagnostics')
> par(opar)
> dev.off()
null device
1
> if (n > n25) {
+ postscript(file="/var/www/html/rcomp/tmp/105u041258526123.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
+ plot(kp3:nmkm3,gqarr[,2], main='Goldfeld-Quandt test',ylab='2-sided p-value',xlab='breakpoint')
+ grid()
+ dev.off()
+ }
null device
1
>
> #Note: the /var/www/html/rcomp/createtable file can be downloaded at http://www.wessa.net/cretab
> load(file="/var/www/html/rcomp/createtable")
>
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a, 'Multiple Linear Regression - Estimated Regression Equation', 1, TRUE)
> a<-table.row.end(a)
> myeq <- colnames(x)[1]
> myeq <- paste(myeq, '[t] = ', sep='')
> for (i in 1:k){
+ if (mysum$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/11ciwc1258526123.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/12v3zd1258526123.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/138djp1258526123.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/1495at1258526124.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/150yb91258526124.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/16iqir1258526124.tab")
+ }
>
> system("convert tmp/1rhaf1258526123.ps tmp/1rhaf1258526123.png")
> system("convert tmp/2mrin1258526123.ps tmp/2mrin1258526123.png")
> system("convert tmp/3lh4r1258526123.ps tmp/3lh4r1258526123.png")
> system("convert tmp/4vf1h1258526123.ps tmp/4vf1h1258526123.png")
> system("convert tmp/5sk8s1258526123.ps tmp/5sk8s1258526123.png")
> system("convert tmp/68q6e1258526123.ps tmp/68q6e1258526123.png")
> system("convert tmp/78nyf1258526123.ps tmp/78nyf1258526123.png")
> system("convert tmp/8kxy01258526123.ps tmp/8kxy01258526123.png")
> system("convert tmp/9ffvo1258526123.ps tmp/9ffvo1258526123.png")
> system("convert tmp/105u041258526123.ps tmp/105u041258526123.png")
>
>
> proc.time()
user system elapsed
2.410 1.511 3.897