R version 2.15.2 (2012-10-26) -- "Trick or Treat"
Copyright (C) 2012 The R Foundation for Statistical Computing
ISBN 3-900051-07-0
Platform: i686-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(1418
+ ,210907
+ ,56
+ ,396
+ ,81
+ ,3
+ ,79
+ ,30
+ ,869
+ ,120982
+ ,56
+ ,297
+ ,55
+ ,4
+ ,58
+ ,28
+ ,1530
+ ,176508
+ ,54
+ ,559
+ ,50
+ ,12
+ ,60
+ ,38
+ ,2172
+ ,179321
+ ,89
+ ,967
+ ,125
+ ,2
+ ,108
+ ,30
+ ,901
+ ,123185
+ ,40
+ ,270
+ ,40
+ ,1
+ ,49
+ ,22
+ ,463
+ ,52746
+ ,25
+ ,143
+ ,37
+ ,3
+ ,0
+ ,26
+ ,3201
+ ,385534
+ ,92
+ ,1562
+ ,63
+ ,0
+ ,121
+ ,25
+ ,371
+ ,33170
+ ,18
+ ,109
+ ,44
+ ,0
+ ,1
+ ,18
+ ,1192
+ ,101645
+ ,63
+ ,371
+ ,88
+ ,0
+ ,20
+ ,11
+ ,1583
+ ,149061
+ ,44
+ ,656
+ ,66
+ ,5
+ ,43
+ ,26
+ ,1439
+ ,165446
+ ,33
+ ,511
+ ,57
+ ,0
+ ,69
+ ,25
+ ,1764
+ ,237213
+ ,84
+ ,655
+ ,74
+ ,0
+ ,78
+ ,38
+ ,1495
+ ,173326
+ ,88
+ ,465
+ ,49
+ ,7
+ ,86
+ ,44
+ ,1373
+ ,133131
+ ,55
+ ,525
+ ,52
+ ,7
+ ,44
+ ,30
+ ,2187
+ ,258873
+ ,60
+ ,885
+ ,88
+ ,3
+ ,104
+ ,40
+ ,1491
+ ,180083
+ ,66
+ ,497
+ ,36
+ ,9
+ ,63
+ ,34
+ ,4041
+ ,324799
+ ,154
+ ,1436
+ ,108
+ ,0
+ ,158
+ ,47
+ ,1706
+ ,230964
+ ,53
+ ,612
+ ,43
+ ,4
+ ,102
+ ,30
+ ,2152
+ ,236785
+ ,119
+ ,865
+ ,75
+ ,3
+ ,77
+ ,31
+ ,1036
+ ,135473
+ ,41
+ ,385
+ ,32
+ ,0
+ ,82
+ ,23
+ ,1882
+ ,202925
+ ,61
+ ,567
+ ,44
+ ,7
+ ,115
+ ,36
+ ,1929
+ ,215147
+ ,58
+ ,639
+ ,85
+ ,0
+ ,101
+ ,36
+ ,2242
+ ,344297
+ ,75
+ ,963
+ ,86
+ ,1
+ ,80
+ ,30
+ ,1220
+ ,153935
+ ,33
+ ,398
+ ,56
+ ,5
+ ,50
+ ,25
+ ,1289
+ ,132943
+ ,40
+ ,410
+ ,50
+ ,7
+ ,83
+ ,39
+ ,2515
+ ,174724
+ ,92
+ ,966
+ ,135
+ ,0
+ ,123
+ ,34
+ ,2147
+ ,174415
+ ,100
+ ,801
+ ,63
+ ,0
+ ,73
+ ,31
+ ,2352
+ ,225548
+ ,112
+ ,892
+ ,81
+ ,5
+ ,81
+ ,31
+ ,1638
+ ,223632
+ ,73
+ ,513
+ ,5)
+ ,dim=c(8
+ ,29)
+ ,dimnames=list(c('pageviews'
+ ,'time_in_rfc'
+ ,'logins'
+ ,'compendium_views_info'
+ ,'compendium_views_pr'
+ ,'shared_compendiums'
+ ,'blogged_computations'
+ ,'compendiums_reviewed
')
+ ,1:29))
> y <- array(NA,dim=c(8,29),dimnames=list(c('pageviews','time_in_rfc','logins','compendium_views_info','compendium_views_pr','shared_compendiums','blogged_computations','compendiums_reviewed
'),1:29))
> 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'
> 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, 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
pageviews time_in_rfc logins compendium_views_info compendium_views_pr
1 1418 210907 56 396 81
2 869 120982 56 297 55
3 1530 176508 54 559 50
4 2172 179321 89 967 125
5 901 123185 40 270 40
6 463 52746 25 143 37
7 3201 385534 92 1562 63
8 371 33170 18 109 44
9 1192 101645 63 371 88
10 1583 149061 44 656 66
11 1439 165446 33 511 57
12 1764 237213 84 655 74
13 1495 173326 88 465 49
14 1373 133131 55 525 52
15 2187 258873 60 885 88
16 1491 180083 66 497 36
17 4041 324799 154 1436 108
18 1706 230964 53 612 43
19 2152 236785 119 865 75
20 1036 135473 41 385 32
21 1882 202925 61 567 44
22 1929 215147 58 639 85
23 2242 344297 75 963 86
24 1220 153935 33 398 56
25 1289 132943 40 410 50
26 2515 174724 92 966 135
27 2147 174415 100 801 63
28 2352 225548 112 892 81
29 1638 223632 73 513 5
shared_compendiums blogged_computations compendiums_reviewed\r
1 3 79 30
2 4 58 28
3 12 60 38
4 2 108 30
5 1 49 22
6 3 0 26
7 0 121 25
8 0 1 18
9 0 20 11
10 5 43 26
11 0 69 25
12 0 78 38
13 7 86 44
14 7 44 30
15 3 104 40
16 9 63 34
17 0 158 47
18 4 102 30
19 3 77 31
20 0 82 23
21 7 115 36
22 0 101 36
23 1 80 30
24 5 50 25
25 7 83 39
26 0 123 34
27 0 73 31
28 5 81 31
29 1418 210907 56
> k <- length(x[1,])
> df <- as.data.frame(x)
> (mylm <- lm(df))
Call:
lm(formula = df)
Coefficients:
(Intercept) time_in_rfc
-1.512e+02 6.296e-04
logins compendium_views_info
4.039e+00 1.554e+00
compendium_views_pr shared_compendiums
1.284e+00 -8.591e+00
blogged_computations `compendiums_reviewed\\r`
5.667e-02 1.394e+01
> (mysum <- summary(mylm))
Call:
lm(formula = df)
Residuals:
Min 1Q Median 3Q Max
-220.50 -126.06 5.40 93.93 331.11
Coefficients:
Estimate Std. Error t value Pr(>|t|)
(Intercept) -1.512e+02 1.471e+02 -1.028 0.3157
time_in_rfc 6.296e-04 8.548e-04 0.737 0.4695
logins 4.039e+00 1.779e+00 2.270 0.0339 *
compendium_views_info 1.554e+00 2.455e-01 6.331 2.81e-06 ***
compendium_views_pr 1.284e+00 1.715e+00 0.749 0.4622
shared_compendiums -8.591e+00 1.199e+01 -0.717 0.4815
blogged_computations 5.667e-02 7.996e-02 0.709 0.4863
`compendiums_reviewed\\r` 1.394e+01 5.535e+00 2.518 0.0200 *
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
Residual standard error: 160.7 on 21 degrees of freedom
Multiple R-squared: 0.9665, Adjusted R-squared: 0.9553
F-statistic: 86.51 on 7 and 21 DF, p-value: 4.769e-14
> 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,] 0.10731204 0.2146241 0.8926880
[2,] 0.13743650 0.2748730 0.8625635
[3,] 0.22640309 0.4528062 0.7735969
[4,] 0.12976600 0.2595320 0.8702340
[5,] 0.14344689 0.2868938 0.8565531
[6,] 0.08001516 0.1600303 0.9199848
[7,] 0.61885796 0.7622841 0.3811420
[8,] 0.44557815 0.8911563 0.5544219
> postscript(file="/var/wessaorg/rcomp/tmp/1ad9e1354890187.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$resid)
> grid()
> dev.off()
null device
1
> postscript(file="/var/wessaorg/rcomp/tmp/2k8fj1354890188.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> plot(mysum$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/3vkg31354890188.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> hist(mysum$resid, main='Residual Histogram', xlab='values of Residuals')
> grid()
> dev.off()
null device
1
> postscript(file="/var/wessaorg/rcomp/tmp/4qqhb1354890188.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> densityplot(~mysum$resid,col='black',main='Residual Density Plot', xlab='values of Residuals')
> dev.off()
null device
1
> postscript(file="/var/wessaorg/rcomp/tmp/5ecaz1354890188.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 = 29
Frequency = 1
1 2 3 4 5 6
93.9331840 -173.5287582 -10.9595276 -219.7082767 41.2945259 -126.3149564
7 8 9 10 11 12
-126.0553971 -48.2001147 180.6829615 36.4585815 133.0085302 -220.4968760
13 14 15 16 17 18
-161.9413950 -24.9683500 -93.2396080 43.4728407 331.1091601 101.7918515
19 20 21 22 23 24
-177.8859874 -28.3461127 273.2089055 100.7171693 -147.7258117 142.2069323
25 26 27 28 29
5.4049350 29.0004514 22.4600877 24.7447529 -0.1236979
> postscript(file="/var/wessaorg/rcomp/tmp/6goei1354890188.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 = 29
Frequency = 1
lag(myerror, k = 1) myerror
0 93.9331840 NA
1 -173.5287582 93.9331840
2 -10.9595276 -173.5287582
3 -219.7082767 -10.9595276
4 41.2945259 -219.7082767
5 -126.3149564 41.2945259
6 -126.0553971 -126.3149564
7 -48.2001147 -126.0553971
8 180.6829615 -48.2001147
9 36.4585815 180.6829615
10 133.0085302 36.4585815
11 -220.4968760 133.0085302
12 -161.9413950 -220.4968760
13 -24.9683500 -161.9413950
14 -93.2396080 -24.9683500
15 43.4728407 -93.2396080
16 331.1091601 43.4728407
17 101.7918515 331.1091601
18 -177.8859874 101.7918515
19 -28.3461127 -177.8859874
20 273.2089055 -28.3461127
21 100.7171693 273.2089055
22 -147.7258117 100.7171693
23 142.2069323 -147.7258117
24 5.4049350 142.2069323
25 29.0004514 5.4049350
26 22.4600877 29.0004514
27 24.7447529 22.4600877
28 -0.1236979 24.7447529
29 NA -0.1236979
> dum1 <- dum[2:length(myerror),]
> dum1
lag(myerror, k = 1) myerror
[1,] -173.5287582 93.933184
[2,] -10.9595276 -173.528758
[3,] -219.7082767 -10.959528
[4,] 41.2945259 -219.708277
[5,] -126.3149564 41.294526
[6,] -126.0553971 -126.314956
[7,] -48.2001147 -126.055397
[8,] 180.6829615 -48.200115
[9,] 36.4585815 180.682961
[10,] 133.0085302 36.458582
[11,] -220.4968760 133.008530
[12,] -161.9413950 -220.496876
[13,] -24.9683500 -161.941395
[14,] -93.2396080 -24.968350
[15,] 43.4728407 -93.239608
[16,] 331.1091601 43.472841
[17,] 101.7918515 331.109160
[18,] -177.8859874 101.791852
[19,] -28.3461127 -177.885987
[20,] 273.2089055 -28.346113
[21,] 100.7171693 273.208906
[22,] -147.7258117 100.717169
[23,] 142.2069323 -147.725812
[24,] 5.4049350 142.206932
[25,] 29.0004514 5.404935
[26,] 22.4600877 29.000451
[27,] 24.7447529 22.460088
[28,] -0.1236979 24.744753
> z <- as.data.frame(dum1)
> z
lag(myerror, k = 1) myerror
1 -173.5287582 93.933184
2 -10.9595276 -173.528758
3 -219.7082767 -10.959528
4 41.2945259 -219.708277
5 -126.3149564 41.294526
6 -126.0553971 -126.314956
7 -48.2001147 -126.055397
8 180.6829615 -48.200115
9 36.4585815 180.682961
10 133.0085302 36.458582
11 -220.4968760 133.008530
12 -161.9413950 -220.496876
13 -24.9683500 -161.941395
14 -93.2396080 -24.968350
15 43.4728407 -93.239608
16 331.1091601 43.472841
17 101.7918515 331.109160
18 -177.8859874 101.791852
19 -28.3461127 -177.885987
20 273.2089055 -28.346113
21 100.7171693 273.208906
22 -147.7258117 100.717169
23 142.2069323 -147.725812
24 5.4049350 142.206932
25 29.0004514 5.404935
26 22.4600877 29.000451
27 24.7447529 22.460088
28 -0.1236979 24.744753
> 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/7ydxa1354890188.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> acf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/wessaorg/rcomp/tmp/8kqp21354890188.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> pacf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Partial Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/wessaorg/rcomp/tmp/9vosa1354890188.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> opar <- par(mfrow = c(2,2), oma = c(0, 0, 1.1, 0))
> plot(mylm, las = 1, sub='Residual Diagnostics')
Warning messages:
1: In sqrt(crit * p * (1 - hh)/hh) : NaNs produced
2: In sqrt(crit * p * (1 - hh)/hh) : NaNs produced
> par(opar)
> dev.off()
null device
1
> if (n > n25) {
+ postscript(file="/var/wessaorg/rcomp/tmp/106j9r1354890188.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
+ plot(kp3:nmkm3,gqarr[,2], main='Goldfeld-Quandt test',ylab='2-sided p-value',xlab='breakpoint')
+ grid()
+ dev.off()
+ }
null device
1
>
> #Note: the /var/wessaorg/rcomp/createtable file can be downloaded at http://www.wessa.net/cretab
> load(file="/var/wessaorg/rcomp/createtable")
>
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a, 'Multiple Linear Regression - Estimated Regression Equation', 1, TRUE)
> a<-table.row.end(a)
> myeq <- colnames(x)[1]
> myeq <- paste(myeq, '[t] = ', sep='')
> for (i in 1:k){
+ if (mysum$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/11q4o11354890188.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/125abr1354890188.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/13q4je1354890188.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/14qzg61354890188.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/152ka71354890188.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/16msly1354890188.tab")
+ }
>
> try(system("convert tmp/1ad9e1354890187.ps tmp/1ad9e1354890187.png",intern=TRUE))
character(0)
> try(system("convert tmp/2k8fj1354890188.ps tmp/2k8fj1354890188.png",intern=TRUE))
character(0)
> try(system("convert tmp/3vkg31354890188.ps tmp/3vkg31354890188.png",intern=TRUE))
character(0)
> try(system("convert tmp/4qqhb1354890188.ps tmp/4qqhb1354890188.png",intern=TRUE))
character(0)
> try(system("convert tmp/5ecaz1354890188.ps tmp/5ecaz1354890188.png",intern=TRUE))
character(0)
> try(system("convert tmp/6goei1354890188.ps tmp/6goei1354890188.png",intern=TRUE))
character(0)
> try(system("convert tmp/7ydxa1354890188.ps tmp/7ydxa1354890188.png",intern=TRUE))
character(0)
> try(system("convert tmp/8kqp21354890188.ps tmp/8kqp21354890188.png",intern=TRUE))
character(0)
> try(system("convert tmp/9vosa1354890188.ps tmp/9vosa1354890188.png",intern=TRUE))
character(0)
> try(system("convert tmp/106j9r1354890188.ps tmp/106j9r1354890188.png",intern=TRUE))
character(0)
>
>
> proc.time()
user system elapsed
5.967 0.960 6.921