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(2490,0,3266,0,3475,0,3127,0,2955,0,3870,0,2852,0,3142,0,3029,0,3180,0,2560,0,2733,0,2452,0,2553,0,2777,0,2520,0,2318,0,2873,0,2311,0,2395,0,2099,0,2268,0,2316,0,2181,0,2175,0,2627,0,2578,0,3090,0,2634,0,3225,0,2938,0,3174,0,3350,0,2588,0,2061,0,2691,0,2061,0,2918,0,2223,0,2651,0,2379,0,3146,0,2883,0,2768,0,3258,0,2839,0,2470,0,5072,1,1463,1,1600,1,2203,1,2013,1,2169,1,2640,1,2411,1,2528,1,2292,1,1988,1,1774,1,2279,1),dim=c(2,60),dimnames=list(c('Y','X'),1:60))
> y <- array(NA,dim=c(2,60),dimnames=list(c('Y','X'),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 = '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
Y X
1 2490 0
2 3266 0
3 3475 0
4 3127 0
5 2955 0
6 3870 0
7 2852 0
8 3142 0
9 3029 0
10 3180 0
11 2560 0
12 2733 0
13 2452 0
14 2553 0
15 2777 0
16 2520 0
17 2318 0
18 2873 0
19 2311 0
20 2395 0
21 2099 0
22 2268 0
23 2316 0
24 2181 0
25 2175 0
26 2627 0
27 2578 0
28 3090 0
29 2634 0
30 3225 0
31 2938 0
32 3174 0
33 3350 0
34 2588 0
35 2061 0
36 2691 0
37 2061 0
38 2918 0
39 2223 0
40 2651 0
41 2379 0
42 3146 0
43 2883 0
44 2768 0
45 3258 0
46 2839 0
47 2470 0
48 5072 1
49 1463 1
50 1600 1
51 2203 1
52 2013 1
53 2169 1
54 2640 1
55 2411 1
56 2528 1
57 2292 1
58 1988 1
59 1774 1
60 2279 1
> k <- length(x[1,])
> df <- as.data.frame(x)
> (mylm <- lm(df))
Call:
lm(formula = df)
Coefficients:
(Intercept) X
2733.4 -392.5
> (mysum <- summary(mylm))
Call:
lm(formula = df)
Residuals:
Min 1Q Median 3Q Max
-877.92 -342.02 -72.15 240.12 2731.08
Coefficients:
Estimate Std. Error t value Pr(>|t|)
(Intercept) 2733.38 79.87 34.221 <2e-16 ***
X -392.46 171.60 -2.287 0.0259 *
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
Residual standard error: 547.6 on 58 degrees of freedom
Multiple R-squared: 0.08273, Adjusted R-squared: 0.06691
F-statistic: 5.231 on 1 and 58 DF, p-value: 0.02586
> 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,] 3.848190e-01 0.7696379101 0.61518104
[2,] 5.647577e-01 0.8704845854 0.43524229
[3,] 4.646244e-01 0.9292487736 0.53537561
[4,] 3.398183e-01 0.6796365528 0.66018172
[5,] 2.391189e-01 0.4782377376 0.76088113
[6,] 1.624536e-01 0.3249072077 0.83754640
[7,] 1.800555e-01 0.3601109512 0.81994452
[8,] 1.428576e-01 0.2857151124 0.85714244
[9,] 1.605192e-01 0.3210384366 0.83948078
[10,] 1.424496e-01 0.2848991276 0.85755044
[11,] 1.002864e-01 0.2005727483 0.89971363
[12,] 8.699071e-02 0.1739814221 0.91300929
[13,] 9.828784e-02 0.1965756825 0.90171216
[14,] 6.555059e-02 0.1311011823 0.93444941
[15,] 6.998920e-02 0.1399783971 0.93001080
[16,] 6.209758e-02 0.1241951670 0.93790242
[17,] 8.666392e-02 0.1733278496 0.91333608
[18,] 8.418435e-02 0.1683687033 0.91581565
[19,] 7.494045e-02 0.1498808942 0.92505955
[20,] 7.841530e-02 0.1568305921 0.92158470
[21,] 8.085400e-02 0.1617079949 0.91914600
[22,] 5.578292e-02 0.1115658306 0.94421708
[23,] 3.807954e-02 0.0761590897 0.96192046
[24,] 3.014446e-02 0.0602889132 0.96985554
[25,] 1.932763e-02 0.0386552533 0.98067237
[26,] 1.804832e-02 0.0360966395 0.98195168
[27,] 1.186102e-02 0.0237220336 0.98813898
[28,] 1.006650e-02 0.0201329914 0.98993350
[29,] 1.192409e-02 0.0238481744 0.98807591
[30,] 7.397165e-03 0.0147943299 0.99260284
[31,] 9.576007e-03 0.0191520143 0.99042399
[32,] 5.630144e-03 0.0112602870 0.99436986
[33,] 7.256772e-03 0.0145135439 0.99274323
[34,] 4.421429e-03 0.0088428579 0.99557857
[35,] 4.077732e-03 0.0081554649 0.99592227
[36,] 2.297817e-03 0.0045956331 0.99770218
[37,] 1.678883e-03 0.0033577655 0.99832112
[38,] 1.153795e-03 0.0023075896 0.99884621
[39,] 5.982869e-04 0.0011965737 0.99940171
[40,] 2.894888e-04 0.0005789775 0.99971051
[41,] 2.416382e-04 0.0004832764 0.99975836
[42,] 1.176625e-04 0.0002353250 0.99988234
[43,] 5.498314e-05 0.0001099663 0.99994502
[44,] 5.945740e-01 0.8108520400 0.40542602
[45,] 9.510173e-01 0.0979653852 0.04898269
[46,] 9.841956e-01 0.0316087419 0.01580437
[47,] 9.659437e-01 0.0681125604 0.03405628
[48,] 9.442669e-01 0.1114661889 0.05573309
[49,] 8.899782e-01 0.2200435122 0.11002176
[50,] 8.744073e-01 0.2511854041 0.12559270
[51,] 7.804593e-01 0.4390813713 0.21954069
> postscript(file="/var/www/html/rcomp/tmp/1gveb1229781053.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$resid)
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/296p31229781053.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> plot(mysum$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/3w56y1229781053.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> hist(mysum$resid, main='Residual Histogram', xlab='values of Residuals')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/41cmn1229781053.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> densityplot(~mysum$resid,col='black',main='Residual Density Plot', xlab='values of Residuals')
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/5fto11229781053.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
-243.3829787 532.6170213 741.6170213 393.6170213 221.6170213 1136.6170213
7 8 9 10 11 12
118.6170213 408.6170213 295.6170213 446.6170213 -173.3829787 -0.3829787
13 14 15 16 17 18
-281.3829787 -180.3829787 43.6170213 -213.3829787 -415.3829787 139.6170213
19 20 21 22 23 24
-422.3829787 -338.3829787 -634.3829787 -465.3829787 -417.3829787 -552.3829787
25 26 27 28 29 30
-558.3829787 -106.3829787 -155.3829787 356.6170213 -99.3829787 491.6170213
31 32 33 34 35 36
204.6170213 440.6170213 616.6170213 -145.3829787 -672.3829787 -42.3829787
37 38 39 40 41 42
-672.3829787 184.6170213 -510.3829787 -82.3829787 -354.3829787 412.6170213
43 44 45 46 47 48
149.6170213 34.6170213 524.6170213 105.6170213 -263.3829787 2731.0769231
49 50 51 52 53 54
-877.9230769 -740.9230769 -137.9230769 -327.9230769 -171.9230769 299.0769231
55 56 57 58 59 60
70.0769231 187.0769231 -48.9230769 -352.9230769 -566.9230769 -61.9230769
> postscript(file="/var/www/html/rcomp/tmp/6kzrc1229781053.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 -243.3829787 NA
1 532.6170213 -243.3829787
2 741.6170213 532.6170213
3 393.6170213 741.6170213
4 221.6170213 393.6170213
5 1136.6170213 221.6170213
6 118.6170213 1136.6170213
7 408.6170213 118.6170213
8 295.6170213 408.6170213
9 446.6170213 295.6170213
10 -173.3829787 446.6170213
11 -0.3829787 -173.3829787
12 -281.3829787 -0.3829787
13 -180.3829787 -281.3829787
14 43.6170213 -180.3829787
15 -213.3829787 43.6170213
16 -415.3829787 -213.3829787
17 139.6170213 -415.3829787
18 -422.3829787 139.6170213
19 -338.3829787 -422.3829787
20 -634.3829787 -338.3829787
21 -465.3829787 -634.3829787
22 -417.3829787 -465.3829787
23 -552.3829787 -417.3829787
24 -558.3829787 -552.3829787
25 -106.3829787 -558.3829787
26 -155.3829787 -106.3829787
27 356.6170213 -155.3829787
28 -99.3829787 356.6170213
29 491.6170213 -99.3829787
30 204.6170213 491.6170213
31 440.6170213 204.6170213
32 616.6170213 440.6170213
33 -145.3829787 616.6170213
34 -672.3829787 -145.3829787
35 -42.3829787 -672.3829787
36 -672.3829787 -42.3829787
37 184.6170213 -672.3829787
38 -510.3829787 184.6170213
39 -82.3829787 -510.3829787
40 -354.3829787 -82.3829787
41 412.6170213 -354.3829787
42 149.6170213 412.6170213
43 34.6170213 149.6170213
44 524.6170213 34.6170213
45 105.6170213 524.6170213
46 -263.3829787 105.6170213
47 2731.0769231 -263.3829787
48 -877.9230769 2731.0769231
49 -740.9230769 -877.9230769
50 -137.9230769 -740.9230769
51 -327.9230769 -137.9230769
52 -171.9230769 -327.9230769
53 299.0769231 -171.9230769
54 70.0769231 299.0769231
55 187.0769231 70.0769231
56 -48.9230769 187.0769231
57 -352.9230769 -48.9230769
58 -566.9230769 -352.9230769
59 -61.9230769 -566.9230769
60 NA -61.9230769
> dum1 <- dum[2:length(myerror),]
> dum1
lag(myerror, k = 1) myerror
[1,] 532.6170213 -243.3829787
[2,] 741.6170213 532.6170213
[3,] 393.6170213 741.6170213
[4,] 221.6170213 393.6170213
[5,] 1136.6170213 221.6170213
[6,] 118.6170213 1136.6170213
[7,] 408.6170213 118.6170213
[8,] 295.6170213 408.6170213
[9,] 446.6170213 295.6170213
[10,] -173.3829787 446.6170213
[11,] -0.3829787 -173.3829787
[12,] -281.3829787 -0.3829787
[13,] -180.3829787 -281.3829787
[14,] 43.6170213 -180.3829787
[15,] -213.3829787 43.6170213
[16,] -415.3829787 -213.3829787
[17,] 139.6170213 -415.3829787
[18,] -422.3829787 139.6170213
[19,] -338.3829787 -422.3829787
[20,] -634.3829787 -338.3829787
[21,] -465.3829787 -634.3829787
[22,] -417.3829787 -465.3829787
[23,] -552.3829787 -417.3829787
[24,] -558.3829787 -552.3829787
[25,] -106.3829787 -558.3829787
[26,] -155.3829787 -106.3829787
[27,] 356.6170213 -155.3829787
[28,] -99.3829787 356.6170213
[29,] 491.6170213 -99.3829787
[30,] 204.6170213 491.6170213
[31,] 440.6170213 204.6170213
[32,] 616.6170213 440.6170213
[33,] -145.3829787 616.6170213
[34,] -672.3829787 -145.3829787
[35,] -42.3829787 -672.3829787
[36,] -672.3829787 -42.3829787
[37,] 184.6170213 -672.3829787
[38,] -510.3829787 184.6170213
[39,] -82.3829787 -510.3829787
[40,] -354.3829787 -82.3829787
[41,] 412.6170213 -354.3829787
[42,] 149.6170213 412.6170213
[43,] 34.6170213 149.6170213
[44,] 524.6170213 34.6170213
[45,] 105.6170213 524.6170213
[46,] -263.3829787 105.6170213
[47,] 2731.0769231 -263.3829787
[48,] -877.9230769 2731.0769231
[49,] -740.9230769 -877.9230769
[50,] -137.9230769 -740.9230769
[51,] -327.9230769 -137.9230769
[52,] -171.9230769 -327.9230769
[53,] 299.0769231 -171.9230769
[54,] 70.0769231 299.0769231
[55,] 187.0769231 70.0769231
[56,] -48.9230769 187.0769231
[57,] -352.9230769 -48.9230769
[58,] -566.9230769 -352.9230769
[59,] -61.9230769 -566.9230769
> z <- as.data.frame(dum1)
> z
lag(myerror, k = 1) myerror
1 532.6170213 -243.3829787
2 741.6170213 532.6170213
3 393.6170213 741.6170213
4 221.6170213 393.6170213
5 1136.6170213 221.6170213
6 118.6170213 1136.6170213
7 408.6170213 118.6170213
8 295.6170213 408.6170213
9 446.6170213 295.6170213
10 -173.3829787 446.6170213
11 -0.3829787 -173.3829787
12 -281.3829787 -0.3829787
13 -180.3829787 -281.3829787
14 43.6170213 -180.3829787
15 -213.3829787 43.6170213
16 -415.3829787 -213.3829787
17 139.6170213 -415.3829787
18 -422.3829787 139.6170213
19 -338.3829787 -422.3829787
20 -634.3829787 -338.3829787
21 -465.3829787 -634.3829787
22 -417.3829787 -465.3829787
23 -552.3829787 -417.3829787
24 -558.3829787 -552.3829787
25 -106.3829787 -558.3829787
26 -155.3829787 -106.3829787
27 356.6170213 -155.3829787
28 -99.3829787 356.6170213
29 491.6170213 -99.3829787
30 204.6170213 491.6170213
31 440.6170213 204.6170213
32 616.6170213 440.6170213
33 -145.3829787 616.6170213
34 -672.3829787 -145.3829787
35 -42.3829787 -672.3829787
36 -672.3829787 -42.3829787
37 184.6170213 -672.3829787
38 -510.3829787 184.6170213
39 -82.3829787 -510.3829787
40 -354.3829787 -82.3829787
41 412.6170213 -354.3829787
42 149.6170213 412.6170213
43 34.6170213 149.6170213
44 524.6170213 34.6170213
45 105.6170213 524.6170213
46 -263.3829787 105.6170213
47 2731.0769231 -263.3829787
48 -877.9230769 2731.0769231
49 -740.9230769 -877.9230769
50 -137.9230769 -740.9230769
51 -327.9230769 -137.9230769
52 -171.9230769 -327.9230769
53 299.0769231 -171.9230769
54 70.0769231 299.0769231
55 187.0769231 70.0769231
56 -48.9230769 187.0769231
57 -352.9230769 -48.9230769
58 -566.9230769 -352.9230769
59 -61.9230769 -566.9230769
> 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/7fime1229781053.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> acf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/8vrht1229781053.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> pacf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Partial Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/94v5l1229781053.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> opar <- par(mfrow = c(2,2), oma = c(0, 0, 1.1, 0))
> plot(mylm, las = 1, sub='Residual Diagnostics')
> par(opar)
> dev.off()
null device
1
> if (n > n25) {
+ postscript(file="/var/www/html/rcomp/tmp/10m1dn1229781053.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
+ plot(kp3:nmkm3,gqarr[,2], main='Goldfeld-Quandt test',ylab='2-sided p-value',xlab='breakpoint')
+ grid()
+ dev.off()
+ }
null device
1
>
> #Note: the /var/www/html/rcomp/createtable file can be downloaded at http://www.wessa.net/cretab
> load(file="/var/www/html/rcomp/createtable")
>
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a, 'Multiple Linear Regression - Estimated Regression Equation', 1, TRUE)
> a<-table.row.end(a)
> myeq <- colnames(x)[1]
> myeq <- paste(myeq, '[t] = ', sep='')
> for (i in 1:k){
+ if (mysum$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/11hkgn1229781053.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/12lj431229781053.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/13x4l21229781054.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/1472bv1229781054.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/15xfyg1229781054.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/16243m1229781054.tab")
+ }
>
> system("convert tmp/1gveb1229781053.ps tmp/1gveb1229781053.png")
> system("convert tmp/296p31229781053.ps tmp/296p31229781053.png")
> system("convert tmp/3w56y1229781053.ps tmp/3w56y1229781053.png")
> system("convert tmp/41cmn1229781053.ps tmp/41cmn1229781053.png")
> system("convert tmp/5fto11229781053.ps tmp/5fto11229781053.png")
> system("convert tmp/6kzrc1229781053.ps tmp/6kzrc1229781053.png")
> system("convert tmp/7fime1229781053.ps tmp/7fime1229781053.png")
> system("convert tmp/8vrht1229781053.ps tmp/8vrht1229781053.png")
> system("convert tmp/94v5l1229781053.ps tmp/94v5l1229781053.png")
> system("convert tmp/10m1dn1229781053.ps tmp/10m1dn1229781053.png")
>
>
> proc.time()
user system elapsed
2.499 1.585 3.650