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(286602,0,283042,0,276687,0,277915,0,277128,0,277103,0,275037,0,270150,0,267140,0,264993,0,287259,0,291186,0,292300,0,288186,0,281477,0,282656,0,280190,0,280408,0,276836,0,275216,0,274352,0,271311,0,289802,0,290726,0,292300,0,278506,0,269826,0,265861,0,269034,0,264176,0,255198,0,253353,0,246057,0,235372,0,258556,0,260993,0,254663,0,250643,0,243422,0,247105,0,248541,0,245039,0,237080,0,237085,0,225554,0,226839,0,247934,0,248333,0,246969,1,245098,1,246263,1,255765,1,264319,1,268347,1,273046,1,273963,1,267430,1,271993,1,292710,1,295881,1),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 286602 0
2 283042 0
3 276687 0
4 277915 0
5 277128 0
6 277103 0
7 275037 0
8 270150 0
9 267140 0
10 264993 0
11 287259 0
12 291186 0
13 292300 0
14 288186 0
15 281477 0
16 282656 0
17 280190 0
18 280408 0
19 276836 0
20 275216 0
21 274352 0
22 271311 0
23 289802 0
24 290726 0
25 292300 0
26 278506 0
27 269826 0
28 265861 0
29 269034 0
30 264176 0
31 255198 0
32 253353 0
33 246057 0
34 235372 0
35 258556 0
36 260993 0
37 254663 0
38 250643 0
39 243422 0
40 247105 0
41 248541 0
42 245039 0
43 237080 0
44 237085 0
45 225554 0
46 226839 0
47 247934 0
48 248333 0
49 246969 1
50 245098 1
51 246263 1
52 255765 1
53 264319 1
54 268347 1
55 273046 1
56 273963 1
57 267430 1
58 271993 1
59 292710 1
60 295881 1
> k <- length(x[1,])
> df <- as.data.frame(x)
> (mylm <- lm(df))
Call:
lm(formula = df)
Coefficients:
(Intercept) X
266232.8 582.6
> (mysum <- summary(mylm))
Call:
lm(formula = df)
Residuals:
Min 1Q Median 3Q Max
-40679 -16115 3197 12694 29066
Coefficients:
Estimate Std. Error t value Pr(>|t|)
(Intercept) 266232.8 2617.0 101.7 <2e-16 ***
X 582.6 5851.7 0.1 0.921
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
Residual standard error: 18130 on 58 degrees of freedom
Multiple R-squared: 0.0001709, Adjusted R-squared: -0.01707
F-statistic: 0.009912 on 1 and 58 DF, p-value: 0.921
> 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,] 2.686368e-02 0.0537273596 0.9731363
[2,] 7.285634e-03 0.0145712688 0.9927144
[3,] 2.496691e-03 0.0049933816 0.9975033
[4,] 2.278275e-03 0.0045565497 0.9977217
[5,] 2.614476e-03 0.0052289524 0.9973855
[6,] 2.907297e-03 0.0058145933 0.9970927
[7,] 3.130538e-03 0.0062610770 0.9968695
[8,] 5.144040e-03 0.0102880796 0.9948560
[9,] 7.622691e-03 0.0152453821 0.9923773
[10,] 6.251462e-03 0.0125029243 0.9937485
[11,] 3.363273e-03 0.0067265454 0.9966367
[12,] 1.900090e-03 0.0038001804 0.9980999
[13,] 9.973108e-04 0.0019946215 0.9990027
[14,] 5.321048e-04 0.0010642097 0.9994679
[15,] 2.836311e-04 0.0005672622 0.9997164
[16,] 1.594414e-04 0.0003188828 0.9998406
[17,] 9.358295e-05 0.0001871659 0.9999064
[18,] 6.730704e-05 0.0001346141 0.9999327
[19,] 1.420157e-04 0.0002840314 0.9998580
[20,] 4.108982e-04 0.0008217965 0.9995891
[21,] 2.019166e-03 0.0040383319 0.9979808
[22,] 2.528665e-03 0.0050573301 0.9974713
[23,] 3.656277e-03 0.0073125537 0.9963437
[24,] 6.513632e-03 0.0130272649 0.9934864
[25,] 1.010522e-02 0.0202104356 0.9898948
[26,] 1.850294e-02 0.0370058702 0.9814971
[27,] 4.858648e-02 0.0971729507 0.9514135
[28,] 9.730850e-02 0.1946170076 0.9026915
[29,] 2.047669e-01 0.4095338749 0.7952331
[30,] 4.558064e-01 0.9116128525 0.5441936
[31,] 4.695232e-01 0.9390464820 0.5304768
[32,] 4.976249e-01 0.9952497196 0.5023751
[33,] 5.177703e-01 0.9644594131 0.4822297
[34,] 5.370184e-01 0.9259632951 0.4629816
[35,] 5.700745e-01 0.8598510006 0.4299255
[36,] 5.737776e-01 0.8524448330 0.4262224
[37,] 5.710196e-01 0.8579608071 0.4289804
[38,] 5.662299e-01 0.8675401533 0.4337701
[39,] 5.766034e-01 0.8467931908 0.4233966
[40,] 5.700889e-01 0.8598222753 0.4299111
[41,] 6.460031e-01 0.7079937194 0.3539969
[42,] 7.150046e-01 0.5699907899 0.2849954
[43,] 6.433403e-01 0.7133194539 0.3566597
[44,] 5.612680e-01 0.8774639073 0.4387320
[45,] 5.709062e-01 0.8581875838 0.4290938
[46,] 6.441132e-01 0.7117736681 0.3558868
[47,] 7.662048e-01 0.4675903159 0.2337952
[48,] 8.027744e-01 0.3944511769 0.1972256
[49,] 7.661497e-01 0.4677005815 0.2338503
[50,] 6.898631e-01 0.6202738948 0.3101369
[51,] 5.529317e-01 0.8941365517 0.4470683
> postscript(file="/var/www/html/rcomp/tmp/1tslq1258641859.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$resid)
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/2zzjx1258641859.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> plot(mysum$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/30vhb1258641859.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> hist(mysum$resid, main='Residual Histogram', xlab='values of Residuals')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/47b8i1258641859.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> densityplot(~mysum$resid,col='black',main='Residual Density Plot', xlab='values of Residuals')
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/5qapu1258641859.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
20369.2500 16809.2500 10454.2500 11682.2500 10895.2500 10870.2500
7 8 9 10 11 12
8804.2500 3917.2500 907.2500 -1239.7500 21026.2500 24953.2500
13 14 15 16 17 18
26067.2500 21953.2500 15244.2500 16423.2500 13957.2500 14175.2500
19 20 21 22 23 24
10603.2500 8983.2500 8119.2500 5078.2500 23569.2500 24493.2500
25 26 27 28 29 30
26067.2500 12273.2500 3593.2500 -371.7500 2801.2500 -2056.7500
31 32 33 34 35 36
-11034.7500 -12879.7500 -20175.7500 -30860.7500 -7676.7500 -5239.7500
37 38 39 40 41 42
-11569.7500 -15589.7500 -22810.7500 -19127.7500 -17691.7500 -21193.7500
43 44 45 46 47 48
-29152.7500 -29147.7500 -40678.7500 -39393.7500 -18298.7500 -17899.7500
49 50 51 52 53 54
-19846.3333 -21717.3333 -20552.3333 -11050.3333 -2496.3333 1531.6667
55 56 57 58 59 60
6230.6667 7147.6667 614.6667 5177.6667 25894.6667 29065.6667
> postscript(file="/var/www/html/rcomp/tmp/6453d1258641859.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 20369.2500 NA
1 16809.2500 20369.2500
2 10454.2500 16809.2500
3 11682.2500 10454.2500
4 10895.2500 11682.2500
5 10870.2500 10895.2500
6 8804.2500 10870.2500
7 3917.2500 8804.2500
8 907.2500 3917.2500
9 -1239.7500 907.2500
10 21026.2500 -1239.7500
11 24953.2500 21026.2500
12 26067.2500 24953.2500
13 21953.2500 26067.2500
14 15244.2500 21953.2500
15 16423.2500 15244.2500
16 13957.2500 16423.2500
17 14175.2500 13957.2500
18 10603.2500 14175.2500
19 8983.2500 10603.2500
20 8119.2500 8983.2500
21 5078.2500 8119.2500
22 23569.2500 5078.2500
23 24493.2500 23569.2500
24 26067.2500 24493.2500
25 12273.2500 26067.2500
26 3593.2500 12273.2500
27 -371.7500 3593.2500
28 2801.2500 -371.7500
29 -2056.7500 2801.2500
30 -11034.7500 -2056.7500
31 -12879.7500 -11034.7500
32 -20175.7500 -12879.7500
33 -30860.7500 -20175.7500
34 -7676.7500 -30860.7500
35 -5239.7500 -7676.7500
36 -11569.7500 -5239.7500
37 -15589.7500 -11569.7500
38 -22810.7500 -15589.7500
39 -19127.7500 -22810.7500
40 -17691.7500 -19127.7500
41 -21193.7500 -17691.7500
42 -29152.7500 -21193.7500
43 -29147.7500 -29152.7500
44 -40678.7500 -29147.7500
45 -39393.7500 -40678.7500
46 -18298.7500 -39393.7500
47 -17899.7500 -18298.7500
48 -19846.3333 -17899.7500
49 -21717.3333 -19846.3333
50 -20552.3333 -21717.3333
51 -11050.3333 -20552.3333
52 -2496.3333 -11050.3333
53 1531.6667 -2496.3333
54 6230.6667 1531.6667
55 7147.6667 6230.6667
56 614.6667 7147.6667
57 5177.6667 614.6667
58 25894.6667 5177.6667
59 29065.6667 25894.6667
60 NA 29065.6667
> dum1 <- dum[2:length(myerror),]
> dum1
lag(myerror, k = 1) myerror
[1,] 16809.2500 20369.2500
[2,] 10454.2500 16809.2500
[3,] 11682.2500 10454.2500
[4,] 10895.2500 11682.2500
[5,] 10870.2500 10895.2500
[6,] 8804.2500 10870.2500
[7,] 3917.2500 8804.2500
[8,] 907.2500 3917.2500
[9,] -1239.7500 907.2500
[10,] 21026.2500 -1239.7500
[11,] 24953.2500 21026.2500
[12,] 26067.2500 24953.2500
[13,] 21953.2500 26067.2500
[14,] 15244.2500 21953.2500
[15,] 16423.2500 15244.2500
[16,] 13957.2500 16423.2500
[17,] 14175.2500 13957.2500
[18,] 10603.2500 14175.2500
[19,] 8983.2500 10603.2500
[20,] 8119.2500 8983.2500
[21,] 5078.2500 8119.2500
[22,] 23569.2500 5078.2500
[23,] 24493.2500 23569.2500
[24,] 26067.2500 24493.2500
[25,] 12273.2500 26067.2500
[26,] 3593.2500 12273.2500
[27,] -371.7500 3593.2500
[28,] 2801.2500 -371.7500
[29,] -2056.7500 2801.2500
[30,] -11034.7500 -2056.7500
[31,] -12879.7500 -11034.7500
[32,] -20175.7500 -12879.7500
[33,] -30860.7500 -20175.7500
[34,] -7676.7500 -30860.7500
[35,] -5239.7500 -7676.7500
[36,] -11569.7500 -5239.7500
[37,] -15589.7500 -11569.7500
[38,] -22810.7500 -15589.7500
[39,] -19127.7500 -22810.7500
[40,] -17691.7500 -19127.7500
[41,] -21193.7500 -17691.7500
[42,] -29152.7500 -21193.7500
[43,] -29147.7500 -29152.7500
[44,] -40678.7500 -29147.7500
[45,] -39393.7500 -40678.7500
[46,] -18298.7500 -39393.7500
[47,] -17899.7500 -18298.7500
[48,] -19846.3333 -17899.7500
[49,] -21717.3333 -19846.3333
[50,] -20552.3333 -21717.3333
[51,] -11050.3333 -20552.3333
[52,] -2496.3333 -11050.3333
[53,] 1531.6667 -2496.3333
[54,] 6230.6667 1531.6667
[55,] 7147.6667 6230.6667
[56,] 614.6667 7147.6667
[57,] 5177.6667 614.6667
[58,] 25894.6667 5177.6667
[59,] 29065.6667 25894.6667
> z <- as.data.frame(dum1)
> z
lag(myerror, k = 1) myerror
1 16809.2500 20369.2500
2 10454.2500 16809.2500
3 11682.2500 10454.2500
4 10895.2500 11682.2500
5 10870.2500 10895.2500
6 8804.2500 10870.2500
7 3917.2500 8804.2500
8 907.2500 3917.2500
9 -1239.7500 907.2500
10 21026.2500 -1239.7500
11 24953.2500 21026.2500
12 26067.2500 24953.2500
13 21953.2500 26067.2500
14 15244.2500 21953.2500
15 16423.2500 15244.2500
16 13957.2500 16423.2500
17 14175.2500 13957.2500
18 10603.2500 14175.2500
19 8983.2500 10603.2500
20 8119.2500 8983.2500
21 5078.2500 8119.2500
22 23569.2500 5078.2500
23 24493.2500 23569.2500
24 26067.2500 24493.2500
25 12273.2500 26067.2500
26 3593.2500 12273.2500
27 -371.7500 3593.2500
28 2801.2500 -371.7500
29 -2056.7500 2801.2500
30 -11034.7500 -2056.7500
31 -12879.7500 -11034.7500
32 -20175.7500 -12879.7500
33 -30860.7500 -20175.7500
34 -7676.7500 -30860.7500
35 -5239.7500 -7676.7500
36 -11569.7500 -5239.7500
37 -15589.7500 -11569.7500
38 -22810.7500 -15589.7500
39 -19127.7500 -22810.7500
40 -17691.7500 -19127.7500
41 -21193.7500 -17691.7500
42 -29152.7500 -21193.7500
43 -29147.7500 -29152.7500
44 -40678.7500 -29147.7500
45 -39393.7500 -40678.7500
46 -18298.7500 -39393.7500
47 -17899.7500 -18298.7500
48 -19846.3333 -17899.7500
49 -21717.3333 -19846.3333
50 -20552.3333 -21717.3333
51 -11050.3333 -20552.3333
52 -2496.3333 -11050.3333
53 1531.6667 -2496.3333
54 6230.6667 1531.6667
55 7147.6667 6230.6667
56 614.6667 7147.6667
57 5177.6667 614.6667
58 25894.6667 5177.6667
59 29065.6667 25894.6667
> 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/7ne431258641860.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> acf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/8tg2c1258641860.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> pacf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Partial Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/9eckc1258641860.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> opar <- par(mfrow = c(2,2), oma = c(0, 0, 1.1, 0))
> plot(mylm, las = 1, sub='Residual Diagnostics')
> par(opar)
> dev.off()
null device
1
> if (n > n25) {
+ postscript(file="/var/www/html/rcomp/tmp/102sfv1258641860.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
+ plot(kp3:nmkm3,gqarr[,2], main='Goldfeld-Quandt test',ylab='2-sided p-value',xlab='breakpoint')
+ grid()
+ dev.off()
+ }
null device
1
>
> #Note: the /var/www/html/rcomp/createtable file can be downloaded at http://www.wessa.net/cretab
> load(file="/var/www/html/rcomp/createtable")
>
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a, 'Multiple Linear Regression - Estimated Regression Equation', 1, TRUE)
> a<-table.row.end(a)
> myeq <- colnames(x)[1]
> myeq <- paste(myeq, '[t] = ', sep='')
> for (i in 1:k){
+ if (mysum$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/11q9511258641860.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/12alo01258641860.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/13hcjs1258641860.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/149hp41258641860.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/15u13e1258641860.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/16iymp1258641860.tab")
+ }
>
> system("convert tmp/1tslq1258641859.ps tmp/1tslq1258641859.png")
> system("convert tmp/2zzjx1258641859.ps tmp/2zzjx1258641859.png")
> system("convert tmp/30vhb1258641859.ps tmp/30vhb1258641859.png")
> system("convert tmp/47b8i1258641859.ps tmp/47b8i1258641859.png")
> system("convert tmp/5qapu1258641859.ps tmp/5qapu1258641859.png")
> system("convert tmp/6453d1258641859.ps tmp/6453d1258641859.png")
> system("convert tmp/7ne431258641860.ps tmp/7ne431258641860.png")
> system("convert tmp/8tg2c1258641860.ps tmp/8tg2c1258641860.png")
> system("convert tmp/9eckc1258641860.ps tmp/9eckc1258641860.png")
> system("convert tmp/102sfv1258641860.ps tmp/102sfv1258641860.png")
>
>
> proc.time()
user system elapsed
2.455 1.593 4.193