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(921365,0,987921,0,1132614,0,1332224,0,1418133,0,1411549,0,1695920,0,1636173,0,1539653,0,1395314,0,1127575,0,1036076,0,989236,0,1008380,0,1207763,0,1368839,0,1469798,0,1498721,0,1761769,0,1653214,0,1599104,0,1421179,0,1163995,0,1037735,0,1015407,0,1039210,0,1258049,0,1469445,0,1552346,0,1549144,0,1785895,0,1662335,0,1629440,0,1467430,0,1202209,0,1076982,0,1039367,1,1063449,1,1335135,1,1491602,1,1591972,1,1641248,1,1898849,1,1798580,1,1762444,1,1622044,1,1368955,1,1262973,1,1195650,1,1269530,1,1479279,1,1607819,1,1712466,1,1721766,1,1949843,1,1821326,1,1757802,1,1590367,1,1260647,1,1149235,1),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 921365 0
2 987921 0
3 1132614 0
4 1332224 0
5 1418133 0
6 1411549 0
7 1695920 0
8 1636173 0
9 1539653 0
10 1395314 0
11 1127575 0
12 1036076 0
13 989236 0
14 1008380 0
15 1207763 0
16 1368839 0
17 1469798 0
18 1498721 0
19 1761769 0
20 1653214 0
21 1599104 0
22 1421179 0
23 1163995 0
24 1037735 0
25 1015407 0
26 1039210 0
27 1258049 0
28 1469445 0
29 1552346 0
30 1549144 0
31 1785895 0
32 1662335 0
33 1629440 0
34 1467430 0
35 1202209 0
36 1076982 0
37 1039367 1
38 1063449 1
39 1335135 1
40 1491602 1
41 1591972 1
42 1641248 1
43 1898849 1
44 1798580 1
45 1762444 1
46 1622044 1
47 1368955 1
48 1262973 1
49 1195650 1
50 1269530 1
51 1479279 1
52 1607819 1
53 1712466 1
54 1721766 1
55 1949843 1
56 1821326 1
57 1757802 1
58 1590367 1
59 1260647 1
60 1149235 1
> k <- length(x[1,])
> df <- as.data.frame(x)
> (mylm <- lm(df))
Call:
lm(formula = df)
Coefficients:
(Intercept) X
1347837 168511
> (mysum <- summary(mylm))
Call:
lm(formula = df)
Residuals:
Min 1Q Median 3Q Max
-476981 -248457 67004 204736 438058
Coefficients:
Estimate Std. Error t value Pr(>|t|)
(Intercept) 1347837 43663 30.869 <2e-16 ***
X 168511 69037 2.441 0.0177 *
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
Residual standard error: 262000 on 58 degrees of freedom
Multiple R-squared: 0.09315, Adjusted R-squared: 0.07752
F-statistic: 5.958 on 1 and 58 DF, p-value: 0.01773
> 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,] 0.5544579 0.8910842 0.4455421
[2,] 0.5050541 0.9898917 0.4949459
[3,] 0.7253954 0.5492093 0.2746046
[4,] 0.7584437 0.4831126 0.2415563
[5,] 0.7111278 0.5777445 0.2888722
[6,] 0.6113400 0.7773201 0.3886600
[7,] 0.5684146 0.8631707 0.4315854
[8,] 0.5794950 0.8410101 0.4205050
[9,] 0.6162995 0.7674009 0.3837005
[10,] 0.6320885 0.7358230 0.3679115
[11,] 0.5570555 0.8858891 0.4429445
[12,] 0.4795152 0.9590303 0.5204848
[13,] 0.4316521 0.8633042 0.5683479
[14,] 0.3930606 0.7861213 0.6069394
[15,] 0.5354838 0.9290324 0.4645162
[16,] 0.5648932 0.8702135 0.4351068
[17,] 0.5552466 0.8895067 0.4447534
[18,] 0.4809881 0.9619761 0.5190119
[19,] 0.4386991 0.8773983 0.5613009
[20,] 0.4664031 0.9328061 0.5335969
[21,] 0.5163701 0.9672598 0.4836299
[22,] 0.5618451 0.8763097 0.4381549
[23,] 0.5098749 0.9802502 0.4901251
[24,] 0.4501988 0.9003976 0.5498012
[25,] 0.4113085 0.8226169 0.5886915
[26,] 0.3699002 0.7398003 0.6300998
[27,] 0.4664996 0.9329991 0.5335004
[28,] 0.4857995 0.9715990 0.5142005
[29,] 0.5086473 0.9827053 0.4913527
[30,] 0.4804773 0.9609545 0.5195227
[31,] 0.4196382 0.8392765 0.5803618
[32,] 0.3774230 0.7548460 0.6225770
[33,] 0.4537454 0.9074908 0.5462546
[34,] 0.5537722 0.8924555 0.4462278
[35,] 0.5400300 0.9199400 0.4599700
[36,] 0.5001808 0.9996385 0.4998192
[37,] 0.4577655 0.9155310 0.5422345
[38,] 0.4134207 0.8268414 0.5865793
[39,] 0.5115089 0.9769822 0.4884911
[40,] 0.5194255 0.9611490 0.4805745
[41,] 0.5029224 0.9941552 0.4970776
[42,] 0.4249943 0.8499887 0.5750057
[43,] 0.3598596 0.7197192 0.6401404
[44,] 0.3506897 0.7013794 0.6493103
[45,] 0.4106521 0.8213043 0.5893479
[46,] 0.4374674 0.8749347 0.5625326
[47,] 0.3502435 0.7004871 0.6497565
[48,] 0.2507101 0.5014202 0.7492899
[49,] 0.1764416 0.3528833 0.8235584
[50,] 0.1159552 0.2319104 0.8840448
[51,] 0.1699379 0.3398759 0.8300621
> postscript(file="/var/www/html/rcomp/tmp/141ff1261310205.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$resid)
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/2pvt11261310205.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> plot(mysum$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/3o2781261310205.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> hist(mysum$resid, main='Residual Histogram', xlab='values of Residuals')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/4zjgc1261310205.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> densityplot(~mysum$resid,col='black',main='Residual Density Plot', xlab='values of Residuals')
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/5g1im1261310205.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> qqnorm(mysum$resid, main='Residual Normal Q-Q Plot')
> qqline(mysum$resid)
> grid()
> dev.off()
null device
1
> (myerror <- as.ts(mysum$resid))
Time Series:
Start = 1
End = 60
Frequency = 1
1 2 3 4 5 6 7
-426472.28 -359916.28 -215223.28 -15613.28 70295.72 63711.72 348082.72
8 9 10 11 12 13 14
288335.72 191815.72 47476.72 -220262.28 -311761.28 -358601.28 -339457.28
15 16 17 18 19 20 21
-140074.28 21001.72 121960.72 150883.72 413931.72 305376.72 251266.72
22 23 24 25 26 27 28
73341.72 -183842.28 -310102.28 -332430.28 -308627.28 -89788.28 121607.72
29 30 31 32 33 34 35
204508.72 201306.72 438057.72 314497.72 281602.72 119592.72 -145628.28
36 37 38 39 40 41 42
-270855.28 -476980.83 -452898.83 -181212.83 -24745.83 75624.17 124900.17
43 44 45 46 47 48 49
382501.17 282232.17 246096.17 105696.17 -147392.83 -253374.83 -320697.83
50 51 52 53 54 55 56
-246817.83 -37068.83 91471.17 196118.17 205418.17 433495.17 304978.17
57 58 59 60
241454.17 74019.17 -255700.83 -367112.83
> postscript(file="/var/www/html/rcomp/tmp/60l5n1261310205.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 -426472.28 NA
1 -359916.28 -426472.28
2 -215223.28 -359916.28
3 -15613.28 -215223.28
4 70295.72 -15613.28
5 63711.72 70295.72
6 348082.72 63711.72
7 288335.72 348082.72
8 191815.72 288335.72
9 47476.72 191815.72
10 -220262.28 47476.72
11 -311761.28 -220262.28
12 -358601.28 -311761.28
13 -339457.28 -358601.28
14 -140074.28 -339457.28
15 21001.72 -140074.28
16 121960.72 21001.72
17 150883.72 121960.72
18 413931.72 150883.72
19 305376.72 413931.72
20 251266.72 305376.72
21 73341.72 251266.72
22 -183842.28 73341.72
23 -310102.28 -183842.28
24 -332430.28 -310102.28
25 -308627.28 -332430.28
26 -89788.28 -308627.28
27 121607.72 -89788.28
28 204508.72 121607.72
29 201306.72 204508.72
30 438057.72 201306.72
31 314497.72 438057.72
32 281602.72 314497.72
33 119592.72 281602.72
34 -145628.28 119592.72
35 -270855.28 -145628.28
36 -476980.83 -270855.28
37 -452898.83 -476980.83
38 -181212.83 -452898.83
39 -24745.83 -181212.83
40 75624.17 -24745.83
41 124900.17 75624.17
42 382501.17 124900.17
43 282232.17 382501.17
44 246096.17 282232.17
45 105696.17 246096.17
46 -147392.83 105696.17
47 -253374.83 -147392.83
48 -320697.83 -253374.83
49 -246817.83 -320697.83
50 -37068.83 -246817.83
51 91471.17 -37068.83
52 196118.17 91471.17
53 205418.17 196118.17
54 433495.17 205418.17
55 304978.17 433495.17
56 241454.17 304978.17
57 74019.17 241454.17
58 -255700.83 74019.17
59 -367112.83 -255700.83
60 NA -367112.83
> dum1 <- dum[2:length(myerror),]
> dum1
lag(myerror, k = 1) myerror
[1,] -359916.28 -426472.28
[2,] -215223.28 -359916.28
[3,] -15613.28 -215223.28
[4,] 70295.72 -15613.28
[5,] 63711.72 70295.72
[6,] 348082.72 63711.72
[7,] 288335.72 348082.72
[8,] 191815.72 288335.72
[9,] 47476.72 191815.72
[10,] -220262.28 47476.72
[11,] -311761.28 -220262.28
[12,] -358601.28 -311761.28
[13,] -339457.28 -358601.28
[14,] -140074.28 -339457.28
[15,] 21001.72 -140074.28
[16,] 121960.72 21001.72
[17,] 150883.72 121960.72
[18,] 413931.72 150883.72
[19,] 305376.72 413931.72
[20,] 251266.72 305376.72
[21,] 73341.72 251266.72
[22,] -183842.28 73341.72
[23,] -310102.28 -183842.28
[24,] -332430.28 -310102.28
[25,] -308627.28 -332430.28
[26,] -89788.28 -308627.28
[27,] 121607.72 -89788.28
[28,] 204508.72 121607.72
[29,] 201306.72 204508.72
[30,] 438057.72 201306.72
[31,] 314497.72 438057.72
[32,] 281602.72 314497.72
[33,] 119592.72 281602.72
[34,] -145628.28 119592.72
[35,] -270855.28 -145628.28
[36,] -476980.83 -270855.28
[37,] -452898.83 -476980.83
[38,] -181212.83 -452898.83
[39,] -24745.83 -181212.83
[40,] 75624.17 -24745.83
[41,] 124900.17 75624.17
[42,] 382501.17 124900.17
[43,] 282232.17 382501.17
[44,] 246096.17 282232.17
[45,] 105696.17 246096.17
[46,] -147392.83 105696.17
[47,] -253374.83 -147392.83
[48,] -320697.83 -253374.83
[49,] -246817.83 -320697.83
[50,] -37068.83 -246817.83
[51,] 91471.17 -37068.83
[52,] 196118.17 91471.17
[53,] 205418.17 196118.17
[54,] 433495.17 205418.17
[55,] 304978.17 433495.17
[56,] 241454.17 304978.17
[57,] 74019.17 241454.17
[58,] -255700.83 74019.17
[59,] -367112.83 -255700.83
> z <- as.data.frame(dum1)
> z
lag(myerror, k = 1) myerror
1 -359916.28 -426472.28
2 -215223.28 -359916.28
3 -15613.28 -215223.28
4 70295.72 -15613.28
5 63711.72 70295.72
6 348082.72 63711.72
7 288335.72 348082.72
8 191815.72 288335.72
9 47476.72 191815.72
10 -220262.28 47476.72
11 -311761.28 -220262.28
12 -358601.28 -311761.28
13 -339457.28 -358601.28
14 -140074.28 -339457.28
15 21001.72 -140074.28
16 121960.72 21001.72
17 150883.72 121960.72
18 413931.72 150883.72
19 305376.72 413931.72
20 251266.72 305376.72
21 73341.72 251266.72
22 -183842.28 73341.72
23 -310102.28 -183842.28
24 -332430.28 -310102.28
25 -308627.28 -332430.28
26 -89788.28 -308627.28
27 121607.72 -89788.28
28 204508.72 121607.72
29 201306.72 204508.72
30 438057.72 201306.72
31 314497.72 438057.72
32 281602.72 314497.72
33 119592.72 281602.72
34 -145628.28 119592.72
35 -270855.28 -145628.28
36 -476980.83 -270855.28
37 -452898.83 -476980.83
38 -181212.83 -452898.83
39 -24745.83 -181212.83
40 75624.17 -24745.83
41 124900.17 75624.17
42 382501.17 124900.17
43 282232.17 382501.17
44 246096.17 282232.17
45 105696.17 246096.17
46 -147392.83 105696.17
47 -253374.83 -147392.83
48 -320697.83 -253374.83
49 -246817.83 -320697.83
50 -37068.83 -246817.83
51 91471.17 -37068.83
52 196118.17 91471.17
53 205418.17 196118.17
54 433495.17 205418.17
55 304978.17 433495.17
56 241454.17 304978.17
57 74019.17 241454.17
58 -255700.83 74019.17
59 -367112.83 -255700.83
> 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/76nyn1261310205.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> acf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/8g4de1261310205.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> pacf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Partial Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/996pe1261310205.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> opar <- par(mfrow = c(2,2), oma = c(0, 0, 1.1, 0))
> plot(mylm, las = 1, sub='Residual Diagnostics')
> par(opar)
> dev.off()
null device
1
> if (n > n25) {
+ postscript(file="/var/www/html/rcomp/tmp/101fzj1261310205.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
+ plot(kp3:nmkm3,gqarr[,2], main='Goldfeld-Quandt test',ylab='2-sided p-value',xlab='breakpoint')
+ grid()
+ dev.off()
+ }
null device
1
>
> #Note: the /var/www/html/rcomp/createtable file can be downloaded at http://www.wessa.net/cretab
> load(file="/var/www/html/rcomp/createtable")
>
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a, 'Multiple Linear Regression - Estimated Regression Equation', 1, TRUE)
> a<-table.row.end(a)
> myeq <- colnames(x)[1]
> myeq <- paste(myeq, '[t] = ', sep='')
> for (i in 1:k){
+ if (mysum$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/11snfh1261310205.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/12sycm1261310205.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/13aase1261310205.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/146tzt1261310205.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/15rbdf1261310205.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/16nz901261310205.tab")
+ }
>
> try(system("convert tmp/141ff1261310205.ps tmp/141ff1261310205.png",intern=TRUE))
character(0)
> try(system("convert tmp/2pvt11261310205.ps tmp/2pvt11261310205.png",intern=TRUE))
character(0)
> try(system("convert tmp/3o2781261310205.ps tmp/3o2781261310205.png",intern=TRUE))
character(0)
> try(system("convert tmp/4zjgc1261310205.ps tmp/4zjgc1261310205.png",intern=TRUE))
character(0)
> try(system("convert tmp/5g1im1261310205.ps tmp/5g1im1261310205.png",intern=TRUE))
character(0)
> try(system("convert tmp/60l5n1261310205.ps tmp/60l5n1261310205.png",intern=TRUE))
character(0)
> try(system("convert tmp/76nyn1261310205.ps tmp/76nyn1261310205.png",intern=TRUE))
character(0)
> try(system("convert tmp/8g4de1261310205.ps tmp/8g4de1261310205.png",intern=TRUE))
character(0)
> try(system("convert tmp/996pe1261310205.ps tmp/996pe1261310205.png",intern=TRUE))
character(0)
> try(system("convert tmp/101fzj1261310205.ps tmp/101fzj1261310205.png",intern=TRUE))
character(0)
>
>
> proc.time()
user system elapsed
2.458 1.545 4.214