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(286602,0,283042,0,276687,0,277915,0,277128,0,277103,0,275037,0,270150,0,267140,0,264993,0,287259,0,291186,0,292300,0,288186,0,281477,0,282656,0,280190,0,280408,0,276836,0,275216,0,274352,0,271311,0,289802,0,290726,0,292300,0,278506,0,269826,0,265861,0,269034,0,264176,0,255198,0,253353,0,246057,0,235372,0,258556,0,260993,0,254663,0,250643,0,243422,0,247105,0,248541,0,245039,0,237080,0,237085,0,225554,0,226839,0,247934,0,248333,1,246969,1,245098,1,246263,1,255765,1,264319,1,268347,1,273046,1,273963,1,267430,1,271993,1,292710,1,295881,1),dim=c(2,60),dimnames=list(c('nwwmb','dummy_variable'),1:60))
> y <- array(NA,dim=c(2,60),dimnames=list(c('nwwmb','dummy_variable'),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
nwwmb dummy_variable
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 1
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) dummy_variable
266614 -1220
> (mysum <- summary(mylm))
Call:
lm(formula = df)
Residuals:
Min 1Q Median 3Q Max
-41060 -16243 3083 12313 30487
Coefficients:
Estimate Std. Error t value Pr(>|t|)
(Intercept) 266614 2644 100.844 <2e-16 ***
dummy_variable -1220 5680 -0.215 0.83
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
Residual standard error: 18130 on 58 degrees of freedom
Multiple R-squared: 0.0007948, Adjusted R-squared: -0.01643
F-statistic: 0.04614 on 1 and 58 DF, p-value: 0.8307
> 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,] 2.676862e-02 0.0535372406 0.9732314
[2,] 7.243317e-03 0.0144866341 0.9927567
[3,] 2.475713e-03 0.0049514268 0.9975243
[4,] 2.254086e-03 0.0045081716 0.9977459
[5,] 2.581898e-03 0.0051637962 0.9974181
[6,] 2.866717e-03 0.0057334333 0.9971333
[7,] 3.067847e-03 0.0061356935 0.9969322
[8,] 5.001696e-03 0.0100033914 0.9949983
[9,] 7.341920e-03 0.0146838396 0.9926581
[10,] 5.954717e-03 0.0119094337 0.9940453
[11,] 3.166384e-03 0.0063327675 0.9968336
[12,] 1.764018e-03 0.0035280362 0.9982360
[13,] 9.120135e-04 0.0018240271 0.9990880
[14,] 4.782011e-04 0.0009564022 0.9995218
[15,] 2.505427e-04 0.0005010853 0.9997495
[16,] 1.383590e-04 0.0002767179 0.9998616
[17,] 7.969623e-05 0.0001593925 0.9999203
[18,] 5.636255e-05 0.0001127251 0.9999436
[19,] 1.147399e-04 0.0002294798 0.9998853
[20,] 3.181224e-04 0.0006362447 0.9996819
[21,] 1.487128e-03 0.0029742554 0.9985129
[22,] 1.779649e-03 0.0035592982 0.9982204
[23,] 2.513539e-03 0.0050270770 0.9974865
[24,] 4.445936e-03 0.0088918723 0.9955541
[25,] 6.763806e-03 0.0135276115 0.9932362
[26,] 1.242750e-02 0.0248550006 0.9875725
[27,] 3.426132e-02 0.0685226357 0.9657387
[28,] 7.181498e-02 0.1436299553 0.9281850
[29,] 1.609109e-01 0.3218218276 0.8390891
[30,] 3.890761e-01 0.7781522142 0.6109239
[31,] 4.017262e-01 0.8034524313 0.5982738
[32,] 4.283817e-01 0.8567633986 0.5716183
[33,] 4.500077e-01 0.9000153167 0.5499923
[34,] 4.722223e-01 0.9444446191 0.5277777
[35,] 5.080018e-01 0.9839964991 0.4919982
[36,] 5.161589e-01 0.9676822030 0.4838411
[37,] 5.204484e-01 0.9591032759 0.4795516
[38,] 5.239023e-01 0.9521953605 0.4760977
[39,] 5.368748e-01 0.9262503826 0.4631252
[40,] 5.336029e-01 0.9327941300 0.4663971
[41,] 5.906877e-01 0.8186245506 0.4093123
[42,] 6.434415e-01 0.7131169389 0.3565585
[43,] 5.676389e-01 0.8647221442 0.4323611
[44,] 5.453434e-01 0.9093131099 0.4546566
[45,] 5.558521e-01 0.8882957697 0.4441479
[46,] 6.310055e-01 0.7379889294 0.3689945
[47,] 7.566524e-01 0.4866952275 0.2433476
[48,] 7.949695e-01 0.4100609278 0.2050305
[49,] 7.585770e-01 0.4828459130 0.2414230
[50,] 6.825582e-01 0.6348836861 0.3174418
[51,] 5.464316e-01 0.9071367919 0.4535684
> postscript(file="/var/www/html/rcomp/tmp/1b0661258674070.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$resid)
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/20t171258674070.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> plot(mysum$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/3sk1d1258674070.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> hist(mysum$resid, main='Residual Histogram', xlab='values of Residuals')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/4p6h81258674070.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> densityplot(~mysum$resid,col='black',main='Residual Density Plot', xlab='values of Residuals')
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/5aanz1258674070.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
19988.4043 16428.4043 10073.4043 11301.4043 10514.4043 10489.4043
7 8 9 10 11 12
8423.4043 3536.4043 526.4043 -1620.5957 20645.4043 24572.4043
13 14 15 16 17 18
25686.4043 21572.4043 14863.4043 16042.4043 13576.4043 13794.4043
19 20 21 22 23 24
10222.4043 8602.4043 7738.4043 4697.4043 23188.4043 24112.4043
25 26 27 28 29 30
25686.4043 11892.4043 3212.4043 -752.5957 2420.4043 -2437.5957
31 32 33 34 35 36
-11415.5957 -13260.5957 -20556.5957 -31241.5957 -8057.5957 -5620.5957
37 38 39 40 41 42
-11950.5957 -15970.5957 -23191.5957 -19508.5957 -18072.5957 -21574.5957
43 44 45 46 47 48
-29533.5957 -29528.5957 -41059.5957 -39774.5957 -18679.5957 -17060.6154
49 50 51 52 53 54
-18424.6154 -20295.6154 -19130.6154 -9628.6154 -1074.6154 2953.3846
55 56 57 58 59 60
7652.3846 8569.3846 2036.3846 6599.3846 27316.3846 30487.3846
> postscript(file="/var/www/html/rcomp/tmp/6ud9i1258674070.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 19988.4043 NA
1 16428.4043 19988.4043
2 10073.4043 16428.4043
3 11301.4043 10073.4043
4 10514.4043 11301.4043
5 10489.4043 10514.4043
6 8423.4043 10489.4043
7 3536.4043 8423.4043
8 526.4043 3536.4043
9 -1620.5957 526.4043
10 20645.4043 -1620.5957
11 24572.4043 20645.4043
12 25686.4043 24572.4043
13 21572.4043 25686.4043
14 14863.4043 21572.4043
15 16042.4043 14863.4043
16 13576.4043 16042.4043
17 13794.4043 13576.4043
18 10222.4043 13794.4043
19 8602.4043 10222.4043
20 7738.4043 8602.4043
21 4697.4043 7738.4043
22 23188.4043 4697.4043
23 24112.4043 23188.4043
24 25686.4043 24112.4043
25 11892.4043 25686.4043
26 3212.4043 11892.4043
27 -752.5957 3212.4043
28 2420.4043 -752.5957
29 -2437.5957 2420.4043
30 -11415.5957 -2437.5957
31 -13260.5957 -11415.5957
32 -20556.5957 -13260.5957
33 -31241.5957 -20556.5957
34 -8057.5957 -31241.5957
35 -5620.5957 -8057.5957
36 -11950.5957 -5620.5957
37 -15970.5957 -11950.5957
38 -23191.5957 -15970.5957
39 -19508.5957 -23191.5957
40 -18072.5957 -19508.5957
41 -21574.5957 -18072.5957
42 -29533.5957 -21574.5957
43 -29528.5957 -29533.5957
44 -41059.5957 -29528.5957
45 -39774.5957 -41059.5957
46 -18679.5957 -39774.5957
47 -17060.6154 -18679.5957
48 -18424.6154 -17060.6154
49 -20295.6154 -18424.6154
50 -19130.6154 -20295.6154
51 -9628.6154 -19130.6154
52 -1074.6154 -9628.6154
53 2953.3846 -1074.6154
54 7652.3846 2953.3846
55 8569.3846 7652.3846
56 2036.3846 8569.3846
57 6599.3846 2036.3846
58 27316.3846 6599.3846
59 30487.3846 27316.3846
60 NA 30487.3846
> dum1 <- dum[2:length(myerror),]
> dum1
lag(myerror, k = 1) myerror
[1,] 16428.4043 19988.4043
[2,] 10073.4043 16428.4043
[3,] 11301.4043 10073.4043
[4,] 10514.4043 11301.4043
[5,] 10489.4043 10514.4043
[6,] 8423.4043 10489.4043
[7,] 3536.4043 8423.4043
[8,] 526.4043 3536.4043
[9,] -1620.5957 526.4043
[10,] 20645.4043 -1620.5957
[11,] 24572.4043 20645.4043
[12,] 25686.4043 24572.4043
[13,] 21572.4043 25686.4043
[14,] 14863.4043 21572.4043
[15,] 16042.4043 14863.4043
[16,] 13576.4043 16042.4043
[17,] 13794.4043 13576.4043
[18,] 10222.4043 13794.4043
[19,] 8602.4043 10222.4043
[20,] 7738.4043 8602.4043
[21,] 4697.4043 7738.4043
[22,] 23188.4043 4697.4043
[23,] 24112.4043 23188.4043
[24,] 25686.4043 24112.4043
[25,] 11892.4043 25686.4043
[26,] 3212.4043 11892.4043
[27,] -752.5957 3212.4043
[28,] 2420.4043 -752.5957
[29,] -2437.5957 2420.4043
[30,] -11415.5957 -2437.5957
[31,] -13260.5957 -11415.5957
[32,] -20556.5957 -13260.5957
[33,] -31241.5957 -20556.5957
[34,] -8057.5957 -31241.5957
[35,] -5620.5957 -8057.5957
[36,] -11950.5957 -5620.5957
[37,] -15970.5957 -11950.5957
[38,] -23191.5957 -15970.5957
[39,] -19508.5957 -23191.5957
[40,] -18072.5957 -19508.5957
[41,] -21574.5957 -18072.5957
[42,] -29533.5957 -21574.5957
[43,] -29528.5957 -29533.5957
[44,] -41059.5957 -29528.5957
[45,] -39774.5957 -41059.5957
[46,] -18679.5957 -39774.5957
[47,] -17060.6154 -18679.5957
[48,] -18424.6154 -17060.6154
[49,] -20295.6154 -18424.6154
[50,] -19130.6154 -20295.6154
[51,] -9628.6154 -19130.6154
[52,] -1074.6154 -9628.6154
[53,] 2953.3846 -1074.6154
[54,] 7652.3846 2953.3846
[55,] 8569.3846 7652.3846
[56,] 2036.3846 8569.3846
[57,] 6599.3846 2036.3846
[58,] 27316.3846 6599.3846
[59,] 30487.3846 27316.3846
> z <- as.data.frame(dum1)
> z
lag(myerror, k = 1) myerror
1 16428.4043 19988.4043
2 10073.4043 16428.4043
3 11301.4043 10073.4043
4 10514.4043 11301.4043
5 10489.4043 10514.4043
6 8423.4043 10489.4043
7 3536.4043 8423.4043
8 526.4043 3536.4043
9 -1620.5957 526.4043
10 20645.4043 -1620.5957
11 24572.4043 20645.4043
12 25686.4043 24572.4043
13 21572.4043 25686.4043
14 14863.4043 21572.4043
15 16042.4043 14863.4043
16 13576.4043 16042.4043
17 13794.4043 13576.4043
18 10222.4043 13794.4043
19 8602.4043 10222.4043
20 7738.4043 8602.4043
21 4697.4043 7738.4043
22 23188.4043 4697.4043
23 24112.4043 23188.4043
24 25686.4043 24112.4043
25 11892.4043 25686.4043
26 3212.4043 11892.4043
27 -752.5957 3212.4043
28 2420.4043 -752.5957
29 -2437.5957 2420.4043
30 -11415.5957 -2437.5957
31 -13260.5957 -11415.5957
32 -20556.5957 -13260.5957
33 -31241.5957 -20556.5957
34 -8057.5957 -31241.5957
35 -5620.5957 -8057.5957
36 -11950.5957 -5620.5957
37 -15970.5957 -11950.5957
38 -23191.5957 -15970.5957
39 -19508.5957 -23191.5957
40 -18072.5957 -19508.5957
41 -21574.5957 -18072.5957
42 -29533.5957 -21574.5957
43 -29528.5957 -29533.5957
44 -41059.5957 -29528.5957
45 -39774.5957 -41059.5957
46 -18679.5957 -39774.5957
47 -17060.6154 -18679.5957
48 -18424.6154 -17060.6154
49 -20295.6154 -18424.6154
50 -19130.6154 -20295.6154
51 -9628.6154 -19130.6154
52 -1074.6154 -9628.6154
53 2953.3846 -1074.6154
54 7652.3846 2953.3846
55 8569.3846 7652.3846
56 2036.3846 8569.3846
57 6599.3846 2036.3846
58 27316.3846 6599.3846
59 30487.3846 27316.3846
> 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/7unzi1258674070.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> acf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/8ncn51258674070.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> pacf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Partial Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/9d11c1258674070.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> opar <- par(mfrow = c(2,2), oma = c(0, 0, 1.1, 0))
> plot(mylm, las = 1, sub='Residual Diagnostics')
> par(opar)
> dev.off()
null device
1
> if (n > n25) {
+ postscript(file="/var/www/html/rcomp/tmp/1048951258674070.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
+ plot(kp3:nmkm3,gqarr[,2], main='Goldfeld-Quandt test',ylab='2-sided p-value',xlab='breakpoint')
+ grid()
+ dev.off()
+ }
null device
1
>
> #Note: the /var/www/html/rcomp/createtable file can be downloaded at http://www.wessa.net/cretab
> load(file="/var/www/html/rcomp/createtable")
>
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a, 'Multiple Linear Regression - Estimated Regression Equation', 1, TRUE)
> a<-table.row.end(a)
> myeq <- colnames(x)[1]
> myeq <- paste(myeq, '[t] = ', sep='')
> for (i in 1:k){
+ if (mysum$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/114pp21258674070.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/12vch31258674070.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/13ikbo1258674070.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/14hrog1258674070.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/15vd8w1258674070.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/16rnde1258674070.tab")
+ }
>
> system("convert tmp/1b0661258674070.ps tmp/1b0661258674070.png")
> system("convert tmp/20t171258674070.ps tmp/20t171258674070.png")
> system("convert tmp/3sk1d1258674070.ps tmp/3sk1d1258674070.png")
> system("convert tmp/4p6h81258674070.ps tmp/4p6h81258674070.png")
> system("convert tmp/5aanz1258674070.ps tmp/5aanz1258674070.png")
> system("convert tmp/6ud9i1258674070.ps tmp/6ud9i1258674070.png")
> system("convert tmp/7unzi1258674070.ps tmp/7unzi1258674070.png")
> system("convert tmp/8ncn51258674070.ps tmp/8ncn51258674070.png")
> system("convert tmp/9d11c1258674070.ps tmp/9d11c1258674070.png")
> system("convert tmp/1048951258674070.ps tmp/1048951258674070.png")
>
>
> proc.time()
user system elapsed
2.512 1.599 2.923