R version 2.8.0 (2008-10-20)
Copyright (C) 2008 The R Foundation for Statistical Computing
ISBN 3-900051-07-0
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Type 'license()' or 'licence()' for distribution details.
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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
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Type 'q()' to quit R.
> x <- array(list(2174.56,0,2196.72,0,2350.44,0,2440.25,0,2408.64,0,2472.81,0,2407.6,0,2454.62,0,2448.05,0,2497.84,0,2645.64,0,2756.76,0,2849.27,0,2921.44,0,2981.85,0,3080.58,0,3106.22,0,3119.31,0,3061.26,0,3097.31,0,3161.69,0,3257.16,0,3277.01,0,3295.32,0,3363.99,0,3494.17,0,3667.03,0,3813.06,0,3917.96,0,3895.51,0,3801.06,0,3570.12,0,3701.61,0,3862.27,0,3970.1,0,4138.52,0,4199.75,0,4290.89,0,4443.91,0,4502.64,0,4356.98,0,4591.27,0,4696.96,0,4621.4,0,4562.84,0,4202.52,0,4296.49,0,4435.23,0,4105.18,0,4116.68,0,3844.49,0,3720.98,0,3674.4,0,3857.62,0,3801.06,0,3504.37,1,3032.6,1,3047.03,1,2962.34,1,2197.82,1,2014.45,1),dim=c(2,61),dimnames=list(c('Bel_20','dummy'),1:61))
> y <- array(NA,dim=c(2,61),dimnames=list(c('Bel_20','dummy'),1:61))
> 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
Bel_20 dummy
1 2174.56 0
2 2196.72 0
3 2350.44 0
4 2440.25 0
5 2408.64 0
6 2472.81 0
7 2407.60 0
8 2454.62 0
9 2448.05 0
10 2497.84 0
11 2645.64 0
12 2756.76 0
13 2849.27 0
14 2921.44 0
15 2981.85 0
16 3080.58 0
17 3106.22 0
18 3119.31 0
19 3061.26 0
20 3097.31 0
21 3161.69 0
22 3257.16 0
23 3277.01 0
24 3295.32 0
25 3363.99 0
26 3494.17 0
27 3667.03 0
28 3813.06 0
29 3917.96 0
30 3895.51 0
31 3801.06 0
32 3570.12 0
33 3701.61 0
34 3862.27 0
35 3970.10 0
36 4138.52 0
37 4199.75 0
38 4290.89 0
39 4443.91 0
40 4502.64 0
41 4356.98 0
42 4591.27 0
43 4696.96 0
44 4621.40 0
45 4562.84 0
46 4202.52 0
47 4296.49 0
48 4435.23 0
49 4105.18 0
50 4116.68 0
51 3844.49 0
52 3720.98 0
53 3674.40 0
54 3857.62 0
55 3801.06 0
56 3504.37 1
57 3032.60 1
58 3047.03 1
59 2962.34 1
60 2197.82 1
61 2014.45 1
> k <- length(x[1,])
> df <- as.data.frame(x)
> (mylm <- lm(df))
Call:
lm(formula = df)
Coefficients:
(Intercept) dummy
3490.5 -697.4
> (mysum <- summary(mylm))
Call:
lm(formula = df)
Residuals:
Min 1Q Median 3Q Max
-1316.0 -569.1 176.5 614.7 1206.4
Coefficients:
Estimate Std. Error t value Pr(>|t|)
(Intercept) 3490.53 97.51 35.797 <2e-16 ***
dummy -697.43 310.91 -2.243 0.0287 *
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
Residual standard error: 723.1 on 59 degrees of freedom
Multiple R-squared: 0.07858, Adjusted R-squared: 0.06297
F-statistic: 5.032 on 1 and 59 DF, p-value: 0.02865
> 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,] 1.329236e-02 2.658471e-02 0.986707643
[2,] 4.595937e-03 9.191875e-03 0.995404063
[3,] 1.130303e-03 2.260606e-03 0.998869697
[4,] 3.427528e-04 6.855056e-04 0.999657247
[5,] 1.033540e-04 2.067080e-04 0.999896646
[6,] 4.406626e-05 8.813252e-05 0.999955934
[7,] 7.464024e-05 1.492805e-04 0.999925360
[8,] 2.310121e-04 4.620242e-04 0.999768988
[9,] 7.653570e-04 1.530714e-03 0.999234643
[10,] 2.198401e-03 4.396802e-03 0.997801599
[11,] 5.422542e-03 1.084508e-02 0.994577458
[12,] 1.378390e-02 2.756779e-02 0.986216104
[13,] 2.718590e-02 5.437180e-02 0.972814101
[14,] 4.551447e-02 9.102894e-02 0.954485529
[15,] 6.402359e-02 1.280472e-01 0.935976409
[16,] 9.211824e-02 1.842365e-01 0.907881756
[17,] 1.367647e-01 2.735293e-01 0.863235342
[18,] 2.070129e-01 4.140257e-01 0.792987134
[19,] 2.945571e-01 5.891142e-01 0.705442910
[20,] 3.989761e-01 7.979522e-01 0.601023901
[21,] 5.194075e-01 9.611850e-01 0.480592502
[22,] 6.454942e-01 7.090116e-01 0.354505816
[23,] 7.622039e-01 4.755921e-01 0.237796070
[24,] 8.509328e-01 2.981343e-01 0.149067167
[25,] 9.072875e-01 1.854250e-01 0.092712475
[26,] 9.342935e-01 1.314130e-01 0.065706485
[27,] 9.470496e-01 1.059009e-01 0.052950430
[28,] 9.596698e-01 8.066040e-02 0.040330199
[29,] 9.675744e-01 6.485121e-02 0.032425605
[30,] 9.721756e-01 5.564874e-02 0.027824370
[31,] 9.749976e-01 5.000474e-02 0.025002368
[32,] 9.775602e-01 4.487953e-02 0.022439766
[33,] 9.788608e-01 4.227843e-02 0.021139215
[34,] 9.799715e-01 4.005691e-02 0.020028454
[35,] 9.829938e-01 3.401248e-02 0.017006242
[36,] 9.856079e-01 2.878426e-02 0.014392129
[37,] 9.836243e-01 3.275135e-02 0.016375675
[38,] 9.866180e-01 2.676402e-02 0.013382010
[39,] 9.914400e-01 1.711994e-02 0.008559972
[40,] 9.936125e-01 1.277492e-02 0.006387459
[41,] 9.948052e-01 1.038959e-02 0.005194795
[42,] 9.914915e-01 1.701707e-02 0.008508536
[43,] 9.881213e-01 2.375740e-02 0.011878701
[44,] 9.885732e-01 2.285355e-02 0.011426776
[45,] 9.806953e-01 3.860947e-02 0.019304737
[46,] 9.697168e-01 6.056638e-02 0.030283190
[47,] 9.427040e-01 1.145921e-01 0.057296040
[48,] 8.958406e-01 2.083188e-01 0.104159382
[49,] 8.241128e-01 3.517743e-01 0.175887169
[50,] 7.172039e-01 5.655922e-01 0.282796122
[51,] 5.736331e-01 8.527339e-01 0.426366946
[52,] 6.039654e-01 7.920692e-01 0.396034616
> postscript(file="/var/www/html/rcomp/tmp/1qds71229719035.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$resid)
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/2jcy31229719035.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> plot(mysum$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/3kybm1229719035.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> hist(mysum$resid, main='Residual Histogram', xlab='values of Residuals')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/4oj1l1229719035.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> densityplot(~mysum$resid,col='black',main='Residual Density Plot', xlab='values of Residuals')
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/5nobe1229719035.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 = 61
Frequency = 1
1 2 3 4 5 6 7
-1315.9680 -1293.8080 -1140.0880 -1050.2780 -1081.8880 -1017.7180 -1082.9280
8 9 10 11 12 13 14
-1035.9080 -1042.4780 -992.6880 -844.8880 -733.7680 -641.2580 -569.0880
15 16 17 18 19 20 21
-508.6780 -409.9480 -384.3080 -371.2180 -429.2680 -393.2180 -328.8380
22 23 24 25 26 27 28
-233.3680 -213.5180 -195.2080 -126.5380 3.6420 176.5020 322.5320
29 30 31 32 33 34 35
427.4320 404.9820 310.5320 79.5920 211.0820 371.7420 479.5720
36 37 38 39 40 41 42
647.9920 709.2220 800.3620 953.3820 1012.1120 866.4520 1100.7420
43 44 45 46 47 48 49
1206.4320 1130.8720 1072.3120 711.9920 805.9620 944.7020 614.6520
50 51 52 53 54 55 56
626.1520 353.9620 230.4520 183.8720 367.0920 310.5320 711.2683
57 58 59 60 61
239.4983 253.9283 169.2383 -595.2817 -778.6517
> postscript(file="/var/www/html/rcomp/tmp/6a7vn1229719035.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 = 61
Frequency = 1
lag(myerror, k = 1) myerror
0 -1315.9680 NA
1 -1293.8080 -1315.9680
2 -1140.0880 -1293.8080
3 -1050.2780 -1140.0880
4 -1081.8880 -1050.2780
5 -1017.7180 -1081.8880
6 -1082.9280 -1017.7180
7 -1035.9080 -1082.9280
8 -1042.4780 -1035.9080
9 -992.6880 -1042.4780
10 -844.8880 -992.6880
11 -733.7680 -844.8880
12 -641.2580 -733.7680
13 -569.0880 -641.2580
14 -508.6780 -569.0880
15 -409.9480 -508.6780
16 -384.3080 -409.9480
17 -371.2180 -384.3080
18 -429.2680 -371.2180
19 -393.2180 -429.2680
20 -328.8380 -393.2180
21 -233.3680 -328.8380
22 -213.5180 -233.3680
23 -195.2080 -213.5180
24 -126.5380 -195.2080
25 3.6420 -126.5380
26 176.5020 3.6420
27 322.5320 176.5020
28 427.4320 322.5320
29 404.9820 427.4320
30 310.5320 404.9820
31 79.5920 310.5320
32 211.0820 79.5920
33 371.7420 211.0820
34 479.5720 371.7420
35 647.9920 479.5720
36 709.2220 647.9920
37 800.3620 709.2220
38 953.3820 800.3620
39 1012.1120 953.3820
40 866.4520 1012.1120
41 1100.7420 866.4520
42 1206.4320 1100.7420
43 1130.8720 1206.4320
44 1072.3120 1130.8720
45 711.9920 1072.3120
46 805.9620 711.9920
47 944.7020 805.9620
48 614.6520 944.7020
49 626.1520 614.6520
50 353.9620 626.1520
51 230.4520 353.9620
52 183.8720 230.4520
53 367.0920 183.8720
54 310.5320 367.0920
55 711.2683 310.5320
56 239.4983 711.2683
57 253.9283 239.4983
58 169.2383 253.9283
59 -595.2817 169.2383
60 -778.6517 -595.2817
61 NA -778.6517
> dum1 <- dum[2:length(myerror),]
> dum1
lag(myerror, k = 1) myerror
[1,] -1293.8080 -1315.9680
[2,] -1140.0880 -1293.8080
[3,] -1050.2780 -1140.0880
[4,] -1081.8880 -1050.2780
[5,] -1017.7180 -1081.8880
[6,] -1082.9280 -1017.7180
[7,] -1035.9080 -1082.9280
[8,] -1042.4780 -1035.9080
[9,] -992.6880 -1042.4780
[10,] -844.8880 -992.6880
[11,] -733.7680 -844.8880
[12,] -641.2580 -733.7680
[13,] -569.0880 -641.2580
[14,] -508.6780 -569.0880
[15,] -409.9480 -508.6780
[16,] -384.3080 -409.9480
[17,] -371.2180 -384.3080
[18,] -429.2680 -371.2180
[19,] -393.2180 -429.2680
[20,] -328.8380 -393.2180
[21,] -233.3680 -328.8380
[22,] -213.5180 -233.3680
[23,] -195.2080 -213.5180
[24,] -126.5380 -195.2080
[25,] 3.6420 -126.5380
[26,] 176.5020 3.6420
[27,] 322.5320 176.5020
[28,] 427.4320 322.5320
[29,] 404.9820 427.4320
[30,] 310.5320 404.9820
[31,] 79.5920 310.5320
[32,] 211.0820 79.5920
[33,] 371.7420 211.0820
[34,] 479.5720 371.7420
[35,] 647.9920 479.5720
[36,] 709.2220 647.9920
[37,] 800.3620 709.2220
[38,] 953.3820 800.3620
[39,] 1012.1120 953.3820
[40,] 866.4520 1012.1120
[41,] 1100.7420 866.4520
[42,] 1206.4320 1100.7420
[43,] 1130.8720 1206.4320
[44,] 1072.3120 1130.8720
[45,] 711.9920 1072.3120
[46,] 805.9620 711.9920
[47,] 944.7020 805.9620
[48,] 614.6520 944.7020
[49,] 626.1520 614.6520
[50,] 353.9620 626.1520
[51,] 230.4520 353.9620
[52,] 183.8720 230.4520
[53,] 367.0920 183.8720
[54,] 310.5320 367.0920
[55,] 711.2683 310.5320
[56,] 239.4983 711.2683
[57,] 253.9283 239.4983
[58,] 169.2383 253.9283
[59,] -595.2817 169.2383
[60,] -778.6517 -595.2817
> z <- as.data.frame(dum1)
> z
lag(myerror, k = 1) myerror
1 -1293.8080 -1315.9680
2 -1140.0880 -1293.8080
3 -1050.2780 -1140.0880
4 -1081.8880 -1050.2780
5 -1017.7180 -1081.8880
6 -1082.9280 -1017.7180
7 -1035.9080 -1082.9280
8 -1042.4780 -1035.9080
9 -992.6880 -1042.4780
10 -844.8880 -992.6880
11 -733.7680 -844.8880
12 -641.2580 -733.7680
13 -569.0880 -641.2580
14 -508.6780 -569.0880
15 -409.9480 -508.6780
16 -384.3080 -409.9480
17 -371.2180 -384.3080
18 -429.2680 -371.2180
19 -393.2180 -429.2680
20 -328.8380 -393.2180
21 -233.3680 -328.8380
22 -213.5180 -233.3680
23 -195.2080 -213.5180
24 -126.5380 -195.2080
25 3.6420 -126.5380
26 176.5020 3.6420
27 322.5320 176.5020
28 427.4320 322.5320
29 404.9820 427.4320
30 310.5320 404.9820
31 79.5920 310.5320
32 211.0820 79.5920
33 371.7420 211.0820
34 479.5720 371.7420
35 647.9920 479.5720
36 709.2220 647.9920
37 800.3620 709.2220
38 953.3820 800.3620
39 1012.1120 953.3820
40 866.4520 1012.1120
41 1100.7420 866.4520
42 1206.4320 1100.7420
43 1130.8720 1206.4320
44 1072.3120 1130.8720
45 711.9920 1072.3120
46 805.9620 711.9920
47 944.7020 805.9620
48 614.6520 944.7020
49 626.1520 614.6520
50 353.9620 626.1520
51 230.4520 353.9620
52 183.8720 230.4520
53 367.0920 183.8720
54 310.5320 367.0920
55 711.2683 310.5320
56 239.4983 711.2683
57 253.9283 239.4983
58 169.2383 253.9283
59 -595.2817 169.2383
60 -778.6517 -595.2817
> 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/76qav1229719035.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> acf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/8iho71229719035.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> pacf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Partial Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/948q81229719035.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> opar <- par(mfrow = c(2,2), oma = c(0, 0, 1.1, 0))
> plot(mylm, las = 1, sub='Residual Diagnostics')
> par(opar)
> dev.off()
null device
1
> if (n > n25) {
+ postscript(file="/var/www/html/rcomp/tmp/10t2cm1229719035.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
+ plot(kp3:nmkm3,gqarr[,2], main='Goldfeld-Quandt test',ylab='2-sided p-value',xlab='breakpoint')
+ grid()
+ dev.off()
+ }
null device
1
>
> #Note: the /var/www/html/rcomp/createtable file can be downloaded at http://www.wessa.net/cretab
> load(file="/var/www/html/rcomp/createtable")
>
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a, 'Multiple Linear Regression - Estimated Regression Equation', 1, TRUE)
> a<-table.row.end(a)
> myeq <- colnames(x)[1]
> myeq <- paste(myeq, '[t] = ', sep='')
> for (i in 1:k){
+ if (mysum$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/110xtt1229719035.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/12xgdi1229719035.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/132u431229719036.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/14h0wq1229719036.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/153yxa1229719036.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/16gkze1229719036.tab")
+ }
>
> system("convert tmp/1qds71229719035.ps tmp/1qds71229719035.png")
> system("convert tmp/2jcy31229719035.ps tmp/2jcy31229719035.png")
> system("convert tmp/3kybm1229719035.ps tmp/3kybm1229719035.png")
> system("convert tmp/4oj1l1229719035.ps tmp/4oj1l1229719035.png")
> system("convert tmp/5nobe1229719035.ps tmp/5nobe1229719035.png")
> system("convert tmp/6a7vn1229719035.ps tmp/6a7vn1229719035.png")
> system("convert tmp/76qav1229719035.ps tmp/76qav1229719035.png")
> system("convert tmp/8iho71229719035.ps tmp/8iho71229719035.png")
> system("convert tmp/948q81229719035.ps tmp/948q81229719035.png")
> system("convert tmp/10t2cm1229719035.ps tmp/10t2cm1229719035.png")
>
>
> proc.time()
user system elapsed
2.492 1.564 4.552