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(160.90,334.10,193.70,273.90,201.40,300.20,176.60,300.90,172.00,332.70,200.10,403.60,172.00,341.00,136.10,391.20,182.60,396.60,208.70,434.10,142.30,418.30,188.80,377.20,143.90,424.80,149.70,509.10,196.90,453.70,231.50,435.60,219.20,406.80,220.70,428.30,244.20,418.40,182.50,576.70,229.80,486.80,238.10,423.00,206.50,491.30,249.30,488.80,181.80,522.60,218.00,418.50,246.40,471.30,214.30,424.60,242.30,495.80,220.70,489.50,204.50,460.70,180.70,514.30,233.00,503.20,236.50,561.60,239.40,623.60,208.70,503.10,209.00,674.60,247.20,491.00,284.30,526.30,245.80,501.60,249.10,529.10,251.40,541.90,251.20,671.20,207.20,673.40,228.30,610.30,254.30,625.00,217.90,562.80,244.40,568.50,233.20,691.40,212.60,538.40,239.50,532.10,335.50,595.00,248.80,641.10,264.60,641.90,275.40,658.80,180.70,758.50,256.10,788.80,247.40,946.10,227.80,650.60,248.10,656.70),dim=c(2,60),dimnames=list(c('E','I'),1:60))
> y <- array(NA,dim=c(2,60),dimnames=list(c('E','I'),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
E I
1 160.9 334.1
2 193.7 273.9
3 201.4 300.2
4 176.6 300.9
5 172.0 332.7
6 200.1 403.6
7 172.0 341.0
8 136.1 391.2
9 182.6 396.6
10 208.7 434.1
11 142.3 418.3
12 188.8 377.2
13 143.9 424.8
14 149.7 509.1
15 196.9 453.7
16 231.5 435.6
17 219.2 406.8
18 220.7 428.3
19 244.2 418.4
20 182.5 576.7
21 229.8 486.8
22 238.1 423.0
23 206.5 491.3
24 249.3 488.8
25 181.8 522.6
26 218.0 418.5
27 246.4 471.3
28 214.3 424.6
29 242.3 495.8
30 220.7 489.5
31 204.5 460.7
32 180.7 514.3
33 233.0 503.2
34 236.5 561.6
35 239.4 623.6
36 208.7 503.1
37 209.0 674.6
38 247.2 491.0
39 284.3 526.3
40 245.8 501.6
41 249.1 529.1
42 251.4 541.9
43 251.2 671.2
44 207.2 673.4
45 228.3 610.3
46 254.3 625.0
47 217.9 562.8
48 244.4 568.5
49 233.2 691.4
50 212.6 538.4
51 239.5 532.1
52 335.5 595.0
53 248.8 641.1
54 264.6 641.9
55 275.4 658.8
56 180.7 758.5
57 256.1 788.8
58 247.4 946.1
59 227.8 650.6
60 248.1 656.7
> k <- length(x[1,])
> df <- as.data.frame(x)
> (mylm <- lm(df))
Call:
lm(formula = df)
Coefficients:
(Intercept) I
147.7851 0.1380
> (mysum <- summary(mylm))
Call:
lm(formula = df)
Residuals:
Min 1Q Median 3Q Max
-71.777 -15.112 5.447 18.766 105.590
Coefficients:
Estimate Std. Error t value Pr(>|t|)
(Intercept) 147.78506 17.77438 8.314 1.82e-11 ***
I 0.13803 0.03349 4.121 0.000121 ***
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
Residual standard error: 33.06 on 58 degrees of freedom
Multiple R-squared: 0.2265, Adjusted R-squared: 0.2132
F-statistic: 16.98 on 1 and 58 DF, p-value: 0.0001214
> 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,] 0.05180064 0.1036013 0.9481994
[2,] 0.11916807 0.2383361 0.8808319
[3,] 0.06472026 0.1294405 0.9352797
[4,] 0.15084237 0.3016847 0.8491576
[5,] 0.10361214 0.2072243 0.8963879
[6,] 0.13175650 0.2635130 0.8682435
[7,] 0.19834144 0.3966829 0.8016586
[8,] 0.14686045 0.2937209 0.8531395
[9,] 0.19867945 0.3973589 0.8013206
[10,] 0.22152360 0.4430472 0.7784764
[11,] 0.25417702 0.5083540 0.7458230
[12,] 0.46890056 0.9378011 0.5310994
[13,] 0.50894762 0.9821048 0.4910524
[14,] 0.53348125 0.9330375 0.4665187
[15,] 0.66550435 0.6689913 0.3344957
[16,] 0.66774019 0.6645196 0.3322598
[17,] 0.67410265 0.6517947 0.3258973
[18,] 0.70643225 0.5871355 0.2935678
[19,] 0.65992783 0.6801443 0.3400722
[20,] 0.70156850 0.5968630 0.2984315
[21,] 0.73455333 0.5308933 0.2654467
[22,] 0.69630868 0.6073826 0.3036913
[23,] 0.70901790 0.5819642 0.2909821
[24,] 0.66339383 0.6732123 0.3366062
[25,] 0.63936079 0.7212784 0.3606392
[26,] 0.58116994 0.8376601 0.4188301
[27,] 0.54963332 0.9007334 0.4503667
[28,] 0.66201595 0.6759681 0.3379840
[29,] 0.61648101 0.7670380 0.3835190
[30,] 0.55617754 0.8876449 0.4438225
[31,] 0.48357952 0.9671590 0.5164205
[32,] 0.48144226 0.9628845 0.5185577
[33,] 0.48103679 0.9620736 0.5189632
[34,] 0.44959176 0.8991835 0.5504082
[35,] 0.57141979 0.8571604 0.4285802
[36,] 0.51608599 0.9678280 0.4839140
[37,] 0.45552703 0.9110541 0.5444730
[38,] 0.39403893 0.7880779 0.6059611
[39,] 0.31910755 0.6382151 0.6808924
[40,] 0.33331647 0.6666329 0.6666835
[41,] 0.27192762 0.5438552 0.7280724
[42,] 0.21090534 0.4218107 0.7890947
[43,] 0.18692706 0.3738541 0.8130729
[44,] 0.13501721 0.2700344 0.8649828
[45,] 0.09499257 0.1899851 0.9050074
[46,] 0.11387767 0.2277553 0.8861223
[47,] 0.10179051 0.2035810 0.8982095
[48,] 0.51635355 0.9672929 0.4836464
[49,] 0.38465970 0.7693194 0.6153403
[50,] 0.29702860 0.5940572 0.7029714
[51,] 0.33230355 0.6646071 0.6676965
> postscript(file="/var/www/html/rcomp/tmp/1weck1258748305.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$resid)
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/20wvx1258748305.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> plot(mysum$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/3en6l1258748305.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> hist(mysum$resid, main='Residual Histogram', xlab='values of Residuals')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/46kzq1258748305.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> densityplot(~mysum$resid,col='black',main='Residual Density Plot', xlab='values of Residuals')
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/580a91258748305.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
-32.9992725 8.1098438 12.1797813 -12.7168363 -21.7060372 -3.3920229
7 8 9 10 11 12
-22.8516463 -65.6805106 -19.9258466 0.9982089 -63.2209932 -11.0481580
13 14 15 16 17 18
-62.5181569 -68.3536801 -13.5070848 23.5911711 15.2662965 13.7987550
19 20 21 22 23 24
38.6652043 -44.8841827 14.8242815 31.9302884 -9.0968318 34.0482312
25 26 27 28 29 30
-38.1170201 12.4514018 33.5636719 7.9094481 26.0820549 5.3516135
31 32 33 34 35 36
-6.8732611 -38.0714111 15.7606685 11.1999976 5.5424360 -8.5255290
37 38 39 40 41 42
-31.8968485 31.6445758 63.8722867 28.7815088 28.2858162 28.8190938
43 44 45 46 47 48
10.7724371 -33.5312183 -3.7218290 20.2492008 -7.5656326 18.1476238
49 50 51 52 53 54
-10.0156716 -9.4978181 18.2717406 105.5899564 12.5269953 28.2165751
55 56 57 58 59 60
36.6839495 -71.7771616 -0.5593248 -30.9706866 -9.7842440 9.6738024
> postscript(file="/var/www/html/rcomp/tmp/68xhs1258748305.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 -32.9992725 NA
1 8.1098438 -32.9992725
2 12.1797813 8.1098438
3 -12.7168363 12.1797813
4 -21.7060372 -12.7168363
5 -3.3920229 -21.7060372
6 -22.8516463 -3.3920229
7 -65.6805106 -22.8516463
8 -19.9258466 -65.6805106
9 0.9982089 -19.9258466
10 -63.2209932 0.9982089
11 -11.0481580 -63.2209932
12 -62.5181569 -11.0481580
13 -68.3536801 -62.5181569
14 -13.5070848 -68.3536801
15 23.5911711 -13.5070848
16 15.2662965 23.5911711
17 13.7987550 15.2662965
18 38.6652043 13.7987550
19 -44.8841827 38.6652043
20 14.8242815 -44.8841827
21 31.9302884 14.8242815
22 -9.0968318 31.9302884
23 34.0482312 -9.0968318
24 -38.1170201 34.0482312
25 12.4514018 -38.1170201
26 33.5636719 12.4514018
27 7.9094481 33.5636719
28 26.0820549 7.9094481
29 5.3516135 26.0820549
30 -6.8732611 5.3516135
31 -38.0714111 -6.8732611
32 15.7606685 -38.0714111
33 11.1999976 15.7606685
34 5.5424360 11.1999976
35 -8.5255290 5.5424360
36 -31.8968485 -8.5255290
37 31.6445758 -31.8968485
38 63.8722867 31.6445758
39 28.7815088 63.8722867
40 28.2858162 28.7815088
41 28.8190938 28.2858162
42 10.7724371 28.8190938
43 -33.5312183 10.7724371
44 -3.7218290 -33.5312183
45 20.2492008 -3.7218290
46 -7.5656326 20.2492008
47 18.1476238 -7.5656326
48 -10.0156716 18.1476238
49 -9.4978181 -10.0156716
50 18.2717406 -9.4978181
51 105.5899564 18.2717406
52 12.5269953 105.5899564
53 28.2165751 12.5269953
54 36.6839495 28.2165751
55 -71.7771616 36.6839495
56 -0.5593248 -71.7771616
57 -30.9706866 -0.5593248
58 -9.7842440 -30.9706866
59 9.6738024 -9.7842440
60 NA 9.6738024
> dum1 <- dum[2:length(myerror),]
> dum1
lag(myerror, k = 1) myerror
[1,] 8.1098438 -32.9992725
[2,] 12.1797813 8.1098438
[3,] -12.7168363 12.1797813
[4,] -21.7060372 -12.7168363
[5,] -3.3920229 -21.7060372
[6,] -22.8516463 -3.3920229
[7,] -65.6805106 -22.8516463
[8,] -19.9258466 -65.6805106
[9,] 0.9982089 -19.9258466
[10,] -63.2209932 0.9982089
[11,] -11.0481580 -63.2209932
[12,] -62.5181569 -11.0481580
[13,] -68.3536801 -62.5181569
[14,] -13.5070848 -68.3536801
[15,] 23.5911711 -13.5070848
[16,] 15.2662965 23.5911711
[17,] 13.7987550 15.2662965
[18,] 38.6652043 13.7987550
[19,] -44.8841827 38.6652043
[20,] 14.8242815 -44.8841827
[21,] 31.9302884 14.8242815
[22,] -9.0968318 31.9302884
[23,] 34.0482312 -9.0968318
[24,] -38.1170201 34.0482312
[25,] 12.4514018 -38.1170201
[26,] 33.5636719 12.4514018
[27,] 7.9094481 33.5636719
[28,] 26.0820549 7.9094481
[29,] 5.3516135 26.0820549
[30,] -6.8732611 5.3516135
[31,] -38.0714111 -6.8732611
[32,] 15.7606685 -38.0714111
[33,] 11.1999976 15.7606685
[34,] 5.5424360 11.1999976
[35,] -8.5255290 5.5424360
[36,] -31.8968485 -8.5255290
[37,] 31.6445758 -31.8968485
[38,] 63.8722867 31.6445758
[39,] 28.7815088 63.8722867
[40,] 28.2858162 28.7815088
[41,] 28.8190938 28.2858162
[42,] 10.7724371 28.8190938
[43,] -33.5312183 10.7724371
[44,] -3.7218290 -33.5312183
[45,] 20.2492008 -3.7218290
[46,] -7.5656326 20.2492008
[47,] 18.1476238 -7.5656326
[48,] -10.0156716 18.1476238
[49,] -9.4978181 -10.0156716
[50,] 18.2717406 -9.4978181
[51,] 105.5899564 18.2717406
[52,] 12.5269953 105.5899564
[53,] 28.2165751 12.5269953
[54,] 36.6839495 28.2165751
[55,] -71.7771616 36.6839495
[56,] -0.5593248 -71.7771616
[57,] -30.9706866 -0.5593248
[58,] -9.7842440 -30.9706866
[59,] 9.6738024 -9.7842440
> z <- as.data.frame(dum1)
> z
lag(myerror, k = 1) myerror
1 8.1098438 -32.9992725
2 12.1797813 8.1098438
3 -12.7168363 12.1797813
4 -21.7060372 -12.7168363
5 -3.3920229 -21.7060372
6 -22.8516463 -3.3920229
7 -65.6805106 -22.8516463
8 -19.9258466 -65.6805106
9 0.9982089 -19.9258466
10 -63.2209932 0.9982089
11 -11.0481580 -63.2209932
12 -62.5181569 -11.0481580
13 -68.3536801 -62.5181569
14 -13.5070848 -68.3536801
15 23.5911711 -13.5070848
16 15.2662965 23.5911711
17 13.7987550 15.2662965
18 38.6652043 13.7987550
19 -44.8841827 38.6652043
20 14.8242815 -44.8841827
21 31.9302884 14.8242815
22 -9.0968318 31.9302884
23 34.0482312 -9.0968318
24 -38.1170201 34.0482312
25 12.4514018 -38.1170201
26 33.5636719 12.4514018
27 7.9094481 33.5636719
28 26.0820549 7.9094481
29 5.3516135 26.0820549
30 -6.8732611 5.3516135
31 -38.0714111 -6.8732611
32 15.7606685 -38.0714111
33 11.1999976 15.7606685
34 5.5424360 11.1999976
35 -8.5255290 5.5424360
36 -31.8968485 -8.5255290
37 31.6445758 -31.8968485
38 63.8722867 31.6445758
39 28.7815088 63.8722867
40 28.2858162 28.7815088
41 28.8190938 28.2858162
42 10.7724371 28.8190938
43 -33.5312183 10.7724371
44 -3.7218290 -33.5312183
45 20.2492008 -3.7218290
46 -7.5656326 20.2492008
47 18.1476238 -7.5656326
48 -10.0156716 18.1476238
49 -9.4978181 -10.0156716
50 18.2717406 -9.4978181
51 105.5899564 18.2717406
52 12.5269953 105.5899564
53 28.2165751 12.5269953
54 36.6839495 28.2165751
55 -71.7771616 36.6839495
56 -0.5593248 -71.7771616
57 -30.9706866 -0.5593248
58 -9.7842440 -30.9706866
59 9.6738024 -9.7842440
> 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/704ig1258748305.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> acf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/85h901258748305.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> pacf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Partial Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/96ykv1258748305.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> opar <- par(mfrow = c(2,2), oma = c(0, 0, 1.1, 0))
> plot(mylm, las = 1, sub='Residual Diagnostics')
> par(opar)
> dev.off()
null device
1
> if (n > n25) {
+ postscript(file="/var/www/html/rcomp/tmp/10ww7t1258748305.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
+ plot(kp3:nmkm3,gqarr[,2], main='Goldfeld-Quandt test',ylab='2-sided p-value',xlab='breakpoint')
+ grid()
+ dev.off()
+ }
null device
1
>
> #Note: the /var/www/html/rcomp/createtable file can be downloaded at http://www.wessa.net/cretab
> load(file="/var/www/html/rcomp/createtable")
>
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a, 'Multiple Linear Regression - Estimated Regression Equation', 1, TRUE)
> a<-table.row.end(a)
> myeq <- colnames(x)[1]
> myeq <- paste(myeq, '[t] = ', sep='')
> for (i in 1:k){
+ if (mysum$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/112tz01258748305.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/12xoq21258748305.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/13r24c1258748305.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/14a9ap1258748305.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/15x7k51258748305.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/16ad051258748305.tab")
+ }
>
> system("convert tmp/1weck1258748305.ps tmp/1weck1258748305.png")
> system("convert tmp/20wvx1258748305.ps tmp/20wvx1258748305.png")
> system("convert tmp/3en6l1258748305.ps tmp/3en6l1258748305.png")
> system("convert tmp/46kzq1258748305.ps tmp/46kzq1258748305.png")
> system("convert tmp/580a91258748305.ps tmp/580a91258748305.png")
> system("convert tmp/68xhs1258748305.ps tmp/68xhs1258748305.png")
> system("convert tmp/704ig1258748305.ps tmp/704ig1258748305.png")
> system("convert tmp/85h901258748305.ps tmp/85h901258748305.png")
> system("convert tmp/96ykv1258748305.ps tmp/96ykv1258748305.png")
> system("convert tmp/10ww7t1258748305.ps tmp/10ww7t1258748305.png")
>
>
> proc.time()
user system elapsed
2.417 1.487 3.678