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.
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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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> x <- array(list(2529,314,2196,318,3202,320,2718,323,2728,325,2354,327,2697,330,2651,331,2067,332,2641,334,2539,334,2294,334,2712,339,2314,345,3092,346,2677,352,2813,355,2668,358,2939,361,2617,363,2231,364,2481,365,2421,366,2408,370,2560,371,2100,371,3315,372,2801,373,2403,373,3024,374,2507,375,2980,375,2211,376,2471,376,2594,377,2452,377,2232,378,2373,379,3127,380,2802,384,2641,389,2787,390,2619,391,2806,392,2193,393,2323,394,2529,394,2412,395,2262,396,2154,397,3230,398,2295,399,2715,400,2733,400,2317,401,2730,401,1913,406,2390,407,2484,423,1960,427),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 = 'Linear Trend'
> par2 = 'Include Monthly 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 M1 M2 M3 M4 M5 M6 M7 M8 M9 M10 M11 t
1 2529 314 1 0 0 0 0 0 0 0 0 0 0 1
2 2196 318 0 1 0 0 0 0 0 0 0 0 0 2
3 3202 320 0 0 1 0 0 0 0 0 0 0 0 3
4 2718 323 0 0 0 1 0 0 0 0 0 0 0 4
5 2728 325 0 0 0 0 1 0 0 0 0 0 0 5
6 2354 327 0 0 0 0 0 1 0 0 0 0 0 6
7 2697 330 0 0 0 0 0 0 1 0 0 0 0 7
8 2651 331 0 0 0 0 0 0 0 1 0 0 0 8
9 2067 332 0 0 0 0 0 0 0 0 1 0 0 9
10 2641 334 0 0 0 0 0 0 0 0 0 1 0 10
11 2539 334 0 0 0 0 0 0 0 0 0 0 1 11
12 2294 334 0 0 0 0 0 0 0 0 0 0 0 12
13 2712 339 1 0 0 0 0 0 0 0 0 0 0 13
14 2314 345 0 1 0 0 0 0 0 0 0 0 0 14
15 3092 346 0 0 1 0 0 0 0 0 0 0 0 15
16 2677 352 0 0 0 1 0 0 0 0 0 0 0 16
17 2813 355 0 0 0 0 1 0 0 0 0 0 0 17
18 2668 358 0 0 0 0 0 1 0 0 0 0 0 18
19 2939 361 0 0 0 0 0 0 1 0 0 0 0 19
20 2617 363 0 0 0 0 0 0 0 1 0 0 0 20
21 2231 364 0 0 0 0 0 0 0 0 1 0 0 21
22 2481 365 0 0 0 0 0 0 0 0 0 1 0 22
23 2421 366 0 0 0 0 0 0 0 0 0 0 1 23
24 2408 370 0 0 0 0 0 0 0 0 0 0 0 24
25 2560 371 1 0 0 0 0 0 0 0 0 0 0 25
26 2100 371 0 1 0 0 0 0 0 0 0 0 0 26
27 3315 372 0 0 1 0 0 0 0 0 0 0 0 27
28 2801 373 0 0 0 1 0 0 0 0 0 0 0 28
29 2403 373 0 0 0 0 1 0 0 0 0 0 0 29
30 3024 374 0 0 0 0 0 1 0 0 0 0 0 30
31 2507 375 0 0 0 0 0 0 1 0 0 0 0 31
32 2980 375 0 0 0 0 0 0 0 1 0 0 0 32
33 2211 376 0 0 0 0 0 0 0 0 1 0 0 33
34 2471 376 0 0 0 0 0 0 0 0 0 1 0 34
35 2594 377 0 0 0 0 0 0 0 0 0 0 1 35
36 2452 377 0 0 0 0 0 0 0 0 0 0 0 36
37 2232 378 1 0 0 0 0 0 0 0 0 0 0 37
38 2373 379 0 1 0 0 0 0 0 0 0 0 0 38
39 3127 380 0 0 1 0 0 0 0 0 0 0 0 39
40 2802 384 0 0 0 1 0 0 0 0 0 0 0 40
41 2641 389 0 0 0 0 1 0 0 0 0 0 0 41
42 2787 390 0 0 0 0 0 1 0 0 0 0 0 42
43 2619 391 0 0 0 0 0 0 1 0 0 0 0 43
44 2806 392 0 0 0 0 0 0 0 1 0 0 0 44
45 2193 393 0 0 0 0 0 0 0 0 1 0 0 45
46 2323 394 0 0 0 0 0 0 0 0 0 1 0 46
47 2529 394 0 0 0 0 0 0 0 0 0 0 1 47
48 2412 395 0 0 0 0 0 0 0 0 0 0 0 48
49 2262 396 1 0 0 0 0 0 0 0 0 0 0 49
50 2154 397 0 1 0 0 0 0 0 0 0 0 0 50
51 3230 398 0 0 1 0 0 0 0 0 0 0 0 51
52 2295 399 0 0 0 1 0 0 0 0 0 0 0 52
53 2715 400 0 0 0 0 1 0 0 0 0 0 0 53
54 2733 400 0 0 0 0 0 1 0 0 0 0 0 54
55 2317 401 0 0 0 0 0 0 1 0 0 0 0 55
56 2730 401 0 0 0 0 0 0 0 1 0 0 0 56
57 1913 406 0 0 0 0 0 0 0 0 1 0 0 57
58 2390 407 0 0 0 0 0 0 0 0 0 1 0 58
59 2484 423 0 0 0 0 0 0 0 0 0 0 1 59
60 1960 427 0 0 0 0 0 0 0 0 0 0 0 60
> k <- length(x[1,])
> df <- as.data.frame(x)
> (mylm <- lm(df))
Call:
lm(formula = df)
Coefficients:
(Intercept) X M1 M2 M3 M4
1219.032 3.608 141.869 -90.417 879.026 341.574
M5 M6 M7 M8 M9 M10
343.009 399.131 303.209 449.295 -183.027 159.538
M11 t
206.722 -7.972
> (mysum <- summary(mylm))
Call:
lm(formula = df)
Residuals:
Min 1Q Median 3Q Max
-396.1 -101.3 26.4 96.9 295.6
Coefficients:
Estimate Std. Error t value Pr(>|t|)
(Intercept) 1219.032 1238.875 0.984 0.330271
X 3.608 3.808 0.948 0.348313
M1 141.869 105.916 1.339 0.187007
M2 -90.417 105.360 -0.858 0.395247
M3 879.026 105.377 8.342 9.32e-11 ***
M4 341.574 104.718 3.262 0.002089 **
M5 343.009 104.461 3.284 0.001963 **
M6 399.131 104.393 3.823 0.000394 ***
M7 303.209 104.265 2.908 0.005582 **
M8 449.295 104.366 4.305 8.66e-05 ***
M9 -183.027 104.251 -1.756 0.085807 .
M10 159.538 104.368 1.529 0.133211
M11 206.722 103.986 1.988 0.052785 .
t -7.972 6.056 -1.316 0.194557
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
Residual standard error: 164.4 on 46 degrees of freedom
Multiple R-squared: 0.7833, Adjusted R-squared: 0.722
F-statistic: 12.79 on 13 and 46 DF, p-value: 3.255e-11
> 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,] 0.2071570 0.4143140 0.7928430
[2,] 0.2716578 0.5433156 0.7283422
[3,] 0.2050387 0.4100773 0.7949613
[4,] 0.2721013 0.5442027 0.7278987
[5,] 0.1722539 0.3445077 0.8277461
[6,] 0.2433788 0.4867576 0.7566212
[7,] 0.2892629 0.5785258 0.7107371
[8,] 0.2049077 0.4098154 0.7950923
[9,] 0.2075546 0.4151093 0.7924454
[10,] 0.2425059 0.4850118 0.7574941
[11,] 0.2266667 0.4533335 0.7733333
[12,] 0.1829881 0.3659762 0.8170119
[13,] 0.5626671 0.8746657 0.4373329
[14,] 0.8567526 0.2864949 0.1432474
[15,] 0.8766011 0.2467979 0.1233989
[16,] 0.8790614 0.2418772 0.1209386
[17,] 0.8173205 0.3653591 0.1826795
[18,] 0.7560670 0.4878659 0.2439330
[19,] 0.7070564 0.5858872 0.2929436
[20,] 0.6069214 0.7861572 0.3930786
[21,] 0.6649269 0.6701462 0.3350731
[22,] 0.5761963 0.8476073 0.4238037
[23,] 0.5884050 0.8231901 0.4115950
[24,] 0.7242148 0.5515704 0.2757852
[25,] 0.6753171 0.6493658 0.3246829
[26,] 0.5406772 0.9186456 0.4593228
[27,] 0.4838893 0.9677786 0.5161107
> postscript(file="/var/www/html/rcomp/tmp/1mz9d1258719864.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$resid)
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/2fr071258719864.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> plot(mysum$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/3ue351258719864.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> hist(mysum$resid, main='Residual Histogram', xlab='values of Residuals')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/4s5nn1258719864.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> densityplot(~mysum$resid,col='black',main='Residual Density Plot', xlab='values of Residuals')
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/5hwzo1258719864.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
43.182056 -63.990626 -26.676966 23.923034 33.244619 -396.120137
7 8 9 10 11 12
39.950352 -147.771233 -95.084892 137.107182 -4.104285 -34.410018
13 14 15 16 17 18
231.653591 52.265057 -134.813357 -26.037135 105.676524 -98.296158
19 20 21 22 23 24
265.774331 -201.555180 49.131161 -39.068839 -141.888232 45.374331
25 26 27 28 29 30
59.869644 -159.871334 90.050251 117.866103 -273.596459 295.646711
31 32 33 34 35 36
-121.066948 213.819392 81.505733 6.913659 87.094267 159.788533
37 38 39 40 41 42
-197.716154 179.934943 -31.143472 174.848602 2.346409 96.589580
43 44 45 46 47 48
28.875920 74.154335 97.840676 -110.359324 56.429209 150.515550
49 50 51 52 53 54
-136.989137 -8.338041 102.583545 -290.600604 132.328908 102.180004
55 56 57 58 59 60
-213.533655 61.352686 -133.392678 5.407322 2.469040 -321.268397
> postscript(file="/var/www/html/rcomp/tmp/6qniq1258719864.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 43.182056 NA
1 -63.990626 43.182056
2 -26.676966 -63.990626
3 23.923034 -26.676966
4 33.244619 23.923034
5 -396.120137 33.244619
6 39.950352 -396.120137
7 -147.771233 39.950352
8 -95.084892 -147.771233
9 137.107182 -95.084892
10 -4.104285 137.107182
11 -34.410018 -4.104285
12 231.653591 -34.410018
13 52.265057 231.653591
14 -134.813357 52.265057
15 -26.037135 -134.813357
16 105.676524 -26.037135
17 -98.296158 105.676524
18 265.774331 -98.296158
19 -201.555180 265.774331
20 49.131161 -201.555180
21 -39.068839 49.131161
22 -141.888232 -39.068839
23 45.374331 -141.888232
24 59.869644 45.374331
25 -159.871334 59.869644
26 90.050251 -159.871334
27 117.866103 90.050251
28 -273.596459 117.866103
29 295.646711 -273.596459
30 -121.066948 295.646711
31 213.819392 -121.066948
32 81.505733 213.819392
33 6.913659 81.505733
34 87.094267 6.913659
35 159.788533 87.094267
36 -197.716154 159.788533
37 179.934943 -197.716154
38 -31.143472 179.934943
39 174.848602 -31.143472
40 2.346409 174.848602
41 96.589580 2.346409
42 28.875920 96.589580
43 74.154335 28.875920
44 97.840676 74.154335
45 -110.359324 97.840676
46 56.429209 -110.359324
47 150.515550 56.429209
48 -136.989137 150.515550
49 -8.338041 -136.989137
50 102.583545 -8.338041
51 -290.600604 102.583545
52 132.328908 -290.600604
53 102.180004 132.328908
54 -213.533655 102.180004
55 61.352686 -213.533655
56 -133.392678 61.352686
57 5.407322 -133.392678
58 2.469040 5.407322
59 -321.268397 2.469040
60 NA -321.268397
> dum1 <- dum[2:length(myerror),]
> dum1
lag(myerror, k = 1) myerror
[1,] -63.990626 43.182056
[2,] -26.676966 -63.990626
[3,] 23.923034 -26.676966
[4,] 33.244619 23.923034
[5,] -396.120137 33.244619
[6,] 39.950352 -396.120137
[7,] -147.771233 39.950352
[8,] -95.084892 -147.771233
[9,] 137.107182 -95.084892
[10,] -4.104285 137.107182
[11,] -34.410018 -4.104285
[12,] 231.653591 -34.410018
[13,] 52.265057 231.653591
[14,] -134.813357 52.265057
[15,] -26.037135 -134.813357
[16,] 105.676524 -26.037135
[17,] -98.296158 105.676524
[18,] 265.774331 -98.296158
[19,] -201.555180 265.774331
[20,] 49.131161 -201.555180
[21,] -39.068839 49.131161
[22,] -141.888232 -39.068839
[23,] 45.374331 -141.888232
[24,] 59.869644 45.374331
[25,] -159.871334 59.869644
[26,] 90.050251 -159.871334
[27,] 117.866103 90.050251
[28,] -273.596459 117.866103
[29,] 295.646711 -273.596459
[30,] -121.066948 295.646711
[31,] 213.819392 -121.066948
[32,] 81.505733 213.819392
[33,] 6.913659 81.505733
[34,] 87.094267 6.913659
[35,] 159.788533 87.094267
[36,] -197.716154 159.788533
[37,] 179.934943 -197.716154
[38,] -31.143472 179.934943
[39,] 174.848602 -31.143472
[40,] 2.346409 174.848602
[41,] 96.589580 2.346409
[42,] 28.875920 96.589580
[43,] 74.154335 28.875920
[44,] 97.840676 74.154335
[45,] -110.359324 97.840676
[46,] 56.429209 -110.359324
[47,] 150.515550 56.429209
[48,] -136.989137 150.515550
[49,] -8.338041 -136.989137
[50,] 102.583545 -8.338041
[51,] -290.600604 102.583545
[52,] 132.328908 -290.600604
[53,] 102.180004 132.328908
[54,] -213.533655 102.180004
[55,] 61.352686 -213.533655
[56,] -133.392678 61.352686
[57,] 5.407322 -133.392678
[58,] 2.469040 5.407322
[59,] -321.268397 2.469040
> z <- as.data.frame(dum1)
> z
lag(myerror, k = 1) myerror
1 -63.990626 43.182056
2 -26.676966 -63.990626
3 23.923034 -26.676966
4 33.244619 23.923034
5 -396.120137 33.244619
6 39.950352 -396.120137
7 -147.771233 39.950352
8 -95.084892 -147.771233
9 137.107182 -95.084892
10 -4.104285 137.107182
11 -34.410018 -4.104285
12 231.653591 -34.410018
13 52.265057 231.653591
14 -134.813357 52.265057
15 -26.037135 -134.813357
16 105.676524 -26.037135
17 -98.296158 105.676524
18 265.774331 -98.296158
19 -201.555180 265.774331
20 49.131161 -201.555180
21 -39.068839 49.131161
22 -141.888232 -39.068839
23 45.374331 -141.888232
24 59.869644 45.374331
25 -159.871334 59.869644
26 90.050251 -159.871334
27 117.866103 90.050251
28 -273.596459 117.866103
29 295.646711 -273.596459
30 -121.066948 295.646711
31 213.819392 -121.066948
32 81.505733 213.819392
33 6.913659 81.505733
34 87.094267 6.913659
35 159.788533 87.094267
36 -197.716154 159.788533
37 179.934943 -197.716154
38 -31.143472 179.934943
39 174.848602 -31.143472
40 2.346409 174.848602
41 96.589580 2.346409
42 28.875920 96.589580
43 74.154335 28.875920
44 97.840676 74.154335
45 -110.359324 97.840676
46 56.429209 -110.359324
47 150.515550 56.429209
48 -136.989137 150.515550
49 -8.338041 -136.989137
50 102.583545 -8.338041
51 -290.600604 102.583545
52 132.328908 -290.600604
53 102.180004 132.328908
54 -213.533655 102.180004
55 61.352686 -213.533655
56 -133.392678 61.352686
57 5.407322 -133.392678
58 2.469040 5.407322
59 -321.268397 2.469040
> 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/7p1e01258719864.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> acf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/86hsq1258719864.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> pacf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Partial Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/9ypep1258719864.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> opar <- par(mfrow = c(2,2), oma = c(0, 0, 1.1, 0))
> plot(mylm, las = 1, sub='Residual Diagnostics')
> par(opar)
> dev.off()
null device
1
> if (n > n25) {
+ postscript(file="/var/www/html/rcomp/tmp/10hjwu1258719864.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
+ plot(kp3:nmkm3,gqarr[,2], main='Goldfeld-Quandt test',ylab='2-sided p-value',xlab='breakpoint')
+ grid()
+ dev.off()
+ }
null device
1
>
> #Note: the /var/www/html/rcomp/createtable file can be downloaded at http://www.wessa.net/cretab
> load(file="/var/www/html/rcomp/createtable")
>
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a, 'Multiple Linear Regression - Estimated Regression Equation', 1, TRUE)
> a<-table.row.end(a)
> myeq <- colnames(x)[1]
> myeq <- paste(myeq, '[t] = ', sep='')
> for (i in 1:k){
+ if (mysum$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/11mftj1258719864.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/12b99j1258719864.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/130d2h1258719864.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/14d0l11258719864.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/15r0n81258719864.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/16xjmc1258719864.tab")
+ }
> system("convert tmp/1mz9d1258719864.ps tmp/1mz9d1258719864.png")
> system("convert tmp/2fr071258719864.ps tmp/2fr071258719864.png")
> system("convert tmp/3ue351258719864.ps tmp/3ue351258719864.png")
> system("convert tmp/4s5nn1258719864.ps tmp/4s5nn1258719864.png")
> system("convert tmp/5hwzo1258719864.ps tmp/5hwzo1258719864.png")
> system("convert tmp/6qniq1258719864.ps tmp/6qniq1258719864.png")
> system("convert tmp/7p1e01258719864.ps tmp/7p1e01258719864.png")
> system("convert tmp/86hsq1258719864.ps tmp/86hsq1258719864.png")
> system("convert tmp/9ypep1258719864.ps tmp/9ypep1258719864.png")
> system("convert tmp/10hjwu1258719864.ps tmp/10hjwu1258719864.png")
>
>
> proc.time()
user system elapsed
2.371 1.574 3.325