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(7291,4071,6820,4351,8031,4871,7862,4649,7357,4922,7213,4879,7079,4853,7012,4545,7319,4733,8148,5191,7599,4983,6908,4593,7878,4656,7407,4513,7911,4857,7323,4681,7179,4897,6758,4547,6934,4692,6696,4390,7688,5341,8296,5415,7697,4890,7907,5120,7592,4422,7710,4797,9011,5689,8225,5171,7733,4265,8062,5215,7859,4874,8221,4590,8330,4994,8868,4988,9053,5110,8811,5141,8120,4395,7953,4523,8878,5306,8601,5365,8361,5496,9116,5647,9310,5443,9891,5546,10147,5912,10317,5665,10682,5963,10276,5861,10614,5366,9413,5619,11068,6721,9772,6054,10350,6619,10541,6856,10049,6193,10714,6317,10759,6618,11684,6585,11462,6852,10485,6586,11056,6154,10184,6193,11082,7606,10554,6588,11315,7143,10847,7629,11104,7041,11026,7146,11073,7200,12073,7739,12328,7953,11172,7082),dim=c(2,72),dimnames=list(c('UivEU','InvnietEU'),1:72))
> y <- array(NA,dim=c(2,72),dimnames=list(c('UivEU','InvnietEU'),1:72))
> 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
UivEU InvnietEU
1 7291 4071
2 6820 4351
3 8031 4871
4 7862 4649
5 7357 4922
6 7213 4879
7 7079 4853
8 7012 4545
9 7319 4733
10 8148 5191
11 7599 4983
12 6908 4593
13 7878 4656
14 7407 4513
15 7911 4857
16 7323 4681
17 7179 4897
18 6758 4547
19 6934 4692
20 6696 4390
21 7688 5341
22 8296 5415
23 7697 4890
24 7907 5120
25 7592 4422
26 7710 4797
27 9011 5689
28 8225 5171
29 7733 4265
30 8062 5215
31 7859 4874
32 8221 4590
33 8330 4994
34 8868 4988
35 9053 5110
36 8811 5141
37 8120 4395
38 7953 4523
39 8878 5306
40 8601 5365
41 8361 5496
42 9116 5647
43 9310 5443
44 9891 5546
45 10147 5912
46 10317 5665
47 10682 5963
48 10276 5861
49 10614 5366
50 9413 5619
51 11068 6721
52 9772 6054
53 10350 6619
54 10541 6856
55 10049 6193
56 10714 6317
57 10759 6618
58 11684 6585
59 11462 6852
60 10485 6586
61 11056 6154
62 10184 6193
63 11082 7606
64 10554 6588
65 11315 7143
66 10847 7629
67 11104 7041
68 11026 7146
69 11073 7200
70 12073 7739
71 12328 7953
72 11172 7082
> k <- length(x[1,])
> df <- as.data.frame(x)
> (mylm <- lm(df))
Call:
lm(formula = df)
Coefficients:
(Intercept) InvnietEU
803.321 1.478
> (mysum <- summary(mylm))
Call:
lm(formula = df)
Residuals:
Min 1Q Median 3Q Max
-1228.71 -420.89 -66.74 424.68 1882.03
Coefficients:
Estimate Std. Error t value Pr(>|t|)
(Intercept) 803.32051 414.63001 1.937 0.0567 .
InvnietEU 1.47757 0.07334 20.147 <2e-16 ***
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
Residual standard error: 611.2 on 70 degrees of freedom
Multiple R-squared: 0.8529, Adjusted R-squared: 0.8508
F-statistic: 405.9 on 1 and 70 DF, p-value: < 2.2e-16
> 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,] 0.34988666 0.699773311 0.650113344
[2,] 0.28650492 0.573009845 0.713495078
[3,] 0.24678025 0.493560507 0.753219747
[4,] 0.17919495 0.358389896 0.820805052
[5,] 0.10823918 0.216478357 0.891760822
[6,] 0.09978976 0.199579519 0.900210240
[7,] 0.06021605 0.120432098 0.939783951
[8,] 0.05386416 0.107728312 0.946135844
[9,] 0.05539638 0.110792763 0.944603619
[10,] 0.03331660 0.066633196 0.966683402
[11,] 0.02515582 0.050311648 0.974844176
[12,] 0.01526550 0.030530999 0.984734501
[13,] 0.01590127 0.031802531 0.984098735
[14,] 0.02191504 0.043830078 0.978084961
[15,] 0.02632621 0.052652423 0.973673789
[16,] 0.02860480 0.057209590 0.971395205
[17,] 0.03238216 0.064764311 0.967617845
[18,] 0.03100011 0.062000221 0.968999890
[19,] 0.02569215 0.051384291 0.974307855
[20,] 0.02302786 0.046055714 0.976972143
[21,] 0.02420690 0.048413790 0.975793105
[22,] 0.02180700 0.043614002 0.978192999
[23,] 0.03097644 0.061952874 0.969023563
[24,] 0.02997382 0.059947635 0.970026182
[25,] 0.04949919 0.098998377 0.950500812
[26,] 0.05483622 0.109672442 0.945163779
[27,] 0.05915763 0.118315255 0.940842373
[28,] 0.09942354 0.198847087 0.900576456
[29,] 0.11322706 0.226454113 0.886772943
[30,] 0.19954860 0.399097201 0.800451400
[31,] 0.29059031 0.581180626 0.709409687
[32,] 0.30852299 0.617045970 0.691477015
[33,] 0.34818451 0.696369026 0.651815487
[34,] 0.35645134 0.712902680 0.643548660
[35,] 0.36369128 0.727382551 0.636308724
[36,] 0.41297969 0.825959387 0.587020306
[37,] 0.65505190 0.689896206 0.344948103
[38,] 0.73679705 0.526405907 0.263202954
[39,] 0.78921372 0.421572567 0.210786283
[40,] 0.83034330 0.339313407 0.169656704
[41,] 0.82136990 0.357260208 0.178630104
[42,] 0.85351616 0.292967681 0.146483841
[43,] 0.86706080 0.265878392 0.132939196
[44,] 0.84023619 0.319527616 0.159763808
[45,] 0.95860325 0.082793499 0.041396750
[46,] 0.95114924 0.097701524 0.048850762
[47,] 0.93304525 0.133909497 0.066954749
[48,] 0.93117712 0.137645756 0.068822878
[49,] 0.92724943 0.145501146 0.072750573
[50,] 0.92548197 0.149036052 0.074518026
[51,] 0.92145329 0.157093417 0.078546708
[52,] 0.88540155 0.229196897 0.114598448
[53,] 0.83738562 0.325228769 0.162614385
[54,] 0.91968886 0.160622279 0.080311139
[55,] 0.91879190 0.162416206 0.081208103
[56,] 0.88652583 0.226948343 0.113474171
[57,] 0.94764704 0.104705916 0.052352958
[58,] 0.90683956 0.186320887 0.093160443
[59,] 0.92974512 0.140509754 0.070254877
[60,] 0.87121960 0.257560808 0.128780404
[61,] 0.79770568 0.404588637 0.202294319
[62,] 0.99652978 0.006940445 0.003470223
[63,] 0.98825850 0.023482994 0.011741497
> postscript(file="/var/www/html/rcomp/tmp/142fp1258559504.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$resid)
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/22jtq1258559504.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> plot(mysum$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/38e5l1258559504.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> hist(mysum$resid, main='Residual Histogram', xlab='values of Residuals')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/4qs2q1258559504.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> densityplot(~mysum$resid,col='black',main='Residual Density Plot', xlab='values of Residuals')
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/5n1sb1258559504.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 = 72
Frequency = 1
1 2 3 4 5 6
472.48576 -412.23427 30.42853 189.44941 -718.92762 -799.39205
7 8 9 10 11 12
-894.97519 -506.88315 -477.66660 -325.39437 -567.05949 -681.80659
13 14 15 16 17 18
195.10641 -64.60086 -68.88547 -396.83288 -859.98833 -763.83830
19 20 21 22 23 24
-802.08617 -593.85956 -1007.03010 -508.37039 -331.64533 -461.48679
25 26 27 28 29 30
254.85815 -181.23118 -198.22499 -218.84294 627.83688 -446.85608
31 32 33 34 35 36
-146.00419 635.62613 147.68723 694.55266 699.28893 411.48421
37 38 39 40 41 42
822.75258 466.62342 234.68491 -129.49181 -563.05369 -31.16699
43 44 45 46 47 48
464.25761 893.06774 608.27655 1143.23672 1067.92040 812.63270
49 50 51 52 53 54
1882.03061 307.20501 333.92118 23.46139 -233.36652 -392.55098
55 56 57 58 59 60
95.07895 576.86008 177.11105 1150.87091 534.35931 -49.60666
61 62 63 64 65 66
1159.70424 230.07895 -959.72963 16.43819 -42.61401 -1228.71378
67 68 69 70 71 72
-102.90171 -336.04673 -368.83559 -165.24665 -226.44696 -95.48215
> postscript(file="/var/www/html/rcomp/tmp/6r61d1258559504.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 = 72
Frequency = 1
lag(myerror, k = 1) myerror
0 472.48576 NA
1 -412.23427 472.48576
2 30.42853 -412.23427
3 189.44941 30.42853
4 -718.92762 189.44941
5 -799.39205 -718.92762
6 -894.97519 -799.39205
7 -506.88315 -894.97519
8 -477.66660 -506.88315
9 -325.39437 -477.66660
10 -567.05949 -325.39437
11 -681.80659 -567.05949
12 195.10641 -681.80659
13 -64.60086 195.10641
14 -68.88547 -64.60086
15 -396.83288 -68.88547
16 -859.98833 -396.83288
17 -763.83830 -859.98833
18 -802.08617 -763.83830
19 -593.85956 -802.08617
20 -1007.03010 -593.85956
21 -508.37039 -1007.03010
22 -331.64533 -508.37039
23 -461.48679 -331.64533
24 254.85815 -461.48679
25 -181.23118 254.85815
26 -198.22499 -181.23118
27 -218.84294 -198.22499
28 627.83688 -218.84294
29 -446.85608 627.83688
30 -146.00419 -446.85608
31 635.62613 -146.00419
32 147.68723 635.62613
33 694.55266 147.68723
34 699.28893 694.55266
35 411.48421 699.28893
36 822.75258 411.48421
37 466.62342 822.75258
38 234.68491 466.62342
39 -129.49181 234.68491
40 -563.05369 -129.49181
41 -31.16699 -563.05369
42 464.25761 -31.16699
43 893.06774 464.25761
44 608.27655 893.06774
45 1143.23672 608.27655
46 1067.92040 1143.23672
47 812.63270 1067.92040
48 1882.03061 812.63270
49 307.20501 1882.03061
50 333.92118 307.20501
51 23.46139 333.92118
52 -233.36652 23.46139
53 -392.55098 -233.36652
54 95.07895 -392.55098
55 576.86008 95.07895
56 177.11105 576.86008
57 1150.87091 177.11105
58 534.35931 1150.87091
59 -49.60666 534.35931
60 1159.70424 -49.60666
61 230.07895 1159.70424
62 -959.72963 230.07895
63 16.43819 -959.72963
64 -42.61401 16.43819
65 -1228.71378 -42.61401
66 -102.90171 -1228.71378
67 -336.04673 -102.90171
68 -368.83559 -336.04673
69 -165.24665 -368.83559
70 -226.44696 -165.24665
71 -95.48215 -226.44696
72 NA -95.48215
> dum1 <- dum[2:length(myerror),]
> dum1
lag(myerror, k = 1) myerror
[1,] -412.23427 472.48576
[2,] 30.42853 -412.23427
[3,] 189.44941 30.42853
[4,] -718.92762 189.44941
[5,] -799.39205 -718.92762
[6,] -894.97519 -799.39205
[7,] -506.88315 -894.97519
[8,] -477.66660 -506.88315
[9,] -325.39437 -477.66660
[10,] -567.05949 -325.39437
[11,] -681.80659 -567.05949
[12,] 195.10641 -681.80659
[13,] -64.60086 195.10641
[14,] -68.88547 -64.60086
[15,] -396.83288 -68.88547
[16,] -859.98833 -396.83288
[17,] -763.83830 -859.98833
[18,] -802.08617 -763.83830
[19,] -593.85956 -802.08617
[20,] -1007.03010 -593.85956
[21,] -508.37039 -1007.03010
[22,] -331.64533 -508.37039
[23,] -461.48679 -331.64533
[24,] 254.85815 -461.48679
[25,] -181.23118 254.85815
[26,] -198.22499 -181.23118
[27,] -218.84294 -198.22499
[28,] 627.83688 -218.84294
[29,] -446.85608 627.83688
[30,] -146.00419 -446.85608
[31,] 635.62613 -146.00419
[32,] 147.68723 635.62613
[33,] 694.55266 147.68723
[34,] 699.28893 694.55266
[35,] 411.48421 699.28893
[36,] 822.75258 411.48421
[37,] 466.62342 822.75258
[38,] 234.68491 466.62342
[39,] -129.49181 234.68491
[40,] -563.05369 -129.49181
[41,] -31.16699 -563.05369
[42,] 464.25761 -31.16699
[43,] 893.06774 464.25761
[44,] 608.27655 893.06774
[45,] 1143.23672 608.27655
[46,] 1067.92040 1143.23672
[47,] 812.63270 1067.92040
[48,] 1882.03061 812.63270
[49,] 307.20501 1882.03061
[50,] 333.92118 307.20501
[51,] 23.46139 333.92118
[52,] -233.36652 23.46139
[53,] -392.55098 -233.36652
[54,] 95.07895 -392.55098
[55,] 576.86008 95.07895
[56,] 177.11105 576.86008
[57,] 1150.87091 177.11105
[58,] 534.35931 1150.87091
[59,] -49.60666 534.35931
[60,] 1159.70424 -49.60666
[61,] 230.07895 1159.70424
[62,] -959.72963 230.07895
[63,] 16.43819 -959.72963
[64,] -42.61401 16.43819
[65,] -1228.71378 -42.61401
[66,] -102.90171 -1228.71378
[67,] -336.04673 -102.90171
[68,] -368.83559 -336.04673
[69,] -165.24665 -368.83559
[70,] -226.44696 -165.24665
[71,] -95.48215 -226.44696
> z <- as.data.frame(dum1)
> z
lag(myerror, k = 1) myerror
1 -412.23427 472.48576
2 30.42853 -412.23427
3 189.44941 30.42853
4 -718.92762 189.44941
5 -799.39205 -718.92762
6 -894.97519 -799.39205
7 -506.88315 -894.97519
8 -477.66660 -506.88315
9 -325.39437 -477.66660
10 -567.05949 -325.39437
11 -681.80659 -567.05949
12 195.10641 -681.80659
13 -64.60086 195.10641
14 -68.88547 -64.60086
15 -396.83288 -68.88547
16 -859.98833 -396.83288
17 -763.83830 -859.98833
18 -802.08617 -763.83830
19 -593.85956 -802.08617
20 -1007.03010 -593.85956
21 -508.37039 -1007.03010
22 -331.64533 -508.37039
23 -461.48679 -331.64533
24 254.85815 -461.48679
25 -181.23118 254.85815
26 -198.22499 -181.23118
27 -218.84294 -198.22499
28 627.83688 -218.84294
29 -446.85608 627.83688
30 -146.00419 -446.85608
31 635.62613 -146.00419
32 147.68723 635.62613
33 694.55266 147.68723
34 699.28893 694.55266
35 411.48421 699.28893
36 822.75258 411.48421
37 466.62342 822.75258
38 234.68491 466.62342
39 -129.49181 234.68491
40 -563.05369 -129.49181
41 -31.16699 -563.05369
42 464.25761 -31.16699
43 893.06774 464.25761
44 608.27655 893.06774
45 1143.23672 608.27655
46 1067.92040 1143.23672
47 812.63270 1067.92040
48 1882.03061 812.63270
49 307.20501 1882.03061
50 333.92118 307.20501
51 23.46139 333.92118
52 -233.36652 23.46139
53 -392.55098 -233.36652
54 95.07895 -392.55098
55 576.86008 95.07895
56 177.11105 576.86008
57 1150.87091 177.11105
58 534.35931 1150.87091
59 -49.60666 534.35931
60 1159.70424 -49.60666
61 230.07895 1159.70424
62 -959.72963 230.07895
63 16.43819 -959.72963
64 -42.61401 16.43819
65 -1228.71378 -42.61401
66 -102.90171 -1228.71378
67 -336.04673 -102.90171
68 -368.83559 -336.04673
69 -165.24665 -368.83559
70 -226.44696 -165.24665
71 -95.48215 -226.44696
> 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/78c0l1258559504.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> acf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/8p6j11258559504.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> pacf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Partial Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/99pe41258559504.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> opar <- par(mfrow = c(2,2), oma = c(0, 0, 1.1, 0))
> plot(mylm, las = 1, sub='Residual Diagnostics')
> par(opar)
> dev.off()
null device
1
> if (n > n25) {
+ postscript(file="/var/www/html/rcomp/tmp/1072lr1258559504.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
+ plot(kp3:nmkm3,gqarr[,2], main='Goldfeld-Quandt test',ylab='2-sided p-value',xlab='breakpoint')
+ grid()
+ dev.off()
+ }
null device
1
>
> #Note: the /var/www/html/rcomp/createtable file can be downloaded at http://www.wessa.net/cretab
> load(file="/var/www/html/rcomp/createtable")
>
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a, 'Multiple Linear Regression - Estimated Regression Equation', 1, TRUE)
> a<-table.row.end(a)
> myeq <- colnames(x)[1]
> myeq <- paste(myeq, '[t] = ', sep='')
> for (i in 1:k){
+ if (mysum$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/11jbj11258559504.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/12985y1258559504.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/13ekv81258559504.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/1486np1258559504.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/15khow1258559504.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/16omra1258559504.tab")
+ }
>
> system("convert tmp/142fp1258559504.ps tmp/142fp1258559504.png")
> system("convert tmp/22jtq1258559504.ps tmp/22jtq1258559504.png")
> system("convert tmp/38e5l1258559504.ps tmp/38e5l1258559504.png")
> system("convert tmp/4qs2q1258559504.ps tmp/4qs2q1258559504.png")
> system("convert tmp/5n1sb1258559504.ps tmp/5n1sb1258559504.png")
> system("convert tmp/6r61d1258559504.ps tmp/6r61d1258559504.png")
> system("convert tmp/78c0l1258559504.ps tmp/78c0l1258559504.png")
> system("convert tmp/8p6j11258559504.ps tmp/8p6j11258559504.png")
> system("convert tmp/99pe41258559504.ps tmp/99pe41258559504.png")
> system("convert tmp/1072lr1258559504.ps tmp/1072lr1258559504.png")
>
>
> proc.time()
user system elapsed
2.636 1.606 3.547