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(13768040.14
+ ,14731798.37
+ ,17487530.67
+ ,16471559.62
+ ,16198106.13
+ ,15213975.95
+ ,17535166.38
+ ,17637387.4
+ ,16571771.60
+ ,17972385.83
+ ,16198892.67
+ ,16896235.55
+ ,16554237.93
+ ,16697955.94
+ ,19554176.37
+ ,19691579.52
+ ,15903762.33
+ ,15930700.75
+ ,18003781.65
+ ,17444615.98
+ ,18329610.38
+ ,17699369.88
+ ,16260733.42
+ ,15189796.81
+ ,14851949.20
+ ,15672722.75
+ ,18174068.44
+ ,17180794.3
+ ,18406552.23
+ ,17664893.45
+ ,18466459.42
+ ,17862884.98
+ ,16016524.60
+ ,16162288.88
+ ,17428458.32
+ ,17463628.82
+ ,17167191.42
+ ,16772112.17
+ ,19629987.60
+ ,19106861.48
+ ,17183629.01
+ ,16721314.25
+ ,18344657.85
+ ,18161267.85
+ ,19301440.71
+ ,18509941.2
+ ,18147463.68
+ ,17802737.97
+ ,16192909.22
+ ,16409869.75
+ ,18374420.60
+ ,17967742.04
+ ,20515191.95
+ ,20286602.27
+ ,18957217.20
+ ,19537280.81
+ ,16471529.53
+ ,18021889.62
+ ,18746813.27
+ ,20194317.23
+ ,19009453.59
+ ,19049596.62
+ ,19211178.55
+ ,20244720.94
+ ,20547653.75
+ ,21473302.24
+ ,19325754.03
+ ,19673603.19
+ ,20605542.58
+ ,21053177.29
+ ,20056915.06
+ ,20159479.84
+ ,16141449.72
+ ,18203628.31
+ ,20359793.22
+ ,21289464.94
+ ,19711553.27
+ ,20432335.71
+ ,15638580.70
+ ,17180395.07
+ ,14384486.00
+ ,15816786.32
+ ,13855616.12
+ ,15071819.75
+ ,14308336.46
+ ,14521120.61
+ ,15290621.44
+ ,15668789.39
+ ,14423755.53
+ ,14346884.11
+ ,13779681.49
+ ,13881008.13
+ ,15686348.94
+ ,15465943.69
+ ,14733828.17
+ ,14238232.92
+ ,12522497.94
+ ,13557713.21
+ ,16189383.57
+ ,16127590.29
+ ,16059123.25
+ ,16793894.2
+ ,16007123.26
+ ,16014007.43
+ ,15806842.33
+ ,16867867.15
+ ,15159951.13
+ ,16014583.21
+ ,15692144.17
+ ,15878594.85
+ ,18908869.11
+ ,18664899.14
+ ,16969881.42
+ ,17962530.06
+ ,16997477.78
+ ,17332692.2
+ ,19858875.65
+ ,19542066.35
+ ,17681170.13
+ ,17203555.19)
+ ,dim=c(2
+ ,60)
+ ,dimnames=list(c('Uitvoer'
+ ,'Invoer')
+ ,1:60))
> y <- array(NA,dim=c(2,60),dimnames=list(c('Uitvoer','Invoer'),1:60))
> for (i in 1:dim(x)[1])
+ {
+ for (j in 1:dim(x)[2])
+ {
+ y[i,j] <- as.numeric(x[i,j])
+ }
+ }
> par20 = ''
> par19 = ''
> par18 = ''
> par17 = ''
> par16 = ''
> par15 = ''
> par14 = ''
> par13 = ''
> par12 = ''
> par11 = ''
> par10 = ''
> par9 = ''
> par8 = ''
> par7 = ''
> par6 = ''
> par5 = ''
> par4 = ''
> par3 = 'No Linear Trend'
> par2 = 'Do not include Seasonal Dummies'
> par1 = '2'
> ylab = ''
> xlab = ''
> main = ''
> #'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
Invoer Uitvoer
1 14731798 13768040
2 16471560 17487531
3 15213976 16198106
4 17637387 17535166
5 17972386 16571772
6 16896236 16198893
7 16697956 16554238
8 19691580 19554176
9 15930701 15903762
10 17444616 18003782
11 17699370 18329610
12 15189797 16260733
13 15672723 14851949
14 17180794 18174068
15 17664893 18406552
16 17862885 18466459
17 16162289 16016525
18 17463629 17428458
19 16772112 17167191
20 19106861 19629988
21 16721314 17183629
22 18161268 18344658
23 18509941 19301441
24 17802738 18147464
25 16409870 16192909
26 17967742 18374421
27 20286602 20515192
28 19537281 18957217
29 18021890 16471530
30 20194317 18746813
31 19049597 19009454
32 20244721 19211179
33 21473302 20547654
34 19673603 19325754
35 21053177 20605543
36 20159480 20056915
37 18203628 16141450
38 21289465 20359793
39 20432336 19711553
40 17180395 15638581
41 15816786 14384486
42 15071820 13855616
43 14521121 14308336
44 15668789 15290621
45 14346884 14423756
46 13881008 13779681
47 15465944 15686349
48 14238233 14733828
49 13557713 12522498
50 16127590 16189384
51 16793894 16059123
52 16014007 16007123
53 16867867 15806842
54 16014583 15159951
55 15878595 15692144
56 18664899 18908869
57 17962530 16969881
58 17332692 16997478
59 19542066 19858876
60 17203555 17681170
> k <- length(x[1,])
> df <- as.data.frame(x)
> (mylm <- lm(df))
Call:
lm(formula = df)
Coefficients:
(Intercept) Uitvoer
1.841e+06 9.055e-01
> (mysum <- summary(mylm))
Call:
lm(formula = df)
Residuals:
Min 1Q Median 3Q Max
-1375030 -521914 -131644 467584 1746814
Coefficients:
Estimate Std. Error t value Pr(>|t|)
(Intercept) 1.841e+06 8.229e+05 2.237 0.0292 *
Uitvoer 9.055e-01 4.764e-02 19.008 <2e-16 ***
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
Residual standard error: 728000 on 58 degrees of freedom
Multiple R-squared: 0.8617, Adjusted R-squared: 0.8593
F-statistic: 361.3 on 1 and 58 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,] 0.9397157 0.12056861 0.06028430
[2,] 0.9022520 0.19549602 0.09774801
[3,] 0.8305125 0.33897491 0.16948746
[4,] 0.7944851 0.41102979 0.20551489
[5,] 0.7132356 0.57352881 0.28676441
[6,] 0.6555055 0.68898902 0.34449451
[7,] 0.5930825 0.81383510 0.40691755
[8,] 0.7425348 0.51493042 0.25746521
[9,] 0.6864176 0.62716480 0.31358240
[10,] 0.6993614 0.60127724 0.30063862
[11,] 0.6614054 0.67718921 0.33859460
[12,] 0.6096911 0.78061780 0.39030890
[13,] 0.5276985 0.94460291 0.47230145
[14,] 0.4565338 0.91306755 0.54346623
[15,] 0.4085329 0.81706575 0.59146713
[16,] 0.3663515 0.73270306 0.63364847
[17,] 0.3388672 0.67773430 0.66113285
[18,] 0.2903063 0.58061253 0.70969373
[19,] 0.2889647 0.57792940 0.71103530
[20,] 0.2561902 0.51238042 0.74380979
[21,] 0.2034957 0.40699132 0.79650434
[22,] 0.1858955 0.37179093 0.81410454
[23,] 0.1958689 0.39173783 0.80413108
[24,] 0.2379180 0.47583599 0.76208200
[25,] 0.4462975 0.89259509 0.55370246
[26,] 0.6999569 0.60008621 0.30004311
[27,] 0.6508854 0.69822915 0.34911458
[28,] 0.7166107 0.56677859 0.28338930
[29,] 0.7595998 0.48080046 0.24040023
[30,] 0.7057081 0.58858381 0.29429191
[31,] 0.6584521 0.68309570 0.34154785
[32,] 0.5874620 0.82507592 0.41253796
[33,] 0.8717290 0.25654195 0.12827097
[34,] 0.8974459 0.20510819 0.10255410
[35,] 0.9082386 0.18352278 0.09176139
[36,] 0.9612691 0.07746188 0.03873094
[37,] 0.9768808 0.04623843 0.02311921
[38,] 0.9797212 0.04055763 0.02027881
[39,] 0.9673596 0.06528087 0.03264043
[40,] 0.9462714 0.10745725 0.05372863
[41,] 0.9352386 0.12952272 0.06476136
[42,] 0.9186532 0.16269353 0.08134676
[43,] 0.9101037 0.17979268 0.08989634
[44,] 0.9737755 0.05244892 0.02622446
[45,] 0.9541996 0.09160085 0.04580042
[46,] 0.9469798 0.10604044 0.05302022
[47,] 0.9100248 0.17995048 0.08997524
[48,] 0.8992954 0.20140918 0.10070459
[49,] 0.8702126 0.25957474 0.12978737
[50,] 0.7754658 0.44906844 0.22453422
[51,] 0.6907458 0.61850832 0.30925416
> postscript(file="/var/www/html/rcomp/tmp/14qd11290501644.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$resid)
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/2xzul1290501644.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> plot(mysum$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/3xzul1290501644.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> hist(mysum$resid, main='Residual Histogram', xlab='values of Residuals')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/4xzul1290501644.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> densityplot(~mysum$resid,col='black',main='Residual Density Plot', xlab='values of Residuals')
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/589tp1290501644.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
424112.641 -1204135.031 -1294141.228 -81441.518 1125913.539 387406.158
7 8 9 10 11 12
-132639.564 144531.494 -310887.306 -698545.356 -738830.269 -1375029.552
13 14 15 16 17 18
383554.381 -1116562.194 -842977.756 -699232.352 -181405.722 -158575.656
19 20 21 22 23 24
-613514.408 -508833.824 -679196.611 -290557.824 -808253.990 -470527.840
25 26 27 28 29 30
-93541.612 -511033.886 -130648.012 530780.957 1266186.800 1378338.715
31 32 33 34 35 36
-4203.428 1008258.385 1026657.709 333392.222 554114.264 157200.545
37 38 39 40 41 42
1746813.667 1012928.636 742782.467 1178929.710 950907.166 684833.730
43 44 45 46 47 48
-275804.926 -17597.901 -554553.711 -437218.874 -578775.943 -943976.531
49 50 51 52 53 54
377869.374 -372628.586 411626.403 -321174.233 714040.421 446518.245
55 56 57 58 59 60
-171372.379 -297821.385 755568.231 100741.791 -280887.714 -647480.526
> postscript(file="/var/www/html/rcomp/tmp/689tp1290501644.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 424112.641 NA
1 -1204135.031 424112.641
2 -1294141.228 -1204135.031
3 -81441.518 -1294141.228
4 1125913.539 -81441.518
5 387406.158 1125913.539
6 -132639.564 387406.158
7 144531.494 -132639.564
8 -310887.306 144531.494
9 -698545.356 -310887.306
10 -738830.269 -698545.356
11 -1375029.552 -738830.269
12 383554.381 -1375029.552
13 -1116562.194 383554.381
14 -842977.756 -1116562.194
15 -699232.352 -842977.756
16 -181405.722 -699232.352
17 -158575.656 -181405.722
18 -613514.408 -158575.656
19 -508833.824 -613514.408
20 -679196.611 -508833.824
21 -290557.824 -679196.611
22 -808253.990 -290557.824
23 -470527.840 -808253.990
24 -93541.612 -470527.840
25 -511033.886 -93541.612
26 -130648.012 -511033.886
27 530780.957 -130648.012
28 1266186.800 530780.957
29 1378338.715 1266186.800
30 -4203.428 1378338.715
31 1008258.385 -4203.428
32 1026657.709 1008258.385
33 333392.222 1026657.709
34 554114.264 333392.222
35 157200.545 554114.264
36 1746813.667 157200.545
37 1012928.636 1746813.667
38 742782.467 1012928.636
39 1178929.710 742782.467
40 950907.166 1178929.710
41 684833.730 950907.166
42 -275804.926 684833.730
43 -17597.901 -275804.926
44 -554553.711 -17597.901
45 -437218.874 -554553.711
46 -578775.943 -437218.874
47 -943976.531 -578775.943
48 377869.374 -943976.531
49 -372628.586 377869.374
50 411626.403 -372628.586
51 -321174.233 411626.403
52 714040.421 -321174.233
53 446518.245 714040.421
54 -171372.379 446518.245
55 -297821.385 -171372.379
56 755568.231 -297821.385
57 100741.791 755568.231
58 -280887.714 100741.791
59 -647480.526 -280887.714
60 NA -647480.526
> dum1 <- dum[2:length(myerror),]
> dum1
lag(myerror, k = 1) myerror
[1,] -1204135.031 424112.641
[2,] -1294141.228 -1204135.031
[3,] -81441.518 -1294141.228
[4,] 1125913.539 -81441.518
[5,] 387406.158 1125913.539
[6,] -132639.564 387406.158
[7,] 144531.494 -132639.564
[8,] -310887.306 144531.494
[9,] -698545.356 -310887.306
[10,] -738830.269 -698545.356
[11,] -1375029.552 -738830.269
[12,] 383554.381 -1375029.552
[13,] -1116562.194 383554.381
[14,] -842977.756 -1116562.194
[15,] -699232.352 -842977.756
[16,] -181405.722 -699232.352
[17,] -158575.656 -181405.722
[18,] -613514.408 -158575.656
[19,] -508833.824 -613514.408
[20,] -679196.611 -508833.824
[21,] -290557.824 -679196.611
[22,] -808253.990 -290557.824
[23,] -470527.840 -808253.990
[24,] -93541.612 -470527.840
[25,] -511033.886 -93541.612
[26,] -130648.012 -511033.886
[27,] 530780.957 -130648.012
[28,] 1266186.800 530780.957
[29,] 1378338.715 1266186.800
[30,] -4203.428 1378338.715
[31,] 1008258.385 -4203.428
[32,] 1026657.709 1008258.385
[33,] 333392.222 1026657.709
[34,] 554114.264 333392.222
[35,] 157200.545 554114.264
[36,] 1746813.667 157200.545
[37,] 1012928.636 1746813.667
[38,] 742782.467 1012928.636
[39,] 1178929.710 742782.467
[40,] 950907.166 1178929.710
[41,] 684833.730 950907.166
[42,] -275804.926 684833.730
[43,] -17597.901 -275804.926
[44,] -554553.711 -17597.901
[45,] -437218.874 -554553.711
[46,] -578775.943 -437218.874
[47,] -943976.531 -578775.943
[48,] 377869.374 -943976.531
[49,] -372628.586 377869.374
[50,] 411626.403 -372628.586
[51,] -321174.233 411626.403
[52,] 714040.421 -321174.233
[53,] 446518.245 714040.421
[54,] -171372.379 446518.245
[55,] -297821.385 -171372.379
[56,] 755568.231 -297821.385
[57,] 100741.791 755568.231
[58,] -280887.714 100741.791
[59,] -647480.526 -280887.714
> z <- as.data.frame(dum1)
> z
lag(myerror, k = 1) myerror
1 -1204135.031 424112.641
2 -1294141.228 -1204135.031
3 -81441.518 -1294141.228
4 1125913.539 -81441.518
5 387406.158 1125913.539
6 -132639.564 387406.158
7 144531.494 -132639.564
8 -310887.306 144531.494
9 -698545.356 -310887.306
10 -738830.269 -698545.356
11 -1375029.552 -738830.269
12 383554.381 -1375029.552
13 -1116562.194 383554.381
14 -842977.756 -1116562.194
15 -699232.352 -842977.756
16 -181405.722 -699232.352
17 -158575.656 -181405.722
18 -613514.408 -158575.656
19 -508833.824 -613514.408
20 -679196.611 -508833.824
21 -290557.824 -679196.611
22 -808253.990 -290557.824
23 -470527.840 -808253.990
24 -93541.612 -470527.840
25 -511033.886 -93541.612
26 -130648.012 -511033.886
27 530780.957 -130648.012
28 1266186.800 530780.957
29 1378338.715 1266186.800
30 -4203.428 1378338.715
31 1008258.385 -4203.428
32 1026657.709 1008258.385
33 333392.222 1026657.709
34 554114.264 333392.222
35 157200.545 554114.264
36 1746813.667 157200.545
37 1012928.636 1746813.667
38 742782.467 1012928.636
39 1178929.710 742782.467
40 950907.166 1178929.710
41 684833.730 950907.166
42 -275804.926 684833.730
43 -17597.901 -275804.926
44 -554553.711 -17597.901
45 -437218.874 -554553.711
46 -578775.943 -437218.874
47 -943976.531 -578775.943
48 377869.374 -943976.531
49 -372628.586 377869.374
50 411626.403 -372628.586
51 -321174.233 411626.403
52 714040.421 -321174.233
53 446518.245 714040.421
54 -171372.379 446518.245
55 -297821.385 -171372.379
56 755568.231 -297821.385
57 100741.791 755568.231
58 -280887.714 100741.791
59 -647480.526 -280887.714
> 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/7j0br1290501644.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> acf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/8j0br1290501644.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> pacf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Partial Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/9brac1290501644.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> opar <- par(mfrow = c(2,2), oma = c(0, 0, 1.1, 0))
> plot(mylm, las = 1, sub='Residual Diagnostics')
> par(opar)
> dev.off()
null device
1
> if (n > n25) {
+ postscript(file="/var/www/html/rcomp/tmp/10brac1290501644.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
+ plot(kp3:nmkm3,gqarr[,2], main='Goldfeld-Quandt test',ylab='2-sided p-value',xlab='breakpoint')
+ grid()
+ dev.off()
+ }
null device
1
>
> #Note: the /var/www/html/rcomp/createtable file can be downloaded at http://www.wessa.net/cretab
> load(file="/var/www/html/rcomp/createtable")
>
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a, 'Multiple Linear Regression - Estimated Regression Equation', 1, TRUE)
> a<-table.row.end(a)
> myeq <- colnames(x)[1]
> myeq <- paste(myeq, '[t] = ', sep='')
> for (i in 1:k){
+ if (mysum$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/11xaq01290501644.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/120spo1290501644.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/137tm01290501644.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/14ill31290501644.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/153lkr1290501644.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/16hdh01290501644.tab")
+ }
>
> try(system("convert tmp/14qd11290501644.ps tmp/14qd11290501644.png",intern=TRUE))
character(0)
> try(system("convert tmp/2xzul1290501644.ps tmp/2xzul1290501644.png",intern=TRUE))
character(0)
> try(system("convert tmp/3xzul1290501644.ps tmp/3xzul1290501644.png",intern=TRUE))
character(0)
> try(system("convert tmp/4xzul1290501644.ps tmp/4xzul1290501644.png",intern=TRUE))
character(0)
> try(system("convert tmp/589tp1290501644.ps tmp/589tp1290501644.png",intern=TRUE))
character(0)
> try(system("convert tmp/689tp1290501644.ps tmp/689tp1290501644.png",intern=TRUE))
character(0)
> try(system("convert tmp/7j0br1290501644.ps tmp/7j0br1290501644.png",intern=TRUE))
character(0)
> try(system("convert tmp/8j0br1290501644.ps tmp/8j0br1290501644.png",intern=TRUE))
character(0)
> try(system("convert tmp/9brac1290501644.ps tmp/9brac1290501644.png",intern=TRUE))
character(0)
> try(system("convert tmp/10brac1290501644.ps tmp/10brac1290501644.png",intern=TRUE))
character(0)
>
>
> proc.time()
user system elapsed
2.532 1.603 6.857