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(13132.1
+ ,12002.4
+ ,17665.9
+ ,15525.5
+ ,16913
+ ,14247.9
+ ,17318.8
+ ,15000.7
+ ,16224.2
+ ,14931.4
+ ,15469.6
+ ,13333.7
+ ,16557.5
+ ,14711.2
+ ,19414.8
+ ,17197.3
+ ,17335
+ ,14985.2
+ ,16525.2
+ ,14734.4
+ ,18160.4
+ ,15937.8
+ ,15553.8
+ ,13028.1
+ ,15262.2
+ ,13836.8
+ ,18581
+ ,16677.5
+ ,17564.1
+ ,15130
+ ,18948.6
+ ,17504
+ ,17187.8
+ ,16979.9
+ ,17564.8
+ ,16012.5
+ ,17668.4
+ ,16247.7
+ ,20811.7
+ ,19268.2
+ ,17257.8
+ ,15533
+ ,18984.2
+ ,16803.3
+ ,20532.6
+ ,17396.1
+ ,17082.3
+ ,15155.4
+ ,16894.9
+ ,15692.4
+ ,20274.9
+ ,18063.7
+ ,20078.6
+ ,17568.6
+ ,19900.9
+ ,18154.3
+ ,17012.2
+ ,15467.4
+ ,19642.9
+ ,16956.1
+ ,19024
+ ,16854
+ ,21691
+ ,19396.4
+ ,18835.9
+ ,16457.6
+ ,19873.4
+ ,17284.5
+ ,21468.2
+ ,18395.3
+ ,19406.8
+ ,16938.7
+ ,18385.3
+ ,16414.3
+ ,20739.3
+ ,18173.4
+ ,22268.3
+ ,19919.7
+ ,21569
+ ,19623.8
+ ,17514.8
+ ,17228.1
+ ,21124.7
+ ,18730.3
+ ,21251
+ ,19039.1
+ ,21393
+ ,19413.3
+ ,22145.2
+ ,20013.6
+ ,20310.5
+ ,17917.2
+ ,23466.9
+ ,21270.3
+ ,21264.6
+ ,18766.1
+ ,18388.1
+ ,16790.8
+ ,22635.4
+ ,19960.6
+ ,22014.3
+ ,19586.7
+ ,18422.7
+ ,17179
+ ,16120.2
+ ,14964.9
+ ,16037.7
+ ,13918.5
+ ,16410.7
+ ,14401.3
+ ,17749.8
+ ,15994.6
+ ,16349.8
+ ,14521.1
+ ,15662.3
+ ,13746.5
+ ,17782.3
+ ,15956
+ ,16398.9
+ ,14332.2)
+ ,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])
+ }
+ }
> 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
Uitvoer Invoer
1 13132.1 12002.4
2 17665.9 15525.5
3 16913.0 14247.9
4 17318.8 15000.7
5 16224.2 14931.4
6 15469.6 13333.7
7 16557.5 14711.2
8 19414.8 17197.3
9 17335.0 14985.2
10 16525.2 14734.4
11 18160.4 15937.8
12 15553.8 13028.1
13 15262.2 13836.8
14 18581.0 16677.5
15 17564.1 15130.0
16 18948.6 17504.0
17 17187.8 16979.9
18 17564.8 16012.5
19 17668.4 16247.7
20 20811.7 19268.2
21 17257.8 15533.0
22 18984.2 16803.3
23 20532.6 17396.1
24 17082.3 15155.4
25 16894.9 15692.4
26 20274.9 18063.7
27 20078.6 17568.6
28 19900.9 18154.3
29 17012.2 15467.4
30 19642.9 16956.1
31 19024.0 16854.0
32 21691.0 19396.4
33 18835.9 16457.6
34 19873.4 17284.5
35 21468.2 18395.3
36 19406.8 16938.7
37 18385.3 16414.3
38 20739.3 18173.4
39 22268.3 19919.7
40 21569.0 19623.8
41 17514.8 17228.1
42 21124.7 18730.3
43 21251.0 19039.1
44 21393.0 19413.3
45 22145.2 20013.6
46 20310.5 17917.2
47 23466.9 21270.3
48 21264.6 18766.1
49 18388.1 16790.8
50 22635.4 19960.6
51 22014.3 19586.7
52 18422.7 17179.0
53 16120.2 14964.9
54 16037.7 13918.5
55 16410.7 14401.3
56 17749.8 15994.6
57 16349.8 14521.1
58 15662.3 13746.5
59 17782.3 15956.0
60 16398.9 14332.2
> k <- length(x[1,])
> df <- as.data.frame(x)
> (mylm <- lm(df))
Call:
lm(formula = df)
Coefficients:
(Intercept) Invoer
899.268 1.066
> (mysum <- summary(mylm))
Call:
lm(formula = df)
Residuals:
Min 1Q Median 3Q Max
-1815.1 -278.1 109.3 355.0 1086.0
Coefficients:
Estimate Std. Error t value Pr(>|t|)
(Intercept) 899.26790 588.47226 1.528 0.132
Invoer 1.06618 0.03515 30.334 <2e-16 ***
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
Residual standard error: 548.7 on 58 degrees of freedom
Multiple R-squared: 0.9407, Adjusted R-squared: 0.9397
F-statistic: 920.2 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,] 0.7577836 0.484432734 0.2422163670
[2,] 0.6821215 0.635757044 0.3178785220
[3,] 0.5568753 0.886249382 0.4431246910
[4,] 0.4381908 0.876381643 0.5618091785
[5,] 0.3605456 0.721091257 0.6394543717
[6,] 0.2705319 0.541063817 0.7294680913
[7,] 0.1870647 0.374129378 0.8129353110
[8,] 0.2686545 0.537309008 0.7313454961
[9,] 0.2593112 0.518622458 0.7406887710
[10,] 0.2048004 0.409600705 0.7951996475
[11,] 0.1848019 0.369603814 0.8151980931
[12,] 0.2369314 0.473862815 0.7630685923
[13,] 0.8712983 0.257403431 0.1287017153
[14,] 0.8372661 0.325467752 0.1627338760
[15,] 0.8151498 0.369700447 0.1848502237
[16,] 0.7960372 0.407925620 0.2039628098
[17,] 0.7385392 0.522921666 0.2614608328
[18,] 0.7011032 0.597793534 0.2988967670
[19,] 0.9030090 0.193982044 0.0969910219
[20,] 0.8656415 0.268716930 0.1343584650
[21,] 0.8880281 0.223943843 0.1119719213
[22,] 0.8574194 0.285161123 0.1425805615
[23,] 0.8520026 0.295994848 0.1479974240
[24,] 0.8200973 0.359805419 0.1799027097
[25,] 0.7903846 0.419230757 0.2096153783
[26,] 0.8218070 0.356385990 0.1781929952
[27,] 0.7738473 0.452305389 0.2261526946
[28,] 0.7194255 0.561148932 0.2805744660
[29,] 0.6882444 0.623511235 0.3117556175
[30,] 0.6902212 0.619557533 0.3097787667
[31,] 0.8164261 0.367147743 0.1835738717
[32,] 0.8048943 0.390211388 0.1951056942
[33,] 0.7461800 0.507640010 0.2538200048
[34,] 0.7352817 0.529436685 0.2647183426
[35,] 0.6712538 0.657492343 0.3287461716
[36,] 0.6077449 0.784510115 0.3922550575
[37,] 0.9926236 0.014752766 0.0073763832
[38,] 0.9885846 0.022830724 0.0114153622
[39,] 0.9795502 0.040899542 0.0204497711
[40,] 0.9679366 0.064126891 0.0320634455
[41,] 0.9478182 0.104363548 0.0521817739
[42,] 0.9298687 0.140262626 0.0701313129
[43,] 0.8944432 0.211113563 0.1055567815
[44,] 0.8674190 0.265161933 0.1325809665
[45,] 0.8401080 0.319783973 0.1598919866
[46,] 0.8525952 0.294809601 0.1474048004
[47,] 0.9715999 0.056800108 0.0284000540
[48,] 0.9495978 0.100804334 0.0504021671
[49,] 0.9994719 0.001056176 0.0005280879
[50,] 0.9983187 0.003362671 0.0016813353
[51,] 0.9919579 0.016084183 0.0080420913
> postscript(file="/var/www/html/rcomp/tmp/1jo4x1258577119.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$resid)
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/225l41258577119.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> plot(mysum$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/3rmkq1258577119.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> hist(mysum$resid, main='Residual Histogram', xlab='values of Residuals')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/4eswq1258577119.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> densityplot(~mysum$resid,col='black',main='Residual Density Plot', xlab='values of Residuals')
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/5oibc1258577119.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
-563.86833 213.67831 822.92792 426.10877 -594.60506 354.22828
7 8 9 10 11 12
-26.53256 180.14115 458.83454 -83.56790 268.59293 764.25242
13 14 15 16 17 18
-389.56611 -99.45928 533.55190 -613.05578 -1815.07165 -406.65060
19 20 21 22 23 24
-553.81577 -630.90783 -202.41802 169.61547 1085.98487 24.67097
25 26 27 28 29 30
-735.26687 116.50413 448.06909 -354.09164 -378.07672 665.40340
31 32 33 34 35 36
155.36022 111.70809 389.89337 545.77039 956.25935 447.85491
37 38 39 40 41 42
-14.54111 463.94435 131.07690 -252.74090 -1752.69714 255.58956
43 44 45 46 47 48
52.65365 -204.31033 -92.13726 308.29928 -110.30374 357.32038
49 50 51 52 53 54
-413.15730 454.57020 232.11433 -792.44778 -734.32204 298.82711
55 56 57 58 59 60
157.07615 -202.56600 -31.55203 106.80981 -128.91152 218.94908
> postscript(file="/var/www/html/rcomp/tmp/6foyd1258577119.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 -563.86833 NA
1 213.67831 -563.86833
2 822.92792 213.67831
3 426.10877 822.92792
4 -594.60506 426.10877
5 354.22828 -594.60506
6 -26.53256 354.22828
7 180.14115 -26.53256
8 458.83454 180.14115
9 -83.56790 458.83454
10 268.59293 -83.56790
11 764.25242 268.59293
12 -389.56611 764.25242
13 -99.45928 -389.56611
14 533.55190 -99.45928
15 -613.05578 533.55190
16 -1815.07165 -613.05578
17 -406.65060 -1815.07165
18 -553.81577 -406.65060
19 -630.90783 -553.81577
20 -202.41802 -630.90783
21 169.61547 -202.41802
22 1085.98487 169.61547
23 24.67097 1085.98487
24 -735.26687 24.67097
25 116.50413 -735.26687
26 448.06909 116.50413
27 -354.09164 448.06909
28 -378.07672 -354.09164
29 665.40340 -378.07672
30 155.36022 665.40340
31 111.70809 155.36022
32 389.89337 111.70809
33 545.77039 389.89337
34 956.25935 545.77039
35 447.85491 956.25935
36 -14.54111 447.85491
37 463.94435 -14.54111
38 131.07690 463.94435
39 -252.74090 131.07690
40 -1752.69714 -252.74090
41 255.58956 -1752.69714
42 52.65365 255.58956
43 -204.31033 52.65365
44 -92.13726 -204.31033
45 308.29928 -92.13726
46 -110.30374 308.29928
47 357.32038 -110.30374
48 -413.15730 357.32038
49 454.57020 -413.15730
50 232.11433 454.57020
51 -792.44778 232.11433
52 -734.32204 -792.44778
53 298.82711 -734.32204
54 157.07615 298.82711
55 -202.56600 157.07615
56 -31.55203 -202.56600
57 106.80981 -31.55203
58 -128.91152 106.80981
59 218.94908 -128.91152
60 NA 218.94908
> dum1 <- dum[2:length(myerror),]
> dum1
lag(myerror, k = 1) myerror
[1,] 213.67831 -563.86833
[2,] 822.92792 213.67831
[3,] 426.10877 822.92792
[4,] -594.60506 426.10877
[5,] 354.22828 -594.60506
[6,] -26.53256 354.22828
[7,] 180.14115 -26.53256
[8,] 458.83454 180.14115
[9,] -83.56790 458.83454
[10,] 268.59293 -83.56790
[11,] 764.25242 268.59293
[12,] -389.56611 764.25242
[13,] -99.45928 -389.56611
[14,] 533.55190 -99.45928
[15,] -613.05578 533.55190
[16,] -1815.07165 -613.05578
[17,] -406.65060 -1815.07165
[18,] -553.81577 -406.65060
[19,] -630.90783 -553.81577
[20,] -202.41802 -630.90783
[21,] 169.61547 -202.41802
[22,] 1085.98487 169.61547
[23,] 24.67097 1085.98487
[24,] -735.26687 24.67097
[25,] 116.50413 -735.26687
[26,] 448.06909 116.50413
[27,] -354.09164 448.06909
[28,] -378.07672 -354.09164
[29,] 665.40340 -378.07672
[30,] 155.36022 665.40340
[31,] 111.70809 155.36022
[32,] 389.89337 111.70809
[33,] 545.77039 389.89337
[34,] 956.25935 545.77039
[35,] 447.85491 956.25935
[36,] -14.54111 447.85491
[37,] 463.94435 -14.54111
[38,] 131.07690 463.94435
[39,] -252.74090 131.07690
[40,] -1752.69714 -252.74090
[41,] 255.58956 -1752.69714
[42,] 52.65365 255.58956
[43,] -204.31033 52.65365
[44,] -92.13726 -204.31033
[45,] 308.29928 -92.13726
[46,] -110.30374 308.29928
[47,] 357.32038 -110.30374
[48,] -413.15730 357.32038
[49,] 454.57020 -413.15730
[50,] 232.11433 454.57020
[51,] -792.44778 232.11433
[52,] -734.32204 -792.44778
[53,] 298.82711 -734.32204
[54,] 157.07615 298.82711
[55,] -202.56600 157.07615
[56,] -31.55203 -202.56600
[57,] 106.80981 -31.55203
[58,] -128.91152 106.80981
[59,] 218.94908 -128.91152
> z <- as.data.frame(dum1)
> z
lag(myerror, k = 1) myerror
1 213.67831 -563.86833
2 822.92792 213.67831
3 426.10877 822.92792
4 -594.60506 426.10877
5 354.22828 -594.60506
6 -26.53256 354.22828
7 180.14115 -26.53256
8 458.83454 180.14115
9 -83.56790 458.83454
10 268.59293 -83.56790
11 764.25242 268.59293
12 -389.56611 764.25242
13 -99.45928 -389.56611
14 533.55190 -99.45928
15 -613.05578 533.55190
16 -1815.07165 -613.05578
17 -406.65060 -1815.07165
18 -553.81577 -406.65060
19 -630.90783 -553.81577
20 -202.41802 -630.90783
21 169.61547 -202.41802
22 1085.98487 169.61547
23 24.67097 1085.98487
24 -735.26687 24.67097
25 116.50413 -735.26687
26 448.06909 116.50413
27 -354.09164 448.06909
28 -378.07672 -354.09164
29 665.40340 -378.07672
30 155.36022 665.40340
31 111.70809 155.36022
32 389.89337 111.70809
33 545.77039 389.89337
34 956.25935 545.77039
35 447.85491 956.25935
36 -14.54111 447.85491
37 463.94435 -14.54111
38 131.07690 463.94435
39 -252.74090 131.07690
40 -1752.69714 -252.74090
41 255.58956 -1752.69714
42 52.65365 255.58956
43 -204.31033 52.65365
44 -92.13726 -204.31033
45 308.29928 -92.13726
46 -110.30374 308.29928
47 357.32038 -110.30374
48 -413.15730 357.32038
49 454.57020 -413.15730
50 232.11433 454.57020
51 -792.44778 232.11433
52 -734.32204 -792.44778
53 298.82711 -734.32204
54 157.07615 298.82711
55 -202.56600 157.07615
56 -31.55203 -202.56600
57 106.80981 -31.55203
58 -128.91152 106.80981
59 218.94908 -128.91152
> 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/75jz91258577119.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> acf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/8fic81258577119.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> pacf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Partial Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/9x0qw1258577119.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> opar <- par(mfrow = c(2,2), oma = c(0, 0, 1.1, 0))
> plot(mylm, las = 1, sub='Residual Diagnostics')
> par(opar)
> dev.off()
null device
1
> if (n > n25) {
+ postscript(file="/var/www/html/rcomp/tmp/10dk4p1258577119.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
+ plot(kp3:nmkm3,gqarr[,2], main='Goldfeld-Quandt test',ylab='2-sided p-value',xlab='breakpoint')
+ grid()
+ dev.off()
+ }
null device
1
>
> #Note: the /var/www/html/rcomp/createtable file can be downloaded at http://www.wessa.net/cretab
> load(file="/var/www/html/rcomp/createtable")
>
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a, 'Multiple Linear Regression - Estimated Regression Equation', 1, TRUE)
> a<-table.row.end(a)
> myeq <- colnames(x)[1]
> myeq <- paste(myeq, '[t] = ', sep='')
> for (i in 1:k){
+ if (mysum$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/114sji1258577119.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/125ntx1258577119.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/13qqp51258577119.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/14nuky1258577119.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/15c1o31258577119.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/16rb5c1258577120.tab")
+ }
>
> system("convert tmp/1jo4x1258577119.ps tmp/1jo4x1258577119.png")
> system("convert tmp/225l41258577119.ps tmp/225l41258577119.png")
> system("convert tmp/3rmkq1258577119.ps tmp/3rmkq1258577119.png")
> system("convert tmp/4eswq1258577119.ps tmp/4eswq1258577119.png")
> system("convert tmp/5oibc1258577119.ps tmp/5oibc1258577119.png")
> system("convert tmp/6foyd1258577119.ps tmp/6foyd1258577119.png")
> system("convert tmp/75jz91258577119.ps tmp/75jz91258577119.png")
> system("convert tmp/8fic81258577119.ps tmp/8fic81258577119.png")
> system("convert tmp/9x0qw1258577119.ps tmp/9x0qw1258577119.png")
> system("convert tmp/10dk4p1258577119.ps tmp/10dk4p1258577119.png")
>
>
> proc.time()
user system elapsed
2.482 1.630 4.216