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(2756.76
+ ,3016.70
+ ,2849.27
+ ,3052.40
+ ,2921.44
+ ,3099.60
+ ,2981.85
+ ,3103.30
+ ,3080.58
+ ,3119.80
+ ,3106.22
+ ,3093.70
+ ,3119.31
+ ,3164.90
+ ,3061.26
+ ,3311.50
+ ,3097.31
+ ,3410.60
+ ,3161.69
+ ,3392.60
+ ,3257.16
+ ,3338.20
+ ,3277.01
+ ,3285.10
+ ,3295.32
+ ,3294.80
+ ,3363.99
+ ,3611.20
+ ,3494.17
+ ,3611.30
+ ,3667.03
+ ,3521.00
+ ,3813.06
+ ,3519.30
+ ,3917.96
+ ,3438.30
+ ,3895.51
+ ,3534.90
+ ,3801.06
+ ,3705.80
+ ,3570.12
+ ,3807.60
+ ,3701.61
+ ,3663.00
+ ,3862.27
+ ,3604.50
+ ,3970.10
+ ,3563.80
+ ,4138.52
+ ,3511.40
+ ,4199.75
+ ,3546.50
+ ,4290.89
+ ,3525.40
+ ,4443.91
+ ,3529.90
+ ,4502.64
+ ,3591.60
+ ,4356.98
+ ,3668.30
+ ,4591.27
+ ,3728.80
+ ,4696.96
+ ,3853.60
+ ,4621.40
+ ,3897.70
+ ,4562.84
+ ,3640.70
+ ,4202.52
+ ,3495.50
+ ,4296.49
+ ,3495.10
+ ,4435.23
+ ,3268.00
+ ,4105.18
+ ,3479.10
+ ,4116.68
+ ,3417.80
+ ,3844.49
+ ,3521.30
+ ,3720.98
+ ,3487.10
+ ,3674.40
+ ,3529.90
+ ,3857.62
+ ,3544.30
+ ,3801.06
+ ,3710.80
+ ,3504.37
+ ,3641.90
+ ,3032.60
+ ,3447.10
+ ,3047.03
+ ,3386.80
+ ,2962.34
+ ,3438.50
+ ,2197.82
+ ,3364.30
+ ,2014.45
+ ,3462.70
+ ,1862.83
+ ,3291.90
+ ,1905.41
+ ,3550.00
+ ,1810.99
+ ,3611.00
+ ,1670.07
+ ,3708.60
+ ,1864.44
+ ,3771.10
+ ,2052.02
+ ,4042.70
+ ,2029.60
+ ,3988.40
+ ,2070.83
+ ,3851.20
+ ,2293.41
+ ,3876.70)
+ ,dim=c(2
+ ,59)
+ ,dimnames=list(c('Bel20'
+ ,'Zichtrekeningen
')
+ ,1:59))
> y <- array(NA,dim=c(2,59),dimnames=list(c('Bel20','Zichtrekeningen
'),1:59))
> 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
Bel20 Zichtrekeningen\r
1 2756.76 3016.7
2 2849.27 3052.4
3 2921.44 3099.6
4 2981.85 3103.3
5 3080.58 3119.8
6 3106.22 3093.7
7 3119.31 3164.9
8 3061.26 3311.5
9 3097.31 3410.6
10 3161.69 3392.6
11 3257.16 3338.2
12 3277.01 3285.1
13 3295.32 3294.8
14 3363.99 3611.2
15 3494.17 3611.3
16 3667.03 3521.0
17 3813.06 3519.3
18 3917.96 3438.3
19 3895.51 3534.9
20 3801.06 3705.8
21 3570.12 3807.6
22 3701.61 3663.0
23 3862.27 3604.5
24 3970.10 3563.8
25 4138.52 3511.4
26 4199.75 3546.5
27 4290.89 3525.4
28 4443.91 3529.9
29 4502.64 3591.6
30 4356.98 3668.3
31 4591.27 3728.8
32 4696.96 3853.6
33 4621.40 3897.7
34 4562.84 3640.7
35 4202.52 3495.5
36 4296.49 3495.1
37 4435.23 3268.0
38 4105.18 3479.1
39 4116.68 3417.8
40 3844.49 3521.3
41 3720.98 3487.1
42 3674.40 3529.9
43 3857.62 3544.3
44 3801.06 3710.8
45 3504.37 3641.9
46 3032.60 3447.1
47 3047.03 3386.8
48 2962.34 3438.5
49 2197.82 3364.3
50 2014.45 3462.7
51 1862.83 3291.9
52 1905.41 3550.0
53 1810.99 3611.0
54 1670.07 3708.6
55 1864.44 3771.1
56 2052.02 4042.7
57 2029.60 3988.4
58 2070.83 3851.2
59 2293.41 3876.7
> k <- length(x[1,])
> df <- as.data.frame(x)
> (mylm <- lm(df))
Call:
lm(formula = df)
Coefficients:
(Intercept) `Zichtrekeningen\r`
2724.0442 0.1887
> (mysum <- summary(mylm))
Call:
lm(formula = df)
Residuals:
Min 1Q Median 3Q Max
-1753.7 -364.6 93.2 649.2 1245.8
Coefficients:
Estimate Std. Error t value Pr(>|t|)
(Intercept) 2724.0442 1711.2043 1.592 0.117
`Zichtrekeningen\r` 0.1887 0.4864 0.388 0.700
Residual standard error: 854 on 57 degrees of freedom
Multiple R-squared: 0.002633, Adjusted R-squared: -0.01486
F-statistic: 0.1505 on 1 and 57 DF, p-value: 0.6995
> 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,] 1.602609e-04 3.205217e-04 0.999839739
[2,] 1.075906e-04 2.151811e-04 0.999892409
[3,] 1.092165e-05 2.184329e-05 0.999989078
[4,] 1.758158e-05 3.516316e-05 0.999982418
[5,] 2.939947e-06 5.879894e-06 0.999997060
[6,] 3.245018e-07 6.490037e-07 0.999999675
[7,] 7.205807e-08 1.441161e-07 0.999999928
[8,] 2.412269e-08 4.824539e-08 0.999999976
[9,] 6.888320e-09 1.377664e-08 0.999999993
[10,] 8.602181e-10 1.720436e-09 0.999999999
[11,] 1.222527e-10 2.445054e-10 1.000000000
[12,] 2.468929e-10 4.937857e-10 1.000000000
[13,] 9.947947e-10 1.989589e-09 0.999999999
[14,] 1.001799e-08 2.003597e-08 0.999999990
[15,] 7.009958e-09 1.401992e-08 0.999999993
[16,] 1.468966e-09 2.937932e-09 0.999999999
[17,] 9.777086e-10 1.955417e-09 0.999999999
[18,] 1.998812e-10 3.997624e-10 1.000000000
[19,] 7.300719e-11 1.460144e-10 1.000000000
[20,] 6.103012e-11 1.220602e-10 1.000000000
[21,] 2.461306e-10 4.922613e-10 1.000000000
[22,] 5.824697e-10 1.164939e-09 0.999999999
[23,] 2.020231e-09 4.040461e-09 0.999999998
[24,] 1.125437e-08 2.250873e-08 0.999999989
[25,] 3.208879e-08 6.417757e-08 0.999999968
[26,] 2.622025e-08 5.244049e-08 0.999999974
[27,] 4.127257e-08 8.254513e-08 0.999999959
[28,] 7.997742e-08 1.599548e-07 0.999999920
[29,] 2.468911e-07 4.937822e-07 0.999999753
[30,] 1.116749e-06 2.233497e-06 0.999998883
[31,] 1.576113e-06 3.152226e-06 0.999998424
[32,] 3.683550e-06 7.367100e-06 0.999996316
[33,] 4.533938e-05 9.067876e-05 0.999954661
[34,] 6.763382e-05 1.352676e-04 0.999932366
[35,] 1.354492e-04 2.708984e-04 0.999864551
[36,] 1.900918e-04 3.801835e-04 0.999809908
[37,] 2.548625e-04 5.097250e-04 0.999745137
[38,] 4.702210e-04 9.404420e-04 0.999529779
[39,] 2.231106e-03 4.462212e-03 0.997768894
[40,] 3.083176e-02 6.166351e-02 0.969168243
[41,] 2.159150e-01 4.318301e-01 0.784084960
[42,] 3.782495e-01 7.564989e-01 0.621750525
[43,] 6.824199e-01 6.351602e-01 0.317580117
[44,] 9.923099e-01 1.538022e-02 0.007690108
[45,] 9.973067e-01 5.386676e-03 0.002693338
[46,] 9.976029e-01 4.794206e-03 0.002397103
[47,] 9.964707e-01 7.058686e-03 0.003529343
[48,] 9.945888e-01 1.082233e-02 0.005411163
[49,] 9.869331e-01 2.613375e-02 0.013066876
[50,] 9.815391e-01 3.692184e-02 0.018460922
> postscript(file="/var/www/html/rcomp/tmp/127u01258732597.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$resid)
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/2g8ad1258732597.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> plot(mysum$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/37hpa1258732597.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> hist(mysum$resid, main='Residual Histogram', xlab='values of Residuals')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/4nicp1258732597.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> densityplot(~mysum$resid,col='black',main='Residual Density Plot', xlab='values of Residuals')
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/54izr1258732597.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 = 59
Frequency = 1
1 2 3 4 5 6
-536.45146 -450.67705 -387.41238 -327.70046 -232.08355 -201.51921
7 8 9 10 11 12
-201.86267 -287.57200 -270.21941 -202.44331 -96.70955 -66.84106
13 14 15 16 17 18
-50.36118 -41.38704 88.77409 278.67119 425.02193 545.20437
19 20 21 22 23 24
504.52864 377.83457 127.68775 286.45974 458.15706 573.66602
25 26 27 28 29 30
751.97244 806.58005 901.70103 1053.87200 1100.96093 940.82978
31 32 33 34 35 36
1163.70512 1245.84883 1161.96839 1151.89713 818.97232 913.01779
37 38 39 40 41 42
1094.60524 724.72655 747.79215 456.07458 339.01717 284.36200
43 44 45 46 47 48
464.86512 376.89121 93.20072 -341.81594 -316.00901 -410.45336
49 50 51 52 53 54
-1160.97389 -1362.90923 -1482.30403 -1488.42031 -1594.34931 -1753.68371
55 56 57 58 59
-1571.10572 -1434.76907 -1446.94417 -1379.82835 -1162.05949
> postscript(file="/var/www/html/rcomp/tmp/65imb1258732597.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 = 59
Frequency = 1
lag(myerror, k = 1) myerror
0 -536.45146 NA
1 -450.67705 -536.45146
2 -387.41238 -450.67705
3 -327.70046 -387.41238
4 -232.08355 -327.70046
5 -201.51921 -232.08355
6 -201.86267 -201.51921
7 -287.57200 -201.86267
8 -270.21941 -287.57200
9 -202.44331 -270.21941
10 -96.70955 -202.44331
11 -66.84106 -96.70955
12 -50.36118 -66.84106
13 -41.38704 -50.36118
14 88.77409 -41.38704
15 278.67119 88.77409
16 425.02193 278.67119
17 545.20437 425.02193
18 504.52864 545.20437
19 377.83457 504.52864
20 127.68775 377.83457
21 286.45974 127.68775
22 458.15706 286.45974
23 573.66602 458.15706
24 751.97244 573.66602
25 806.58005 751.97244
26 901.70103 806.58005
27 1053.87200 901.70103
28 1100.96093 1053.87200
29 940.82978 1100.96093
30 1163.70512 940.82978
31 1245.84883 1163.70512
32 1161.96839 1245.84883
33 1151.89713 1161.96839
34 818.97232 1151.89713
35 913.01779 818.97232
36 1094.60524 913.01779
37 724.72655 1094.60524
38 747.79215 724.72655
39 456.07458 747.79215
40 339.01717 456.07458
41 284.36200 339.01717
42 464.86512 284.36200
43 376.89121 464.86512
44 93.20072 376.89121
45 -341.81594 93.20072
46 -316.00901 -341.81594
47 -410.45336 -316.00901
48 -1160.97389 -410.45336
49 -1362.90923 -1160.97389
50 -1482.30403 -1362.90923
51 -1488.42031 -1482.30403
52 -1594.34931 -1488.42031
53 -1753.68371 -1594.34931
54 -1571.10572 -1753.68371
55 -1434.76907 -1571.10572
56 -1446.94417 -1434.76907
57 -1379.82835 -1446.94417
58 -1162.05949 -1379.82835
59 NA -1162.05949
> dum1 <- dum[2:length(myerror),]
> dum1
lag(myerror, k = 1) myerror
[1,] -450.67705 -536.45146
[2,] -387.41238 -450.67705
[3,] -327.70046 -387.41238
[4,] -232.08355 -327.70046
[5,] -201.51921 -232.08355
[6,] -201.86267 -201.51921
[7,] -287.57200 -201.86267
[8,] -270.21941 -287.57200
[9,] -202.44331 -270.21941
[10,] -96.70955 -202.44331
[11,] -66.84106 -96.70955
[12,] -50.36118 -66.84106
[13,] -41.38704 -50.36118
[14,] 88.77409 -41.38704
[15,] 278.67119 88.77409
[16,] 425.02193 278.67119
[17,] 545.20437 425.02193
[18,] 504.52864 545.20437
[19,] 377.83457 504.52864
[20,] 127.68775 377.83457
[21,] 286.45974 127.68775
[22,] 458.15706 286.45974
[23,] 573.66602 458.15706
[24,] 751.97244 573.66602
[25,] 806.58005 751.97244
[26,] 901.70103 806.58005
[27,] 1053.87200 901.70103
[28,] 1100.96093 1053.87200
[29,] 940.82978 1100.96093
[30,] 1163.70512 940.82978
[31,] 1245.84883 1163.70512
[32,] 1161.96839 1245.84883
[33,] 1151.89713 1161.96839
[34,] 818.97232 1151.89713
[35,] 913.01779 818.97232
[36,] 1094.60524 913.01779
[37,] 724.72655 1094.60524
[38,] 747.79215 724.72655
[39,] 456.07458 747.79215
[40,] 339.01717 456.07458
[41,] 284.36200 339.01717
[42,] 464.86512 284.36200
[43,] 376.89121 464.86512
[44,] 93.20072 376.89121
[45,] -341.81594 93.20072
[46,] -316.00901 -341.81594
[47,] -410.45336 -316.00901
[48,] -1160.97389 -410.45336
[49,] -1362.90923 -1160.97389
[50,] -1482.30403 -1362.90923
[51,] -1488.42031 -1482.30403
[52,] -1594.34931 -1488.42031
[53,] -1753.68371 -1594.34931
[54,] -1571.10572 -1753.68371
[55,] -1434.76907 -1571.10572
[56,] -1446.94417 -1434.76907
[57,] -1379.82835 -1446.94417
[58,] -1162.05949 -1379.82835
> z <- as.data.frame(dum1)
> z
lag(myerror, k = 1) myerror
1 -450.67705 -536.45146
2 -387.41238 -450.67705
3 -327.70046 -387.41238
4 -232.08355 -327.70046
5 -201.51921 -232.08355
6 -201.86267 -201.51921
7 -287.57200 -201.86267
8 -270.21941 -287.57200
9 -202.44331 -270.21941
10 -96.70955 -202.44331
11 -66.84106 -96.70955
12 -50.36118 -66.84106
13 -41.38704 -50.36118
14 88.77409 -41.38704
15 278.67119 88.77409
16 425.02193 278.67119
17 545.20437 425.02193
18 504.52864 545.20437
19 377.83457 504.52864
20 127.68775 377.83457
21 286.45974 127.68775
22 458.15706 286.45974
23 573.66602 458.15706
24 751.97244 573.66602
25 806.58005 751.97244
26 901.70103 806.58005
27 1053.87200 901.70103
28 1100.96093 1053.87200
29 940.82978 1100.96093
30 1163.70512 940.82978
31 1245.84883 1163.70512
32 1161.96839 1245.84883
33 1151.89713 1161.96839
34 818.97232 1151.89713
35 913.01779 818.97232
36 1094.60524 913.01779
37 724.72655 1094.60524
38 747.79215 724.72655
39 456.07458 747.79215
40 339.01717 456.07458
41 284.36200 339.01717
42 464.86512 284.36200
43 376.89121 464.86512
44 93.20072 376.89121
45 -341.81594 93.20072
46 -316.00901 -341.81594
47 -410.45336 -316.00901
48 -1160.97389 -410.45336
49 -1362.90923 -1160.97389
50 -1482.30403 -1362.90923
51 -1488.42031 -1482.30403
52 -1594.34931 -1488.42031
53 -1753.68371 -1594.34931
54 -1571.10572 -1753.68371
55 -1434.76907 -1571.10572
56 -1446.94417 -1434.76907
57 -1379.82835 -1446.94417
58 -1162.05949 -1379.82835
> 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/76nxt1258732597.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> acf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/8a8fe1258732597.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> pacf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Partial Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/92tqf1258732597.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> opar <- par(mfrow = c(2,2), oma = c(0, 0, 1.1, 0))
> plot(mylm, las = 1, sub='Residual Diagnostics')
> par(opar)
> dev.off()
null device
1
> if (n > n25) {
+ postscript(file="/var/www/html/rcomp/tmp/10mpkz1258732597.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
+ plot(kp3:nmkm3,gqarr[,2], main='Goldfeld-Quandt test',ylab='2-sided p-value',xlab='breakpoint')
+ grid()
+ dev.off()
+ }
null device
1
>
> #Note: the /var/www/html/rcomp/createtable file can be downloaded at http://www.wessa.net/cretab
> load(file="/var/www/html/rcomp/createtable")
>
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a, 'Multiple Linear Regression - Estimated Regression Equation', 1, TRUE)
> a<-table.row.end(a)
> myeq <- colnames(x)[1]
> myeq <- paste(myeq, '[t] = ', sep='')
> for (i in 1:k){
+ if (mysum$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/11kwl71258732597.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/12gkao1258732597.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/13jn701258732597.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/14rwoe1258732598.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/15ip6c1258732598.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/16un741258732598.tab")
+ }
>
> system("convert tmp/127u01258732597.ps tmp/127u01258732597.png")
> system("convert tmp/2g8ad1258732597.ps tmp/2g8ad1258732597.png")
> system("convert tmp/37hpa1258732597.ps tmp/37hpa1258732597.png")
> system("convert tmp/4nicp1258732597.ps tmp/4nicp1258732597.png")
> system("convert tmp/54izr1258732597.ps tmp/54izr1258732597.png")
> system("convert tmp/65imb1258732597.ps tmp/65imb1258732597.png")
> system("convert tmp/76nxt1258732597.ps tmp/76nxt1258732597.png")
> system("convert tmp/8a8fe1258732597.ps tmp/8a8fe1258732597.png")
> system("convert tmp/92tqf1258732597.ps tmp/92tqf1258732597.png")
> system("convert tmp/10mpkz1258732597.ps tmp/10mpkz1258732597.png")
>
>
> proc.time()
user system elapsed
2.455 1.555 2.818