R version 2.9.0 (2009-04-17)
Copyright (C) 2009 The R Foundation for Statistical Computing
ISBN 3-900051-07-0
R is free software and comes with ABSOLUTELY NO WARRANTY.
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Type 'license()' or 'licence()' for distribution details.
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Type 'contributors()' for more information and
'citation()' on how to cite R or R packages in publications.
Type 'demo()' for some demos, 'help()' for on-line help, or
'help.start()' for an HTML browser interface to help.
Type 'q()' to quit R.
> x <- array(list(1.43,0.51,1.43,0.51,1.43,0.51,1.43,0.51,1.43,0.52,1.43,0.52,1.44,0.52,1.48,0.53,1.48,0.53,1.48,0.52,1.48,0.52,1.48,0.52,1.48,0.52,1.48,0.52,1.48,0.52,1.48,0.52,1.48,0.52,1.48,0.52,1.48,0.52,1.48,0.53,1.48,0.53,1.48,0.53,1.48,0.54,1.48,0.54,1.48,0.54,1.48,0.54,1.48,0.54,1.48,0.54,1.48,0.54,1.48,0.54,1.48,0.54,1.48,0.54,1.48,0.53,1.48,0.53,1.48,0.53,1.48,0.53,1.48,0.53,1.57,0.54,1.58,0.55,1.58,0.55,1.58,0.55,1.58,0.55,1.59,0.55,1.6,0.55,1.6,0.55,1.61,0.55,1.61,0.56,1.61,0.56,1.62,0.56,1.63,0.56,1.63,0.56,1.64,0.55,1.64,0.56,1.64,0.55,1.64,0.55,1.64,0.56,1.65,0.55,1.65,0.55,1.65,0.55,1.65,0.55),dim=c(2,60),dimnames=list(c('Broodprijs','Bakmeelprijs'),1:60))
> y <- array(NA,dim=c(2,60),dimnames=list(c('Broodprijs','Bakmeelprijs'),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
Broodprijs Bakmeelprijs
1 1.43 0.51
2 1.43 0.51
3 1.43 0.51
4 1.43 0.51
5 1.43 0.52
6 1.43 0.52
7 1.44 0.52
8 1.48 0.53
9 1.48 0.53
10 1.48 0.52
11 1.48 0.52
12 1.48 0.52
13 1.48 0.52
14 1.48 0.52
15 1.48 0.52
16 1.48 0.52
17 1.48 0.52
18 1.48 0.52
19 1.48 0.52
20 1.48 0.53
21 1.48 0.53
22 1.48 0.53
23 1.48 0.54
24 1.48 0.54
25 1.48 0.54
26 1.48 0.54
27 1.48 0.54
28 1.48 0.54
29 1.48 0.54
30 1.48 0.54
31 1.48 0.54
32 1.48 0.54
33 1.48 0.53
34 1.48 0.53
35 1.48 0.53
36 1.48 0.53
37 1.48 0.53
38 1.57 0.54
39 1.58 0.55
40 1.58 0.55
41 1.58 0.55
42 1.58 0.55
43 1.59 0.55
44 1.60 0.55
45 1.60 0.55
46 1.61 0.55
47 1.61 0.56
48 1.61 0.56
49 1.62 0.56
50 1.63 0.56
51 1.63 0.56
52 1.64 0.55
53 1.64 0.56
54 1.64 0.55
55 1.64 0.55
56 1.64 0.56
57 1.65 0.55
58 1.65 0.55
59 1.65 0.55
60 1.65 0.55
> k <- length(x[1,])
> df <- as.data.frame(x)
> (mylm <- lm(df))
Call:
lm(formula = df)
Coefficients:
(Intercept) Bakmeelprijs
-0.7997 4.3337
> (mysum <- summary(mylm))
Call:
lm(formula = df)
Residuals:
Min 1Q Median 3Q Max
-0.060557 -0.017219 -0.000563 0.026118 0.066106
Coefficients:
Estimate Std. Error t value Pr(>|t|)
(Intercept) -0.7997 0.1710 -4.676 1.79e-05 ***
Bakmeelprijs 4.3337 0.3184 13.610 < 2e-16 ***
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
Residual standard error: 0.037 on 58 degrees of freedom
Multiple R-squared: 0.7615, Adjusted R-squared: 0.7574
F-statistic: 185.2 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,] 3.878097e-43 7.756194e-43 1.000000e+00
[2,] 2.950960e-57 5.901919e-57 1.000000e+00
[3,] 2.346283e-05 4.692566e-05 9.999765e-01
[4,] 2.666780e-03 5.333561e-03 9.973332e-01
[5,] 1.324674e-03 2.649349e-03 9.986753e-01
[6,] 4.356403e-03 8.712806e-03 9.956436e-01
[7,] 5.819962e-03 1.163992e-02 9.941800e-01
[8,] 5.758726e-03 1.151745e-02 9.942413e-01
[9,] 4.934832e-03 9.869663e-03 9.950652e-01
[10,] 3.912695e-03 7.825391e-03 9.960873e-01
[11,] 2.984512e-03 5.969024e-03 9.970155e-01
[12,] 2.261213e-03 4.522426e-03 9.977388e-01
[13,] 1.763804e-03 3.527607e-03 9.982362e-01
[14,] 1.491527e-03 2.983053e-03 9.985085e-01
[15,] 1.495909e-03 2.991819e-03 9.985041e-01
[16,] 8.291217e-04 1.658243e-03 9.991709e-01
[17,] 4.306091e-04 8.612181e-04 9.995694e-01
[18,] 2.143417e-04 4.286834e-04 9.997857e-01
[19,] 2.683663e-04 5.367326e-04 9.997316e-01
[20,] 2.394958e-04 4.789916e-04 9.997605e-01
[21,] 1.948104e-04 3.896208e-04 9.998052e-01
[22,] 1.574444e-04 3.148889e-04 9.998426e-01
[23,] 1.327698e-04 2.655397e-04 9.998672e-01
[24,] 1.216627e-04 2.433254e-04 9.998783e-01
[25,] 1.265443e-04 2.530887e-04 9.998735e-01
[26,] 1.577720e-04 3.155439e-04 9.998422e-01
[27,] 2.540141e-04 5.080282e-04 9.997460e-01
[28,] 5.882658e-04 1.176532e-03 9.994117e-01
[29,] 3.592928e-04 7.185855e-04 9.996407e-01
[30,] 2.348560e-04 4.697120e-04 9.997651e-01
[31,] 1.815589e-04 3.631177e-04 9.998184e-01
[32,] 2.234998e-04 4.469996e-04 9.997765e-01
[33,] 1.852706e-03 3.705412e-03 9.981473e-01
[34,] 8.106894e-02 1.621379e-01 9.189311e-01
[35,] 2.651364e-01 5.302728e-01 7.348636e-01
[36,] 4.705301e-01 9.410602e-01 5.294699e-01
[37,] 6.711915e-01 6.576171e-01 3.288085e-01
[38,] 8.552595e-01 2.894810e-01 1.447405e-01
[39,] 9.491818e-01 1.016363e-01 5.081817e-02
[40,] 9.833951e-01 3.320971e-02 1.660485e-02
[41,] 9.980691e-01 3.861895e-03 1.930947e-03
[42,] 9.999070e-01 1.859792e-04 9.298959e-05
[43,] 9.999337e-01 1.326949e-04 6.634744e-05
[44,] 9.999885e-01 2.293435e-05 1.146718e-05
[45,] 9.999946e-01 1.081367e-05 5.406837e-06
[46,] 9.999837e-01 3.250743e-05 1.625371e-05
[47,] 9.999722e-01 5.551066e-05 2.775533e-05
[48,] 9.999420e-01 1.159143e-04 5.795716e-05
[49,] 9.996213e-01 7.574005e-04 3.787002e-04
[50,] 9.992611e-01 1.477894e-03 7.389469e-04
[51,] 1.000000e+00 0.000000e+00 0.000000e+00
> postscript(file="/var/www/html/rcomp/tmp/116hw1258718673.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$resid)
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/2f59w1258718673.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> plot(mysum$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/3x1oj1258718673.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> hist(mysum$resid, main='Residual Histogram', xlab='values of Residuals')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/42c4d1258718673.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> densityplot(~mysum$resid,col='black',main='Residual Density Plot', xlab='values of Residuals')
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/5z68q1258718673.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
0.019455488 0.019455488 0.019455488 0.019455488 -0.023881961 -0.023881961
7 8 9 10 11 12
-0.013881961 -0.017219410 -0.017219410 0.026118039 0.026118039 0.026118039
13 14 15 16 17 18
0.026118039 0.026118039 0.026118039 0.026118039 0.026118039 0.026118039
19 20 21 22 23 24
0.026118039 -0.017219410 -0.017219410 -0.017219410 -0.060556859 -0.060556859
25 26 27 28 29 30
-0.060556859 -0.060556859 -0.060556859 -0.060556859 -0.060556859 -0.060556859
31 32 33 34 35 36
-0.060556859 -0.060556859 -0.017219410 -0.017219410 -0.017219410 -0.017219410
37 38 39 40 41 42
-0.017219410 0.029443141 -0.003894308 -0.003894308 -0.003894308 -0.003894308
43 44 45 46 47 48
0.006105692 0.016105692 0.016105692 0.026105692 -0.017231757 -0.017231757
49 50 51 52 53 54
-0.007231757 0.002768243 0.002768243 0.056105692 0.012768243 0.056105692
55 56 57 58 59 60
0.056105692 0.012768243 0.066105692 0.066105692 0.066105692 0.066105692
> postscript(file="/var/www/html/rcomp/tmp/65zh11258718673.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 0.019455488 NA
1 0.019455488 0.019455488
2 0.019455488 0.019455488
3 0.019455488 0.019455488
4 -0.023881961 0.019455488
5 -0.023881961 -0.023881961
6 -0.013881961 -0.023881961
7 -0.017219410 -0.013881961
8 -0.017219410 -0.017219410
9 0.026118039 -0.017219410
10 0.026118039 0.026118039
11 0.026118039 0.026118039
12 0.026118039 0.026118039
13 0.026118039 0.026118039
14 0.026118039 0.026118039
15 0.026118039 0.026118039
16 0.026118039 0.026118039
17 0.026118039 0.026118039
18 0.026118039 0.026118039
19 -0.017219410 0.026118039
20 -0.017219410 -0.017219410
21 -0.017219410 -0.017219410
22 -0.060556859 -0.017219410
23 -0.060556859 -0.060556859
24 -0.060556859 -0.060556859
25 -0.060556859 -0.060556859
26 -0.060556859 -0.060556859
27 -0.060556859 -0.060556859
28 -0.060556859 -0.060556859
29 -0.060556859 -0.060556859
30 -0.060556859 -0.060556859
31 -0.060556859 -0.060556859
32 -0.017219410 -0.060556859
33 -0.017219410 -0.017219410
34 -0.017219410 -0.017219410
35 -0.017219410 -0.017219410
36 -0.017219410 -0.017219410
37 0.029443141 -0.017219410
38 -0.003894308 0.029443141
39 -0.003894308 -0.003894308
40 -0.003894308 -0.003894308
41 -0.003894308 -0.003894308
42 0.006105692 -0.003894308
43 0.016105692 0.006105692
44 0.016105692 0.016105692
45 0.026105692 0.016105692
46 -0.017231757 0.026105692
47 -0.017231757 -0.017231757
48 -0.007231757 -0.017231757
49 0.002768243 -0.007231757
50 0.002768243 0.002768243
51 0.056105692 0.002768243
52 0.012768243 0.056105692
53 0.056105692 0.012768243
54 0.056105692 0.056105692
55 0.012768243 0.056105692
56 0.066105692 0.012768243
57 0.066105692 0.066105692
58 0.066105692 0.066105692
59 0.066105692 0.066105692
60 NA 0.066105692
> dum1 <- dum[2:length(myerror),]
> dum1
lag(myerror, k = 1) myerror
[1,] 0.019455488 0.019455488
[2,] 0.019455488 0.019455488
[3,] 0.019455488 0.019455488
[4,] -0.023881961 0.019455488
[5,] -0.023881961 -0.023881961
[6,] -0.013881961 -0.023881961
[7,] -0.017219410 -0.013881961
[8,] -0.017219410 -0.017219410
[9,] 0.026118039 -0.017219410
[10,] 0.026118039 0.026118039
[11,] 0.026118039 0.026118039
[12,] 0.026118039 0.026118039
[13,] 0.026118039 0.026118039
[14,] 0.026118039 0.026118039
[15,] 0.026118039 0.026118039
[16,] 0.026118039 0.026118039
[17,] 0.026118039 0.026118039
[18,] 0.026118039 0.026118039
[19,] -0.017219410 0.026118039
[20,] -0.017219410 -0.017219410
[21,] -0.017219410 -0.017219410
[22,] -0.060556859 -0.017219410
[23,] -0.060556859 -0.060556859
[24,] -0.060556859 -0.060556859
[25,] -0.060556859 -0.060556859
[26,] -0.060556859 -0.060556859
[27,] -0.060556859 -0.060556859
[28,] -0.060556859 -0.060556859
[29,] -0.060556859 -0.060556859
[30,] -0.060556859 -0.060556859
[31,] -0.060556859 -0.060556859
[32,] -0.017219410 -0.060556859
[33,] -0.017219410 -0.017219410
[34,] -0.017219410 -0.017219410
[35,] -0.017219410 -0.017219410
[36,] -0.017219410 -0.017219410
[37,] 0.029443141 -0.017219410
[38,] -0.003894308 0.029443141
[39,] -0.003894308 -0.003894308
[40,] -0.003894308 -0.003894308
[41,] -0.003894308 -0.003894308
[42,] 0.006105692 -0.003894308
[43,] 0.016105692 0.006105692
[44,] 0.016105692 0.016105692
[45,] 0.026105692 0.016105692
[46,] -0.017231757 0.026105692
[47,] -0.017231757 -0.017231757
[48,] -0.007231757 -0.017231757
[49,] 0.002768243 -0.007231757
[50,] 0.002768243 0.002768243
[51,] 0.056105692 0.002768243
[52,] 0.012768243 0.056105692
[53,] 0.056105692 0.012768243
[54,] 0.056105692 0.056105692
[55,] 0.012768243 0.056105692
[56,] 0.066105692 0.012768243
[57,] 0.066105692 0.066105692
[58,] 0.066105692 0.066105692
[59,] 0.066105692 0.066105692
> z <- as.data.frame(dum1)
> z
lag(myerror, k = 1) myerror
1 0.019455488 0.019455488
2 0.019455488 0.019455488
3 0.019455488 0.019455488
4 -0.023881961 0.019455488
5 -0.023881961 -0.023881961
6 -0.013881961 -0.023881961
7 -0.017219410 -0.013881961
8 -0.017219410 -0.017219410
9 0.026118039 -0.017219410
10 0.026118039 0.026118039
11 0.026118039 0.026118039
12 0.026118039 0.026118039
13 0.026118039 0.026118039
14 0.026118039 0.026118039
15 0.026118039 0.026118039
16 0.026118039 0.026118039
17 0.026118039 0.026118039
18 0.026118039 0.026118039
19 -0.017219410 0.026118039
20 -0.017219410 -0.017219410
21 -0.017219410 -0.017219410
22 -0.060556859 -0.017219410
23 -0.060556859 -0.060556859
24 -0.060556859 -0.060556859
25 -0.060556859 -0.060556859
26 -0.060556859 -0.060556859
27 -0.060556859 -0.060556859
28 -0.060556859 -0.060556859
29 -0.060556859 -0.060556859
30 -0.060556859 -0.060556859
31 -0.060556859 -0.060556859
32 -0.017219410 -0.060556859
33 -0.017219410 -0.017219410
34 -0.017219410 -0.017219410
35 -0.017219410 -0.017219410
36 -0.017219410 -0.017219410
37 0.029443141 -0.017219410
38 -0.003894308 0.029443141
39 -0.003894308 -0.003894308
40 -0.003894308 -0.003894308
41 -0.003894308 -0.003894308
42 0.006105692 -0.003894308
43 0.016105692 0.006105692
44 0.016105692 0.016105692
45 0.026105692 0.016105692
46 -0.017231757 0.026105692
47 -0.017231757 -0.017231757
48 -0.007231757 -0.017231757
49 0.002768243 -0.007231757
50 0.002768243 0.002768243
51 0.056105692 0.002768243
52 0.012768243 0.056105692
53 0.056105692 0.012768243
54 0.056105692 0.056105692
55 0.012768243 0.056105692
56 0.066105692 0.012768243
57 0.066105692 0.066105692
58 0.066105692 0.066105692
59 0.066105692 0.066105692
> 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/7qwq81258718673.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> acf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/8ttst1258718673.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> pacf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Partial Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/9kf3w1258718673.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> opar <- par(mfrow = c(2,2), oma = c(0, 0, 1.1, 0))
> plot(mylm, las = 1, sub='Residual Diagnostics')
> par(opar)
> dev.off()
null device
1
> if (n > n25) {
+ postscript(file="/var/www/html/rcomp/tmp/10w76m1258718673.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
+ plot(kp3:nmkm3,gqarr[,2], main='Goldfeld-Quandt test',ylab='2-sided p-value',xlab='breakpoint')
+ grid()
+ dev.off()
+ }
null device
1
>
> #Note: the /var/www/html/rcomp/createtable file can be downloaded at http://www.wessa.net/cretab
> load(file="/var/www/html/rcomp/createtable")
>
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a, 'Multiple Linear Regression - Estimated Regression Equation', 1, TRUE)
> a<-table.row.end(a)
> myeq <- colnames(x)[1]
> myeq <- paste(myeq, '[t] = ', sep='')
> for (i in 1:k){
+ if (mysum$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/11ixrr1258718673.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/12w1591258718673.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/13luls1258718673.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/14kwdc1258718673.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/15eqge1258718673.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/16jc811258718673.tab")
+ }
>
> system("convert tmp/116hw1258718673.ps tmp/116hw1258718673.png")
> system("convert tmp/2f59w1258718673.ps tmp/2f59w1258718673.png")
> system("convert tmp/3x1oj1258718673.ps tmp/3x1oj1258718673.png")
> system("convert tmp/42c4d1258718673.ps tmp/42c4d1258718673.png")
> system("convert tmp/5z68q1258718673.ps tmp/5z68q1258718673.png")
> system("convert tmp/65zh11258718673.ps tmp/65zh11258718673.png")
> system("convert tmp/7qwq81258718673.ps tmp/7qwq81258718673.png")
> system("convert tmp/8ttst1258718673.ps tmp/8ttst1258718673.png")
> system("convert tmp/9kf3w1258718673.ps tmp/9kf3w1258718673.png")
> system("convert tmp/10w76m1258718673.ps tmp/10w76m1258718673.png")
>
>
> proc.time()
user system elapsed
2.436 1.530 2.845