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(4.24,0,4.15,0,3.93,0,3.7,0,3.7,0,3.65,0,3.55,0,3.43,0,3.47,0,3.58,0,3.67,0,3.72,0,3.8,0,3.76,0,3.63,0,3.48,0,3.41,0,3.43,0,3.5,0,3.62,0,3.58,0,3.52,0,3.45,0,3.36,0,3.27,0,3.21,0,3.19,0,3.16,0,3.12,0,3.06,0,3.01,0,2.98,0,2.97,0,3.02,0,3.07,0,3.18,0,3.29,1,3.43,1,3.61,1,3.74,1,3.87,1,3.88,1,4.09,1,4.19,1,4.2,1,4.29,1,4.37,1,4.47,1,4.61,1,4.65,1,4.69,1,4.82,1,4.86,1,4.87,1,5.01,1,5.03,1,5.13,1,5.18,1,5.21,1,5.26,1,5.25,1,5.2,1,5.16,1,5.19,1,5.39,1,5.58,1,5.76,1,5.89,1,5.98,1,6.02,1,5.62,1,4.87,1),dim=c(2,72),dimnames=list(c('Rente','dummy'),1:72))
> y <- array(NA,dim=c(2,72),dimnames=list(c('Rente','dummy'),1:72))
> for (i in 1:dim(x)[1])
+ {
+ for (j in 1:dim(x)[2])
+ {
+ y[i,j] <- as.numeric(x[i,j])
+ }
+ }
> par3 = 'No Linear Trend'
> par2 = 'Do not include Seasonal Dummies'
> par1 = '1'
> #'GNU S' R Code compiled by R2WASP v. 1.0.44 ()
> #Author: Prof. Dr. P. Wessa
> #To cite this work: AUTHOR(S), (YEAR), YOUR SOFTWARE TITLE (vNUMBER) in Free Statistics Software (v$_version), Office for Research Development and Education, URL http://www.wessa.net/rwasp_YOURPAGE.wasp/
> #Source of accompanying publication: Office for Research, Development, and Education
> #Technical description: Write here your technical program description (don't use hard returns!)
> library(lattice)
> library(lmtest)
Loading required package: zoo
Attaching package: 'zoo'
The following object(s) are masked from package:base :
as.Date.numeric
> n25 <- 25 #minimum number of obs. for Goldfeld-Quandt test
> par1 <- as.numeric(par1)
> x <- t(y)
> k <- length(x[1,])
> n <- length(x[,1])
> x1 <- cbind(x[,par1], x[,1:k!=par1])
> mycolnames <- c(colnames(x)[par1], colnames(x)[1:k!=par1])
> colnames(x1) <- mycolnames #colnames(x)[par1]
> x <- x1
> if (par3 == 'First Differences'){
+ x2 <- array(0, dim=c(n-1,k), dimnames=list(1:(n-1), paste('(1-B)',colnames(x),sep='')))
+ for (i in 1:n-1) {
+ for (j in 1:k) {
+ x2[i,j] <- x[i+1,j] - x[i,j]
+ }
+ }
+ x <- x2
+ }
> if (par2 == 'Include Monthly Dummies'){
+ x2 <- array(0, dim=c(n,11), dimnames=list(1:n, paste('M', seq(1:11), sep ='')))
+ for (i in 1:11){
+ x2[seq(i,n,12),i] <- 1
+ }
+ x <- cbind(x, x2)
+ }
> if (par2 == 'Include Quarterly Dummies'){
+ x2 <- array(0, dim=c(n,3), dimnames=list(1:n, paste('Q', seq(1:3), sep ='')))
+ for (i in 1:3){
+ x2[seq(i,n,4),i] <- 1
+ }
+ x <- cbind(x, x2)
+ }
> k <- length(x[1,])
> if (par3 == 'Linear Trend'){
+ x <- cbind(x, c(1:n))
+ colnames(x)[k+1] <- 't'
+ }
> x
Rente dummy
1 4.24 0
2 4.15 0
3 3.93 0
4 3.70 0
5 3.70 0
6 3.65 0
7 3.55 0
8 3.43 0
9 3.47 0
10 3.58 0
11 3.67 0
12 3.72 0
13 3.80 0
14 3.76 0
15 3.63 0
16 3.48 0
17 3.41 0
18 3.43 0
19 3.50 0
20 3.62 0
21 3.58 0
22 3.52 0
23 3.45 0
24 3.36 0
25 3.27 0
26 3.21 0
27 3.19 0
28 3.16 0
29 3.12 0
30 3.06 0
31 3.01 0
32 2.98 0
33 2.97 0
34 3.02 0
35 3.07 0
36 3.18 0
37 3.29 1
38 3.43 1
39 3.61 1
40 3.74 1
41 3.87 1
42 3.88 1
43 4.09 1
44 4.19 1
45 4.20 1
46 4.29 1
47 4.37 1
48 4.47 1
49 4.61 1
50 4.65 1
51 4.69 1
52 4.82 1
53 4.86 1
54 4.87 1
55 5.01 1
56 5.03 1
57 5.13 1
58 5.18 1
59 5.21 1
60 5.26 1
61 5.25 1
62 5.20 1
63 5.16 1
64 5.19 1
65 5.39 1
66 5.58 1
67 5.76 1
68 5.89 1
69 5.98 1
70 6.02 1
71 5.62 1
72 4.87 1
> k <- length(x[1,])
> df <- as.data.frame(x)
> (mylm <- lm(df))
Call:
lm(formula = df)
Coefficients:
(Intercept) dummy
3.460 1.336
> (mysum <- summary(mylm))
Call:
lm(formula = df)
Residuals:
Min 1Q Median 3Q Max
-1.50611 -0.32965 0.04972 0.33535 1.22389
Coefficients:
Estimate Std. Error t value Pr(>|t|)
(Intercept) 3.4603 0.0930 37.21 < 2e-16 ***
dummy 1.3358 0.1315 10.16 2.08e-15 ***
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
Residual standard error: 0.558 on 70 degrees of freedom
Multiple R-squared: 0.5957, Adjusted R-squared: 0.59
F-statistic: 103.2 on 1 and 70 DF, p-value: 2.085e-15
> 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,] 1.514764e-01 3.029528e-01 0.8485236
[2,] 9.480993e-02 1.896199e-01 0.9051901
[3,] 6.980736e-02 1.396147e-01 0.9301926
[4,] 6.328500e-02 1.265700e-01 0.9367150
[5,] 4.457983e-02 8.915967e-02 0.9554202
[6,] 2.402056e-02 4.804112e-02 0.9759794
[7,] 1.131113e-02 2.262226e-02 0.9886889
[8,] 5.021730e-03 1.004346e-02 0.9949783
[9,] 2.235129e-03 4.470258e-03 0.9977649
[10,] 9.354694e-04 1.870939e-03 0.9990645
[11,] 4.004421e-04 8.008841e-04 0.9995996
[12,] 2.388452e-04 4.776904e-04 0.9997612
[13,] 1.737105e-04 3.474211e-04 0.9998263
[14,] 1.081819e-04 2.163638e-04 0.9998918
[15,] 5.238169e-05 1.047634e-04 0.9999476
[16,] 2.087676e-05 4.175351e-05 0.9999791
[17,] 8.434379e-06 1.686876e-05 0.9999916
[18,] 3.681499e-06 7.362998e-06 0.9999963
[19,] 1.888499e-06 3.776997e-06 0.9999981
[20,] 1.311526e-06 2.623053e-06 0.9999987
[21,] 1.298685e-06 2.597369e-06 0.9999987
[22,] 1.540795e-06 3.081589e-06 0.9999985
[23,] 1.728533e-06 3.457067e-06 0.9999983
[24,] 1.946279e-06 3.892557e-06 0.9999981
[25,] 2.299684e-06 4.599369e-06 0.9999977
[26,] 3.092952e-06 6.185904e-06 0.9999969
[27,] 4.417096e-06 8.834193e-06 0.9999956
[28,] 6.068674e-06 1.213735e-05 0.9999939
[29,] 7.487898e-06 1.497580e-05 0.9999925
[30,] 6.933190e-06 1.386638e-05 0.9999931
[31,] 5.189836e-06 1.037967e-05 0.9999948
[32,] 2.891744e-06 5.783488e-06 0.9999971
[33,] 6.229777e-06 1.245955e-05 0.9999938
[34,] 1.420375e-05 2.840749e-05 0.9999858
[35,] 3.233836e-05 6.467672e-05 0.9999677
[36,] 7.666292e-05 1.533258e-04 0.9999233
[37,] 1.864871e-04 3.729742e-04 0.9998135
[38,] 5.151773e-04 1.030355e-03 0.9994848
[39,] 1.347605e-03 2.695209e-03 0.9986524
[40,] 3.373633e-03 6.747267e-03 0.9966264
[41,] 8.477735e-03 1.695547e-02 0.9915223
[42,] 2.032688e-02 4.065376e-02 0.9796731
[43,] 4.548859e-02 9.097719e-02 0.9545114
[44,] 9.096000e-02 1.819200e-01 0.9090400
[45,] 1.553115e-01 3.106229e-01 0.8446885
[46,] 2.400601e-01 4.801202e-01 0.7599399
[47,] 3.425797e-01 6.851595e-01 0.6574203
[48,] 4.345629e-01 8.691259e-01 0.5654371
[49,] 5.191666e-01 9.616668e-01 0.4808334
[50,] 6.015732e-01 7.968536e-01 0.3984268
[51,] 6.499040e-01 7.001920e-01 0.3500960
[52,] 6.872537e-01 6.254926e-01 0.3127463
[53,] 7.016919e-01 5.966161e-01 0.2983081
[54,] 7.017363e-01 5.965275e-01 0.2982637
[55,] 6.905076e-01 6.189847e-01 0.3094924
[56,] 6.657458e-01 6.685083e-01 0.3342542
[57,] 6.345773e-01 7.308454e-01 0.3654227
[58,] 6.101299e-01 7.797401e-01 0.3898701
[59,] 6.039591e-01 7.920817e-01 0.3960409
[60,] 6.018775e-01 7.962449e-01 0.3981225
[61,] 5.379160e-01 9.241681e-01 0.4620840
[62,] 4.312762e-01 8.625524e-01 0.5687238
[63,] 3.160852e-01 6.321704e-01 0.6839148
> postscript(file="/var/www/html/rcomp/tmp/1gj0h1293565576.ps",horizontal=F,onefile=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$resid)
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/2gj0h1293565576.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> plot(mysum$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/3rbzk1293565576.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> hist(mysum$resid, main='Residual Histogram', xlab='values of Residuals')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/4rbzk1293565576.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> densityplot(~mysum$resid,col='black',main='Residual Density Plot', xlab='values of Residuals')
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/5rbzk1293565576.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> qqnorm(mysum$resid, main='Residual Normal Q-Q Plot')
> qqline(mysum$resid)
> grid()
> dev.off()
null device
1
> (myerror <- as.ts(mysum$resid))
Time Series:
Start = 1
End = 72
Frequency = 1
1 2 3 4 5 6
0.779722222 0.689722222 0.469722222 0.239722222 0.239722222 0.189722222
7 8 9 10 11 12
0.089722222 -0.030277778 0.009722222 0.119722222 0.209722222 0.259722222
13 14 15 16 17 18
0.339722222 0.299722222 0.169722222 0.019722222 -0.050277778 -0.030277778
19 20 21 22 23 24
0.039722222 0.159722222 0.119722222 0.059722222 -0.010277778 -0.100277778
25 26 27 28 29 30
-0.190277778 -0.250277778 -0.270277778 -0.300277778 -0.340277778 -0.400277778
31 32 33 34 35 36
-0.450277778 -0.480277778 -0.490277778 -0.440277778 -0.390277778 -0.280277778
37 38 39 40 41 42
-1.506111111 -1.366111111 -1.186111111 -1.056111111 -0.926111111 -0.916111111
43 44 45 46 47 48
-0.706111111 -0.606111111 -0.596111111 -0.506111111 -0.426111111 -0.326111111
49 50 51 52 53 54
-0.186111111 -0.146111111 -0.106111111 0.023888889 0.063888889 0.073888889
55 56 57 58 59 60
0.213888889 0.233888889 0.333888889 0.383888889 0.413888889 0.463888889
61 62 63 64 65 66
0.453888889 0.403888889 0.363888889 0.393888889 0.593888889 0.783888889
67 68 69 70 71 72
0.963888889 1.093888889 1.183888889 1.223888889 0.823888889 0.073888889
> postscript(file="/var/www/html/rcomp/tmp/622y51293565576.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> dum <- cbind(lag(myerror,k=1),myerror)
> dum
Time Series:
Start = 0
End = 72
Frequency = 1
lag(myerror, k = 1) myerror
0 0.779722222 NA
1 0.689722222 0.779722222
2 0.469722222 0.689722222
3 0.239722222 0.469722222
4 0.239722222 0.239722222
5 0.189722222 0.239722222
6 0.089722222 0.189722222
7 -0.030277778 0.089722222
8 0.009722222 -0.030277778
9 0.119722222 0.009722222
10 0.209722222 0.119722222
11 0.259722222 0.209722222
12 0.339722222 0.259722222
13 0.299722222 0.339722222
14 0.169722222 0.299722222
15 0.019722222 0.169722222
16 -0.050277778 0.019722222
17 -0.030277778 -0.050277778
18 0.039722222 -0.030277778
19 0.159722222 0.039722222
20 0.119722222 0.159722222
21 0.059722222 0.119722222
22 -0.010277778 0.059722222
23 -0.100277778 -0.010277778
24 -0.190277778 -0.100277778
25 -0.250277778 -0.190277778
26 -0.270277778 -0.250277778
27 -0.300277778 -0.270277778
28 -0.340277778 -0.300277778
29 -0.400277778 -0.340277778
30 -0.450277778 -0.400277778
31 -0.480277778 -0.450277778
32 -0.490277778 -0.480277778
33 -0.440277778 -0.490277778
34 -0.390277778 -0.440277778
35 -0.280277778 -0.390277778
36 -1.506111111 -0.280277778
37 -1.366111111 -1.506111111
38 -1.186111111 -1.366111111
39 -1.056111111 -1.186111111
40 -0.926111111 -1.056111111
41 -0.916111111 -0.926111111
42 -0.706111111 -0.916111111
43 -0.606111111 -0.706111111
44 -0.596111111 -0.606111111
45 -0.506111111 -0.596111111
46 -0.426111111 -0.506111111
47 -0.326111111 -0.426111111
48 -0.186111111 -0.326111111
49 -0.146111111 -0.186111111
50 -0.106111111 -0.146111111
51 0.023888889 -0.106111111
52 0.063888889 0.023888889
53 0.073888889 0.063888889
54 0.213888889 0.073888889
55 0.233888889 0.213888889
56 0.333888889 0.233888889
57 0.383888889 0.333888889
58 0.413888889 0.383888889
59 0.463888889 0.413888889
60 0.453888889 0.463888889
61 0.403888889 0.453888889
62 0.363888889 0.403888889
63 0.393888889 0.363888889
64 0.593888889 0.393888889
65 0.783888889 0.593888889
66 0.963888889 0.783888889
67 1.093888889 0.963888889
68 1.183888889 1.093888889
69 1.223888889 1.183888889
70 0.823888889 1.223888889
71 0.073888889 0.823888889
72 NA 0.073888889
> dum1 <- dum[2:length(myerror),]
> dum1
lag(myerror, k = 1) myerror
[1,] 0.689722222 0.779722222
[2,] 0.469722222 0.689722222
[3,] 0.239722222 0.469722222
[4,] 0.239722222 0.239722222
[5,] 0.189722222 0.239722222
[6,] 0.089722222 0.189722222
[7,] -0.030277778 0.089722222
[8,] 0.009722222 -0.030277778
[9,] 0.119722222 0.009722222
[10,] 0.209722222 0.119722222
[11,] 0.259722222 0.209722222
[12,] 0.339722222 0.259722222
[13,] 0.299722222 0.339722222
[14,] 0.169722222 0.299722222
[15,] 0.019722222 0.169722222
[16,] -0.050277778 0.019722222
[17,] -0.030277778 -0.050277778
[18,] 0.039722222 -0.030277778
[19,] 0.159722222 0.039722222
[20,] 0.119722222 0.159722222
[21,] 0.059722222 0.119722222
[22,] -0.010277778 0.059722222
[23,] -0.100277778 -0.010277778
[24,] -0.190277778 -0.100277778
[25,] -0.250277778 -0.190277778
[26,] -0.270277778 -0.250277778
[27,] -0.300277778 -0.270277778
[28,] -0.340277778 -0.300277778
[29,] -0.400277778 -0.340277778
[30,] -0.450277778 -0.400277778
[31,] -0.480277778 -0.450277778
[32,] -0.490277778 -0.480277778
[33,] -0.440277778 -0.490277778
[34,] -0.390277778 -0.440277778
[35,] -0.280277778 -0.390277778
[36,] -1.506111111 -0.280277778
[37,] -1.366111111 -1.506111111
[38,] -1.186111111 -1.366111111
[39,] -1.056111111 -1.186111111
[40,] -0.926111111 -1.056111111
[41,] -0.916111111 -0.926111111
[42,] -0.706111111 -0.916111111
[43,] -0.606111111 -0.706111111
[44,] -0.596111111 -0.606111111
[45,] -0.506111111 -0.596111111
[46,] -0.426111111 -0.506111111
[47,] -0.326111111 -0.426111111
[48,] -0.186111111 -0.326111111
[49,] -0.146111111 -0.186111111
[50,] -0.106111111 -0.146111111
[51,] 0.023888889 -0.106111111
[52,] 0.063888889 0.023888889
[53,] 0.073888889 0.063888889
[54,] 0.213888889 0.073888889
[55,] 0.233888889 0.213888889
[56,] 0.333888889 0.233888889
[57,] 0.383888889 0.333888889
[58,] 0.413888889 0.383888889
[59,] 0.463888889 0.413888889
[60,] 0.453888889 0.463888889
[61,] 0.403888889 0.453888889
[62,] 0.363888889 0.403888889
[63,] 0.393888889 0.363888889
[64,] 0.593888889 0.393888889
[65,] 0.783888889 0.593888889
[66,] 0.963888889 0.783888889
[67,] 1.093888889 0.963888889
[68,] 1.183888889 1.093888889
[69,] 1.223888889 1.183888889
[70,] 0.823888889 1.223888889
[71,] 0.073888889 0.823888889
> z <- as.data.frame(dum1)
> z
lag(myerror, k = 1) myerror
1 0.689722222 0.779722222
2 0.469722222 0.689722222
3 0.239722222 0.469722222
4 0.239722222 0.239722222
5 0.189722222 0.239722222
6 0.089722222 0.189722222
7 -0.030277778 0.089722222
8 0.009722222 -0.030277778
9 0.119722222 0.009722222
10 0.209722222 0.119722222
11 0.259722222 0.209722222
12 0.339722222 0.259722222
13 0.299722222 0.339722222
14 0.169722222 0.299722222
15 0.019722222 0.169722222
16 -0.050277778 0.019722222
17 -0.030277778 -0.050277778
18 0.039722222 -0.030277778
19 0.159722222 0.039722222
20 0.119722222 0.159722222
21 0.059722222 0.119722222
22 -0.010277778 0.059722222
23 -0.100277778 -0.010277778
24 -0.190277778 -0.100277778
25 -0.250277778 -0.190277778
26 -0.270277778 -0.250277778
27 -0.300277778 -0.270277778
28 -0.340277778 -0.300277778
29 -0.400277778 -0.340277778
30 -0.450277778 -0.400277778
31 -0.480277778 -0.450277778
32 -0.490277778 -0.480277778
33 -0.440277778 -0.490277778
34 -0.390277778 -0.440277778
35 -0.280277778 -0.390277778
36 -1.506111111 -0.280277778
37 -1.366111111 -1.506111111
38 -1.186111111 -1.366111111
39 -1.056111111 -1.186111111
40 -0.926111111 -1.056111111
41 -0.916111111 -0.926111111
42 -0.706111111 -0.916111111
43 -0.606111111 -0.706111111
44 -0.596111111 -0.606111111
45 -0.506111111 -0.596111111
46 -0.426111111 -0.506111111
47 -0.326111111 -0.426111111
48 -0.186111111 -0.326111111
49 -0.146111111 -0.186111111
50 -0.106111111 -0.146111111
51 0.023888889 -0.106111111
52 0.063888889 0.023888889
53 0.073888889 0.063888889
54 0.213888889 0.073888889
55 0.233888889 0.213888889
56 0.333888889 0.233888889
57 0.383888889 0.333888889
58 0.413888889 0.383888889
59 0.463888889 0.413888889
60 0.453888889 0.463888889
61 0.403888889 0.453888889
62 0.363888889 0.403888889
63 0.393888889 0.363888889
64 0.593888889 0.393888889
65 0.783888889 0.593888889
66 0.963888889 0.783888889
67 1.093888889 0.963888889
68 1.183888889 1.093888889
69 1.223888889 1.183888889
70 0.823888889 1.223888889
71 0.073888889 0.823888889
> 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/7vbgq1293565576.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> acf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/8vbgq1293565576.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> pacf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Partial Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/9vbgq1293565576.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> opar <- par(mfrow = c(2,2), oma = c(0, 0, 1.1, 0))
> plot(mylm, las = 1, sub='Residual Diagnostics')
hat values (leverages) are all = 0.02777778
and there are no factor predictors; no plot no. 5
> par(opar)
> dev.off()
null device
1
> if (n > n25) {
+ postscript(file="/var/www/html/rcomp/tmp/105lft1293565576.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
+ plot(kp3:nmkm3,gqarr[,2], main='Goldfeld-Quandt test',ylab='2-sided p-value',xlab='breakpoint')
+ grid()
+ dev.off()
+ }
null device
1
>
> #Note: the /var/www/html/rcomp/createtable file can be downloaded at http://www.wessa.net/cretab
> load(file="/var/www/html/rcomp/createtable")
>
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a, 'Multiple Linear Regression - Estimated Regression Equation', 1, TRUE)
> a<-table.row.end(a)
> myeq <- colnames(x)[1]
> myeq <- paste(myeq, '[t] = ', sep='')
> for (i in 1:k){
+ if (mysum$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/11rley1293565576.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/12u3cm1293565576.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/138dsv1293565576.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/14ce8j1293565576.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/15xw7p1293565576.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/160xnd1293565576.tab")
+ }
>
> try(system("convert tmp/1gj0h1293565576.ps tmp/1gj0h1293565576.png",intern=TRUE))
character(0)
> try(system("convert tmp/2gj0h1293565576.ps tmp/2gj0h1293565576.png",intern=TRUE))
character(0)
> try(system("convert tmp/3rbzk1293565576.ps tmp/3rbzk1293565576.png",intern=TRUE))
character(0)
> try(system("convert tmp/4rbzk1293565576.ps tmp/4rbzk1293565576.png",intern=TRUE))
character(0)
> try(system("convert tmp/5rbzk1293565576.ps tmp/5rbzk1293565576.png",intern=TRUE))
character(0)
> try(system("convert tmp/622y51293565576.ps tmp/622y51293565576.png",intern=TRUE))
character(0)
> try(system("convert tmp/7vbgq1293565576.ps tmp/7vbgq1293565576.png",intern=TRUE))
character(0)
> try(system("convert tmp/8vbgq1293565576.ps tmp/8vbgq1293565576.png",intern=TRUE))
character(0)
> try(system("convert tmp/9vbgq1293565576.ps tmp/9vbgq1293565576.png",intern=TRUE))
character(0)
> try(system("convert tmp/105lft1293565576.ps tmp/105lft1293565576.png",intern=TRUE))
character(0)
>
>
> proc.time()
user system elapsed
2.672 1.649 6.343