R version 2.9.0 (2009-04-17)
Copyright (C) 2009 The R Foundation for Statistical Computing
ISBN 3-900051-07-0
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> x <- array(list(2.11,0,2.09,0,2.05,0,2.08,0,2.06,0,2.06,0,2.08,0,2.07,0,2.06,0,2.07,0,2.06,0,2.09,0,2.07,0,2.09,0,2.28,0,2.33,0,2.35,0,2.52,0,2.63,0,2.58,0,2.70,0,2.81,0,2.97,0,3.04,0,3.28,0,3.33,0,3.50,0,3.56,0,3.57,0,3.69,0,3.82,0,3.79,0,3.96,0,4.06,0,4.05,0,4.03,0,3.94,0,4.02,0,3.88,0,4.02,0,4.03,0,4.09,0,3.99,0,4.01,0,4.01,0,4.19,0,4.30,0,4.27,0,3.82,0,3.15,1,2.49,1,1.81,1,1.26,1,1.06,1,0.84,1,0.78,1,0.70,1,0.36,1,0.35,1,0.36,1),dim=c(2,60),dimnames=list(c('Y','X'),1:60))
> y <- array(NA,dim=c(2,60),dimnames=list(c('Y','X'),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 = 'Include Monthly 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
Y X M1 M2 M3 M4 M5 M6 M7 M8 M9 M10 M11
1 2.11 0 1 0 0 0 0 0 0 0 0 0 0
2 2.09 0 0 1 0 0 0 0 0 0 0 0 0
3 2.05 0 0 0 1 0 0 0 0 0 0 0 0
4 2.08 0 0 0 0 1 0 0 0 0 0 0 0
5 2.06 0 0 0 0 0 1 0 0 0 0 0 0
6 2.06 0 0 0 0 0 0 1 0 0 0 0 0
7 2.08 0 0 0 0 0 0 0 1 0 0 0 0
8 2.07 0 0 0 0 0 0 0 0 1 0 0 0
9 2.06 0 0 0 0 0 0 0 0 0 1 0 0
10 2.07 0 0 0 0 0 0 0 0 0 0 1 0
11 2.06 0 0 0 0 0 0 0 0 0 0 0 1
12 2.09 0 0 0 0 0 0 0 0 0 0 0 0
13 2.07 0 1 0 0 0 0 0 0 0 0 0 0
14 2.09 0 0 1 0 0 0 0 0 0 0 0 0
15 2.28 0 0 0 1 0 0 0 0 0 0 0 0
16 2.33 0 0 0 0 1 0 0 0 0 0 0 0
17 2.35 0 0 0 0 0 1 0 0 0 0 0 0
18 2.52 0 0 0 0 0 0 1 0 0 0 0 0
19 2.63 0 0 0 0 0 0 0 1 0 0 0 0
20 2.58 0 0 0 0 0 0 0 0 1 0 0 0
21 2.70 0 0 0 0 0 0 0 0 0 1 0 0
22 2.81 0 0 0 0 0 0 0 0 0 0 1 0
23 2.97 0 0 0 0 0 0 0 0 0 0 0 1
24 3.04 0 0 0 0 0 0 0 0 0 0 0 0
25 3.28 0 1 0 0 0 0 0 0 0 0 0 0
26 3.33 0 0 1 0 0 0 0 0 0 0 0 0
27 3.50 0 0 0 1 0 0 0 0 0 0 0 0
28 3.56 0 0 0 0 1 0 0 0 0 0 0 0
29 3.57 0 0 0 0 0 1 0 0 0 0 0 0
30 3.69 0 0 0 0 0 0 1 0 0 0 0 0
31 3.82 0 0 0 0 0 0 0 1 0 0 0 0
32 3.79 0 0 0 0 0 0 0 0 1 0 0 0
33 3.96 0 0 0 0 0 0 0 0 0 1 0 0
34 4.06 0 0 0 0 0 0 0 0 0 0 1 0
35 4.05 0 0 0 0 0 0 0 0 0 0 0 1
36 4.03 0 0 0 0 0 0 0 0 0 0 0 0
37 3.94 0 1 0 0 0 0 0 0 0 0 0 0
38 4.02 0 0 1 0 0 0 0 0 0 0 0 0
39 3.88 0 0 0 1 0 0 0 0 0 0 0 0
40 4.02 0 0 0 0 1 0 0 0 0 0 0 0
41 4.03 0 0 0 0 0 1 0 0 0 0 0 0
42 4.09 0 0 0 0 0 0 1 0 0 0 0 0
43 3.99 0 0 0 0 0 0 0 1 0 0 0 0
44 4.01 0 0 0 0 0 0 0 0 1 0 0 0
45 4.01 0 0 0 0 0 0 0 0 0 1 0 0
46 4.19 0 0 0 0 0 0 0 0 0 0 1 0
47 4.30 0 0 0 0 0 0 0 0 0 0 0 1
48 4.27 0 0 0 0 0 0 0 0 0 0 0 0
49 3.82 0 1 0 0 0 0 0 0 0 0 0 0
50 3.15 1 0 1 0 0 0 0 0 0 0 0 0
51 2.49 1 0 0 1 0 0 0 0 0 0 0 0
52 1.81 1 0 0 0 1 0 0 0 0 0 0 0
53 1.26 1 0 0 0 0 1 0 0 0 0 0 0
54 1.06 1 0 0 0 0 0 1 0 0 0 0 0
55 0.84 1 0 0 0 0 0 0 1 0 0 0 0
56 0.78 1 0 0 0 0 0 0 0 1 0 0 0
57 0.70 1 0 0 0 0 0 0 0 0 1 0 0
58 0.36 1 0 0 0 0 0 0 0 0 0 1 0
59 0.35 1 0 0 0 0 0 0 0 0 0 0 1
60 0.36 1 0 0 0 0 0 0 0 0 0 0 0
> k <- length(x[1,])
> df <- as.data.frame(x)
> (mylm <- lm(df))
Call:
lm(formula = df)
Coefficients:
(Intercept) X M1 M2 M3 M4
3.14255 -1.92273 -0.09855 0.17800 0.08200 0.00200
M5 M6 M7 M8 M9 M10
-0.10400 -0.07400 -0.08600 -0.11200 -0.07200 -0.06000
M11
-0.01200
> (mysum <- summary(mylm))
Call:
lm(formula = df)
Residuals:
Min 1Q Median 3Q Max
-1.23055 -0.87836 -0.09418 0.87845 1.75218
Coefficients:
Estimate Std. Error t value Pr(>|t|)
(Intercept) 3.14255 0.43284 7.260 3.3e-09 ***
X -1.92273 0.32262 -5.960 3.1e-07 ***
M1 -0.09854 0.60872 -0.162 0.872
M2 0.17800 0.60529 0.294 0.770
M3 0.08200 0.60529 0.135 0.893
M4 0.00200 0.60529 0.003 0.997
M5 -0.10400 0.60529 -0.172 0.864
M6 -0.07400 0.60529 -0.122 0.903
M7 -0.08600 0.60529 -0.142 0.888
M8 -0.11200 0.60529 -0.185 0.854
M9 -0.07200 0.60529 -0.119 0.906
M10 -0.06000 0.60529 -0.099 0.921
M11 -0.01200 0.60529 -0.020 0.984
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
Residual standard error: 0.9571 on 47 degrees of freedom
Multiple R-squared: 0.4366, Adjusted R-squared: 0.2927
F-statistic: 3.035 on 12 and 47 DF, p-value: 0.003170
> 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,] 0.010141438 0.020282876 0.989858562
[2,] 0.005454162 0.010908325 0.994545838
[3,] 0.006980236 0.013960472 0.993019764
[4,] 0.009727805 0.019455611 0.990272195
[5,] 0.010227243 0.020454487 0.989772757
[6,] 0.015033188 0.030066377 0.984966812
[7,] 0.024443295 0.048886589 0.975556705
[8,] 0.047228018 0.094456036 0.952771982
[9,] 0.076201113 0.152402227 0.923798887
[10,] 0.175830787 0.351661574 0.824169213
[11,] 0.437178901 0.874357802 0.562821099
[12,] 0.647540470 0.704919060 0.352459530
[13,] 0.763559657 0.472880685 0.236440343
[14,] 0.817497288 0.365005424 0.182502712
[15,] 0.844067176 0.311865648 0.155932824
[16,] 0.855922624 0.288154751 0.144077376
[17,] 0.857125353 0.285749294 0.142874647
[18,] 0.858322049 0.283355903 0.141677951
[19,] 0.857551836 0.284896328 0.142448164
[20,] 0.841976507 0.316046986 0.158023493
[21,] 0.814514075 0.370971850 0.185485925
[22,] 0.777403429 0.445193142 0.222596571
[23,] 0.935094832 0.129810336 0.064905168
[24,] 0.990132955 0.019734090 0.009867045
[25,] 0.997055717 0.005888565 0.002944283
[26,] 0.997251623 0.005496755 0.002748377
[27,] 0.995612172 0.008775657 0.004387828
[28,] 0.991752445 0.016495109 0.008247555
[29,] 0.985920531 0.028158938 0.014079469
> postscript(file="/var/www/html/rcomp/tmp/1ddqc1259315821.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$resid)
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/27tzf1259315821.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> plot(mysum$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/3r9gc1259315821.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> hist(mysum$resid, main='Residual Histogram', xlab='values of Residuals')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/4kq141259315821.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> densityplot(~mysum$resid,col='black',main='Residual Density Plot', xlab='values of Residuals')
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/55qwe1259315821.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
-0.934000000 -1.230545455 -1.174545455 -1.064545455 -0.978545455 -1.008545455
7 8 9 10 11 12
-0.976545455 -0.960545455 -1.010545455 -1.012545455 -1.070545455 -1.052545455
13 14 15 16 17 18
-0.974000000 -1.230545455 -0.944545455 -0.814545455 -0.688545455 -0.548545455
19 20 21 22 23 24
-0.426545455 -0.450545455 -0.370545455 -0.272545455 -0.160545455 -0.102545455
25 26 27 28 29 30
0.236000000 0.009454545 0.275454545 0.415454545 0.531454545 0.621454545
31 32 33 34 35 36
0.763454545 0.759454545 0.889454545 0.977454545 0.919454545 0.887454545
37 38 39 40 41 42
0.896000000 0.699454545 0.655454545 0.875454545 0.991454545 1.021454545
43 44 45 46 47 48
0.933454545 0.979454545 0.939454545 1.107454545 1.169454545 1.127454545
49 50 51 52 53 54
0.776000000 1.752181818 1.188181818 0.588181818 0.144181818 -0.085818182
55 56 57 58 59 60
-0.293818182 -0.327818182 -0.447818182 -0.799818182 -0.857818182 -0.859818182
> postscript(file="/var/www/html/rcomp/tmp/6qmhs1259315821.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 -0.934000000 NA
1 -1.230545455 -0.934000000
2 -1.174545455 -1.230545455
3 -1.064545455 -1.174545455
4 -0.978545455 -1.064545455
5 -1.008545455 -0.978545455
6 -0.976545455 -1.008545455
7 -0.960545455 -0.976545455
8 -1.010545455 -0.960545455
9 -1.012545455 -1.010545455
10 -1.070545455 -1.012545455
11 -1.052545455 -1.070545455
12 -0.974000000 -1.052545455
13 -1.230545455 -0.974000000
14 -0.944545455 -1.230545455
15 -0.814545455 -0.944545455
16 -0.688545455 -0.814545455
17 -0.548545455 -0.688545455
18 -0.426545455 -0.548545455
19 -0.450545455 -0.426545455
20 -0.370545455 -0.450545455
21 -0.272545455 -0.370545455
22 -0.160545455 -0.272545455
23 -0.102545455 -0.160545455
24 0.236000000 -0.102545455
25 0.009454545 0.236000000
26 0.275454545 0.009454545
27 0.415454545 0.275454545
28 0.531454545 0.415454545
29 0.621454545 0.531454545
30 0.763454545 0.621454545
31 0.759454545 0.763454545
32 0.889454545 0.759454545
33 0.977454545 0.889454545
34 0.919454545 0.977454545
35 0.887454545 0.919454545
36 0.896000000 0.887454545
37 0.699454545 0.896000000
38 0.655454545 0.699454545
39 0.875454545 0.655454545
40 0.991454545 0.875454545
41 1.021454545 0.991454545
42 0.933454545 1.021454545
43 0.979454545 0.933454545
44 0.939454545 0.979454545
45 1.107454545 0.939454545
46 1.169454545 1.107454545
47 1.127454545 1.169454545
48 0.776000000 1.127454545
49 1.752181818 0.776000000
50 1.188181818 1.752181818
51 0.588181818 1.188181818
52 0.144181818 0.588181818
53 -0.085818182 0.144181818
54 -0.293818182 -0.085818182
55 -0.327818182 -0.293818182
56 -0.447818182 -0.327818182
57 -0.799818182 -0.447818182
58 -0.857818182 -0.799818182
59 -0.859818182 -0.857818182
60 NA -0.859818182
> dum1 <- dum[2:length(myerror),]
> dum1
lag(myerror, k = 1) myerror
[1,] -1.230545455 -0.934000000
[2,] -1.174545455 -1.230545455
[3,] -1.064545455 -1.174545455
[4,] -0.978545455 -1.064545455
[5,] -1.008545455 -0.978545455
[6,] -0.976545455 -1.008545455
[7,] -0.960545455 -0.976545455
[8,] -1.010545455 -0.960545455
[9,] -1.012545455 -1.010545455
[10,] -1.070545455 -1.012545455
[11,] -1.052545455 -1.070545455
[12,] -0.974000000 -1.052545455
[13,] -1.230545455 -0.974000000
[14,] -0.944545455 -1.230545455
[15,] -0.814545455 -0.944545455
[16,] -0.688545455 -0.814545455
[17,] -0.548545455 -0.688545455
[18,] -0.426545455 -0.548545455
[19,] -0.450545455 -0.426545455
[20,] -0.370545455 -0.450545455
[21,] -0.272545455 -0.370545455
[22,] -0.160545455 -0.272545455
[23,] -0.102545455 -0.160545455
[24,] 0.236000000 -0.102545455
[25,] 0.009454545 0.236000000
[26,] 0.275454545 0.009454545
[27,] 0.415454545 0.275454545
[28,] 0.531454545 0.415454545
[29,] 0.621454545 0.531454545
[30,] 0.763454545 0.621454545
[31,] 0.759454545 0.763454545
[32,] 0.889454545 0.759454545
[33,] 0.977454545 0.889454545
[34,] 0.919454545 0.977454545
[35,] 0.887454545 0.919454545
[36,] 0.896000000 0.887454545
[37,] 0.699454545 0.896000000
[38,] 0.655454545 0.699454545
[39,] 0.875454545 0.655454545
[40,] 0.991454545 0.875454545
[41,] 1.021454545 0.991454545
[42,] 0.933454545 1.021454545
[43,] 0.979454545 0.933454545
[44,] 0.939454545 0.979454545
[45,] 1.107454545 0.939454545
[46,] 1.169454545 1.107454545
[47,] 1.127454545 1.169454545
[48,] 0.776000000 1.127454545
[49,] 1.752181818 0.776000000
[50,] 1.188181818 1.752181818
[51,] 0.588181818 1.188181818
[52,] 0.144181818 0.588181818
[53,] -0.085818182 0.144181818
[54,] -0.293818182 -0.085818182
[55,] -0.327818182 -0.293818182
[56,] -0.447818182 -0.327818182
[57,] -0.799818182 -0.447818182
[58,] -0.857818182 -0.799818182
[59,] -0.859818182 -0.857818182
> z <- as.data.frame(dum1)
> z
lag(myerror, k = 1) myerror
1 -1.230545455 -0.934000000
2 -1.174545455 -1.230545455
3 -1.064545455 -1.174545455
4 -0.978545455 -1.064545455
5 -1.008545455 -0.978545455
6 -0.976545455 -1.008545455
7 -0.960545455 -0.976545455
8 -1.010545455 -0.960545455
9 -1.012545455 -1.010545455
10 -1.070545455 -1.012545455
11 -1.052545455 -1.070545455
12 -0.974000000 -1.052545455
13 -1.230545455 -0.974000000
14 -0.944545455 -1.230545455
15 -0.814545455 -0.944545455
16 -0.688545455 -0.814545455
17 -0.548545455 -0.688545455
18 -0.426545455 -0.548545455
19 -0.450545455 -0.426545455
20 -0.370545455 -0.450545455
21 -0.272545455 -0.370545455
22 -0.160545455 -0.272545455
23 -0.102545455 -0.160545455
24 0.236000000 -0.102545455
25 0.009454545 0.236000000
26 0.275454545 0.009454545
27 0.415454545 0.275454545
28 0.531454545 0.415454545
29 0.621454545 0.531454545
30 0.763454545 0.621454545
31 0.759454545 0.763454545
32 0.889454545 0.759454545
33 0.977454545 0.889454545
34 0.919454545 0.977454545
35 0.887454545 0.919454545
36 0.896000000 0.887454545
37 0.699454545 0.896000000
38 0.655454545 0.699454545
39 0.875454545 0.655454545
40 0.991454545 0.875454545
41 1.021454545 0.991454545
42 0.933454545 1.021454545
43 0.979454545 0.933454545
44 0.939454545 0.979454545
45 1.107454545 0.939454545
46 1.169454545 1.107454545
47 1.127454545 1.169454545
48 0.776000000 1.127454545
49 1.752181818 0.776000000
50 1.188181818 1.752181818
51 0.588181818 1.188181818
52 0.144181818 0.588181818
53 -0.085818182 0.144181818
54 -0.293818182 -0.085818182
55 -0.327818182 -0.293818182
56 -0.447818182 -0.327818182
57 -0.799818182 -0.447818182
58 -0.857818182 -0.799818182
59 -0.859818182 -0.857818182
> 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/74z5d1259315821.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> acf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/85vbc1259315821.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> pacf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Partial Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/9g3eb1259315821.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> opar <- par(mfrow = c(2,2), oma = c(0, 0, 1.1, 0))
> plot(mylm, las = 1, sub='Residual Diagnostics')
> par(opar)
> dev.off()
null device
1
> if (n > n25) {
+ postscript(file="/var/www/html/rcomp/tmp/10n6zd1259315821.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
+ plot(kp3:nmkm3,gqarr[,2], main='Goldfeld-Quandt test',ylab='2-sided p-value',xlab='breakpoint')
+ grid()
+ dev.off()
+ }
null device
1
>
> #Note: the /var/www/html/rcomp/createtable file can be downloaded at http://www.wessa.net/cretab
> load(file="/var/www/html/rcomp/createtable")
>
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a, 'Multiple Linear Regression - Estimated Regression Equation', 1, TRUE)
> a<-table.row.end(a)
> myeq <- colnames(x)[1]
> myeq <- paste(myeq, '[t] = ', sep='')
> for (i in 1:k){
+ if (mysum$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/11x8wn1259315821.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/12z0r21259315821.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/1377wx1259315821.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/14w8jc1259315821.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/15v3g21259315821.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/16md4v1259315821.tab")
+ }
>
> system("convert tmp/1ddqc1259315821.ps tmp/1ddqc1259315821.png")
> system("convert tmp/27tzf1259315821.ps tmp/27tzf1259315821.png")
> system("convert tmp/3r9gc1259315821.ps tmp/3r9gc1259315821.png")
> system("convert tmp/4kq141259315821.ps tmp/4kq141259315821.png")
> system("convert tmp/55qwe1259315821.ps tmp/55qwe1259315821.png")
> system("convert tmp/6qmhs1259315821.ps tmp/6qmhs1259315821.png")
> system("convert tmp/74z5d1259315821.ps tmp/74z5d1259315821.png")
> system("convert tmp/85vbc1259315821.ps tmp/85vbc1259315821.png")
> system("convert tmp/9g3eb1259315821.ps tmp/9g3eb1259315821.png")
> system("convert tmp/10n6zd1259315821.ps tmp/10n6zd1259315821.png")
>
>
> proc.time()
user system elapsed
2.400 1.556 2.834