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(16198.9
+ ,16896.2
+ ,0
+ ,16554.2
+ ,16698
+ ,0
+ ,19554.2
+ ,19691.6
+ ,0
+ ,15903.8
+ ,15930.7
+ ,0
+ ,18003.8
+ ,17444.6
+ ,0
+ ,18329.6
+ ,17699.4
+ ,0
+ ,16260.7
+ ,15189.8
+ ,0
+ ,14851.9
+ ,15672.7
+ ,0
+ ,18174.1
+ ,17180.8
+ ,0
+ ,18406.6
+ ,17664.9
+ ,0
+ ,18466.5
+ ,17862.9
+ ,0
+ ,16016.5
+ ,16162.3
+ ,0
+ ,17428.5
+ ,17463.6
+ ,0
+ ,17167.2
+ ,16772.1
+ ,0
+ ,19630
+ ,19106.9
+ ,0
+ ,17183.6
+ ,16721.3
+ ,0
+ ,18344.7
+ ,18161.3
+ ,0
+ ,19301.4
+ ,18509.9
+ ,0
+ ,18147.5
+ ,17802.7
+ ,0
+ ,16192.9
+ ,16409.9
+ ,0
+ ,18374.4
+ ,17967.7
+ ,0
+ ,20515.2
+ ,20286.6
+ ,0
+ ,18957.2
+ ,19537.3
+ ,0
+ ,16471.5
+ ,18021.9
+ ,0
+ ,18746.8
+ ,20194.3
+ ,0
+ ,19009.5
+ ,19049.6
+ ,0
+ ,19211.2
+ ,20244.7
+ ,0
+ ,20547.7
+ ,21473.3
+ ,0
+ ,19325.8
+ ,19673.6
+ ,0
+ ,20605.5
+ ,21053.2
+ ,0
+ ,20056.9
+ ,20159.5
+ ,0
+ ,16141.4
+ ,18203.6
+ ,0
+ ,20359.8
+ ,21289.5
+ ,0
+ ,19711.6
+ ,20432.3
+ ,1
+ ,15638.6
+ ,17180.4
+ ,1
+ ,14384.5
+ ,15816.8
+ ,1
+ ,13855.6
+ ,15071.8
+ ,1
+ ,14308.3
+ ,14521.1
+ ,1
+ ,15290.6
+ ,15668.8
+ ,1
+ ,14423.8
+ ,14346.9
+ ,1
+ ,13779.7
+ ,13881
+ ,1
+ ,15686.3
+ ,15465.9
+ ,1
+ ,14733.8
+ ,14238.2
+ ,1
+ ,12522.5
+ ,13557.7
+ ,1
+ ,16189.4
+ ,16127.6
+ ,1
+ ,16059.1
+ ,16793.9
+ ,1
+ ,16007.1
+ ,16014
+ ,1
+ ,15806.8
+ ,16867.9
+ ,1
+ ,15160
+ ,16014.6
+ ,0
+ ,15692.1
+ ,15878.6
+ ,0
+ ,18908.9
+ ,18664.9
+ ,0
+ ,16969.9
+ ,17962.5
+ ,0
+ ,16997.5
+ ,17332.7
+ ,0
+ ,19858.9
+ ,19542.1
+ ,0
+ ,17681.2
+ ,17203.6
+ ,0)
+ ,dim=c(3
+ ,55)
+ ,dimnames=list(c('uitvoer'
+ ,'invoer'
+ ,'crisis')
+ ,1:55))
> y <- array(NA,dim=c(3,55),dimnames=list(c('uitvoer','invoer','crisis'),1:55))
> 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
uitvoer invoer crisis M1 M2 M3 M4 M5 M6 M7 M8 M9 M10 M11
1 16198.9 16896.2 0 1 0 0 0 0 0 0 0 0 0 0
2 16554.2 16698.0 0 0 1 0 0 0 0 0 0 0 0 0
3 19554.2 19691.6 0 0 0 1 0 0 0 0 0 0 0 0
4 15903.8 15930.7 0 0 0 0 1 0 0 0 0 0 0 0
5 18003.8 17444.6 0 0 0 0 0 1 0 0 0 0 0 0
6 18329.6 17699.4 0 0 0 0 0 0 1 0 0 0 0 0
7 16260.7 15189.8 0 0 0 0 0 0 0 1 0 0 0 0
8 14851.9 15672.7 0 0 0 0 0 0 0 0 1 0 0 0
9 18174.1 17180.8 0 0 0 0 0 0 0 0 0 1 0 0
10 18406.6 17664.9 0 0 0 0 0 0 0 0 0 0 1 0
11 18466.5 17862.9 0 0 0 0 0 0 0 0 0 0 0 1
12 16016.5 16162.3 0 0 0 0 0 0 0 0 0 0 0 0
13 17428.5 17463.6 0 1 0 0 0 0 0 0 0 0 0 0
14 17167.2 16772.1 0 0 1 0 0 0 0 0 0 0 0 0
15 19630.0 19106.9 0 0 0 1 0 0 0 0 0 0 0 0
16 17183.6 16721.3 0 0 0 0 1 0 0 0 0 0 0 0
17 18344.7 18161.3 0 0 0 0 0 1 0 0 0 0 0 0
18 19301.4 18509.9 0 0 0 0 0 0 1 0 0 0 0 0
19 18147.5 17802.7 0 0 0 0 0 0 0 1 0 0 0 0
20 16192.9 16409.9 0 0 0 0 0 0 0 0 1 0 0 0
21 18374.4 17967.7 0 0 0 0 0 0 0 0 0 1 0 0
22 20515.2 20286.6 0 0 0 0 0 0 0 0 0 0 1 0
23 18957.2 19537.3 0 0 0 0 0 0 0 0 0 0 0 1
24 16471.5 18021.9 0 0 0 0 0 0 0 0 0 0 0 0
25 18746.8 20194.3 0 1 0 0 0 0 0 0 0 0 0 0
26 19009.5 19049.6 0 0 1 0 0 0 0 0 0 0 0 0
27 19211.2 20244.7 0 0 0 1 0 0 0 0 0 0 0 0
28 20547.7 21473.3 0 0 0 0 1 0 0 0 0 0 0 0
29 19325.8 19673.6 0 0 0 0 0 1 0 0 0 0 0 0
30 20605.5 21053.2 0 0 0 0 0 0 1 0 0 0 0 0
31 20056.9 20159.5 0 0 0 0 0 0 0 1 0 0 0 0
32 16141.4 18203.6 0 0 0 0 0 0 0 0 1 0 0 0
33 20359.8 21289.5 0 0 0 0 0 0 0 0 0 1 0 0
34 19711.6 20432.3 1 0 0 0 0 0 0 0 0 0 1 0
35 15638.6 17180.4 1 0 0 0 0 0 0 0 0 0 0 1
36 14384.5 15816.8 1 0 0 0 0 0 0 0 0 0 0 0
37 13855.6 15071.8 1 1 0 0 0 0 0 0 0 0 0 0
38 14308.3 14521.1 1 0 1 0 0 0 0 0 0 0 0 0
39 15290.6 15668.8 1 0 0 1 0 0 0 0 0 0 0 0
40 14423.8 14346.9 1 0 0 0 1 0 0 0 0 0 0 0
41 13779.7 13881.0 1 0 0 0 0 1 0 0 0 0 0 0
42 15686.3 15465.9 1 0 0 0 0 0 1 0 0 0 0 0
43 14733.8 14238.2 1 0 0 0 0 0 0 1 0 0 0 0
44 12522.5 13557.7 1 0 0 0 0 0 0 0 1 0 0 0
45 16189.4 16127.6 1 0 0 0 0 0 0 0 0 1 0 0
46 16059.1 16793.9 1 0 0 0 0 0 0 0 0 0 1 0
47 16007.1 16014.0 1 0 0 0 0 0 0 0 0 0 0 1
48 15806.8 16867.9 1 0 0 0 0 0 0 0 0 0 0 0
49 15160.0 16014.6 0 1 0 0 0 0 0 0 0 0 0 0
50 15692.1 15878.6 0 0 1 0 0 0 0 0 0 0 0 0
51 18908.9 18664.9 0 0 0 1 0 0 0 0 0 0 0 0
52 16969.9 17962.5 0 0 0 0 1 0 0 0 0 0 0 0
53 16997.5 17332.7 0 0 0 0 0 1 0 0 0 0 0 0
54 19858.9 19542.1 0 0 0 0 0 0 1 0 0 0 0 0
55 17681.2 17203.6 0 0 0 0 0 0 0 1 0 0 0 0
> k <- length(x[1,])
> df <- as.data.frame(x)
> (mylm <- lm(df))
Call:
lm(formula = df)
Coefficients:
(Intercept) invoer crisis M1 M2 M3
3885.4464 0.7349 -1001.2832 5.8095 674.0416 1109.7768
M4 M5 M6 M7 M8 M9
616.8825 892.8245 1509.7493 1257.7076 -437.2239 1307.6929
M10 M11
1476.8239 913.0469
> (mysum <- summary(mylm))
Call:
lm(formula = df)
Residuals:
Min 1Q Median 3Q Max
-784.00 -208.30 62.89 273.81 703.73
Coefficients:
Estimate Std. Error t value Pr(>|t|)
(Intercept) 3.885e+03 8.298e+02 4.682 3.10e-05 ***
invoer 7.349e-01 4.418e-02 16.633 < 2e-16 ***
crisis -1.001e+03 1.813e+02 -5.523 2.06e-06 ***
M1 5.810e+00 2.983e+02 0.019 0.984556
M2 6.740e+02 3.006e+02 2.242 0.030427 *
M3 1.110e+03 3.022e+02 3.672 0.000688 ***
M4 6.169e+02 2.980e+02 2.070 0.044771 *
M5 8.928e+02 2.980e+02 2.996 0.004621 **
M6 1.510e+03 3.007e+02 5.021 1.05e-05 ***
M7 1.258e+03 2.990e+02 4.207 0.000137 ***
M8 -4.372e+02 3.190e+02 -1.371 0.177957
M9 1.308e+03 3.146e+02 4.157 0.000160 ***
M10 1.477e+03 3.241e+02 4.556 4.61e-05 ***
M11 9.130e+02 3.136e+02 2.912 0.005790 **
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
Residual standard error: 439.6 on 41 degrees of freedom
Multiple R-squared: 0.964, Adjusted R-squared: 0.9526
F-statistic: 84.46 on 13 and 41 DF, p-value: < 2.2e-16
> if (n > n25) {
+ kp3 <- k + 3
+ nmkm3 <- n - k - 3
+ gqarr <- array(NA, dim=c(nmkm3-kp3+1,3))
+ numgqtests <- 0
+ numsignificant1 <- 0
+ numsignificant5 <- 0
+ numsignificant10 <- 0
+ for (mypoint in kp3:nmkm3) {
+ j <- 0
+ numgqtests <- numgqtests + 1
+ for (myalt in c('greater', 'two.sided', 'less')) {
+ j <- j + 1
+ gqarr[mypoint-kp3+1,j] <- gqtest(mylm, point=mypoint, alternative=myalt)$p.value
+ }
+ if (gqarr[mypoint-kp3+1,2] < 0.01) numsignificant1 <- numsignificant1 + 1
+ if (gqarr[mypoint-kp3+1,2] < 0.05) numsignificant5 <- numsignificant5 + 1
+ if (gqarr[mypoint-kp3+1,2] < 0.10) numsignificant10 <- numsignificant10 + 1
+ }
+ gqarr
+ }
[,1] [,2] [,3]
[1,] 0.6818467 0.6363067 0.3181533
[2,] 0.5367507 0.9264985 0.4632493
[3,] 0.4644918 0.9289836 0.5355082
[4,] 0.5807073 0.8385853 0.4192927
[5,] 0.5327707 0.9344586 0.4672293
[6,] 0.5093270 0.9813461 0.4906730
[7,] 0.5709251 0.8581498 0.4290749
[8,] 0.6090665 0.7818671 0.3909335
[9,] 0.5004616 0.9990768 0.4995384
[10,] 0.5221428 0.9557144 0.4778572
[11,] 0.6538969 0.6922063 0.3461031
[12,] 0.5785681 0.8428638 0.4214319
[13,] 0.5134401 0.9731198 0.4865599
[14,] 0.4259781 0.8519562 0.5740219
[15,] 0.3270828 0.6541656 0.6729172
[16,] 0.3717443 0.7434887 0.6282557
[17,] 0.3366310 0.6732619 0.6633690
[18,] 0.2975134 0.5950268 0.7024866
[19,] 0.6505312 0.6989376 0.3494688
[20,] 0.6093463 0.7813075 0.3906537
[21,] 0.4572341 0.9144682 0.5427659
[22,] 0.3288392 0.6576783 0.6711608
> postscript(file="/var/www/html/rcomp/tmp/1g8ep1290767422.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$resid)
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/2g8ep1290767422.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> plot(mysum$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/3g8ep1290767422.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> hist(mysum$resid, main='Residual Histogram', xlab='values of Residuals')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/4jsg51290767423.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> densityplot(~mysum$resid,col='black',main='Residual Density Plot', xlab='values of Residuals')
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/5jsg51290767423.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 = 55
Frequency = 1
1 2 3 4 5 6 7
-108.89982 -276.18022 88.17177 -305.55386 405.98145 -72.38875 -45.01238
8 9 10 11 12 13 14
-113.75057 355.27223 62.88969 541.06210 253.83225 703.73382 282.36577
15 16 17 18 19 20 21
593.65141 393.25635 220.19871 303.79751 -78.35937 685.50181 -22.69853
22 23 24 25 26 27 28
244.87583 -198.70754 -657.73568 15.31891 450.99483 -661.28592 265.24471
29 30 31 32 33 34 35
89.95182 -261.10239 99.09435 -684.13806 -478.39626 335.48814 -784.00462
36 37 38 39 40 41 42
-122.98632 -110.21623 78.94574 -217.90208 379.61954 -198.04561 -73.06903
43 44 45 46 47 48 49
128.67495 112.38682 145.82256 -643.25366 441.65006 526.88974 -499.93668
50 51 52 53 54 55
-536.12612 197.36483 -732.56674 -518.08637 102.76266 -104.39757
> postscript(file="/var/www/html/rcomp/tmp/6jsg51290767423.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 = 55
Frequency = 1
lag(myerror, k = 1) myerror
0 -108.89982 NA
1 -276.18022 -108.89982
2 88.17177 -276.18022
3 -305.55386 88.17177
4 405.98145 -305.55386
5 -72.38875 405.98145
6 -45.01238 -72.38875
7 -113.75057 -45.01238
8 355.27223 -113.75057
9 62.88969 355.27223
10 541.06210 62.88969
11 253.83225 541.06210
12 703.73382 253.83225
13 282.36577 703.73382
14 593.65141 282.36577
15 393.25635 593.65141
16 220.19871 393.25635
17 303.79751 220.19871
18 -78.35937 303.79751
19 685.50181 -78.35937
20 -22.69853 685.50181
21 244.87583 -22.69853
22 -198.70754 244.87583
23 -657.73568 -198.70754
24 15.31891 -657.73568
25 450.99483 15.31891
26 -661.28592 450.99483
27 265.24471 -661.28592
28 89.95182 265.24471
29 -261.10239 89.95182
30 99.09435 -261.10239
31 -684.13806 99.09435
32 -478.39626 -684.13806
33 335.48814 -478.39626
34 -784.00462 335.48814
35 -122.98632 -784.00462
36 -110.21623 -122.98632
37 78.94574 -110.21623
38 -217.90208 78.94574
39 379.61954 -217.90208
40 -198.04561 379.61954
41 -73.06903 -198.04561
42 128.67495 -73.06903
43 112.38682 128.67495
44 145.82256 112.38682
45 -643.25366 145.82256
46 441.65006 -643.25366
47 526.88974 441.65006
48 -499.93668 526.88974
49 -536.12612 -499.93668
50 197.36483 -536.12612
51 -732.56674 197.36483
52 -518.08637 -732.56674
53 102.76266 -518.08637
54 -104.39757 102.76266
55 NA -104.39757
> dum1 <- dum[2:length(myerror),]
> dum1
lag(myerror, k = 1) myerror
[1,] -276.18022 -108.89982
[2,] 88.17177 -276.18022
[3,] -305.55386 88.17177
[4,] 405.98145 -305.55386
[5,] -72.38875 405.98145
[6,] -45.01238 -72.38875
[7,] -113.75057 -45.01238
[8,] 355.27223 -113.75057
[9,] 62.88969 355.27223
[10,] 541.06210 62.88969
[11,] 253.83225 541.06210
[12,] 703.73382 253.83225
[13,] 282.36577 703.73382
[14,] 593.65141 282.36577
[15,] 393.25635 593.65141
[16,] 220.19871 393.25635
[17,] 303.79751 220.19871
[18,] -78.35937 303.79751
[19,] 685.50181 -78.35937
[20,] -22.69853 685.50181
[21,] 244.87583 -22.69853
[22,] -198.70754 244.87583
[23,] -657.73568 -198.70754
[24,] 15.31891 -657.73568
[25,] 450.99483 15.31891
[26,] -661.28592 450.99483
[27,] 265.24471 -661.28592
[28,] 89.95182 265.24471
[29,] -261.10239 89.95182
[30,] 99.09435 -261.10239
[31,] -684.13806 99.09435
[32,] -478.39626 -684.13806
[33,] 335.48814 -478.39626
[34,] -784.00462 335.48814
[35,] -122.98632 -784.00462
[36,] -110.21623 -122.98632
[37,] 78.94574 -110.21623
[38,] -217.90208 78.94574
[39,] 379.61954 -217.90208
[40,] -198.04561 379.61954
[41,] -73.06903 -198.04561
[42,] 128.67495 -73.06903
[43,] 112.38682 128.67495
[44,] 145.82256 112.38682
[45,] -643.25366 145.82256
[46,] 441.65006 -643.25366
[47,] 526.88974 441.65006
[48,] -499.93668 526.88974
[49,] -536.12612 -499.93668
[50,] 197.36483 -536.12612
[51,] -732.56674 197.36483
[52,] -518.08637 -732.56674
[53,] 102.76266 -518.08637
[54,] -104.39757 102.76266
> z <- as.data.frame(dum1)
> z
lag(myerror, k = 1) myerror
1 -276.18022 -108.89982
2 88.17177 -276.18022
3 -305.55386 88.17177
4 405.98145 -305.55386
5 -72.38875 405.98145
6 -45.01238 -72.38875
7 -113.75057 -45.01238
8 355.27223 -113.75057
9 62.88969 355.27223
10 541.06210 62.88969
11 253.83225 541.06210
12 703.73382 253.83225
13 282.36577 703.73382
14 593.65141 282.36577
15 393.25635 593.65141
16 220.19871 393.25635
17 303.79751 220.19871
18 -78.35937 303.79751
19 685.50181 -78.35937
20 -22.69853 685.50181
21 244.87583 -22.69853
22 -198.70754 244.87583
23 -657.73568 -198.70754
24 15.31891 -657.73568
25 450.99483 15.31891
26 -661.28592 450.99483
27 265.24471 -661.28592
28 89.95182 265.24471
29 -261.10239 89.95182
30 99.09435 -261.10239
31 -684.13806 99.09435
32 -478.39626 -684.13806
33 335.48814 -478.39626
34 -784.00462 335.48814
35 -122.98632 -784.00462
36 -110.21623 -122.98632
37 78.94574 -110.21623
38 -217.90208 78.94574
39 379.61954 -217.90208
40 -198.04561 379.61954
41 -73.06903 -198.04561
42 128.67495 -73.06903
43 112.38682 128.67495
44 145.82256 112.38682
45 -643.25366 145.82256
46 441.65006 -643.25366
47 526.88974 441.65006
48 -499.93668 526.88974
49 -536.12612 -499.93668
50 197.36483 -536.12612
51 -732.56674 197.36483
52 -518.08637 -732.56674
53 102.76266 -518.08637
54 -104.39757 102.76266
> 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/7u1xq1290767423.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> acf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/8maxt1290767423.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> pacf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Partial Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/9maxt1290767423.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> opar <- par(mfrow = c(2,2), oma = c(0, 0, 1.1, 0))
> plot(mylm, las = 1, sub='Residual Diagnostics')
> par(opar)
> dev.off()
null device
1
> if (n > n25) {
+ postscript(file="/var/www/html/rcomp/tmp/10maxt1290767423.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
+ plot(kp3:nmkm3,gqarr[,2], main='Goldfeld-Quandt test',ylab='2-sided p-value',xlab='breakpoint')
+ grid()
+ dev.off()
+ }
null device
1
>
> #Note: the /var/www/html/rcomp/createtable file can be downloaded at http://www.wessa.net/cretab
> load(file="/var/www/html/rcomp/createtable")
>
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a, 'Multiple Linear Regression - Estimated Regression Equation', 1, TRUE)
> a<-table.row.end(a)
> myeq <- colnames(x)[1]
> myeq <- paste(myeq, '[t] = ', sep='')
> for (i in 1:k){
+ if (mysum$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/118bvz1290767423.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/12bttn1290767423.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/13iu8g1290767423.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/14t48j1290767423.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/15e4o71290767423.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/16sw4g1290767423.tab")
+ }
>
> try(system("convert tmp/1g8ep1290767422.ps tmp/1g8ep1290767422.png",intern=TRUE))
character(0)
> try(system("convert tmp/2g8ep1290767422.ps tmp/2g8ep1290767422.png",intern=TRUE))
character(0)
> try(system("convert tmp/3g8ep1290767422.ps tmp/3g8ep1290767422.png",intern=TRUE))
character(0)
> try(system("convert tmp/4jsg51290767423.ps tmp/4jsg51290767423.png",intern=TRUE))
character(0)
> try(system("convert tmp/5jsg51290767423.ps tmp/5jsg51290767423.png",intern=TRUE))
character(0)
> try(system("convert tmp/6jsg51290767423.ps tmp/6jsg51290767423.png",intern=TRUE))
character(0)
> try(system("convert tmp/7u1xq1290767423.ps tmp/7u1xq1290767423.png",intern=TRUE))
character(0)
> try(system("convert tmp/8maxt1290767423.ps tmp/8maxt1290767423.png",intern=TRUE))
character(0)
> try(system("convert tmp/9maxt1290767423.ps tmp/9maxt1290767423.png",intern=TRUE))
character(0)
> try(system("convert tmp/10maxt1290767423.ps tmp/10maxt1290767423.png",intern=TRUE))
character(0)
>
>
> proc.time()
user system elapsed
2.450 1.598 5.808