R version 2.13.0 (2011-04-13)
Copyright (C) 2011 The R Foundation for Statistical Computing
ISBN 3-900051-07-0
Platform: i486-pc-linux-gnu (32-bit)
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(108,392.5,19,46.2,13,15.7,124,422.2,40,119.4,57,170.9,23,56.9,14,77.5,45,214,10,65.3,5,20.9,48,248.1,11,23.5,23,39.6,7,48.8,2,6.6,24,134.9,6,50.9,3,4.4,23,113,6,14.8,9,48.7,9,52.1,3,13.2,29,103.9,7,77.5,4,11.8,20,98.1,7,27.9,4,38.1,0,0,25,69.2,6,14.6,5,40.3,22,161.5,11,57.2,61,217.6,12,58.1,4,12.6,16,59.6,13,89.9,60,202.4,41,181.3,37,152.8,55,162.8,41,73.4,11,21.3,27,92.6,8,76.1,3,39.9,17,142.1,13,93,13,31.9,15,32.1,8,55.6,29,133.3,30,194.5,24,137.9,9,87.4,31,209.8,14,95.5,53,244.6,26,187.5),dim=c(2,63),dimnames=list(c('Claims','Payments'),1:63))
> y <- array(NA,dim=c(2,63),dimnames=list(c('Claims','Payments'),1:63))
> 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
> 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
Claims Payments
1 108 392.5
2 19 46.2
3 13 15.7
4 124 422.2
5 40 119.4
6 57 170.9
7 23 56.9
8 14 77.5
9 45 214.0
10 10 65.3
11 5 20.9
12 48 248.1
13 11 23.5
14 23 39.6
15 7 48.8
16 2 6.6
17 24 134.9
18 6 50.9
19 3 4.4
20 23 113.0
21 6 14.8
22 9 48.7
23 9 52.1
24 3 13.2
25 29 103.9
26 7 77.5
27 4 11.8
28 20 98.1
29 7 27.9
30 4 38.1
31 0 0.0
32 25 69.2
33 6 14.6
34 5 40.3
35 22 161.5
36 11 57.2
37 61 217.6
38 12 58.1
39 4 12.6
40 16 59.6
41 13 89.9
42 60 202.4
43 41 181.3
44 37 152.8
45 55 162.8
46 41 73.4
47 11 21.3
48 27 92.6
49 8 76.1
50 3 39.9
51 17 142.1
52 13 93.0
53 13 31.9
54 15 32.1
55 8 55.6
56 29 133.3
57 30 194.5
58 24 137.9
59 9 87.4
60 31 209.8
61 14 95.5
62 53 244.6
63 26 187.5
> k <- length(x[1,])
> df <- as.data.frame(x)
> (mylm <- lm(df))
Call:
lm(formula = df)
Coefficients:
(Intercept) Payments
-1.0637 0.2441
> (mysum <- summary(mylm))
Call:
lm(formula = df)
Residuals:
Min 1Q Median 3Q Max
-19.151 -5.661 -1.119 6.302 24.146
Coefficients:
Estimate Std. Error t value Pr(>|t|)
(Intercept) -1.06369 1.83018 -0.581 0.563
Payments 0.24411 0.01398 17.465 <2e-16 ***
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
Residual standard error: 9.611 on 61 degrees of freedom
Multiple R-squared: 0.8333, Adjusted R-squared: 0.8306
F-statistic: 305 on 1 and 61 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,] 0.07615877 0.15231753 0.9238412
[2,] 0.04891099 0.09782198 0.9510890
[3,] 0.01819644 0.03639287 0.9818036
[4,] 0.25173356 0.50346712 0.7482664
[5,] 0.63655261 0.72689479 0.3634474
[6,] 0.66604043 0.66791914 0.3339596
[7,] 0.57097484 0.85805032 0.4290252
[8,] 0.82747909 0.34504181 0.1725209
[9,] 0.77150889 0.45698222 0.2284911
[10,] 0.80223443 0.39553114 0.1977656
[11,] 0.77807659 0.44384683 0.2219234
[12,] 0.70957428 0.58085143 0.2904257
[13,] 0.74294206 0.51411589 0.2570579
[14,] 0.71760750 0.56478500 0.2823925
[15,] 0.64552355 0.70895290 0.3544765
[16,] 0.60110184 0.79779632 0.3988982
[17,] 0.52540653 0.94918694 0.4745935
[18,] 0.45764389 0.91528777 0.5423561
[19,] 0.39628977 0.79257954 0.6037102
[20,] 0.32337869 0.64675738 0.6766213
[21,] 0.27064256 0.54128512 0.7293574
[22,] 0.32231880 0.64463760 0.6776812
[23,] 0.25840014 0.51680028 0.7415999
[24,] 0.21307021 0.42614042 0.7869298
[25,] 0.16236264 0.32472528 0.8376374
[26,] 0.13283212 0.26566424 0.8671679
[27,] 0.09727574 0.19455148 0.9027243
[28,] 0.09264656 0.18529312 0.9073534
[29,] 0.06716113 0.13432227 0.9328389
[30,] 0.05116890 0.10233779 0.9488311
[31,] 0.11664392 0.23328784 0.8833561
[32,] 0.08605530 0.17211060 0.9139447
[33,] 0.10189036 0.20378072 0.8981096
[34,] 0.07330568 0.14661136 0.9266943
[35,] 0.05094427 0.10188853 0.9490557
[36,] 0.03443339 0.06886678 0.9655666
[37,] 0.03127588 0.06255177 0.9687241
[38,] 0.06386122 0.12772243 0.9361388
[39,] 0.05118724 0.10237448 0.9488128
[40,] 0.03984857 0.07969714 0.9601514
[41,] 0.21327802 0.42655604 0.7867220
[42,] 0.84535094 0.30929812 0.1546491
[43,] 0.82071283 0.35857434 0.1792872
[44,] 0.87010831 0.25978339 0.1298917
[45,] 0.85411808 0.29176383 0.1458819
[46,] 0.81970111 0.36059778 0.1802989
[47,] 0.85658013 0.28683974 0.1434199
[48,] 0.81842340 0.36315321 0.1815766
[49,] 0.78304442 0.43391117 0.2169556
[50,] 0.86214149 0.27571702 0.1378585
[51,] 0.78716265 0.42567469 0.2128373
[52,] 0.81586619 0.36826763 0.1841338
[53,] 0.75014033 0.49971934 0.2498597
[54,] 0.62189535 0.75620931 0.3781047
> postscript(file="/var/wessaorg/rcomp/tmp/1lcfc1321394363.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$resid)
> grid()
> dev.off()
null device
1
> postscript(file="/var/wessaorg/rcomp/tmp/2pimy1321394363.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> plot(mysum$resid, type='b', pch=19, main='Residuals', ylab='value of Residuals', xlab='time or index')
> grid()
> dev.off()
null device
1
> postscript(file="/var/wessaorg/rcomp/tmp/312u91321394363.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> hist(mysum$resid, main='Residual Histogram', xlab='values of Residuals')
> grid()
> dev.off()
null device
1
> postscript(file="/var/wessaorg/rcomp/tmp/4fbsm1321394363.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> densityplot(~mysum$resid,col='black',main='Residual Density Plot', xlab='values of Residuals')
> dev.off()
null device
1
> postscript(file="/var/wessaorg/rcomp/tmp/52mj71321394363.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 = 63
Frequency = 1
1 2 3 4 5 6
13.2507202 8.7858309 10.2311699 22.0006689 11.9170175 16.3453796
7 8 9 10 11 12
10.1738595 -3.8547956 -6.1757387 -4.8766600 0.9618006 -11.4998718
13 14 15 16 17 18
6.3271160 14.3969534 -3.8488537 1.4525661 -7.8666794 -5.3614836
19 20 21 22 23 24
2.9896069 -3.5206819 3.4508684 -1.8244428 -2.6544150 0.8414435
25 26 27 28 29 30
4.7007143 -10.8547956 2.1831968 -2.8834508 1.2530343 -4.2368823
31 32 33 34 35 36
1.0636886 9.1713130 3.4996903 -3.7739232 -16.3599914 -1.8993733
37 38 39 40 41 42
8.9454672 -1.1190718 1.9879092 2.5147640 -7.8817531 11.6559312
43 44 45 46 47 48
-2.1933590 0.7637610 16.3226663 24.1460532 6.8641568 5.4591513
49 50 51 52 53 54
-9.5130423 -5.6762794 -16.6242676 -8.6384924 6.2765964 8.2277745
55 56 57 58 59 60
-4.5087981 -2.4761042 -16.4156040 -8.5990078 -11.2714794 -19.1504790
61 62 63
-8.2487661 -5.6454886 -18.7068377
> postscript(file="/var/wessaorg/rcomp/tmp/6xzh91321394363.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 = 63
Frequency = 1
lag(myerror, k = 1) myerror
0 13.2507202 NA
1 8.7858309 13.2507202
2 10.2311699 8.7858309
3 22.0006689 10.2311699
4 11.9170175 22.0006689
5 16.3453796 11.9170175
6 10.1738595 16.3453796
7 -3.8547956 10.1738595
8 -6.1757387 -3.8547956
9 -4.8766600 -6.1757387
10 0.9618006 -4.8766600
11 -11.4998718 0.9618006
12 6.3271160 -11.4998718
13 14.3969534 6.3271160
14 -3.8488537 14.3969534
15 1.4525661 -3.8488537
16 -7.8666794 1.4525661
17 -5.3614836 -7.8666794
18 2.9896069 -5.3614836
19 -3.5206819 2.9896069
20 3.4508684 -3.5206819
21 -1.8244428 3.4508684
22 -2.6544150 -1.8244428
23 0.8414435 -2.6544150
24 4.7007143 0.8414435
25 -10.8547956 4.7007143
26 2.1831968 -10.8547956
27 -2.8834508 2.1831968
28 1.2530343 -2.8834508
29 -4.2368823 1.2530343
30 1.0636886 -4.2368823
31 9.1713130 1.0636886
32 3.4996903 9.1713130
33 -3.7739232 3.4996903
34 -16.3599914 -3.7739232
35 -1.8993733 -16.3599914
36 8.9454672 -1.8993733
37 -1.1190718 8.9454672
38 1.9879092 -1.1190718
39 2.5147640 1.9879092
40 -7.8817531 2.5147640
41 11.6559312 -7.8817531
42 -2.1933590 11.6559312
43 0.7637610 -2.1933590
44 16.3226663 0.7637610
45 24.1460532 16.3226663
46 6.8641568 24.1460532
47 5.4591513 6.8641568
48 -9.5130423 5.4591513
49 -5.6762794 -9.5130423
50 -16.6242676 -5.6762794
51 -8.6384924 -16.6242676
52 6.2765964 -8.6384924
53 8.2277745 6.2765964
54 -4.5087981 8.2277745
55 -2.4761042 -4.5087981
56 -16.4156040 -2.4761042
57 -8.5990078 -16.4156040
58 -11.2714794 -8.5990078
59 -19.1504790 -11.2714794
60 -8.2487661 -19.1504790
61 -5.6454886 -8.2487661
62 -18.7068377 -5.6454886
63 NA -18.7068377
> dum1 <- dum[2:length(myerror),]
> dum1
lag(myerror, k = 1) myerror
[1,] 8.7858309 13.2507202
[2,] 10.2311699 8.7858309
[3,] 22.0006689 10.2311699
[4,] 11.9170175 22.0006689
[5,] 16.3453796 11.9170175
[6,] 10.1738595 16.3453796
[7,] -3.8547956 10.1738595
[8,] -6.1757387 -3.8547956
[9,] -4.8766600 -6.1757387
[10,] 0.9618006 -4.8766600
[11,] -11.4998718 0.9618006
[12,] 6.3271160 -11.4998718
[13,] 14.3969534 6.3271160
[14,] -3.8488537 14.3969534
[15,] 1.4525661 -3.8488537
[16,] -7.8666794 1.4525661
[17,] -5.3614836 -7.8666794
[18,] 2.9896069 -5.3614836
[19,] -3.5206819 2.9896069
[20,] 3.4508684 -3.5206819
[21,] -1.8244428 3.4508684
[22,] -2.6544150 -1.8244428
[23,] 0.8414435 -2.6544150
[24,] 4.7007143 0.8414435
[25,] -10.8547956 4.7007143
[26,] 2.1831968 -10.8547956
[27,] -2.8834508 2.1831968
[28,] 1.2530343 -2.8834508
[29,] -4.2368823 1.2530343
[30,] 1.0636886 -4.2368823
[31,] 9.1713130 1.0636886
[32,] 3.4996903 9.1713130
[33,] -3.7739232 3.4996903
[34,] -16.3599914 -3.7739232
[35,] -1.8993733 -16.3599914
[36,] 8.9454672 -1.8993733
[37,] -1.1190718 8.9454672
[38,] 1.9879092 -1.1190718
[39,] 2.5147640 1.9879092
[40,] -7.8817531 2.5147640
[41,] 11.6559312 -7.8817531
[42,] -2.1933590 11.6559312
[43,] 0.7637610 -2.1933590
[44,] 16.3226663 0.7637610
[45,] 24.1460532 16.3226663
[46,] 6.8641568 24.1460532
[47,] 5.4591513 6.8641568
[48,] -9.5130423 5.4591513
[49,] -5.6762794 -9.5130423
[50,] -16.6242676 -5.6762794
[51,] -8.6384924 -16.6242676
[52,] 6.2765964 -8.6384924
[53,] 8.2277745 6.2765964
[54,] -4.5087981 8.2277745
[55,] -2.4761042 -4.5087981
[56,] -16.4156040 -2.4761042
[57,] -8.5990078 -16.4156040
[58,] -11.2714794 -8.5990078
[59,] -19.1504790 -11.2714794
[60,] -8.2487661 -19.1504790
[61,] -5.6454886 -8.2487661
[62,] -18.7068377 -5.6454886
> z <- as.data.frame(dum1)
> z
lag(myerror, k = 1) myerror
1 8.7858309 13.2507202
2 10.2311699 8.7858309
3 22.0006689 10.2311699
4 11.9170175 22.0006689
5 16.3453796 11.9170175
6 10.1738595 16.3453796
7 -3.8547956 10.1738595
8 -6.1757387 -3.8547956
9 -4.8766600 -6.1757387
10 0.9618006 -4.8766600
11 -11.4998718 0.9618006
12 6.3271160 -11.4998718
13 14.3969534 6.3271160
14 -3.8488537 14.3969534
15 1.4525661 -3.8488537
16 -7.8666794 1.4525661
17 -5.3614836 -7.8666794
18 2.9896069 -5.3614836
19 -3.5206819 2.9896069
20 3.4508684 -3.5206819
21 -1.8244428 3.4508684
22 -2.6544150 -1.8244428
23 0.8414435 -2.6544150
24 4.7007143 0.8414435
25 -10.8547956 4.7007143
26 2.1831968 -10.8547956
27 -2.8834508 2.1831968
28 1.2530343 -2.8834508
29 -4.2368823 1.2530343
30 1.0636886 -4.2368823
31 9.1713130 1.0636886
32 3.4996903 9.1713130
33 -3.7739232 3.4996903
34 -16.3599914 -3.7739232
35 -1.8993733 -16.3599914
36 8.9454672 -1.8993733
37 -1.1190718 8.9454672
38 1.9879092 -1.1190718
39 2.5147640 1.9879092
40 -7.8817531 2.5147640
41 11.6559312 -7.8817531
42 -2.1933590 11.6559312
43 0.7637610 -2.1933590
44 16.3226663 0.7637610
45 24.1460532 16.3226663
46 6.8641568 24.1460532
47 5.4591513 6.8641568
48 -9.5130423 5.4591513
49 -5.6762794 -9.5130423
50 -16.6242676 -5.6762794
51 -8.6384924 -16.6242676
52 6.2765964 -8.6384924
53 8.2277745 6.2765964
54 -4.5087981 8.2277745
55 -2.4761042 -4.5087981
56 -16.4156040 -2.4761042
57 -8.5990078 -16.4156040
58 -11.2714794 -8.5990078
59 -19.1504790 -11.2714794
60 -8.2487661 -19.1504790
61 -5.6454886 -8.2487661
62 -18.7068377 -5.6454886
> 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/wessaorg/rcomp/tmp/7wkq21321394363.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> acf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/wessaorg/rcomp/tmp/86aps1321394363.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> pacf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Partial Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/wessaorg/rcomp/tmp/9m44b1321394363.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> opar <- par(mfrow = c(2,2), oma = c(0, 0, 1.1, 0))
> plot(mylm, las = 1, sub='Residual Diagnostics')
> par(opar)
> dev.off()
null device
1
> if (n > n25) {
+ postscript(file="/var/wessaorg/rcomp/tmp/10nqap1321394363.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
+ plot(kp3:nmkm3,gqarr[,2], main='Goldfeld-Quandt test',ylab='2-sided p-value',xlab='breakpoint')
+ grid()
+ dev.off()
+ }
null device
1
>
> #Note: the /var/wessaorg/rcomp/createtable file can be downloaded at http://www.wessa.net/cretab
> load(file="/var/wessaorg/rcomp/createtable")
>
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a, 'Multiple Linear Regression - Estimated Regression Equation', 1, TRUE)
> a<-table.row.end(a)
> myeq <- colnames(x)[1]
> myeq <- paste(myeq, '[t] = ', sep='')
> for (i in 1:k){
+ if (mysum$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/wessaorg/rcomp/tmp/11t4y91321394363.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/wessaorg/rcomp/tmp/12grvi1321394363.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/wessaorg/rcomp/tmp/13dfqa1321394363.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/wessaorg/rcomp/tmp/14e7ka1321394364.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/wessaorg/rcomp/tmp/15sacy1321394364.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/wessaorg/rcomp/tmp/16k2r71321394364.tab")
+ }
>
> try(system("convert tmp/1lcfc1321394363.ps tmp/1lcfc1321394363.png",intern=TRUE))
character(0)
> try(system("convert tmp/2pimy1321394363.ps tmp/2pimy1321394363.png",intern=TRUE))
character(0)
> try(system("convert tmp/312u91321394363.ps tmp/312u91321394363.png",intern=TRUE))
character(0)
> try(system("convert tmp/4fbsm1321394363.ps tmp/4fbsm1321394363.png",intern=TRUE))
character(0)
> try(system("convert tmp/52mj71321394363.ps tmp/52mj71321394363.png",intern=TRUE))
character(0)
> try(system("convert tmp/6xzh91321394363.ps tmp/6xzh91321394363.png",intern=TRUE))
character(0)
> try(system("convert tmp/7wkq21321394363.ps tmp/7wkq21321394363.png",intern=TRUE))
character(0)
> try(system("convert tmp/86aps1321394363.ps tmp/86aps1321394363.png",intern=TRUE))
character(0)
> try(system("convert tmp/9m44b1321394363.ps tmp/9m44b1321394363.png",intern=TRUE))
character(0)
> try(system("convert tmp/10nqap1321394363.ps tmp/10nqap1321394363.png",intern=TRUE))
character(0)
>
>
> proc.time()
user system elapsed
3.396 0.496 3.926