R version 2.12.0 (2010-10-15)
Copyright (C) 2010 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(-1
+ ,0
+ ,1
+ ,-1
+ ,1
+ ,1
+ ,1
+ ,0
+ ,112.8380813
+ ,-1
+ ,1
+ ,1
+ ,1
+ ,1
+ ,1
+ ,1
+ ,-1
+ ,113.1303269
+ ,-1
+ ,1
+ ,-1
+ ,0
+ ,0
+ ,1
+ ,1
+ ,-1
+ ,97.63171117
+ ,-1
+ ,0
+ ,-1
+ ,-1
+ ,1
+ ,1
+ ,0
+ ,1
+ ,142.5151687
+ ,-1
+ ,-1
+ ,1
+ ,-1
+ ,-1
+ ,1
+ ,-1
+ ,-1
+ ,164.8611618
+ ,1
+ ,-1
+ ,1
+ ,-1
+ ,1
+ ,1
+ ,1
+ ,1
+ ,112.485371
+ ,-1
+ ,1
+ ,1
+ ,1
+ ,1
+ ,1
+ ,1
+ ,-1
+ ,150.1989732
+ ,-1
+ ,1
+ ,1
+ ,-1
+ ,1
+ ,0
+ ,0
+ ,-1
+ ,176.719424
+ ,-1
+ ,0
+ ,-1
+ ,0
+ ,1
+ ,0
+ ,1
+ ,-1
+ ,113.0698623
+ ,0
+ ,0
+ ,0
+ ,0
+ ,0
+ ,0
+ ,0
+ ,0
+ ,116.528822
+ ,-1
+ ,1
+ ,-1
+ ,-1
+ ,1
+ ,0
+ ,1
+ ,1
+ ,112.8481587
+ ,-1
+ ,1
+ ,-1
+ ,1
+ ,1
+ ,1
+ ,-1
+ ,-1
+ ,12.81250709
+ ,0
+ ,1
+ ,1
+ ,1
+ ,-1
+ ,1
+ ,-1
+ ,1
+ ,116.4885123
+ ,-1
+ ,-1
+ ,0
+ ,1
+ ,1
+ ,1
+ ,-1
+ ,-1
+ ,12.42327815
+ ,-1
+ ,1
+ ,-1
+ ,1
+ ,1
+ ,1
+ ,1
+ ,1
+ ,124.2529363
+ ,0
+ ,1
+ ,-1
+ ,1
+ ,1
+ ,1
+ ,1
+ ,-1
+ ,135.1538421
+ ,0
+ ,1
+ ,1
+ ,-1
+ ,1
+ ,1
+ ,-1
+ ,-1
+ ,53.00018956
+ ,-1
+ ,0
+ ,-1
+ ,1
+ ,0
+ ,-1
+ ,1
+ ,1
+ ,64.2235733
+ ,-1
+ ,1
+ ,-1
+ ,-1
+ ,1
+ ,1
+ ,-1
+ ,-1
+ ,120.4311889
+ ,-1
+ ,-1
+ ,-1
+ ,-1
+ ,1
+ ,0
+ ,1
+ ,-1
+ ,113.1101721
+ ,-1
+ ,-1
+ ,-1
+ ,1
+ ,0
+ ,-1
+ ,0
+ ,-1
+ ,131.1607783
+ ,-1
+ ,1
+ ,-1
+ ,1
+ ,1
+ ,1
+ ,1
+ ,-1
+ ,105.2147414
+ ,-1
+ ,-1
+ ,-1
+ ,1
+ ,1
+ ,1
+ ,1
+ ,1
+ ,127.6514314
+ ,-1
+ ,-1
+ ,1
+ ,-1
+ ,-1
+ ,-1
+ ,1
+ ,-1
+ ,146.357071
+ ,1
+ ,1
+ ,-1
+ ,1
+ ,1
+ ,0
+ ,-1
+ ,1
+ ,146.5989294
+ ,-1
+ ,1
+ ,-1
+ ,1
+ ,1
+ ,1
+ ,1
+ ,-1
+ ,109.0969534
+ ,-1
+ ,1
+ ,1
+ ,0
+ ,1
+ ,-1
+ ,1
+ ,0
+ ,165.0123233
+ ,-1
+ ,-1
+ ,-1
+ ,1
+ ,1
+ ,1
+ ,1
+ ,-1
+ ,79.59118241
+ ,1
+ ,1
+ ,1
+ ,-1
+ ,1
+ ,0
+ ,1
+ ,1
+ ,105.5472968
+ ,-1
+ ,-1
+ ,-1
+ ,-1
+ ,1
+ ,1
+ ,1
+ ,-1
+ ,105.3759803
+ ,-1
+ ,1
+ ,1
+ ,1
+ ,1
+ ,-1
+ ,-1
+ ,-1
+ ,143.0190405
+ ,-1
+ ,-1
+ ,1
+ ,-1
+ ,-1
+ ,1
+ ,1
+ ,-1
+ ,120.0280915
+ ,-1
+ ,1
+ ,-1
+ ,-1
+ ,-1
+ ,0
+ ,1
+ ,-1
+ ,108.7442431
+ ,-1
+ ,1
+ ,1
+ ,-1
+ ,1
+ ,1
+ ,1
+ ,-1
+ ,101.5844652
+ ,1
+ ,-1
+ ,1
+ ,-1
+ ,-1
+ ,1
+ ,1
+ ,1
+ ,149.9268825
+ ,1
+ ,-1
+ ,1
+ ,1
+ ,-1
+ ,1
+ ,1
+ ,-1
+ ,149.8160307
+ ,-1
+ ,1
+ ,-1
+ ,1
+ ,0
+ ,-1
+ ,0
+ ,1
+ ,105.3155157
+ ,0
+ ,1
+ ,1
+ ,0
+ ,1
+ ,0
+ ,1
+ ,0
+ ,12.79436771
+ ,-1
+ ,1
+ ,1
+ ,1
+ ,1
+ ,1
+ ,1
+ ,-1
+ ,124.3436333
+ ,-1
+ ,1
+ ,0
+ ,1
+ ,1
+ ,0
+ ,-1
+ ,1
+ ,123.7994517
+ ,-1
+ ,-1
+ ,1
+ ,1
+ ,1
+ ,1
+ ,1
+ ,-1
+ ,131.6041855
+ ,-1
+ ,-1
+ ,1
+ ,-1
+ ,1
+ ,-1
+ ,-1
+ ,-1
+ ,109.0062565
+ ,-1
+ ,-1
+ ,1
+ ,1
+ ,0
+ ,1
+ ,1
+ ,1
+ ,75.39656986
+ ,-1
+ ,1
+ ,1
+ ,0
+ ,1
+ ,1
+ ,1
+ ,-1
+ ,139.378687
+ ,-1
+ ,1
+ ,1
+ ,0
+ ,-1
+ ,1
+ ,1
+ ,0
+ ,124.4242527
+ ,-1
+ ,1
+ ,-1
+ ,1
+ ,1
+ ,-1
+ ,0
+ ,-1
+ ,108.9155595
+ ,-1
+ ,1
+ ,-1
+ ,-1
+ ,-1
+ ,0
+ ,1
+ ,-1
+ ,105.3054383
+ ,-1
+ ,1
+ ,-1
+ ,1
+ ,0
+ ,0
+ ,0
+ ,0
+ ,79.01676853
+ ,-1
+ ,-1
+ ,-1
+ ,1
+ ,1
+ ,0
+ ,1
+ ,1
+ ,153.799017
+ ,-1
+ ,-1
+ ,-1
+ ,-1
+ ,0
+ ,1
+ ,1
+ ,-1
+ ,75.49734422
+ ,-1
+ ,1
+ ,1
+ ,0
+ ,0
+ ,1
+ ,1
+ ,0
+ ,112.878391
+ ,-1
+ ,-1
+ ,-1
+ ,1
+ ,1
+ ,1
+ ,1
+ ,-1
+ ,82.94936774
+ ,-1
+ ,-1
+ ,-1
+ ,1
+ ,0
+ ,0
+ ,1
+ ,1
+ ,157.9130101
+ ,0
+ ,0
+ ,0
+ ,0
+ ,0
+ ,0
+ ,0
+ ,0
+ ,120.5319633
+ ,-1
+ ,1
+ ,-1
+ ,0
+ ,1
+ ,1
+ ,1
+ ,1
+ ,13.50228354
+ ,-1
+ ,-1
+ ,-1
+ ,1
+ ,-1
+ ,0
+ ,1
+ ,-1
+ ,116.921842
+ ,-1
+ ,-1
+ ,-1
+ ,1
+ ,1
+ ,1
+ ,1
+ ,-1
+ ,124.1622394
+ ,-1
+ ,-1
+ ,-1
+ ,0
+ ,-1
+ ,0
+ ,1
+ ,-1
+ ,149.7958758
+ ,-1
+ ,1
+ ,-1
+ ,1
+ ,1
+ ,1
+ ,1
+ ,-1
+ ,142.0516066
+ ,-1
+ ,0
+ ,0
+ ,0
+ ,0
+ ,0
+ ,0
+ ,0
+ ,90.02852611
+ ,-1
+ ,1
+ ,0
+ ,0
+ ,0
+ ,1
+ ,1
+ ,1
+ ,160.7471687
+ ,1
+ ,-1
+ ,-1
+ ,1
+ ,1
+ ,1
+ ,1
+ ,-1
+ ,116.3877379
+ ,1
+ ,1
+ ,1
+ ,-1
+ ,1
+ ,0
+ ,1
+ ,1
+ ,150.1082763
+ ,-1
+ ,-1
+ ,1
+ ,1
+ ,1
+ ,1
+ ,1
+ ,-1
+ ,139.1569834
+ ,-1
+ ,-1
+ ,1
+ ,0
+ ,1
+ ,0
+ ,-1
+ ,-1
+ ,116.8714549
+ ,-1
+ ,1
+ ,-1
+ ,0
+ ,1
+ ,0
+ ,1
+ ,-1
+ ,146.6493166
+ ,-1
+ ,1
+ ,0
+ ,-1
+ ,1
+ ,1
+ ,1
+ ,1
+ ,120.340492
+ ,0
+ ,-1
+ ,1
+ ,-1
+ ,-1
+ ,0
+ ,1
+ ,-1
+ ,67.76315248
+ ,-1
+ ,-1
+ ,-1
+ ,1
+ ,0
+ ,0
+ ,1
+ ,1
+ ,146.7601684
+ ,-1
+ ,1
+ ,1
+ ,1
+ ,1
+ ,1
+ ,1
+ ,1
+ ,112.5156033
+ ,-1
+ ,-1
+ ,-1
+ ,1
+ ,-1
+ ,0
+ ,1
+ ,-1
+ ,139.1166736
+ ,0
+ ,1
+ ,0
+ ,1
+ ,0
+ ,1
+ ,1
+ ,-1
+ ,119.8366202
+ ,-1
+ ,-1
+ ,0
+ ,-1
+ ,0
+ ,1
+ ,1
+ ,1
+ ,63.95148252
+ ,-1
+ ,1
+ ,-1
+ ,-1
+ ,0
+ ,0
+ ,1
+ ,-1
+ ,45.79002452
+ ,-1
+ ,1
+ ,0
+ ,1
+ ,0
+ ,-1
+ ,1
+ ,0
+ ,49.11797754
+ ,0
+ ,0
+ ,0
+ ,0
+ ,0
+ ,0
+ ,0
+ ,0
+ ,64.02202457
+ ,0
+ ,0
+ ,-1
+ ,1
+ ,1
+ ,-1
+ ,1
+ ,1
+ ,64.17318612
+ ,-1
+ ,1
+ ,0
+ ,1
+ ,-1
+ ,1
+ ,1
+ ,0
+ ,75.22525344
+ ,-1
+ ,1
+ ,1
+ ,-1
+ ,-1
+ ,0
+ ,-1
+ ,-1
+ ,64.35457997
+ ,-1
+ ,-1
+ ,1
+ ,-1
+ ,0
+ ,-1
+ ,1
+ ,0
+ ,63.85070815
+ ,-1
+ ,0
+ ,1
+ ,-1
+ ,0
+ ,0
+ ,1
+ ,1
+ ,63.80032097
+ ,-1
+ ,-1
+ ,0
+ ,-1
+ ,-1
+ ,-1
+ ,1
+ ,0
+ ,82.62688977
+ ,0
+ ,1
+ ,0
+ ,0
+ ,0
+ ,0
+ ,0
+ ,-1
+ ,56.75139491
+ ,0
+ ,1
+ ,-1
+ ,1
+ ,0
+ ,1
+ ,-1
+ ,0
+ ,45.53808861
+ ,-1
+ ,-1
+ ,-1
+ ,1
+ ,1
+ ,1
+ ,1
+ ,-1
+ ,63.97163739)
+ ,dim=c(9
+ ,85)
+ ,dimnames=list(c('t1'
+ ,'t2'
+ ,'t3'
+ ,'t4'
+ ,'t5'
+ ,'t6'
+ ,'t7'
+ ,'t8'
+ ,'IF')
+ ,1:85))
> y <- array(NA,dim=c(9,85),dimnames=list(c('t1','t2','t3','t4','t5','t6','t7','t8','IF'),1:85))
> 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 = '9'
> #'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
IF t1 t2 t3 t4 t5 t6 t7 t8
1 112.83808 -1 0 1 -1 1 1 1 0
2 113.13033 -1 1 1 1 1 1 1 -1
3 97.63171 -1 1 -1 0 0 1 1 -1
4 142.51517 -1 0 -1 -1 1 1 0 1
5 164.86116 -1 -1 1 -1 -1 1 -1 -1
6 112.48537 1 -1 1 -1 1 1 1 1
7 150.19897 -1 1 1 1 1 1 1 -1
8 176.71942 -1 1 1 -1 1 0 0 -1
9 113.06986 -1 0 -1 0 1 0 1 -1
10 116.52882 0 0 0 0 0 0 0 0
11 112.84816 -1 1 -1 -1 1 0 1 1
12 12.81251 -1 1 -1 1 1 1 -1 -1
13 116.48851 0 1 1 1 -1 1 -1 1
14 12.42328 -1 -1 0 1 1 1 -1 -1
15 124.25294 -1 1 -1 1 1 1 1 1
16 135.15384 0 1 -1 1 1 1 1 -1
17 53.00019 0 1 1 -1 1 1 -1 -1
18 64.22357 -1 0 -1 1 0 -1 1 1
19 120.43119 -1 1 -1 -1 1 1 -1 -1
20 113.11017 -1 -1 -1 -1 1 0 1 -1
21 131.16078 -1 -1 -1 1 0 -1 0 -1
22 105.21474 -1 1 -1 1 1 1 1 -1
23 127.65143 -1 -1 -1 1 1 1 1 1
24 146.35707 -1 -1 1 -1 -1 -1 1 -1
25 146.59893 1 1 -1 1 1 0 -1 1
26 109.09695 -1 1 -1 1 1 1 1 -1
27 165.01232 -1 1 1 0 1 -1 1 0
28 79.59118 -1 -1 -1 1 1 1 1 -1
29 105.54730 1 1 1 -1 1 0 1 1
30 105.37598 -1 -1 -1 -1 1 1 1 -1
31 143.01904 -1 1 1 1 1 -1 -1 -1
32 120.02809 -1 -1 1 -1 -1 1 1 -1
33 108.74424 -1 1 -1 -1 -1 0 1 -1
34 101.58447 -1 1 1 -1 1 1 1 -1
35 149.92688 1 -1 1 -1 -1 1 1 1
36 149.81603 1 -1 1 1 -1 1 1 -1
37 105.31552 -1 1 -1 1 0 -1 0 1
38 12.79437 0 1 1 0 1 0 1 0
39 124.34363 -1 1 1 1 1 1 1 -1
40 123.79945 -1 1 0 1 1 0 -1 1
41 131.60419 -1 -1 1 1 1 1 1 -1
42 109.00626 -1 -1 1 -1 1 -1 -1 -1
43 75.39657 -1 -1 1 1 0 1 1 1
44 139.37869 -1 1 1 0 1 1 1 -1
45 124.42425 -1 1 1 0 -1 1 1 0
46 108.91556 -1 1 -1 1 1 -1 0 -1
47 105.30544 -1 1 -1 -1 -1 0 1 -1
48 79.01677 -1 1 -1 1 0 0 0 0
49 153.79902 -1 -1 -1 1 1 0 1 1
50 75.49734 -1 -1 -1 -1 0 1 1 -1
51 112.87839 -1 1 1 0 0 1 1 0
52 82.94937 -1 -1 -1 1 1 1 1 -1
53 157.91301 -1 -1 -1 1 0 0 1 1
54 120.53196 0 0 0 0 0 0 0 0
55 13.50228 -1 1 -1 0 1 1 1 1
56 116.92184 -1 -1 -1 1 -1 0 1 -1
57 124.16224 -1 -1 -1 1 1 1 1 -1
58 149.79588 -1 -1 -1 0 -1 0 1 -1
59 142.05161 -1 1 -1 1 1 1 1 -1
60 90.02853 -1 0 0 0 0 0 0 0
61 160.74717 -1 1 0 0 0 1 1 1
62 116.38774 1 -1 -1 1 1 1 1 -1
63 150.10828 1 1 1 -1 1 0 1 1
64 139.15698 -1 -1 1 1 1 1 1 -1
65 116.87145 -1 -1 1 0 1 0 -1 -1
66 146.64932 -1 1 -1 0 1 0 1 -1
67 120.34049 -1 1 0 -1 1 1 1 1
68 67.76315 0 -1 1 -1 -1 0 1 -1
69 146.76017 -1 -1 -1 1 0 0 1 1
70 112.51560 -1 1 1 1 1 1 1 1
71 139.11667 -1 -1 -1 1 -1 0 1 -1
72 119.83662 0 1 0 1 0 1 1 -1
73 63.95148 -1 -1 0 -1 0 1 1 1
74 45.79002 -1 1 -1 -1 0 0 1 -1
75 49.11798 -1 1 0 1 0 -1 1 0
76 64.02202 0 0 0 0 0 0 0 0
77 64.17319 0 0 -1 1 1 -1 1 1
78 75.22525 -1 1 0 1 -1 1 1 0
79 64.35458 -1 1 1 -1 -1 0 -1 -1
80 63.85071 -1 -1 1 -1 0 -1 1 0
81 63.80032 -1 0 1 -1 0 0 1 1
82 82.62689 -1 -1 0 -1 -1 -1 1 0
83 56.75139 0 1 0 0 0 0 0 -1
84 45.53809 0 1 -1 1 0 1 -1 0
85 63.97164 -1 -1 -1 1 1 1 1 -1
> k <- length(x[1,])
> df <- as.data.frame(x)
> (mylm <- lm(df))
Call:
lm(formula = df)
Coefficients:
(Intercept) t1 t2 t3 t4 t5
104.0508 1.2766 -2.7070 5.8312 3.1746 1.2729
t6 t7 t8
-1.1403 6.8928 -0.4163
> (mysum <- summary(mylm))
Call:
lm(formula = df)
Residuals:
Min 1Q Median 3Q Max
-102.546 -27.317 7.829 26.780 72.306
Coefficients:
Estimate Std. Error t value Pr(>|t|)
(Intercept) 104.0508 7.6205 13.654 <2e-16 ***
t1 1.2766 7.2705 0.176 0.861
t2 -2.7070 4.7403 -0.571 0.570
t3 5.8312 5.0400 1.157 0.251
t4 3.1746 5.1437 0.617 0.539
t5 1.2729 5.7518 0.221 0.825
t6 -1.1403 6.1519 -0.185 0.853
t7 6.8928 5.9453 1.159 0.250
t8 -0.4163 5.0960 -0.082 0.935
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
Residual standard error: 39.17 on 76 degrees of freedom
Multiple R-squared: 0.03922, Adjusted R-squared: -0.06191
F-statistic: 0.3878 on 8 and 76 DF, p-value: 0.924
> 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,] 0.7613508 0.47729847 0.238649236
[2,] 0.6209132 0.75817363 0.379086816
[3,] 0.6458053 0.70838932 0.354194661
[4,] 0.6293863 0.74122732 0.370613662
[5,] 0.7506456 0.49870884 0.249354420
[6,] 0.7394717 0.52105665 0.260528325
[7,] 0.7946176 0.41076474 0.205382370
[8,] 0.7693933 0.46121336 0.230606681
[9,] 0.6938549 0.61229029 0.306145147
[10,] 0.7402955 0.51940903 0.259704513
[11,] 0.6636606 0.67267890 0.336339449
[12,] 0.6494408 0.70111836 0.350559179
[13,] 0.6215137 0.75697259 0.378486293
[14,] 0.7512734 0.49745323 0.248726617
[15,] 0.6843052 0.63138962 0.315694808
[16,] 0.6767858 0.64642845 0.323214224
[17,] 0.6241883 0.75162346 0.375811732
[18,] 0.6225078 0.75498450 0.377492250
[19,] 0.5497878 0.90042441 0.450212206
[20,] 0.5389516 0.92209679 0.461048393
[21,] 0.4719156 0.94383113 0.528084434
[22,] 0.4351828 0.87036552 0.564817239
[23,] 0.3862768 0.77255363 0.613723183
[24,] 0.3684617 0.73692337 0.631538316
[25,] 0.3474482 0.69489649 0.652551756
[26,] 0.2947931 0.58958616 0.705206918
[27,] 0.7042508 0.59149833 0.295749167
[28,] 0.6459992 0.70800159 0.354000793
[29,] 0.6108398 0.77832034 0.389160168
[30,] 0.5516876 0.89662489 0.448312446
[31,] 0.5007926 0.99841470 0.499207351
[32,] 0.5294485 0.94110309 0.470551544
[33,] 0.4894747 0.97894931 0.510525345
[34,] 0.4326609 0.86532174 0.567339128
[35,] 0.3744790 0.74895802 0.625520991
[36,] 0.3448276 0.68965530 0.655172350
[37,] 0.2971499 0.59429977 0.702850113
[38,] 0.3044633 0.60892662 0.695536689
[39,] 0.2685658 0.53713163 0.731434187
[40,] 0.2153978 0.43079551 0.784602243
[41,] 0.1940182 0.38803630 0.805981850
[42,] 0.2180186 0.43603718 0.781981408
[43,] 0.1959200 0.39183992 0.804080039
[44,] 0.4462928 0.89258561 0.553707197
[45,] 0.3824061 0.76481217 0.617593913
[46,] 0.3202762 0.64055240 0.679723800
[47,] 0.3903358 0.78067170 0.609664150
[48,] 0.3638464 0.72769287 0.636153563
[49,] 0.3026607 0.60532143 0.697339284
[50,] 0.4071570 0.81431404 0.592842981
[51,] 0.3302892 0.66057838 0.669710809
[52,] 0.4949190 0.98983794 0.505081029
[53,] 0.4126838 0.82536769 0.587316154
[54,] 0.3781820 0.75636397 0.621818017
[55,] 0.5564137 0.88717262 0.443586309
[56,] 0.7201344 0.55973122 0.279865609
[57,] 0.7029866 0.59402681 0.297013404
[58,] 0.8519179 0.29616427 0.148082134
[59,] 0.9593267 0.08134653 0.040673263
[60,] 0.9717157 0.05656868 0.028284338
[61,] 0.9928452 0.01430965 0.007154824
[62,] 0.9738869 0.05222617 0.026113087
> postscript(file="/var/www/rcomp/tmp/1ruo01324135423.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$resid)
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/rcomp/tmp/2f3jm1324135423.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> plot(mysum$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/rcomp/tmp/3dmo01324135423.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> hist(mysum$resid, main='Residual Histogram', xlab='values of Residuals')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/rcomp/tmp/4m04v1324135423.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> densityplot(~mysum$resid,col='black',main='Residual Density Plot', xlab='values of Residuals')
> dev.off()
null device
1
> postscript(file="/var/www/rcomp/tmp/51enr1324135423.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 = 85
Frequency = 1
1 2 3 4 5 6
0.3818989 -3.3843452 -2.7730646 49.0305488 65.6130287 -4.8147848
7 8 9 10 11 12
33.6843011 72.3064460 7.5448621 12.4780071 14.0374370 -78.2541136
13 14 15 16 17 18
15.8612649 -89.8886056 20.2333378 29.0249496 -44.6562965 -43.5107910
19 20 21 22 23 24
35.7137568 8.0527389 26.7795472 0.3624861 18.2177782 31.0426796
25 26 27 28 29 30
52.6713792 4.2446981 49.8079503 -30.6751276 -7.4791161 1.4588589
31 32 33 34 35 36
38.0093793 6.9943238 11.6466350 -8.5810182 35.1724972 27.8797999
37 38 39 40 41 42
7.1809961 -102.5463307 7.8289612 26.5939676 9.6754587 4.9317293
43 44 45 46 47 48
-44.4266149 26.0386092 14.0462738 8.6754978 8.2078302 -18.3937677
49 50 51 52 53 54
43.2250520 -27.1468919 1.2275269 -27.3169422 48.6119303 16.4811484
55 56 57 58 59 60
-87.3427206 8.0609906 13.8959294 44.1096187 37.1993513 -12.7456515
61 62 63 64 65 66
55.3438414 3.5681535 37.0818634 17.2282566 10.7626452 43.8313438
67 68 69 70 71 72
16.8388738 -47.6875643 37.4590886 -3.1664120 30.2558222 9.1494045
73 74 75 76 77 78
-43.6913052 -52.5804688 -62.1568962 -40.0287903 -46.1107006 -32.4961114
79 80 81 82 83 84
-30.6198103 -52.3202400 -48.1069596 -26.4399648 -45.0087210 -45.1159557
85
-46.2946726
> postscript(file="/var/www/rcomp/tmp/6sfx01324135423.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 = 85
Frequency = 1
lag(myerror, k = 1) myerror
0 0.3818989 NA
1 -3.3843452 0.3818989
2 -2.7730646 -3.3843452
3 49.0305488 -2.7730646
4 65.6130287 49.0305488
5 -4.8147848 65.6130287
6 33.6843011 -4.8147848
7 72.3064460 33.6843011
8 7.5448621 72.3064460
9 12.4780071 7.5448621
10 14.0374370 12.4780071
11 -78.2541136 14.0374370
12 15.8612649 -78.2541136
13 -89.8886056 15.8612649
14 20.2333378 -89.8886056
15 29.0249496 20.2333378
16 -44.6562965 29.0249496
17 -43.5107910 -44.6562965
18 35.7137568 -43.5107910
19 8.0527389 35.7137568
20 26.7795472 8.0527389
21 0.3624861 26.7795472
22 18.2177782 0.3624861
23 31.0426796 18.2177782
24 52.6713792 31.0426796
25 4.2446981 52.6713792
26 49.8079503 4.2446981
27 -30.6751276 49.8079503
28 -7.4791161 -30.6751276
29 1.4588589 -7.4791161
30 38.0093793 1.4588589
31 6.9943238 38.0093793
32 11.6466350 6.9943238
33 -8.5810182 11.6466350
34 35.1724972 -8.5810182
35 27.8797999 35.1724972
36 7.1809961 27.8797999
37 -102.5463307 7.1809961
38 7.8289612 -102.5463307
39 26.5939676 7.8289612
40 9.6754587 26.5939676
41 4.9317293 9.6754587
42 -44.4266149 4.9317293
43 26.0386092 -44.4266149
44 14.0462738 26.0386092
45 8.6754978 14.0462738
46 8.2078302 8.6754978
47 -18.3937677 8.2078302
48 43.2250520 -18.3937677
49 -27.1468919 43.2250520
50 1.2275269 -27.1468919
51 -27.3169422 1.2275269
52 48.6119303 -27.3169422
53 16.4811484 48.6119303
54 -87.3427206 16.4811484
55 8.0609906 -87.3427206
56 13.8959294 8.0609906
57 44.1096187 13.8959294
58 37.1993513 44.1096187
59 -12.7456515 37.1993513
60 55.3438414 -12.7456515
61 3.5681535 55.3438414
62 37.0818634 3.5681535
63 17.2282566 37.0818634
64 10.7626452 17.2282566
65 43.8313438 10.7626452
66 16.8388738 43.8313438
67 -47.6875643 16.8388738
68 37.4590886 -47.6875643
69 -3.1664120 37.4590886
70 30.2558222 -3.1664120
71 9.1494045 30.2558222
72 -43.6913052 9.1494045
73 -52.5804688 -43.6913052
74 -62.1568962 -52.5804688
75 -40.0287903 -62.1568962
76 -46.1107006 -40.0287903
77 -32.4961114 -46.1107006
78 -30.6198103 -32.4961114
79 -52.3202400 -30.6198103
80 -48.1069596 -52.3202400
81 -26.4399648 -48.1069596
82 -45.0087210 -26.4399648
83 -45.1159557 -45.0087210
84 -46.2946726 -45.1159557
85 NA -46.2946726
> dum1 <- dum[2:length(myerror),]
> dum1
lag(myerror, k = 1) myerror
[1,] -3.3843452 0.3818989
[2,] -2.7730646 -3.3843452
[3,] 49.0305488 -2.7730646
[4,] 65.6130287 49.0305488
[5,] -4.8147848 65.6130287
[6,] 33.6843011 -4.8147848
[7,] 72.3064460 33.6843011
[8,] 7.5448621 72.3064460
[9,] 12.4780071 7.5448621
[10,] 14.0374370 12.4780071
[11,] -78.2541136 14.0374370
[12,] 15.8612649 -78.2541136
[13,] -89.8886056 15.8612649
[14,] 20.2333378 -89.8886056
[15,] 29.0249496 20.2333378
[16,] -44.6562965 29.0249496
[17,] -43.5107910 -44.6562965
[18,] 35.7137568 -43.5107910
[19,] 8.0527389 35.7137568
[20,] 26.7795472 8.0527389
[21,] 0.3624861 26.7795472
[22,] 18.2177782 0.3624861
[23,] 31.0426796 18.2177782
[24,] 52.6713792 31.0426796
[25,] 4.2446981 52.6713792
[26,] 49.8079503 4.2446981
[27,] -30.6751276 49.8079503
[28,] -7.4791161 -30.6751276
[29,] 1.4588589 -7.4791161
[30,] 38.0093793 1.4588589
[31,] 6.9943238 38.0093793
[32,] 11.6466350 6.9943238
[33,] -8.5810182 11.6466350
[34,] 35.1724972 -8.5810182
[35,] 27.8797999 35.1724972
[36,] 7.1809961 27.8797999
[37,] -102.5463307 7.1809961
[38,] 7.8289612 -102.5463307
[39,] 26.5939676 7.8289612
[40,] 9.6754587 26.5939676
[41,] 4.9317293 9.6754587
[42,] -44.4266149 4.9317293
[43,] 26.0386092 -44.4266149
[44,] 14.0462738 26.0386092
[45,] 8.6754978 14.0462738
[46,] 8.2078302 8.6754978
[47,] -18.3937677 8.2078302
[48,] 43.2250520 -18.3937677
[49,] -27.1468919 43.2250520
[50,] 1.2275269 -27.1468919
[51,] -27.3169422 1.2275269
[52,] 48.6119303 -27.3169422
[53,] 16.4811484 48.6119303
[54,] -87.3427206 16.4811484
[55,] 8.0609906 -87.3427206
[56,] 13.8959294 8.0609906
[57,] 44.1096187 13.8959294
[58,] 37.1993513 44.1096187
[59,] -12.7456515 37.1993513
[60,] 55.3438414 -12.7456515
[61,] 3.5681535 55.3438414
[62,] 37.0818634 3.5681535
[63,] 17.2282566 37.0818634
[64,] 10.7626452 17.2282566
[65,] 43.8313438 10.7626452
[66,] 16.8388738 43.8313438
[67,] -47.6875643 16.8388738
[68,] 37.4590886 -47.6875643
[69,] -3.1664120 37.4590886
[70,] 30.2558222 -3.1664120
[71,] 9.1494045 30.2558222
[72,] -43.6913052 9.1494045
[73,] -52.5804688 -43.6913052
[74,] -62.1568962 -52.5804688
[75,] -40.0287903 -62.1568962
[76,] -46.1107006 -40.0287903
[77,] -32.4961114 -46.1107006
[78,] -30.6198103 -32.4961114
[79,] -52.3202400 -30.6198103
[80,] -48.1069596 -52.3202400
[81,] -26.4399648 -48.1069596
[82,] -45.0087210 -26.4399648
[83,] -45.1159557 -45.0087210
[84,] -46.2946726 -45.1159557
> z <- as.data.frame(dum1)
> z
lag(myerror, k = 1) myerror
1 -3.3843452 0.3818989
2 -2.7730646 -3.3843452
3 49.0305488 -2.7730646
4 65.6130287 49.0305488
5 -4.8147848 65.6130287
6 33.6843011 -4.8147848
7 72.3064460 33.6843011
8 7.5448621 72.3064460
9 12.4780071 7.5448621
10 14.0374370 12.4780071
11 -78.2541136 14.0374370
12 15.8612649 -78.2541136
13 -89.8886056 15.8612649
14 20.2333378 -89.8886056
15 29.0249496 20.2333378
16 -44.6562965 29.0249496
17 -43.5107910 -44.6562965
18 35.7137568 -43.5107910
19 8.0527389 35.7137568
20 26.7795472 8.0527389
21 0.3624861 26.7795472
22 18.2177782 0.3624861
23 31.0426796 18.2177782
24 52.6713792 31.0426796
25 4.2446981 52.6713792
26 49.8079503 4.2446981
27 -30.6751276 49.8079503
28 -7.4791161 -30.6751276
29 1.4588589 -7.4791161
30 38.0093793 1.4588589
31 6.9943238 38.0093793
32 11.6466350 6.9943238
33 -8.5810182 11.6466350
34 35.1724972 -8.5810182
35 27.8797999 35.1724972
36 7.1809961 27.8797999
37 -102.5463307 7.1809961
38 7.8289612 -102.5463307
39 26.5939676 7.8289612
40 9.6754587 26.5939676
41 4.9317293 9.6754587
42 -44.4266149 4.9317293
43 26.0386092 -44.4266149
44 14.0462738 26.0386092
45 8.6754978 14.0462738
46 8.2078302 8.6754978
47 -18.3937677 8.2078302
48 43.2250520 -18.3937677
49 -27.1468919 43.2250520
50 1.2275269 -27.1468919
51 -27.3169422 1.2275269
52 48.6119303 -27.3169422
53 16.4811484 48.6119303
54 -87.3427206 16.4811484
55 8.0609906 -87.3427206
56 13.8959294 8.0609906
57 44.1096187 13.8959294
58 37.1993513 44.1096187
59 -12.7456515 37.1993513
60 55.3438414 -12.7456515
61 3.5681535 55.3438414
62 37.0818634 3.5681535
63 17.2282566 37.0818634
64 10.7626452 17.2282566
65 43.8313438 10.7626452
66 16.8388738 43.8313438
67 -47.6875643 16.8388738
68 37.4590886 -47.6875643
69 -3.1664120 37.4590886
70 30.2558222 -3.1664120
71 9.1494045 30.2558222
72 -43.6913052 9.1494045
73 -52.5804688 -43.6913052
74 -62.1568962 -52.5804688
75 -40.0287903 -62.1568962
76 -46.1107006 -40.0287903
77 -32.4961114 -46.1107006
78 -30.6198103 -32.4961114
79 -52.3202400 -30.6198103
80 -48.1069596 -52.3202400
81 -26.4399648 -48.1069596
82 -45.0087210 -26.4399648
83 -45.1159557 -45.0087210
84 -46.2946726 -45.1159557
> 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/rcomp/tmp/7dc101324135423.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> acf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/rcomp/tmp/8sdsk1324135423.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> pacf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Partial Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/rcomp/tmp/97hkn1324135423.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> opar <- par(mfrow = c(2,2), oma = c(0, 0, 1.1, 0))
> plot(mylm, las = 1, sub='Residual Diagnostics')
> par(opar)
> dev.off()
null device
1
> if (n > n25) {
+ postscript(file="/var/www/rcomp/tmp/10l3ay1324135423.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
+ plot(kp3:nmkm3,gqarr[,2], main='Goldfeld-Quandt test',ylab='2-sided p-value',xlab='breakpoint')
+ grid()
+ dev.off()
+ }
null device
1
>
> #Note: the /var/www/rcomp/createtable file can be downloaded at http://www.wessa.net/cretab
> load(file="/var/www/rcomp/createtable")
>
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a, 'Multiple Linear Regression - Estimated Regression Equation', 1, TRUE)
> a<-table.row.end(a)
> myeq <- colnames(x)[1]
> myeq <- paste(myeq, '[t] = ', sep='')
> for (i in 1:k){
+ if (mysum$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/rcomp/tmp/11qyzc1324135423.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/rcomp/tmp/12y3801324135423.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/rcomp/tmp/13ivsa1324135423.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/rcomp/tmp/14apbo1324135423.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/rcomp/tmp/152cov1324135423.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/rcomp/tmp/16phfx1324135423.tab")
+ }
>
> try(system("convert tmp/1ruo01324135423.ps tmp/1ruo01324135423.png",intern=TRUE))
character(0)
> try(system("convert tmp/2f3jm1324135423.ps tmp/2f3jm1324135423.png",intern=TRUE))
character(0)
> try(system("convert tmp/3dmo01324135423.ps tmp/3dmo01324135423.png",intern=TRUE))
character(0)
> try(system("convert tmp/4m04v1324135423.ps tmp/4m04v1324135423.png",intern=TRUE))
character(0)
> try(system("convert tmp/51enr1324135423.ps tmp/51enr1324135423.png",intern=TRUE))
character(0)
> try(system("convert tmp/6sfx01324135423.ps tmp/6sfx01324135423.png",intern=TRUE))
character(0)
> try(system("convert tmp/7dc101324135423.ps tmp/7dc101324135423.png",intern=TRUE))
character(0)
> try(system("convert tmp/8sdsk1324135423.ps tmp/8sdsk1324135423.png",intern=TRUE))
character(0)
> try(system("convert tmp/97hkn1324135423.ps tmp/97hkn1324135423.png",intern=TRUE))
character(0)
> try(system("convert tmp/10l3ay1324135423.ps tmp/10l3ay1324135423.png",intern=TRUE))
character(0)
>
>
> proc.time()
user system elapsed
4.820 0.410 5.209