R version 2.8.0 (2008-10-20)
Copyright (C) 2008 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.
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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(13363
+ ,0
+ ,12530
+ ,0
+ ,11420
+ ,0
+ ,10948
+ ,0
+ ,10173
+ ,0
+ ,10602
+ ,0
+ ,16094
+ ,0
+ ,19631
+ ,0
+ ,17140
+ ,0
+ ,14345
+ ,0
+ ,12632
+ ,0
+ ,12894
+ ,0
+ ,11808
+ ,0
+ ,10673
+ ,0
+ ,9939
+ ,0
+ ,9890
+ ,0
+ ,9283
+ ,0
+ ,10131
+ ,0
+ ,15864
+ ,0
+ ,19283
+ ,0
+ ,16203
+ ,0
+ ,13919
+ ,0
+ ,11937
+ ,0
+ ,11795
+ ,0
+ ,11268
+ ,0
+ ,10522
+ ,0
+ ,9929
+ ,0
+ ,9725
+ ,0
+ ,9372
+ ,0
+ ,10068
+ ,0
+ ,16230
+ ,0
+ ,19115
+ ,0
+ ,18351
+ ,0
+ ,16265
+ ,0
+ ,14103
+ ,0
+ ,14115
+ ,0
+ ,13327
+ ,0
+ ,12618
+ ,0
+ ,12129
+ ,0
+ ,11775
+ ,0
+ ,11493
+ ,0
+ ,12470
+ ,0
+ ,20792
+ ,0
+ ,22337
+ ,0
+ ,21325
+ ,0
+ ,18581
+ ,0
+ ,16475
+ ,0
+ ,16581
+ ,0
+ ,15745
+ ,0
+ ,14453
+ ,0
+ ,13712
+ ,0
+ ,13766
+ ,0
+ ,13336
+ ,0
+ ,15346
+ ,0
+ ,24446
+ ,0
+ ,26178
+ ,0
+ ,24628
+ ,0
+ ,21282
+ ,0
+ ,18850
+ ,0
+ ,18822
+ ,0
+ ,18060
+ ,0
+ ,17536
+ ,0
+ ,16417
+ ,0
+ ,15842
+ ,0
+ ,15188
+ ,0
+ ,16905
+ ,0
+ ,25430
+ ,0
+ ,27962
+ ,0
+ ,26607
+ ,0
+ ,23364
+ ,0
+ ,20827
+ ,0
+ ,20506
+ ,0
+ ,19181
+ ,0
+ ,18016
+ ,0
+ ,17354
+ ,0
+ ,16256
+ ,0
+ ,15770
+ ,0
+ ,17538
+ ,0
+ ,26899
+ ,0
+ ,28915
+ ,0
+ ,25247
+ ,0
+ ,22856
+ ,0
+ ,19980
+ ,0
+ ,19856
+ ,0
+ ,16994
+ ,0
+ ,16839
+ ,0
+ ,15618
+ ,0
+ ,15883
+ ,0
+ ,15513
+ ,0
+ ,17106
+ ,0
+ ,25272
+ ,0
+ ,26731
+ ,0
+ ,22891
+ ,0
+ ,19583
+ ,0
+ ,16939
+ ,0
+ ,16757
+ ,0
+ ,15435
+ ,0
+ ,14786
+ ,0
+ ,13680
+ ,0
+ ,13208
+ ,0
+ ,12707
+ ,0
+ ,14277
+ ,0
+ ,22436
+ ,0
+ ,23229
+ ,1
+ ,18241
+ ,1
+ ,16145
+ ,1
+ ,13994
+ ,1
+ ,14780
+ ,1
+ ,13100
+ ,1
+ ,12329
+ ,1
+ ,12463
+ ,1
+ ,11532
+ ,1
+ ,10784
+ ,1
+ ,13106
+ ,1
+ ,19491
+ ,1
+ ,20418
+ ,1
+ ,16094
+ ,1
+ ,14491
+ ,1
+ ,13067
+ ,1)
+ ,dim=c(2
+ ,119)
+ ,dimnames=list(c('Profbach'
+ ,'Dummy')
+ ,1:119))
> y <- array(NA,dim=c(2,119),dimnames=list(c('Profbach','Dummy'),1:119))
> 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
Profbach Dummy M1 M2 M3 M4 M5 M6 M7 M8 M9 M10 M11
1 13363 0 1 0 0 0 0 0 0 0 0 0 0
2 12530 0 0 1 0 0 0 0 0 0 0 0 0
3 11420 0 0 0 1 0 0 0 0 0 0 0 0
4 10948 0 0 0 0 1 0 0 0 0 0 0 0
5 10173 0 0 0 0 0 1 0 0 0 0 0 0
6 10602 0 0 0 0 0 0 1 0 0 0 0 0
7 16094 0 0 0 0 0 0 0 1 0 0 0 0
8 19631 0 0 0 0 0 0 0 0 1 0 0 0
9 17140 0 0 0 0 0 0 0 0 0 1 0 0
10 14345 0 0 0 0 0 0 0 0 0 0 1 0
11 12632 0 0 0 0 0 0 0 0 0 0 0 1
12 12894 0 0 0 0 0 0 0 0 0 0 0 0
13 11808 0 1 0 0 0 0 0 0 0 0 0 0
14 10673 0 0 1 0 0 0 0 0 0 0 0 0
15 9939 0 0 0 1 0 0 0 0 0 0 0 0
16 9890 0 0 0 0 1 0 0 0 0 0 0 0
17 9283 0 0 0 0 0 1 0 0 0 0 0 0
18 10131 0 0 0 0 0 0 1 0 0 0 0 0
19 15864 0 0 0 0 0 0 0 1 0 0 0 0
20 19283 0 0 0 0 0 0 0 0 1 0 0 0
21 16203 0 0 0 0 0 0 0 0 0 1 0 0
22 13919 0 0 0 0 0 0 0 0 0 0 1 0
23 11937 0 0 0 0 0 0 0 0 0 0 0 1
24 11795 0 0 0 0 0 0 0 0 0 0 0 0
25 11268 0 1 0 0 0 0 0 0 0 0 0 0
26 10522 0 0 1 0 0 0 0 0 0 0 0 0
27 9929 0 0 0 1 0 0 0 0 0 0 0 0
28 9725 0 0 0 0 1 0 0 0 0 0 0 0
29 9372 0 0 0 0 0 1 0 0 0 0 0 0
30 10068 0 0 0 0 0 0 1 0 0 0 0 0
31 16230 0 0 0 0 0 0 0 1 0 0 0 0
32 19115 0 0 0 0 0 0 0 0 1 0 0 0
33 18351 0 0 0 0 0 0 0 0 0 1 0 0
34 16265 0 0 0 0 0 0 0 0 0 0 1 0
35 14103 0 0 0 0 0 0 0 0 0 0 0 1
36 14115 0 0 0 0 0 0 0 0 0 0 0 0
37 13327 0 1 0 0 0 0 0 0 0 0 0 0
38 12618 0 0 1 0 0 0 0 0 0 0 0 0
39 12129 0 0 0 1 0 0 0 0 0 0 0 0
40 11775 0 0 0 0 1 0 0 0 0 0 0 0
41 11493 0 0 0 0 0 1 0 0 0 0 0 0
42 12470 0 0 0 0 0 0 1 0 0 0 0 0
43 20792 0 0 0 0 0 0 0 1 0 0 0 0
44 22337 0 0 0 0 0 0 0 0 1 0 0 0
45 21325 0 0 0 0 0 0 0 0 0 1 0 0
46 18581 0 0 0 0 0 0 0 0 0 0 1 0
47 16475 0 0 0 0 0 0 0 0 0 0 0 1
48 16581 0 0 0 0 0 0 0 0 0 0 0 0
49 15745 0 1 0 0 0 0 0 0 0 0 0 0
50 14453 0 0 1 0 0 0 0 0 0 0 0 0
51 13712 0 0 0 1 0 0 0 0 0 0 0 0
52 13766 0 0 0 0 1 0 0 0 0 0 0 0
53 13336 0 0 0 0 0 1 0 0 0 0 0 0
54 15346 0 0 0 0 0 0 1 0 0 0 0 0
55 24446 0 0 0 0 0 0 0 1 0 0 0 0
56 26178 0 0 0 0 0 0 0 0 1 0 0 0
57 24628 0 0 0 0 0 0 0 0 0 1 0 0
58 21282 0 0 0 0 0 0 0 0 0 0 1 0
59 18850 0 0 0 0 0 0 0 0 0 0 0 1
60 18822 0 0 0 0 0 0 0 0 0 0 0 0
61 18060 0 1 0 0 0 0 0 0 0 0 0 0
62 17536 0 0 1 0 0 0 0 0 0 0 0 0
63 16417 0 0 0 1 0 0 0 0 0 0 0 0
64 15842 0 0 0 0 1 0 0 0 0 0 0 0
65 15188 0 0 0 0 0 1 0 0 0 0 0 0
66 16905 0 0 0 0 0 0 1 0 0 0 0 0
67 25430 0 0 0 0 0 0 0 1 0 0 0 0
68 27962 0 0 0 0 0 0 0 0 1 0 0 0
69 26607 0 0 0 0 0 0 0 0 0 1 0 0
70 23364 0 0 0 0 0 0 0 0 0 0 1 0
71 20827 0 0 0 0 0 0 0 0 0 0 0 1
72 20506 0 0 0 0 0 0 0 0 0 0 0 0
73 19181 0 1 0 0 0 0 0 0 0 0 0 0
74 18016 0 0 1 0 0 0 0 0 0 0 0 0
75 17354 0 0 0 1 0 0 0 0 0 0 0 0
76 16256 0 0 0 0 1 0 0 0 0 0 0 0
77 15770 0 0 0 0 0 1 0 0 0 0 0 0
78 17538 0 0 0 0 0 0 1 0 0 0 0 0
79 26899 0 0 0 0 0 0 0 1 0 0 0 0
80 28915 0 0 0 0 0 0 0 0 1 0 0 0
81 25247 0 0 0 0 0 0 0 0 0 1 0 0
82 22856 0 0 0 0 0 0 0 0 0 0 1 0
83 19980 0 0 0 0 0 0 0 0 0 0 0 1
84 19856 0 0 0 0 0 0 0 0 0 0 0 0
85 16994 0 1 0 0 0 0 0 0 0 0 0 0
86 16839 0 0 1 0 0 0 0 0 0 0 0 0
87 15618 0 0 0 1 0 0 0 0 0 0 0 0
88 15883 0 0 0 0 1 0 0 0 0 0 0 0
89 15513 0 0 0 0 0 1 0 0 0 0 0 0
90 17106 0 0 0 0 0 0 1 0 0 0 0 0
91 25272 0 0 0 0 0 0 0 1 0 0 0 0
92 26731 0 0 0 0 0 0 0 0 1 0 0 0
93 22891 0 0 0 0 0 0 0 0 0 1 0 0
94 19583 0 0 0 0 0 0 0 0 0 0 1 0
95 16939 0 0 0 0 0 0 0 0 0 0 0 1
96 16757 0 0 0 0 0 0 0 0 0 0 0 0
97 15435 0 1 0 0 0 0 0 0 0 0 0 0
98 14786 0 0 1 0 0 0 0 0 0 0 0 0
99 13680 0 0 0 1 0 0 0 0 0 0 0 0
100 13208 0 0 0 0 1 0 0 0 0 0 0 0
101 12707 0 0 0 0 0 1 0 0 0 0 0 0
102 14277 0 0 0 0 0 0 1 0 0 0 0 0
103 22436 0 0 0 0 0 0 0 1 0 0 0 0
104 23229 1 0 0 0 0 0 0 0 1 0 0 0
105 18241 1 0 0 0 0 0 0 0 0 1 0 0
106 16145 1 0 0 0 0 0 0 0 0 0 1 0
107 13994 1 0 0 0 0 0 0 0 0 0 0 1
108 14780 1 0 0 0 0 0 0 0 0 0 0 0
109 13100 1 1 0 0 0 0 0 0 0 0 0 0
110 12329 1 0 1 0 0 0 0 0 0 0 0 0
111 12463 1 0 0 1 0 0 0 0 0 0 0 0
112 11532 1 0 0 0 1 0 0 0 0 0 0 0
113 10784 1 0 0 0 0 1 0 0 0 0 0 0
114 13106 1 0 0 0 0 0 1 0 0 0 0 0
115 19491 1 0 0 0 0 0 0 1 0 0 0 0
116 20418 1 0 0 0 0 0 0 0 1 0 0 0
117 16094 1 0 0 0 0 0 0 0 0 1 0 0
118 14491 1 0 0 0 0 0 0 0 0 0 1 0
119 13067 1 0 0 0 0 0 0 0 0 0 0 1
> k <- length(x[1,])
> df <- as.data.frame(x)
> (mylm <- lm(df))
Call:
lm(formula = df)
Coefficients:
(Intercept) Dummy M1 M2 M3 M4
16490.9 -2312.3 -1431.6 -2229.5 -2993.6 -3377.2
M5 M6 M7 M8 M9 M10
-3897.8 -2504.8 5035.7 7351.4 4644.2 2054.6
M11
-148.1
> (mysum <- summary(mylm))
Call:
lm(formula = df)
Residuals:
Min 1Q Median 3Q Max
-5662.6 -2398.0 214.7 2732.4 5471.8
Coefficients:
Estimate Std. Error t value Pr(>|t|)
(Intercept) 16490.9 1040.7 15.846 < 2e-16 ***
Dummy -2312.3 843.5 -2.741 0.007185 **
M1 -1431.6 1428.7 -1.002 0.318622
M2 -2229.5 1428.7 -1.560 0.121628
M3 -2993.6 1428.7 -2.095 0.038527 *
M4 -3377.2 1428.7 -2.364 0.019911 *
M5 -3897.8 1428.7 -2.728 0.007457 **
M6 -2504.8 1428.7 -1.753 0.082464 .
M7 5035.7 1428.7 3.525 0.000628 ***
M8 7351.4 1430.7 5.138 1.27e-06 ***
M9 4644.2 1430.7 3.246 0.001566 **
M10 2054.6 1430.7 1.436 0.153905
M11 -148.1 1430.7 -0.103 0.917767
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
Residual standard error: 3109 on 106 degrees of freedom
Multiple R-squared: 0.6018, Adjusted R-squared: 0.5568
F-statistic: 13.35 on 12 and 106 DF, p-value: 2.447e-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,] 8.421738e-02 1.684348e-01 9.157826e-01
[2,] 3.320204e-02 6.640407e-02 9.667980e-01
[3,] 1.156664e-02 2.313327e-02 9.884334e-01
[4,] 4.066461e-03 8.132922e-03 9.959335e-01
[5,] 1.363998e-03 2.727996e-03 9.986360e-01
[6,] 6.031462e-04 1.206292e-03 9.993969e-01
[7,] 2.151710e-04 4.303420e-04 9.997848e-01
[8,] 8.610349e-05 1.722070e-04 9.999139e-01
[9,] 4.908260e-05 9.816521e-05 9.999509e-01
[10,] 4.119060e-05 8.238121e-05 9.999588e-01
[11,] 2.715568e-05 5.431136e-05 9.999728e-01
[12,] 1.396526e-05 2.793052e-05 9.999860e-01
[13,] 7.008649e-06 1.401730e-05 9.999930e-01
[14,] 3.000556e-06 6.001113e-06 9.999970e-01
[15,] 1.521402e-06 3.042803e-06 9.999985e-01
[16,] 1.376754e-06 2.753508e-06 9.999986e-01
[17,] 1.305385e-06 2.610769e-06 9.999987e-01
[18,] 3.584496e-06 7.168992e-06 9.999964e-01
[19,] 1.638017e-05 3.276034e-05 9.999836e-01
[20,] 3.698279e-05 7.396559e-05 9.999630e-01
[21,] 7.891135e-05 1.578227e-04 9.999211e-01
[22,] 8.962798e-05 1.792560e-04 9.999104e-01
[23,] 1.234223e-04 2.468446e-04 9.998766e-01
[24,] 2.181721e-04 4.363443e-04 9.997818e-01
[25,] 3.350808e-04 6.701616e-04 9.996649e-01
[26,] 6.255054e-04 1.251011e-03 9.993745e-01
[27,] 1.863714e-03 3.727428e-03 9.981363e-01
[28,] 4.751927e-02 9.503854e-02 9.524807e-01
[29,] 1.380445e-01 2.760889e-01 8.619555e-01
[30,] 3.099071e-01 6.198142e-01 6.900929e-01
[31,] 4.755252e-01 9.510503e-01 5.244748e-01
[32,] 6.101737e-01 7.796526e-01 3.898263e-01
[33,] 7.302689e-01 5.394621e-01 2.697311e-01
[34,] 7.927293e-01 4.145414e-01 2.072707e-01
[35,] 8.404036e-01 3.191927e-01 1.595964e-01
[36,] 8.781256e-01 2.437489e-01 1.218744e-01
[37,] 9.053776e-01 1.892449e-01 9.462243e-02
[38,] 9.262617e-01 1.474766e-01 7.373829e-02
[39,] 9.588013e-01 8.239743e-02 4.119871e-02
[40,] 9.919017e-01 1.619666e-02 8.098332e-03
[41,] 9.972164e-01 5.567187e-03 2.783594e-03
[42,] 9.989769e-01 2.046294e-03 1.023147e-03
[43,] 9.993773e-01 1.245400e-03 6.226998e-04
[44,] 9.995275e-01 9.449802e-04 4.724901e-04
[45,] 9.996155e-01 7.690108e-04 3.845054e-04
[46,] 9.996824e-01 6.352438e-04 3.176219e-04
[47,] 9.997588e-01 4.824477e-04 2.412238e-04
[48,] 9.997770e-01 4.459455e-04 2.229727e-04
[49,] 9.997658e-01 4.684466e-04 2.342233e-04
[50,] 9.997364e-01 5.272254e-04 2.636127e-04
[51,] 9.997372e-01 5.256517e-04 2.628258e-04
[52,] 9.998167e-01 3.665295e-04 1.832648e-04
[53,] 9.998574e-01 2.852056e-04 1.426028e-04
[54,] 9.999606e-01 7.872556e-05 3.936278e-05
[55,] 9.999803e-01 3.947550e-05 1.973775e-05
[56,] 9.999876e-01 2.484520e-05 1.242260e-05
[57,] 9.999884e-01 2.322788e-05 1.161394e-05
[58,] 9.999910e-01 1.795960e-05 8.979802e-06
[59,] 9.999903e-01 1.938560e-05 9.692801e-06
[60,] 9.999898e-01 2.030921e-05 1.015460e-05
[61,] 9.999849e-01 3.018132e-05 1.509066e-05
[62,] 9.999778e-01 4.439467e-05 2.219733e-05
[63,] 9.999689e-01 6.229904e-05 3.114952e-05
[64,] 9.999847e-01 3.061754e-05 1.530877e-05
[65,] 9.999893e-01 2.147100e-05 1.073550e-05
[66,] 9.999950e-01 9.921887e-06 4.960943e-06
[67,] 9.999983e-01 3.448926e-06 1.724463e-06
[68,] 9.999989e-01 2.118620e-06 1.059310e-06
[69,] 9.999989e-01 2.220248e-06 1.110124e-06
[70,] 9.999974e-01 5.171645e-06 2.585823e-06
[71,] 9.999954e-01 9.174613e-06 4.587306e-06
[72,] 9.999892e-01 2.161867e-05 1.080933e-05
[73,] 9.999836e-01 3.278376e-05 1.639188e-05
[74,] 9.999796e-01 4.085260e-05 2.042630e-05
[75,] 9.999696e-01 6.070264e-05 3.035132e-05
[76,] 9.999804e-01 3.924382e-05 1.962191e-05
[77,] 9.999749e-01 5.022574e-05 2.511287e-05
[78,] 9.999926e-01 1.482178e-05 7.410888e-06
[79,] 9.999920e-01 1.602375e-05 8.011875e-06
[80,] 9.999833e-01 3.338569e-05 1.669284e-05
[81,] 9.999349e-01 1.302934e-04 6.514668e-05
[82,] 9.997669e-01 4.661601e-04 2.330800e-04
[83,] 9.992371e-01 1.525765e-03 7.628826e-04
[84,] 9.976139e-01 4.772199e-03 2.386100e-03
[85,] 9.925044e-01 1.499115e-02 7.495573e-03
[86,] 9.778202e-01 4.435957e-02 2.217979e-02
[87,] 9.486353e-01 1.027294e-01 5.136469e-02
[88,] 8.673209e-01 2.653581e-01 1.326791e-01
> postscript(file="/var/www/html/freestat/rcomp/tmp/1nvmc1229608093.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$resid)
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/freestat/rcomp/tmp/2kl1e1229608093.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> plot(mysum$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/freestat/rcomp/tmp/3hcrf1229608093.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> hist(mysum$resid, main='Residual Histogram', xlab='values of Residuals')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/freestat/rcomp/tmp/40feb1229608093.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> densityplot(~mysum$resid,col='black',main='Residual Density Plot', xlab='values of Residuals')
> dev.off()
null device
1
> postscript(file="/var/www/html/freestat/rcomp/tmp/5bx0t1229608094.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 = 119
Frequency = 1
1 2 3 4 5 6
-1696.32788 -1731.42788 -2077.32788 -2165.72788 -2420.12788 -3384.12788
7 8 9 10 11 12
-5432.62788 -4211.35576 -3995.15576 -4200.55576 -3710.85576 -3596.91987
13 14 15 16 17 18
-3251.32788 -3588.42788 -3558.32788 -3223.72788 -3310.12788 -3855.12788
19 20 21 22 23 24
-5662.62788 -4559.35576 -4932.15576 -4626.55576 -4405.85576 -4695.91987
25 26 27 28 29 30
-3791.32788 -3739.42788 -3568.32788 -3388.72788 -3221.12788 -3918.12788
31 32 33 34 35 36
-5296.62788 -4727.35576 -2784.15576 -2280.55576 -2239.85576 -2375.91987
37 38 39 40 41 42
-1732.32788 -1643.42788 -1368.32788 -1338.72788 -1100.12788 -1516.12788
43 44 45 46 47 48
-734.62788 -1505.35576 189.84424 35.44424 132.14424 90.08013
49 50 51 52 53 54
685.67212 191.57212 214.67212 652.27212 742.87212 1359.87212
55 56 57 58 59 60
2919.37212 2335.64424 3492.84424 2736.44424 2507.14424 2331.08013
61 62 63 64 65 66
3000.67212 3274.57212 2919.67212 2728.27212 2594.87212 2918.87212
67 68 69 70 71 72
3903.37212 4119.64424 5471.84424 4818.44424 4484.14424 4015.08013
73 74 75 76 77 78
4121.67212 3754.57212 3856.67212 3142.27212 3176.87212 3551.87212
79 80 81 82 83 84
5372.37212 5072.64424 4111.84424 4310.44424 3637.14424 3365.08013
85 86 87 88 89 90
1934.67212 2577.57212 2120.67212 2769.27212 2919.87212 3119.87212
91 92 93 94 95 96
3745.37212 2888.64424 1755.84424 1037.44424 596.14424 266.08013
97 98 99 100 101 102
375.67212 524.57212 182.67212 94.27212 113.87212 290.87212
103 104 105 106 107 108
909.37212 1698.92306 -581.87694 -88.27694 -36.57694 601.35895
109 110 111 112 113 114
352.95094 379.85094 1277.95094 730.55094 503.15094 1432.15094
115 116 117 118 119
276.65094 -1112.07694 -2728.87694 -1742.27694 -963.57694
> postscript(file="/var/www/html/freestat/rcomp/tmp/69qf41229608094.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 = 119
Frequency = 1
lag(myerror, k = 1) myerror
0 -1696.32788 NA
1 -1731.42788 -1696.32788
2 -2077.32788 -1731.42788
3 -2165.72788 -2077.32788
4 -2420.12788 -2165.72788
5 -3384.12788 -2420.12788
6 -5432.62788 -3384.12788
7 -4211.35576 -5432.62788
8 -3995.15576 -4211.35576
9 -4200.55576 -3995.15576
10 -3710.85576 -4200.55576
11 -3596.91987 -3710.85576
12 -3251.32788 -3596.91987
13 -3588.42788 -3251.32788
14 -3558.32788 -3588.42788
15 -3223.72788 -3558.32788
16 -3310.12788 -3223.72788
17 -3855.12788 -3310.12788
18 -5662.62788 -3855.12788
19 -4559.35576 -5662.62788
20 -4932.15576 -4559.35576
21 -4626.55576 -4932.15576
22 -4405.85576 -4626.55576
23 -4695.91987 -4405.85576
24 -3791.32788 -4695.91987
25 -3739.42788 -3791.32788
26 -3568.32788 -3739.42788
27 -3388.72788 -3568.32788
28 -3221.12788 -3388.72788
29 -3918.12788 -3221.12788
30 -5296.62788 -3918.12788
31 -4727.35576 -5296.62788
32 -2784.15576 -4727.35576
33 -2280.55576 -2784.15576
34 -2239.85576 -2280.55576
35 -2375.91987 -2239.85576
36 -1732.32788 -2375.91987
37 -1643.42788 -1732.32788
38 -1368.32788 -1643.42788
39 -1338.72788 -1368.32788
40 -1100.12788 -1338.72788
41 -1516.12788 -1100.12788
42 -734.62788 -1516.12788
43 -1505.35576 -734.62788
44 189.84424 -1505.35576
45 35.44424 189.84424
46 132.14424 35.44424
47 90.08013 132.14424
48 685.67212 90.08013
49 191.57212 685.67212
50 214.67212 191.57212
51 652.27212 214.67212
52 742.87212 652.27212
53 1359.87212 742.87212
54 2919.37212 1359.87212
55 2335.64424 2919.37212
56 3492.84424 2335.64424
57 2736.44424 3492.84424
58 2507.14424 2736.44424
59 2331.08013 2507.14424
60 3000.67212 2331.08013
61 3274.57212 3000.67212
62 2919.67212 3274.57212
63 2728.27212 2919.67212
64 2594.87212 2728.27212
65 2918.87212 2594.87212
66 3903.37212 2918.87212
67 4119.64424 3903.37212
68 5471.84424 4119.64424
69 4818.44424 5471.84424
70 4484.14424 4818.44424
71 4015.08013 4484.14424
72 4121.67212 4015.08013
73 3754.57212 4121.67212
74 3856.67212 3754.57212
75 3142.27212 3856.67212
76 3176.87212 3142.27212
77 3551.87212 3176.87212
78 5372.37212 3551.87212
79 5072.64424 5372.37212
80 4111.84424 5072.64424
81 4310.44424 4111.84424
82 3637.14424 4310.44424
83 3365.08013 3637.14424
84 1934.67212 3365.08013
85 2577.57212 1934.67212
86 2120.67212 2577.57212
87 2769.27212 2120.67212
88 2919.87212 2769.27212
89 3119.87212 2919.87212
90 3745.37212 3119.87212
91 2888.64424 3745.37212
92 1755.84424 2888.64424
93 1037.44424 1755.84424
94 596.14424 1037.44424
95 266.08013 596.14424
96 375.67212 266.08013
97 524.57212 375.67212
98 182.67212 524.57212
99 94.27212 182.67212
100 113.87212 94.27212
101 290.87212 113.87212
102 909.37212 290.87212
103 1698.92306 909.37212
104 -581.87694 1698.92306
105 -88.27694 -581.87694
106 -36.57694 -88.27694
107 601.35895 -36.57694
108 352.95094 601.35895
109 379.85094 352.95094
110 1277.95094 379.85094
111 730.55094 1277.95094
112 503.15094 730.55094
113 1432.15094 503.15094
114 276.65094 1432.15094
115 -1112.07694 276.65094
116 -2728.87694 -1112.07694
117 -1742.27694 -2728.87694
118 -963.57694 -1742.27694
119 NA -963.57694
> dum1 <- dum[2:length(myerror),]
> dum1
lag(myerror, k = 1) myerror
[1,] -1731.42788 -1696.32788
[2,] -2077.32788 -1731.42788
[3,] -2165.72788 -2077.32788
[4,] -2420.12788 -2165.72788
[5,] -3384.12788 -2420.12788
[6,] -5432.62788 -3384.12788
[7,] -4211.35576 -5432.62788
[8,] -3995.15576 -4211.35576
[9,] -4200.55576 -3995.15576
[10,] -3710.85576 -4200.55576
[11,] -3596.91987 -3710.85576
[12,] -3251.32788 -3596.91987
[13,] -3588.42788 -3251.32788
[14,] -3558.32788 -3588.42788
[15,] -3223.72788 -3558.32788
[16,] -3310.12788 -3223.72788
[17,] -3855.12788 -3310.12788
[18,] -5662.62788 -3855.12788
[19,] -4559.35576 -5662.62788
[20,] -4932.15576 -4559.35576
[21,] -4626.55576 -4932.15576
[22,] -4405.85576 -4626.55576
[23,] -4695.91987 -4405.85576
[24,] -3791.32788 -4695.91987
[25,] -3739.42788 -3791.32788
[26,] -3568.32788 -3739.42788
[27,] -3388.72788 -3568.32788
[28,] -3221.12788 -3388.72788
[29,] -3918.12788 -3221.12788
[30,] -5296.62788 -3918.12788
[31,] -4727.35576 -5296.62788
[32,] -2784.15576 -4727.35576
[33,] -2280.55576 -2784.15576
[34,] -2239.85576 -2280.55576
[35,] -2375.91987 -2239.85576
[36,] -1732.32788 -2375.91987
[37,] -1643.42788 -1732.32788
[38,] -1368.32788 -1643.42788
[39,] -1338.72788 -1368.32788
[40,] -1100.12788 -1338.72788
[41,] -1516.12788 -1100.12788
[42,] -734.62788 -1516.12788
[43,] -1505.35576 -734.62788
[44,] 189.84424 -1505.35576
[45,] 35.44424 189.84424
[46,] 132.14424 35.44424
[47,] 90.08013 132.14424
[48,] 685.67212 90.08013
[49,] 191.57212 685.67212
[50,] 214.67212 191.57212
[51,] 652.27212 214.67212
[52,] 742.87212 652.27212
[53,] 1359.87212 742.87212
[54,] 2919.37212 1359.87212
[55,] 2335.64424 2919.37212
[56,] 3492.84424 2335.64424
[57,] 2736.44424 3492.84424
[58,] 2507.14424 2736.44424
[59,] 2331.08013 2507.14424
[60,] 3000.67212 2331.08013
[61,] 3274.57212 3000.67212
[62,] 2919.67212 3274.57212
[63,] 2728.27212 2919.67212
[64,] 2594.87212 2728.27212
[65,] 2918.87212 2594.87212
[66,] 3903.37212 2918.87212
[67,] 4119.64424 3903.37212
[68,] 5471.84424 4119.64424
[69,] 4818.44424 5471.84424
[70,] 4484.14424 4818.44424
[71,] 4015.08013 4484.14424
[72,] 4121.67212 4015.08013
[73,] 3754.57212 4121.67212
[74,] 3856.67212 3754.57212
[75,] 3142.27212 3856.67212
[76,] 3176.87212 3142.27212
[77,] 3551.87212 3176.87212
[78,] 5372.37212 3551.87212
[79,] 5072.64424 5372.37212
[80,] 4111.84424 5072.64424
[81,] 4310.44424 4111.84424
[82,] 3637.14424 4310.44424
[83,] 3365.08013 3637.14424
[84,] 1934.67212 3365.08013
[85,] 2577.57212 1934.67212
[86,] 2120.67212 2577.57212
[87,] 2769.27212 2120.67212
[88,] 2919.87212 2769.27212
[89,] 3119.87212 2919.87212
[90,] 3745.37212 3119.87212
[91,] 2888.64424 3745.37212
[92,] 1755.84424 2888.64424
[93,] 1037.44424 1755.84424
[94,] 596.14424 1037.44424
[95,] 266.08013 596.14424
[96,] 375.67212 266.08013
[97,] 524.57212 375.67212
[98,] 182.67212 524.57212
[99,] 94.27212 182.67212
[100,] 113.87212 94.27212
[101,] 290.87212 113.87212
[102,] 909.37212 290.87212
[103,] 1698.92306 909.37212
[104,] -581.87694 1698.92306
[105,] -88.27694 -581.87694
[106,] -36.57694 -88.27694
[107,] 601.35895 -36.57694
[108,] 352.95094 601.35895
[109,] 379.85094 352.95094
[110,] 1277.95094 379.85094
[111,] 730.55094 1277.95094
[112,] 503.15094 730.55094
[113,] 1432.15094 503.15094
[114,] 276.65094 1432.15094
[115,] -1112.07694 276.65094
[116,] -2728.87694 -1112.07694
[117,] -1742.27694 -2728.87694
[118,] -963.57694 -1742.27694
> z <- as.data.frame(dum1)
> z
lag(myerror, k = 1) myerror
1 -1731.42788 -1696.32788
2 -2077.32788 -1731.42788
3 -2165.72788 -2077.32788
4 -2420.12788 -2165.72788
5 -3384.12788 -2420.12788
6 -5432.62788 -3384.12788
7 -4211.35576 -5432.62788
8 -3995.15576 -4211.35576
9 -4200.55576 -3995.15576
10 -3710.85576 -4200.55576
11 -3596.91987 -3710.85576
12 -3251.32788 -3596.91987
13 -3588.42788 -3251.32788
14 -3558.32788 -3588.42788
15 -3223.72788 -3558.32788
16 -3310.12788 -3223.72788
17 -3855.12788 -3310.12788
18 -5662.62788 -3855.12788
19 -4559.35576 -5662.62788
20 -4932.15576 -4559.35576
21 -4626.55576 -4932.15576
22 -4405.85576 -4626.55576
23 -4695.91987 -4405.85576
24 -3791.32788 -4695.91987
25 -3739.42788 -3791.32788
26 -3568.32788 -3739.42788
27 -3388.72788 -3568.32788
28 -3221.12788 -3388.72788
29 -3918.12788 -3221.12788
30 -5296.62788 -3918.12788
31 -4727.35576 -5296.62788
32 -2784.15576 -4727.35576
33 -2280.55576 -2784.15576
34 -2239.85576 -2280.55576
35 -2375.91987 -2239.85576
36 -1732.32788 -2375.91987
37 -1643.42788 -1732.32788
38 -1368.32788 -1643.42788
39 -1338.72788 -1368.32788
40 -1100.12788 -1338.72788
41 -1516.12788 -1100.12788
42 -734.62788 -1516.12788
43 -1505.35576 -734.62788
44 189.84424 -1505.35576
45 35.44424 189.84424
46 132.14424 35.44424
47 90.08013 132.14424
48 685.67212 90.08013
49 191.57212 685.67212
50 214.67212 191.57212
51 652.27212 214.67212
52 742.87212 652.27212
53 1359.87212 742.87212
54 2919.37212 1359.87212
55 2335.64424 2919.37212
56 3492.84424 2335.64424
57 2736.44424 3492.84424
58 2507.14424 2736.44424
59 2331.08013 2507.14424
60 3000.67212 2331.08013
61 3274.57212 3000.67212
62 2919.67212 3274.57212
63 2728.27212 2919.67212
64 2594.87212 2728.27212
65 2918.87212 2594.87212
66 3903.37212 2918.87212
67 4119.64424 3903.37212
68 5471.84424 4119.64424
69 4818.44424 5471.84424
70 4484.14424 4818.44424
71 4015.08013 4484.14424
72 4121.67212 4015.08013
73 3754.57212 4121.67212
74 3856.67212 3754.57212
75 3142.27212 3856.67212
76 3176.87212 3142.27212
77 3551.87212 3176.87212
78 5372.37212 3551.87212
79 5072.64424 5372.37212
80 4111.84424 5072.64424
81 4310.44424 4111.84424
82 3637.14424 4310.44424
83 3365.08013 3637.14424
84 1934.67212 3365.08013
85 2577.57212 1934.67212
86 2120.67212 2577.57212
87 2769.27212 2120.67212
88 2919.87212 2769.27212
89 3119.87212 2919.87212
90 3745.37212 3119.87212
91 2888.64424 3745.37212
92 1755.84424 2888.64424
93 1037.44424 1755.84424
94 596.14424 1037.44424
95 266.08013 596.14424
96 375.67212 266.08013
97 524.57212 375.67212
98 182.67212 524.57212
99 94.27212 182.67212
100 113.87212 94.27212
101 290.87212 113.87212
102 909.37212 290.87212
103 1698.92306 909.37212
104 -581.87694 1698.92306
105 -88.27694 -581.87694
106 -36.57694 -88.27694
107 601.35895 -36.57694
108 352.95094 601.35895
109 379.85094 352.95094
110 1277.95094 379.85094
111 730.55094 1277.95094
112 503.15094 730.55094
113 1432.15094 503.15094
114 276.65094 1432.15094
115 -1112.07694 276.65094
116 -2728.87694 -1112.07694
117 -1742.27694 -2728.87694
118 -963.57694 -1742.27694
> 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/freestat/rcomp/tmp/7uq9h1229608094.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> acf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/freestat/rcomp/tmp/8yz3v1229608094.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> pacf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Partial Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/freestat/rcomp/tmp/9o4871229608094.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> opar <- par(mfrow = c(2,2), oma = c(0, 0, 1.1, 0))
> plot(mylm, las = 1, sub='Residual Diagnostics')
> par(opar)
> dev.off()
null device
1
> if (n > n25) {
+ postscript(file="/var/www/html/freestat/rcomp/tmp/10wpj31229608094.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
+ plot(kp3:nmkm3,gqarr[,2], main='Goldfeld-Quandt test',ylab='2-sided p-value',xlab='breakpoint')
+ grid()
+ dev.off()
+ }
null device
1
>
> #Note: the /var/www/html/freestat/rcomp/createtable file can be downloaded at http://www.wessa.net/cretab
> load(file="/var/www/html/freestat/rcomp/createtable")
>
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a, 'Multiple Linear Regression - Estimated Regression Equation', 1, TRUE)
> a<-table.row.end(a)
> myeq <- colnames(x)[1]
> myeq <- paste(myeq, '[t] = ', sep='')
> for (i in 1:k){
+ if (mysum$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/freestat/rcomp/tmp/115rfm1229608094.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/freestat/rcomp/tmp/12oy831229608094.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/freestat/rcomp/tmp/13409u1229608094.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/freestat/rcomp/tmp/1482jo1229608094.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/freestat/rcomp/tmp/1589qv1229608094.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/freestat/rcomp/tmp/16nnm11229608094.tab")
+ }
>
> system("convert tmp/1nvmc1229608093.ps tmp/1nvmc1229608093.png")
> system("convert tmp/2kl1e1229608093.ps tmp/2kl1e1229608093.png")
> system("convert tmp/3hcrf1229608093.ps tmp/3hcrf1229608093.png")
> system("convert tmp/40feb1229608093.ps tmp/40feb1229608093.png")
> system("convert tmp/5bx0t1229608094.ps tmp/5bx0t1229608094.png")
> system("convert tmp/69qf41229608094.ps tmp/69qf41229608094.png")
> system("convert tmp/7uq9h1229608094.ps tmp/7uq9h1229608094.png")
> system("convert tmp/8yz3v1229608094.ps tmp/8yz3v1229608094.png")
> system("convert tmp/9o4871229608094.ps tmp/9o4871229608094.png")
> system("convert tmp/10wpj31229608094.ps tmp/10wpj31229608094.png")
>
>
> proc.time()
user system elapsed
4.624 2.557 5.065