R version 2.9.0 (2009-04-17)
Copyright (C) 2009 The R Foundation for Statistical Computing
ISBN 3-900051-07-0
R is free software and comes with ABSOLUTELY NO WARRANTY.
You are welcome to redistribute it under certain conditions.
Type 'license()' or 'licence()' for distribution details.
R is a collaborative project with many contributors.
Type 'contributors()' for more information and
'citation()' on how to cite R or R packages in publications.
Type 'demo()' for some demos, 'help()' for on-line help, or
'help.start()' for an HTML browser interface to help.
Type 'q()' to quit R.
> x <- array(list(6.70
+ ,2.04
+ ,6.40
+ ,2.16
+ ,6.30
+ ,2.75
+ ,6.80
+ ,2.79
+ ,7.30
+ ,2.88
+ ,7.10
+ ,3.36
+ ,7.00
+ ,2.97
+ ,6.80
+ ,3.10
+ ,6.60
+ ,2.49
+ ,6.30
+ ,2.20
+ ,6.10
+ ,2.25
+ ,6.10
+ ,2.09
+ ,6.30
+ ,2.79
+ ,6.30
+ ,3.14
+ ,6.00
+ ,2.93
+ ,6.20
+ ,2.65
+ ,6.40
+ ,2.67
+ ,6.80
+ ,2.26
+ ,7.50
+ ,2.35
+ ,7.50
+ ,2.13
+ ,7.60
+ ,2.18
+ ,7.60
+ ,2.90
+ ,7.40
+ ,2.63
+ ,7.30
+ ,2.67
+ ,7.10
+ ,1.81
+ ,6.90
+ ,1.33
+ ,6.80
+ ,0.88
+ ,7.50
+ ,1.28
+ ,7.60
+ ,1.26
+ ,7.80
+ ,1.26
+ ,8.00
+ ,1.29
+ ,8.10
+ ,1.10
+ ,8.20
+ ,1.37
+ ,8.30
+ ,1.21
+ ,8.20
+ ,1.74
+ ,8.00
+ ,1.76
+ ,7.90
+ ,1.48
+ ,7.60
+ ,1.04
+ ,7.60
+ ,1.62
+ ,8.30
+ ,1.49
+ ,8.40
+ ,1.79
+ ,8.40
+ ,1.80
+ ,8.40
+ ,1.58
+ ,8.40
+ ,1.86
+ ,8.60
+ ,1.74
+ ,8.90
+ ,1.59
+ ,8.80
+ ,1.26
+ ,8.30
+ ,1.13
+ ,7.50
+ ,1.92
+ ,7.20
+ ,2.61
+ ,7.40
+ ,2.26
+ ,8.80
+ ,2.41
+ ,9.30
+ ,2.26
+ ,9.30
+ ,2.03
+ ,8.70
+ ,2.86
+ ,8.20
+ ,2.55
+ ,8.30
+ ,2.27
+ ,8.50
+ ,2.26
+ ,8.60
+ ,2.57
+ ,8.50
+ ,3.07
+ ,8.20
+ ,2.76
+ ,8.10
+ ,2.51
+ ,7.90
+ ,2.87
+ ,8.60
+ ,3.14
+ ,8.70
+ ,3.11
+ ,8.70
+ ,3.16
+ ,8.50
+ ,2.47
+ ,8.40
+ ,2.57
+ ,8.50
+ ,2.89
+ ,8.70
+ ,2.63
+ ,8.70
+ ,2.38
+ ,8.60
+ ,1.69
+ ,8.50
+ ,1.96
+ ,8.30
+ ,2.19
+ ,8.00
+ ,1.87
+ ,8.20
+ ,1.60
+ ,8.10
+ ,1.63
+ ,8.10
+ ,1.22
+ ,8.00
+ ,1.21
+ ,7.90
+ ,1.49
+ ,7.90
+ ,1.64
+ ,8.00
+ ,1.66
+ ,8.00
+ ,1.77
+ ,7.90
+ ,1.82
+ ,8.00
+ ,1.78
+ ,7.70
+ ,1.28
+ ,7.20
+ ,1.29
+ ,7.50
+ ,1.37
+ ,7.30
+ ,1.12
+ ,7.00
+ ,1.51
+ ,7.00
+ ,2.24
+ ,7.00
+ ,2.94
+ ,7.20
+ ,3.09
+ ,7.30
+ ,3.46
+ ,7.10
+ ,3.64
+ ,6.80
+ ,4.39
+ ,6.40
+ ,4.15
+ ,6.10
+ ,5.21
+ ,6.50
+ ,5.80
+ ,7.70
+ ,5.91
+ ,7.90
+ ,5.39
+ ,7.50
+ ,5.46
+ ,6.90
+ ,4.72
+ ,6.60
+ ,3.14
+ ,6.90
+ ,2.63
+ ,7.70
+ ,2.32
+ ,8.00
+ ,1.93
+ ,8.00
+ ,0.62)
+ ,dim=c(2
+ ,108)
+ ,dimnames=list(c('Y'
+ ,'X')
+ ,1:108))
> y <- array(NA,dim=c(2,108),dimnames=list(c('Y','X'),1:108))
> for (i in 1:dim(x)[1])
+ {
+ for (j in 1:dim(x)[2])
+ {
+ y[i,j] <- as.numeric(x[i,j])
+ }
+ }
> par3 = 'No Linear Trend'
> par2 = 'Include Monthly Dummies'
> par1 = '1'
> #'GNU S' R Code compiled by R2WASP v. 1.0.44 ()
> #Author: Prof. Dr. P. Wessa
> #To cite this work: AUTHOR(S), (YEAR), YOUR SOFTWARE TITLE (vNUMBER) in Free Statistics Software (v$_version), Office for Research Development and Education, URL http://www.wessa.net/rwasp_YOURPAGE.wasp/
> #Source of accompanying publication: Office for Research, Development, and Education
> #Technical description: Write here your technical program description (don't use hard returns!)
> library(lattice)
> library(lmtest)
Loading required package: zoo
Attaching package: 'zoo'
The following object(s) are masked from package:base :
as.Date.numeric
> n25 <- 25 #minimum number of obs. for Goldfeld-Quandt test
> par1 <- as.numeric(par1)
> x <- t(y)
> k <- length(x[1,])
> n <- length(x[,1])
> x1 <- cbind(x[,par1], x[,1:k!=par1])
> mycolnames <- c(colnames(x)[par1], colnames(x)[1:k!=par1])
> colnames(x1) <- mycolnames #colnames(x)[par1]
> x <- x1
> if (par3 == 'First Differences'){
+ x2 <- array(0, dim=c(n-1,k), dimnames=list(1:(n-1), paste('(1-B)',colnames(x),sep='')))
+ for (i in 1:n-1) {
+ for (j in 1:k) {
+ x2[i,j] <- x[i+1,j] - x[i,j]
+ }
+ }
+ x <- x2
+ }
> if (par2 == 'Include Monthly Dummies'){
+ x2 <- array(0, dim=c(n,11), dimnames=list(1:n, paste('M', seq(1:11), sep ='')))
+ for (i in 1:11){
+ x2[seq(i,n,12),i] <- 1
+ }
+ x <- cbind(x, x2)
+ }
> if (par2 == 'Include Quarterly Dummies'){
+ x2 <- array(0, dim=c(n,3), dimnames=list(1:n, paste('Q', seq(1:3), sep ='')))
+ for (i in 1:3){
+ x2[seq(i,n,4),i] <- 1
+ }
+ x <- cbind(x, x2)
+ }
> k <- length(x[1,])
> if (par3 == 'Linear Trend'){
+ x <- cbind(x, c(1:n))
+ colnames(x)[k+1] <- 't'
+ }
> x
Y X M1 M2 M3 M4 M5 M6 M7 M8 M9 M10 M11
1 6.7 2.04 1 0 0 0 0 0 0 0 0 0 0
2 6.4 2.16 0 1 0 0 0 0 0 0 0 0 0
3 6.3 2.75 0 0 1 0 0 0 0 0 0 0 0
4 6.8 2.79 0 0 0 1 0 0 0 0 0 0 0
5 7.3 2.88 0 0 0 0 1 0 0 0 0 0 0
6 7.1 3.36 0 0 0 0 0 1 0 0 0 0 0
7 7.0 2.97 0 0 0 0 0 0 1 0 0 0 0
8 6.8 3.10 0 0 0 0 0 0 0 1 0 0 0
9 6.6 2.49 0 0 0 0 0 0 0 0 1 0 0
10 6.3 2.20 0 0 0 0 0 0 0 0 0 1 0
11 6.1 2.25 0 0 0 0 0 0 0 0 0 0 1
12 6.1 2.09 0 0 0 0 0 0 0 0 0 0 0
13 6.3 2.79 1 0 0 0 0 0 0 0 0 0 0
14 6.3 3.14 0 1 0 0 0 0 0 0 0 0 0
15 6.0 2.93 0 0 1 0 0 0 0 0 0 0 0
16 6.2 2.65 0 0 0 1 0 0 0 0 0 0 0
17 6.4 2.67 0 0 0 0 1 0 0 0 0 0 0
18 6.8 2.26 0 0 0 0 0 1 0 0 0 0 0
19 7.5 2.35 0 0 0 0 0 0 1 0 0 0 0
20 7.5 2.13 0 0 0 0 0 0 0 1 0 0 0
21 7.6 2.18 0 0 0 0 0 0 0 0 1 0 0
22 7.6 2.90 0 0 0 0 0 0 0 0 0 1 0
23 7.4 2.63 0 0 0 0 0 0 0 0 0 0 1
24 7.3 2.67 0 0 0 0 0 0 0 0 0 0 0
25 7.1 1.81 1 0 0 0 0 0 0 0 0 0 0
26 6.9 1.33 0 1 0 0 0 0 0 0 0 0 0
27 6.8 0.88 0 0 1 0 0 0 0 0 0 0 0
28 7.5 1.28 0 0 0 1 0 0 0 0 0 0 0
29 7.6 1.26 0 0 0 0 1 0 0 0 0 0 0
30 7.8 1.26 0 0 0 0 0 1 0 0 0 0 0
31 8.0 1.29 0 0 0 0 0 0 1 0 0 0 0
32 8.1 1.10 0 0 0 0 0 0 0 1 0 0 0
33 8.2 1.37 0 0 0 0 0 0 0 0 1 0 0
34 8.3 1.21 0 0 0 0 0 0 0 0 0 1 0
35 8.2 1.74 0 0 0 0 0 0 0 0 0 0 1
36 8.0 1.76 0 0 0 0 0 0 0 0 0 0 0
37 7.9 1.48 1 0 0 0 0 0 0 0 0 0 0
38 7.6 1.04 0 1 0 0 0 0 0 0 0 0 0
39 7.6 1.62 0 0 1 0 0 0 0 0 0 0 0
40 8.3 1.49 0 0 0 1 0 0 0 0 0 0 0
41 8.4 1.79 0 0 0 0 1 0 0 0 0 0 0
42 8.4 1.80 0 0 0 0 0 1 0 0 0 0 0
43 8.4 1.58 0 0 0 0 0 0 1 0 0 0 0
44 8.4 1.86 0 0 0 0 0 0 0 1 0 0 0
45 8.6 1.74 0 0 0 0 0 0 0 0 1 0 0
46 8.9 1.59 0 0 0 0 0 0 0 0 0 1 0
47 8.8 1.26 0 0 0 0 0 0 0 0 0 0 1
48 8.3 1.13 0 0 0 0 0 0 0 0 0 0 0
49 7.5 1.92 1 0 0 0 0 0 0 0 0 0 0
50 7.2 2.61 0 1 0 0 0 0 0 0 0 0 0
51 7.4 2.26 0 0 1 0 0 0 0 0 0 0 0
52 8.8 2.41 0 0 0 1 0 0 0 0 0 0 0
53 9.3 2.26 0 0 0 0 1 0 0 0 0 0 0
54 9.3 2.03 0 0 0 0 0 1 0 0 0 0 0
55 8.7 2.86 0 0 0 0 0 0 1 0 0 0 0
56 8.2 2.55 0 0 0 0 0 0 0 1 0 0 0
57 8.3 2.27 0 0 0 0 0 0 0 0 1 0 0
58 8.5 2.26 0 0 0 0 0 0 0 0 0 1 0
59 8.6 2.57 0 0 0 0 0 0 0 0 0 0 1
60 8.5 3.07 0 0 0 0 0 0 0 0 0 0 0
61 8.2 2.76 1 0 0 0 0 0 0 0 0 0 0
62 8.1 2.51 0 1 0 0 0 0 0 0 0 0 0
63 7.9 2.87 0 0 1 0 0 0 0 0 0 0 0
64 8.6 3.14 0 0 0 1 0 0 0 0 0 0 0
65 8.7 3.11 0 0 0 0 1 0 0 0 0 0 0
66 8.7 3.16 0 0 0 0 0 1 0 0 0 0 0
67 8.5 2.47 0 0 0 0 0 0 1 0 0 0 0
68 8.4 2.57 0 0 0 0 0 0 0 1 0 0 0
69 8.5 2.89 0 0 0 0 0 0 0 0 1 0 0
70 8.7 2.63 0 0 0 0 0 0 0 0 0 1 0
71 8.7 2.38 0 0 0 0 0 0 0 0 0 0 1
72 8.6 1.69 0 0 0 0 0 0 0 0 0 0 0
73 8.5 1.96 1 0 0 0 0 0 0 0 0 0 0
74 8.3 2.19 0 1 0 0 0 0 0 0 0 0 0
75 8.0 1.87 0 0 1 0 0 0 0 0 0 0 0
76 8.2 1.60 0 0 0 1 0 0 0 0 0 0 0
77 8.1 1.63 0 0 0 0 1 0 0 0 0 0 0
78 8.1 1.22 0 0 0 0 0 1 0 0 0 0 0
79 8.0 1.21 0 0 0 0 0 0 1 0 0 0 0
80 7.9 1.49 0 0 0 0 0 0 0 1 0 0 0
81 7.9 1.64 0 0 0 0 0 0 0 0 1 0 0
82 8.0 1.66 0 0 0 0 0 0 0 0 0 1 0
83 8.0 1.77 0 0 0 0 0 0 0 0 0 0 1
84 7.9 1.82 0 0 0 0 0 0 0 0 0 0 0
85 8.0 1.78 1 0 0 0 0 0 0 0 0 0 0
86 7.7 1.28 0 1 0 0 0 0 0 0 0 0 0
87 7.2 1.29 0 0 1 0 0 0 0 0 0 0 0
88 7.5 1.37 0 0 0 1 0 0 0 0 0 0 0
89 7.3 1.12 0 0 0 0 1 0 0 0 0 0 0
90 7.0 1.51 0 0 0 0 0 1 0 0 0 0 0
91 7.0 2.24 0 0 0 0 0 0 1 0 0 0 0
92 7.0 2.94 0 0 0 0 0 0 0 1 0 0 0
93 7.2 3.09 0 0 0 0 0 0 0 0 1 0 0
94 7.3 3.46 0 0 0 0 0 0 0 0 0 1 0
95 7.1 3.64 0 0 0 0 0 0 0 0 0 0 1
96 6.8 4.39 0 0 0 0 0 0 0 0 0 0 0
97 6.4 4.15 1 0 0 0 0 0 0 0 0 0 0
98 6.1 5.21 0 1 0 0 0 0 0 0 0 0 0
99 6.5 5.80 0 0 1 0 0 0 0 0 0 0 0
100 7.7 5.91 0 0 0 1 0 0 0 0 0 0 0
101 7.9 5.39 0 0 0 0 1 0 0 0 0 0 0
102 7.5 5.46 0 0 0 0 0 1 0 0 0 0 0
103 6.9 4.72 0 0 0 0 0 0 1 0 0 0 0
104 6.6 3.14 0 0 0 0 0 0 0 1 0 0 0
105 6.9 2.63 0 0 0 0 0 0 0 0 1 0 0
106 7.7 2.32 0 0 0 0 0 0 0 0 0 1 0
107 8.0 1.93 0 0 0 0 0 0 0 0 0 0 1
108 8.0 0.62 0 0 0 0 0 0 0 0 0 0 0
> k <- length(x[1,])
> df <- as.data.frame(x)
> (mylm <- lm(df))
Call:
lm(formula = df)
Coefficients:
(Intercept) X M1 M2 M3 M4
8.20807 -0.22727 -0.28561 -0.48813 -0.56793 0.09697
M5 M6 M7 M8 M9 M10
0.23914 0.20454 0.11742 -0.02525 0.06010 0.22500
M11
0.17904
> (mysum <- summary(mylm))
Call:
lm(formula = df)
Residuals:
Min 1Q Median 3Q Max
-1.77576 -0.51427 0.01919 0.60751 1.36641
Coefficients:
Estimate Std. Error t value Pr(>|t|)
(Intercept) 8.20807 0.29607 27.723 < 2e-16 ***
X -0.22727 0.07133 -3.186 0.00195 **
M1 -0.28561 0.35908 -0.795 0.42837
M2 -0.48813 0.35933 -1.358 0.17754
M3 -0.56793 0.35970 -1.579 0.11768
M4 0.09697 0.35991 0.269 0.78819
M5 0.23914 0.35962 0.665 0.50767
M6 0.20454 0.35959 0.569 0.57082
M7 0.11742 0.35942 0.327 0.74461
M8 -0.02525 0.35913 -0.070 0.94409
M9 0.06010 0.35900 0.167 0.86740
M10 0.22500 0.35898 0.627 0.53231
M11 0.17904 0.35897 0.499 0.61910
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
Residual standard error: 0.7613 on 95 degrees of freedom
Multiple R-squared: 0.2002, Adjusted R-squared: 0.09917
F-statistic: 1.982 on 12 and 95 DF, p-value: 0.03424
> 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,] 0.11209621 0.22419242 0.887903789
[2,] 0.22772664 0.45545327 0.772273364
[3,] 0.15337763 0.30675526 0.846622368
[4,] 0.11457143 0.22914286 0.885428572
[5,] 0.09412652 0.18825303 0.905873483
[6,] 0.13057627 0.26115254 0.869423729
[7,] 0.29608759 0.59217518 0.703912408
[8,] 0.41815681 0.83631362 0.581843190
[9,] 0.47458635 0.94917269 0.525413655
[10,] 0.46110817 0.92221633 0.538891834
[11,] 0.43202355 0.86404710 0.567976452
[12,] 0.39681989 0.79363978 0.603180110
[13,] 0.40443962 0.80887924 0.595560381
[14,] 0.36871798 0.73743595 0.631282023
[15,] 0.32367372 0.64734743 0.676326284
[16,] 0.26528788 0.53057576 0.734712119
[17,] 0.21971056 0.43942113 0.780289437
[18,] 0.21068958 0.42137917 0.789310415
[19,] 0.20725561 0.41451123 0.792744385
[20,] 0.25756831 0.51513662 0.742431691
[21,] 0.28059697 0.56119394 0.719403028
[22,] 0.28080531 0.56161061 0.719194694
[23,] 0.24112433 0.48224865 0.758875675
[24,] 0.25275943 0.50551886 0.747240569
[25,] 0.27857193 0.55714387 0.721428066
[26,] 0.29731230 0.59462460 0.702687699
[27,] 0.29239514 0.58479028 0.707604862
[28,] 0.25673106 0.51346212 0.743268940
[29,] 0.25510807 0.51021613 0.744891933
[30,] 0.27461271 0.54922543 0.725387286
[31,] 0.31849953 0.63699907 0.681500467
[32,] 0.31762369 0.63524739 0.682376305
[33,] 0.27127111 0.54254222 0.728728891
[34,] 0.23696202 0.47392404 0.763037981
[35,] 0.23900753 0.47801506 0.760992470
[36,] 0.23163272 0.46326544 0.768367282
[37,] 0.37808862 0.75617724 0.621911381
[38,] 0.57938067 0.84123866 0.420619331
[39,] 0.72105860 0.55788280 0.278941398
[40,] 0.80236117 0.39527766 0.197638832
[41,] 0.79795373 0.40409253 0.202046267
[42,] 0.78396758 0.43206484 0.216032419
[43,] 0.77154097 0.45691807 0.228459035
[44,] 0.79262341 0.41475317 0.207376586
[45,] 0.84594816 0.30810368 0.154051842
[46,] 0.86130015 0.27739971 0.138699854
[47,] 0.87323900 0.25352199 0.126760997
[48,] 0.88183265 0.23633471 0.118167354
[49,] 0.89826366 0.20347267 0.101736336
[50,] 0.91299782 0.17400437 0.087002183
[51,] 0.93634369 0.12731262 0.063656312
[52,] 0.94552213 0.10895575 0.054477873
[53,] 0.95930493 0.08139013 0.040695067
[54,] 0.97302125 0.05395749 0.026978746
[55,] 0.97927460 0.04145080 0.020725398
[56,] 0.98320625 0.03358751 0.016793754
[57,] 0.98509638 0.02980724 0.014903618
[58,] 0.98983504 0.02032991 0.010164956
[59,] 0.99459475 0.01081049 0.005405246
[60,] 0.99492774 0.01014451 0.005072256
[61,] 0.99142206 0.01715588 0.008577941
[62,] 0.98560630 0.02878740 0.014393699
[63,] 0.97900843 0.04198314 0.020991569
[64,] 0.97465388 0.05069223 0.025346116
[65,] 0.97526780 0.04946439 0.024732197
[66,] 0.97045836 0.05908327 0.029541636
[67,] 0.95443877 0.09112246 0.045561231
[68,] 0.93055976 0.13888048 0.069440241
[69,] 0.90080870 0.19838261 0.099191304
[70,] 0.93734185 0.12531629 0.062658147
[71,] 0.96907146 0.06185708 0.030928538
[72,] 0.95462272 0.09075456 0.045377282
[73,] 0.92154502 0.15690995 0.078454977
[74,] 0.92924992 0.14150016 0.070750078
[75,] 0.98406342 0.03187316 0.015936578
[76,] 0.98745286 0.02509428 0.012547140
[77,] 0.96946847 0.06106305 0.030531525
> postscript(file="/var/www/html/rcomp/tmp/1bqp91258483978.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> plot(x[,1], type='l', main='Actuals and Interpolation', ylab='value of Actuals and Interpolation (dots)', xlab='time or index')
> points(x[,1]-mysum$resid)
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/2bwbu1258483978.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> plot(mysum$resid, type='b', pch=19, main='Residuals', ylab='value of Residuals', xlab='time or index')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/3dtqe1258483978.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> hist(mysum$resid, main='Residual Histogram', xlab='values of Residuals')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/429fx1258483978.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> densityplot(~mysum$resid,col='black',main='Residual Density Plot', xlab='values of Residuals')
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/5v9os1258483978.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 = 108
Frequency = 1
1 2 3 4 5 6
-0.758837512 -0.829039644 -0.715152444 -0.870960521 -0.492678194 -0.548992962
7 8 9 10 11 12
-0.650506937 -0.678285457 -1.102273517 -1.633080647 -1.775757606 -1.633080647
13 14 15 16 17 18
-0.988385493 -0.706315673 -0.974243959 -1.502778231 -1.440404759 -1.098989255
19 20 21 22 23 24
-0.291413939 -0.198736734 -0.172727018 -0.173992097 -0.389395250 -0.301264420
25 26 27 28 29 30
-0.411109464 -0.517673211 -0.640146143 -0.514137251 -0.560854554 -0.326258613
31 32 33 34 35 36
-0.032319458 0.167175828 0.243184802 0.141922689 0.208335022 0.191920465
37 38 39 40 41 42
0.313891648 0.116418675 0.328033182 0.333589314 0.359598206 0.396466840
43 44 45 46 47 48
0.433588655 0.639900540 0.727274464 0.828285045 0.699245730 0.348740769
49 50 51 52 53 54
0.013890166 0.073231567 0.273485571 1.042677123 1.366414804 1.348738793
55 56 57 58 59 60
1.024493433 0.596716397 0.547727224 0.580555514 0.796968589 0.989643323
61 62 63 64 65 66
0.904796426 0.950504631 0.912119879 1.008583754 0.959593758 1.005553167
67 68 69 70 71 72
0.735858384 0.801261784 0.888634226 0.864645177 0.853787411 0.776011610
73 74 75 76 77 78
1.022980940 1.077778437 0.784850522 0.258588944 0.023235109 -0.035349387
79 80 81 82 83 84
-0.050501007 0.055810878 0.004547529 -0.055806100 0.015153103 0.105556626
85 86 87 88 89 90
0.482072455 0.270963321 -0.146965706 -0.493683009 -0.892672264 -1.069441273
91 92 93 94 95 96
-0.816413569 -0.514648554 -0.365911903 -0.346721256 -0.459853198 -0.410361124
97 98 99 100 101 102
-0.579299167 -0.435868103 0.178019097 0.738119875 0.677767894 0.328272690
103 104 105 106 107 108
-0.352785561 -0.869194682 -0.770455807 -0.205808324 0.051516200 -0.067166603
> postscript(file="/var/www/html/rcomp/tmp/673hn1258483978.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 = 108
Frequency = 1
lag(myerror, k = 1) myerror
0 -0.758837512 NA
1 -0.829039644 -0.758837512
2 -0.715152444 -0.829039644
3 -0.870960521 -0.715152444
4 -0.492678194 -0.870960521
5 -0.548992962 -0.492678194
6 -0.650506937 -0.548992962
7 -0.678285457 -0.650506937
8 -1.102273517 -0.678285457
9 -1.633080647 -1.102273517
10 -1.775757606 -1.633080647
11 -1.633080647 -1.775757606
12 -0.988385493 -1.633080647
13 -0.706315673 -0.988385493
14 -0.974243959 -0.706315673
15 -1.502778231 -0.974243959
16 -1.440404759 -1.502778231
17 -1.098989255 -1.440404759
18 -0.291413939 -1.098989255
19 -0.198736734 -0.291413939
20 -0.172727018 -0.198736734
21 -0.173992097 -0.172727018
22 -0.389395250 -0.173992097
23 -0.301264420 -0.389395250
24 -0.411109464 -0.301264420
25 -0.517673211 -0.411109464
26 -0.640146143 -0.517673211
27 -0.514137251 -0.640146143
28 -0.560854554 -0.514137251
29 -0.326258613 -0.560854554
30 -0.032319458 -0.326258613
31 0.167175828 -0.032319458
32 0.243184802 0.167175828
33 0.141922689 0.243184802
34 0.208335022 0.141922689
35 0.191920465 0.208335022
36 0.313891648 0.191920465
37 0.116418675 0.313891648
38 0.328033182 0.116418675
39 0.333589314 0.328033182
40 0.359598206 0.333589314
41 0.396466840 0.359598206
42 0.433588655 0.396466840
43 0.639900540 0.433588655
44 0.727274464 0.639900540
45 0.828285045 0.727274464
46 0.699245730 0.828285045
47 0.348740769 0.699245730
48 0.013890166 0.348740769
49 0.073231567 0.013890166
50 0.273485571 0.073231567
51 1.042677123 0.273485571
52 1.366414804 1.042677123
53 1.348738793 1.366414804
54 1.024493433 1.348738793
55 0.596716397 1.024493433
56 0.547727224 0.596716397
57 0.580555514 0.547727224
58 0.796968589 0.580555514
59 0.989643323 0.796968589
60 0.904796426 0.989643323
61 0.950504631 0.904796426
62 0.912119879 0.950504631
63 1.008583754 0.912119879
64 0.959593758 1.008583754
65 1.005553167 0.959593758
66 0.735858384 1.005553167
67 0.801261784 0.735858384
68 0.888634226 0.801261784
69 0.864645177 0.888634226
70 0.853787411 0.864645177
71 0.776011610 0.853787411
72 1.022980940 0.776011610
73 1.077778437 1.022980940
74 0.784850522 1.077778437
75 0.258588944 0.784850522
76 0.023235109 0.258588944
77 -0.035349387 0.023235109
78 -0.050501007 -0.035349387
79 0.055810878 -0.050501007
80 0.004547529 0.055810878
81 -0.055806100 0.004547529
82 0.015153103 -0.055806100
83 0.105556626 0.015153103
84 0.482072455 0.105556626
85 0.270963321 0.482072455
86 -0.146965706 0.270963321
87 -0.493683009 -0.146965706
88 -0.892672264 -0.493683009
89 -1.069441273 -0.892672264
90 -0.816413569 -1.069441273
91 -0.514648554 -0.816413569
92 -0.365911903 -0.514648554
93 -0.346721256 -0.365911903
94 -0.459853198 -0.346721256
95 -0.410361124 -0.459853198
96 -0.579299167 -0.410361124
97 -0.435868103 -0.579299167
98 0.178019097 -0.435868103
99 0.738119875 0.178019097
100 0.677767894 0.738119875
101 0.328272690 0.677767894
102 -0.352785561 0.328272690
103 -0.869194682 -0.352785561
104 -0.770455807 -0.869194682
105 -0.205808324 -0.770455807
106 0.051516200 -0.205808324
107 -0.067166603 0.051516200
108 NA -0.067166603
> dum1 <- dum[2:length(myerror),]
> dum1
lag(myerror, k = 1) myerror
[1,] -0.829039644 -0.758837512
[2,] -0.715152444 -0.829039644
[3,] -0.870960521 -0.715152444
[4,] -0.492678194 -0.870960521
[5,] -0.548992962 -0.492678194
[6,] -0.650506937 -0.548992962
[7,] -0.678285457 -0.650506937
[8,] -1.102273517 -0.678285457
[9,] -1.633080647 -1.102273517
[10,] -1.775757606 -1.633080647
[11,] -1.633080647 -1.775757606
[12,] -0.988385493 -1.633080647
[13,] -0.706315673 -0.988385493
[14,] -0.974243959 -0.706315673
[15,] -1.502778231 -0.974243959
[16,] -1.440404759 -1.502778231
[17,] -1.098989255 -1.440404759
[18,] -0.291413939 -1.098989255
[19,] -0.198736734 -0.291413939
[20,] -0.172727018 -0.198736734
[21,] -0.173992097 -0.172727018
[22,] -0.389395250 -0.173992097
[23,] -0.301264420 -0.389395250
[24,] -0.411109464 -0.301264420
[25,] -0.517673211 -0.411109464
[26,] -0.640146143 -0.517673211
[27,] -0.514137251 -0.640146143
[28,] -0.560854554 -0.514137251
[29,] -0.326258613 -0.560854554
[30,] -0.032319458 -0.326258613
[31,] 0.167175828 -0.032319458
[32,] 0.243184802 0.167175828
[33,] 0.141922689 0.243184802
[34,] 0.208335022 0.141922689
[35,] 0.191920465 0.208335022
[36,] 0.313891648 0.191920465
[37,] 0.116418675 0.313891648
[38,] 0.328033182 0.116418675
[39,] 0.333589314 0.328033182
[40,] 0.359598206 0.333589314
[41,] 0.396466840 0.359598206
[42,] 0.433588655 0.396466840
[43,] 0.639900540 0.433588655
[44,] 0.727274464 0.639900540
[45,] 0.828285045 0.727274464
[46,] 0.699245730 0.828285045
[47,] 0.348740769 0.699245730
[48,] 0.013890166 0.348740769
[49,] 0.073231567 0.013890166
[50,] 0.273485571 0.073231567
[51,] 1.042677123 0.273485571
[52,] 1.366414804 1.042677123
[53,] 1.348738793 1.366414804
[54,] 1.024493433 1.348738793
[55,] 0.596716397 1.024493433
[56,] 0.547727224 0.596716397
[57,] 0.580555514 0.547727224
[58,] 0.796968589 0.580555514
[59,] 0.989643323 0.796968589
[60,] 0.904796426 0.989643323
[61,] 0.950504631 0.904796426
[62,] 0.912119879 0.950504631
[63,] 1.008583754 0.912119879
[64,] 0.959593758 1.008583754
[65,] 1.005553167 0.959593758
[66,] 0.735858384 1.005553167
[67,] 0.801261784 0.735858384
[68,] 0.888634226 0.801261784
[69,] 0.864645177 0.888634226
[70,] 0.853787411 0.864645177
[71,] 0.776011610 0.853787411
[72,] 1.022980940 0.776011610
[73,] 1.077778437 1.022980940
[74,] 0.784850522 1.077778437
[75,] 0.258588944 0.784850522
[76,] 0.023235109 0.258588944
[77,] -0.035349387 0.023235109
[78,] -0.050501007 -0.035349387
[79,] 0.055810878 -0.050501007
[80,] 0.004547529 0.055810878
[81,] -0.055806100 0.004547529
[82,] 0.015153103 -0.055806100
[83,] 0.105556626 0.015153103
[84,] 0.482072455 0.105556626
[85,] 0.270963321 0.482072455
[86,] -0.146965706 0.270963321
[87,] -0.493683009 -0.146965706
[88,] -0.892672264 -0.493683009
[89,] -1.069441273 -0.892672264
[90,] -0.816413569 -1.069441273
[91,] -0.514648554 -0.816413569
[92,] -0.365911903 -0.514648554
[93,] -0.346721256 -0.365911903
[94,] -0.459853198 -0.346721256
[95,] -0.410361124 -0.459853198
[96,] -0.579299167 -0.410361124
[97,] -0.435868103 -0.579299167
[98,] 0.178019097 -0.435868103
[99,] 0.738119875 0.178019097
[100,] 0.677767894 0.738119875
[101,] 0.328272690 0.677767894
[102,] -0.352785561 0.328272690
[103,] -0.869194682 -0.352785561
[104,] -0.770455807 -0.869194682
[105,] -0.205808324 -0.770455807
[106,] 0.051516200 -0.205808324
[107,] -0.067166603 0.051516200
> z <- as.data.frame(dum1)
> z
lag(myerror, k = 1) myerror
1 -0.829039644 -0.758837512
2 -0.715152444 -0.829039644
3 -0.870960521 -0.715152444
4 -0.492678194 -0.870960521
5 -0.548992962 -0.492678194
6 -0.650506937 -0.548992962
7 -0.678285457 -0.650506937
8 -1.102273517 -0.678285457
9 -1.633080647 -1.102273517
10 -1.775757606 -1.633080647
11 -1.633080647 -1.775757606
12 -0.988385493 -1.633080647
13 -0.706315673 -0.988385493
14 -0.974243959 -0.706315673
15 -1.502778231 -0.974243959
16 -1.440404759 -1.502778231
17 -1.098989255 -1.440404759
18 -0.291413939 -1.098989255
19 -0.198736734 -0.291413939
20 -0.172727018 -0.198736734
21 -0.173992097 -0.172727018
22 -0.389395250 -0.173992097
23 -0.301264420 -0.389395250
24 -0.411109464 -0.301264420
25 -0.517673211 -0.411109464
26 -0.640146143 -0.517673211
27 -0.514137251 -0.640146143
28 -0.560854554 -0.514137251
29 -0.326258613 -0.560854554
30 -0.032319458 -0.326258613
31 0.167175828 -0.032319458
32 0.243184802 0.167175828
33 0.141922689 0.243184802
34 0.208335022 0.141922689
35 0.191920465 0.208335022
36 0.313891648 0.191920465
37 0.116418675 0.313891648
38 0.328033182 0.116418675
39 0.333589314 0.328033182
40 0.359598206 0.333589314
41 0.396466840 0.359598206
42 0.433588655 0.396466840
43 0.639900540 0.433588655
44 0.727274464 0.639900540
45 0.828285045 0.727274464
46 0.699245730 0.828285045
47 0.348740769 0.699245730
48 0.013890166 0.348740769
49 0.073231567 0.013890166
50 0.273485571 0.073231567
51 1.042677123 0.273485571
52 1.366414804 1.042677123
53 1.348738793 1.366414804
54 1.024493433 1.348738793
55 0.596716397 1.024493433
56 0.547727224 0.596716397
57 0.580555514 0.547727224
58 0.796968589 0.580555514
59 0.989643323 0.796968589
60 0.904796426 0.989643323
61 0.950504631 0.904796426
62 0.912119879 0.950504631
63 1.008583754 0.912119879
64 0.959593758 1.008583754
65 1.005553167 0.959593758
66 0.735858384 1.005553167
67 0.801261784 0.735858384
68 0.888634226 0.801261784
69 0.864645177 0.888634226
70 0.853787411 0.864645177
71 0.776011610 0.853787411
72 1.022980940 0.776011610
73 1.077778437 1.022980940
74 0.784850522 1.077778437
75 0.258588944 0.784850522
76 0.023235109 0.258588944
77 -0.035349387 0.023235109
78 -0.050501007 -0.035349387
79 0.055810878 -0.050501007
80 0.004547529 0.055810878
81 -0.055806100 0.004547529
82 0.015153103 -0.055806100
83 0.105556626 0.015153103
84 0.482072455 0.105556626
85 0.270963321 0.482072455
86 -0.146965706 0.270963321
87 -0.493683009 -0.146965706
88 -0.892672264 -0.493683009
89 -1.069441273 -0.892672264
90 -0.816413569 -1.069441273
91 -0.514648554 -0.816413569
92 -0.365911903 -0.514648554
93 -0.346721256 -0.365911903
94 -0.459853198 -0.346721256
95 -0.410361124 -0.459853198
96 -0.579299167 -0.410361124
97 -0.435868103 -0.579299167
98 0.178019097 -0.435868103
99 0.738119875 0.178019097
100 0.677767894 0.738119875
101 0.328272690 0.677767894
102 -0.352785561 0.328272690
103 -0.869194682 -0.352785561
104 -0.770455807 -0.869194682
105 -0.205808324 -0.770455807
106 0.051516200 -0.205808324
107 -0.067166603 0.051516200
> plot(z,main=paste('Residual Lag plot, lowess, and regression line'), ylab='values of Residuals', xlab='lagged values of Residuals')
> lines(lowess(z))
> abline(lm(z))
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/7a8qo1258483978.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> acf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/8zlnz1258483978.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> pacf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Partial Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/95byg1258483978.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> opar <- par(mfrow = c(2,2), oma = c(0, 0, 1.1, 0))
> plot(mylm, las = 1, sub='Residual Diagnostics')
> par(opar)
> dev.off()
null device
1
> if (n > n25) {
+ postscript(file="/var/www/html/rcomp/tmp/10a7vm1258483978.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
+ plot(kp3:nmkm3,gqarr[,2], main='Goldfeld-Quandt test',ylab='2-sided p-value',xlab='breakpoint')
+ grid()
+ dev.off()
+ }
null device
1
>
> #Note: the /var/www/html/rcomp/createtable file can be downloaded at http://www.wessa.net/cretab
> load(file="/var/www/html/rcomp/createtable")
>
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a, 'Multiple Linear Regression - Estimated Regression Equation', 1, TRUE)
> a<-table.row.end(a)
> myeq <- colnames(x)[1]
> myeq <- paste(myeq, '[t] = ', sep='')
> for (i in 1:k){
+ if (mysum$coefficients[i,1] > 0) myeq <- paste(myeq, '+', '')
+ myeq <- paste(myeq, mysum$coefficients[i,1], sep=' ')
+ if (rownames(mysum$coefficients)[i] != '(Intercept)') {
+ myeq <- paste(myeq, rownames(mysum$coefficients)[i], sep='')
+ if (rownames(mysum$coefficients)[i] != 't') myeq <- paste(myeq, '[t]', sep='')
+ }
+ }
> myeq <- paste(myeq, ' + e[t]')
> a<-table.row.start(a)
> a<-table.element(a, myeq)
> a<-table.row.end(a)
> a<-table.end(a)
> table.save(a,file="/var/www/html/rcomp/tmp/111ggp1258483978.tab")
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a,hyperlink('http://www.xycoon.com/ols1.htm','Multiple Linear Regression - Ordinary Least Squares',''), 6, TRUE)
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a,'Variable',header=TRUE)
> a<-table.element(a,'Parameter',header=TRUE)
> a<-table.element(a,'S.D.',header=TRUE)
> a<-table.element(a,'T-STAT
H0: parameter = 0',header=TRUE)
> a<-table.element(a,'2-tail p-value',header=TRUE)
> a<-table.element(a,'1-tail p-value',header=TRUE)
> a<-table.row.end(a)
> for (i in 1:k){
+ a<-table.row.start(a)
+ a<-table.element(a,rownames(mysum$coefficients)[i],header=TRUE)
+ a<-table.element(a,mysum$coefficients[i,1])
+ a<-table.element(a, round(mysum$coefficients[i,2],6))
+ a<-table.element(a, round(mysum$coefficients[i,3],4))
+ a<-table.element(a, round(mysum$coefficients[i,4],6))
+ a<-table.element(a, round(mysum$coefficients[i,4]/2,6))
+ a<-table.row.end(a)
+ }
> a<-table.end(a)
> table.save(a,file="/var/www/html/rcomp/tmp/12z0le1258483978.tab")
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a, 'Multiple Linear Regression - Regression Statistics', 2, TRUE)
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a, 'Multiple R',1,TRUE)
> a<-table.element(a, sqrt(mysum$r.squared))
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a, 'R-squared',1,TRUE)
> a<-table.element(a, mysum$r.squared)
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a, 'Adjusted R-squared',1,TRUE)
> a<-table.element(a, mysum$adj.r.squared)
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a, 'F-TEST (value)',1,TRUE)
> a<-table.element(a, mysum$fstatistic[1])
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a, 'F-TEST (DF numerator)',1,TRUE)
> a<-table.element(a, mysum$fstatistic[2])
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a, 'F-TEST (DF denominator)',1,TRUE)
> a<-table.element(a, mysum$fstatistic[3])
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a, 'p-value',1,TRUE)
> a<-table.element(a, 1-pf(mysum$fstatistic[1],mysum$fstatistic[2],mysum$fstatistic[3]))
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a, 'Multiple Linear Regression - Residual Statistics', 2, TRUE)
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a, 'Residual Standard Deviation',1,TRUE)
> a<-table.element(a, mysum$sigma)
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a, 'Sum Squared Residuals',1,TRUE)
> a<-table.element(a, sum(myerror*myerror))
> a<-table.row.end(a)
> a<-table.end(a)
> table.save(a,file="/var/www/html/rcomp/tmp/137jfe1258483978.tab")
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a, 'Multiple Linear Regression - Actuals, Interpolation, and Residuals', 4, TRUE)
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a, 'Time or Index', 1, TRUE)
> a<-table.element(a, 'Actuals', 1, TRUE)
> a<-table.element(a, 'Interpolation
Forecast', 1, TRUE)
> a<-table.element(a, 'Residuals
Prediction Error', 1, TRUE)
> a<-table.row.end(a)
> for (i in 1:n) {
+ a<-table.row.start(a)
+ a<-table.element(a,i, 1, TRUE)
+ a<-table.element(a,x[i])
+ a<-table.element(a,x[i]-mysum$resid[i])
+ a<-table.element(a,mysum$resid[i])
+ a<-table.row.end(a)
+ }
> a<-table.end(a)
> table.save(a,file="/var/www/html/rcomp/tmp/14h4rn1258483978.tab")
> if (n > n25) {
+ a<-table.start()
+ a<-table.row.start(a)
+ a<-table.element(a,'Goldfeld-Quandt test for Heteroskedasticity',4,TRUE)
+ a<-table.row.end(a)
+ a<-table.row.start(a)
+ a<-table.element(a,'p-values',header=TRUE)
+ a<-table.element(a,'Alternative Hypothesis',3,header=TRUE)
+ a<-table.row.end(a)
+ a<-table.row.start(a)
+ a<-table.element(a,'breakpoint index',header=TRUE)
+ a<-table.element(a,'greater',header=TRUE)
+ a<-table.element(a,'2-sided',header=TRUE)
+ a<-table.element(a,'less',header=TRUE)
+ a<-table.row.end(a)
+ for (mypoint in kp3:nmkm3) {
+ a<-table.row.start(a)
+ a<-table.element(a,mypoint,header=TRUE)
+ a<-table.element(a,gqarr[mypoint-kp3+1,1])
+ a<-table.element(a,gqarr[mypoint-kp3+1,2])
+ a<-table.element(a,gqarr[mypoint-kp3+1,3])
+ a<-table.row.end(a)
+ }
+ a<-table.end(a)
+ table.save(a,file="/var/www/html/rcomp/tmp/15bfqr1258483978.tab")
+ a<-table.start()
+ a<-table.row.start(a)
+ a<-table.element(a,'Meta Analysis of Goldfeld-Quandt test for Heteroskedasticity',4,TRUE)
+ a<-table.row.end(a)
+ a<-table.row.start(a)
+ a<-table.element(a,'Description',header=TRUE)
+ a<-table.element(a,'# significant tests',header=TRUE)
+ a<-table.element(a,'% significant tests',header=TRUE)
+ a<-table.element(a,'OK/NOK',header=TRUE)
+ a<-table.row.end(a)
+ a<-table.row.start(a)
+ a<-table.element(a,'1% type I error level',header=TRUE)
+ a<-table.element(a,numsignificant1)
+ a<-table.element(a,numsignificant1/numgqtests)
+ if (numsignificant1/numgqtests < 0.01) dum <- 'OK' else dum <- 'NOK'
+ a<-table.element(a,dum)
+ a<-table.row.end(a)
+ a<-table.row.start(a)
+ a<-table.element(a,'5% type I error level',header=TRUE)
+ a<-table.element(a,numsignificant5)
+ a<-table.element(a,numsignificant5/numgqtests)
+ if (numsignificant5/numgqtests < 0.05) dum <- 'OK' else dum <- 'NOK'
+ a<-table.element(a,dum)
+ a<-table.row.end(a)
+ a<-table.row.start(a)
+ a<-table.element(a,'10% type I error level',header=TRUE)
+ a<-table.element(a,numsignificant10)
+ a<-table.element(a,numsignificant10/numgqtests)
+ if (numsignificant10/numgqtests < 0.1) dum <- 'OK' else dum <- 'NOK'
+ a<-table.element(a,dum)
+ a<-table.row.end(a)
+ a<-table.end(a)
+ table.save(a,file="/var/www/html/rcomp/tmp/16rdb91258483978.tab")
+ }
>
> system("convert tmp/1bqp91258483978.ps tmp/1bqp91258483978.png")
> system("convert tmp/2bwbu1258483978.ps tmp/2bwbu1258483978.png")
> system("convert tmp/3dtqe1258483978.ps tmp/3dtqe1258483978.png")
> system("convert tmp/429fx1258483978.ps tmp/429fx1258483978.png")
> system("convert tmp/5v9os1258483978.ps tmp/5v9os1258483978.png")
> system("convert tmp/673hn1258483978.ps tmp/673hn1258483978.png")
> system("convert tmp/7a8qo1258483978.ps tmp/7a8qo1258483978.png")
> system("convert tmp/8zlnz1258483978.ps tmp/8zlnz1258483978.png")
> system("convert tmp/95byg1258483978.ps tmp/95byg1258483978.png")
> system("convert tmp/10a7vm1258483978.ps tmp/10a7vm1258483978.png")
>
>
> proc.time()
user system elapsed
3.116 1.660 4.234