R version 2.15.2 (2012-10-26) -- "Trick or Treat"
Copyright (C) 2012 The R Foundation for Statistical Computing
ISBN 3-900051-07-0
Platform: i686-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(4,0,4,0,4,0,4,0,4,0,4,0,4,0,4,0,4,0,4,0,4,0,4,0,4,0,4,0,4,0,4,0,4,1,4,0,4,0,4,1,4,0,4,0,4,0,4,0,4,0,4,0,4,0,4,0,4,0,4,0,4,0,4,0,4,0,4,0,4,0,4,0,4,0,4,0,4,0,4,0,4,1,4,0,4,0,4,0,4,0,4,0,4,0,4,0,4,0,4,0,4,0,4,1,4,0,4,1,4,0,4,0,4,0,4,0,4,0,4,1,4,0,4,0,4,0,4,0,4,0,4,0,4,1,4,0,4,0,4,0,4,0,4,0,4,0,4,0,4,0,4,0,4,0,4,0,4,1,4,0,4,0,4,0,4,0,4,1,4,0,4,0,2,0,2,0,2,0,2,0,2,0,2,0,2,0,2,0,2,0,2,0,2,0,2,0,2,0,2,0,2,0,2,0,2,0,2,0,2,0,2,0,2,0,2,0,2,0,2,0,2,0,2,0,2,0,2,0,2,0,2,0,2,0,2,0,2,0,2,0,2,0,2,0,2,0,2,0,2,0,2,0,2,0,2,0,2,0,2,0,2,0,2,0,2,0,2,0,2,0,2,0,2,0,2,0,2,0,2,0,2,1,2,0,2,0,2,0,2,0,2,0,2,0,2,0,2,0,2,0,2,0,2,1,2,1,2,0),dim=c(2,154),dimnames=list(c('weeks','CorrectAnalysis'),1:154))
> y <- array(NA,dim=c(2,154),dimnames=list(c('weeks','CorrectAnalysis'),1:154))
> for (i in 1:dim(x)[1])
+ {
+ for (j in 1:dim(x)[2])
+ {
+ y[i,j] <- as.numeric(x[i,j])
+ }
+ }
> par3 = 'No Linear Trend'
> par2 = 'Do not include Seasonal Dummies'
> par1 = '1'
> par3 <- 'No Linear Trend'
> par2 <- 'Do not include Seasonal Dummies'
> par1 <- '1'
> #'GNU S' R Code compiled by R2WASP v. 1.0.44 ()
> #Author: Prof. Dr. P. Wessa
> #To cite this work: AUTHOR(S), (YEAR), YOUR SOFTWARE TITLE (vNUMBER) in Free Statistics Software (v$_version), Office for Research Development and Education, URL http://www.wessa.net/rwasp_YOURPAGE.wasp/
> #Source of accompanying publication: Office for Research, Development, and Education
> #Technical description: Write here your technical program description (don't use hard returns!)
> library(lattice)
> library(lmtest)
Loading required package: zoo
Attaching package: 'zoo'
The following object(s) are masked from 'package:base':
as.Date, 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
weeks CorrectAnalysis
1 4 0
2 4 0
3 4 0
4 4 0
5 4 0
6 4 0
7 4 0
8 4 0
9 4 0
10 4 0
11 4 0
12 4 0
13 4 0
14 4 0
15 4 0
16 4 0
17 4 1
18 4 0
19 4 0
20 4 1
21 4 0
22 4 0
23 4 0
24 4 0
25 4 0
26 4 0
27 4 0
28 4 0
29 4 0
30 4 0
31 4 0
32 4 0
33 4 0
34 4 0
35 4 0
36 4 0
37 4 0
38 4 0
39 4 0
40 4 0
41 4 1
42 4 0
43 4 0
44 4 0
45 4 0
46 4 0
47 4 0
48 4 0
49 4 0
50 4 0
51 4 0
52 4 1
53 4 0
54 4 1
55 4 0
56 4 0
57 4 0
58 4 0
59 4 0
60 4 1
61 4 0
62 4 0
63 4 0
64 4 0
65 4 0
66 4 0
67 4 1
68 4 0
69 4 0
70 4 0
71 4 0
72 4 0
73 4 0
74 4 0
75 4 0
76 4 0
77 4 0
78 4 0
79 4 1
80 4 0
81 4 0
82 4 0
83 4 0
84 4 1
85 4 0
86 4 0
87 2 0
88 2 0
89 2 0
90 2 0
91 2 0
92 2 0
93 2 0
94 2 0
95 2 0
96 2 0
97 2 0
98 2 0
99 2 0
100 2 0
101 2 0
102 2 0
103 2 0
104 2 0
105 2 0
106 2 0
107 2 0
108 2 0
109 2 0
110 2 0
111 2 0
112 2 0
113 2 0
114 2 0
115 2 0
116 2 0
117 2 0
118 2 0
119 2 0
120 2 0
121 2 0
122 2 0
123 2 0
124 2 0
125 2 0
126 2 0
127 2 0
128 2 0
129 2 0
130 2 0
131 2 0
132 2 0
133 2 0
134 2 0
135 2 0
136 2 0
137 2 0
138 2 0
139 2 0
140 2 0
141 2 1
142 2 0
143 2 0
144 2 0
145 2 0
146 2 0
147 2 0
148 2 0
149 2 0
150 2 0
151 2 0
152 2 1
153 2 1
154 2 0
> k <- length(x[1,])
> df <- as.data.frame(x)
> (mylm <- lm(df))
Call:
lm(formula = df)
Coefficients:
(Intercept) CorrectAnalysis
3.0845 0.4155
> (mysum <- summary(mylm))
Call:
lm(formula = df)
Residuals:
Min 1Q Median 3Q Max
-1.5000 -1.0845 0.7077 0.9155 0.9155
Coefficients:
Estimate Std. Error t value Pr(>|t|)
(Intercept) 3.08451 0.08336 37.002 <2e-16 ***
CorrectAnalysis 0.41549 0.29863 1.391 0.166
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
Residual standard error: 0.9934 on 152 degrees of freedom
Multiple R-squared: 0.01258, Adjusted R-squared: 0.006079
F-statistic: 1.936 on 1 and 152 DF, p-value: 0.1662
> 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,] 1.614763e-48 3.229526e-48 1.000000e+00
[2,] 4.600765e-62 9.201530e-62 1.000000e+00
[3,] 1.056910e-76 2.113819e-76 1.000000e+00
[4,] 2.039024e-91 4.078047e-91 1.000000e+00
[5,] 3.193364e-109 6.386728e-109 1.000000e+00
[6,] 1.027939e-124 2.055878e-124 1.000000e+00
[7,] 7.145761e-147 1.429152e-146 1.000000e+00
[8,] 2.293144e-152 4.586288e-152 1.000000e+00
[9,] 2.624653e-190 5.249306e-190 1.000000e+00
[10,] 2.530130e-181 5.060259e-181 1.000000e+00
[11,] 1.448950e-196 2.897900e-196 1.000000e+00
[12,] 0.000000e+00 0.000000e+00 1.000000e+00
[13,] 3.157589e-244 6.315179e-244 1.000000e+00
[14,] 3.565847e-244 7.131694e-244 1.000000e+00
[15,] 1.211874e-257 2.423748e-257 1.000000e+00
[16,] 4.705449e-286 9.410899e-286 1.000000e+00
[17,] 0.000000e+00 0.000000e+00 1.000000e+00
[18,] 3.112854e-307 6.225708e-307 1.000000e+00
[19,] 3.030441e-317 6.060882e-317 1.000000e+00
[20,] 0.000000e+00 0.000000e+00 1.000000e+00
[21,] 0.000000e+00 0.000000e+00 1.000000e+00
[22,] 0.000000e+00 0.000000e+00 1.000000e+00
[23,] 0.000000e+00 0.000000e+00 1.000000e+00
[24,] 0.000000e+00 0.000000e+00 1.000000e+00
[25,] 0.000000e+00 0.000000e+00 1.000000e+00
[26,] 0.000000e+00 0.000000e+00 1.000000e+00
[27,] 0.000000e+00 0.000000e+00 1.000000e+00
[28,] 0.000000e+00 0.000000e+00 1.000000e+00
[29,] 0.000000e+00 0.000000e+00 1.000000e+00
[30,] 0.000000e+00 0.000000e+00 1.000000e+00
[31,] 0.000000e+00 0.000000e+00 1.000000e+00
[32,] 0.000000e+00 0.000000e+00 1.000000e+00
[33,] 0.000000e+00 0.000000e+00 1.000000e+00
[34,] 0.000000e+00 0.000000e+00 1.000000e+00
[35,] 0.000000e+00 0.000000e+00 1.000000e+00
[36,] 0.000000e+00 0.000000e+00 1.000000e+00
[37,] 0.000000e+00 0.000000e+00 1.000000e+00
[38,] 0.000000e+00 0.000000e+00 1.000000e+00
[39,] 0.000000e+00 0.000000e+00 1.000000e+00
[40,] 0.000000e+00 0.000000e+00 1.000000e+00
[41,] 0.000000e+00 0.000000e+00 1.000000e+00
[42,] 0.000000e+00 0.000000e+00 1.000000e+00
[43,] 0.000000e+00 0.000000e+00 1.000000e+00
[44,] 0.000000e+00 0.000000e+00 1.000000e+00
[45,] 0.000000e+00 0.000000e+00 1.000000e+00
[46,] 0.000000e+00 0.000000e+00 1.000000e+00
[47,] 0.000000e+00 0.000000e+00 1.000000e+00
[48,] 0.000000e+00 0.000000e+00 1.000000e+00
[49,] 0.000000e+00 0.000000e+00 1.000000e+00
[50,] 0.000000e+00 0.000000e+00 1.000000e+00
[51,] 0.000000e+00 0.000000e+00 1.000000e+00
[52,] 0.000000e+00 0.000000e+00 1.000000e+00
[53,] 0.000000e+00 0.000000e+00 1.000000e+00
[54,] 0.000000e+00 0.000000e+00 1.000000e+00
[55,] 0.000000e+00 0.000000e+00 1.000000e+00
[56,] 0.000000e+00 0.000000e+00 1.000000e+00
[57,] 0.000000e+00 0.000000e+00 1.000000e+00
[58,] 0.000000e+00 0.000000e+00 1.000000e+00
[59,] 0.000000e+00 0.000000e+00 1.000000e+00
[60,] 0.000000e+00 0.000000e+00 1.000000e+00
[61,] 0.000000e+00 0.000000e+00 1.000000e+00
[62,] 0.000000e+00 0.000000e+00 1.000000e+00
[63,] 0.000000e+00 0.000000e+00 1.000000e+00
[64,] 0.000000e+00 0.000000e+00 1.000000e+00
[65,] 0.000000e+00 0.000000e+00 1.000000e+00
[66,] 0.000000e+00 0.000000e+00 1.000000e+00
[67,] 0.000000e+00 0.000000e+00 1.000000e+00
[68,] 0.000000e+00 0.000000e+00 1.000000e+00
[69,] 0.000000e+00 0.000000e+00 1.000000e+00
[70,] 0.000000e+00 0.000000e+00 1.000000e+00
[71,] 0.000000e+00 0.000000e+00 1.000000e+00
[72,] 0.000000e+00 0.000000e+00 1.000000e+00
[73,] 0.000000e+00 0.000000e+00 1.000000e+00
[74,] 0.000000e+00 0.000000e+00 1.000000e+00
[75,] 0.000000e+00 0.000000e+00 1.000000e+00
[76,] 0.000000e+00 0.000000e+00 1.000000e+00
[77,] 0.000000e+00 0.000000e+00 1.000000e+00
[78,] 0.000000e+00 0.000000e+00 1.000000e+00
[79,] 0.000000e+00 0.000000e+00 1.000000e+00
[80,] 0.000000e+00 0.000000e+00 1.000000e+00
[81,] 0.000000e+00 0.000000e+00 1.000000e+00
[82,] 1.000000e+00 2.093219e-20 1.046609e-20
[83,] 1.000000e+00 0.000000e+00 0.000000e+00
[84,] 1.000000e+00 0.000000e+00 0.000000e+00
[85,] 1.000000e+00 0.000000e+00 0.000000e+00
[86,] 1.000000e+00 0.000000e+00 0.000000e+00
[87,] 1.000000e+00 0.000000e+00 0.000000e+00
[88,] 1.000000e+00 0.000000e+00 0.000000e+00
[89,] 1.000000e+00 0.000000e+00 0.000000e+00
[90,] 1.000000e+00 0.000000e+00 0.000000e+00
[91,] 1.000000e+00 0.000000e+00 0.000000e+00
[92,] 1.000000e+00 0.000000e+00 0.000000e+00
[93,] 1.000000e+00 0.000000e+00 0.000000e+00
[94,] 1.000000e+00 0.000000e+00 0.000000e+00
[95,] 1.000000e+00 0.000000e+00 0.000000e+00
[96,] 1.000000e+00 0.000000e+00 0.000000e+00
[97,] 1.000000e+00 0.000000e+00 0.000000e+00
[98,] 1.000000e+00 0.000000e+00 0.000000e+00
[99,] 1.000000e+00 0.000000e+00 0.000000e+00
[100,] 1.000000e+00 0.000000e+00 0.000000e+00
[101,] 1.000000e+00 0.000000e+00 0.000000e+00
[102,] 1.000000e+00 0.000000e+00 0.000000e+00
[103,] 1.000000e+00 0.000000e+00 0.000000e+00
[104,] 1.000000e+00 0.000000e+00 0.000000e+00
[105,] 1.000000e+00 0.000000e+00 0.000000e+00
[106,] 1.000000e+00 0.000000e+00 0.000000e+00
[107,] 1.000000e+00 0.000000e+00 0.000000e+00
[108,] 1.000000e+00 0.000000e+00 0.000000e+00
[109,] 1.000000e+00 0.000000e+00 0.000000e+00
[110,] 1.000000e+00 0.000000e+00 0.000000e+00
[111,] 1.000000e+00 0.000000e+00 0.000000e+00
[112,] 1.000000e+00 0.000000e+00 0.000000e+00
[113,] 1.000000e+00 0.000000e+00 0.000000e+00
[114,] 1.000000e+00 0.000000e+00 0.000000e+00
[115,] 1.000000e+00 0.000000e+00 0.000000e+00
[116,] 1.000000e+00 0.000000e+00 0.000000e+00
[117,] 1.000000e+00 0.000000e+00 0.000000e+00
[118,] 1.000000e+00 0.000000e+00 0.000000e+00
[119,] 1.000000e+00 0.000000e+00 0.000000e+00
[120,] 1.000000e+00 0.000000e+00 0.000000e+00
[121,] 1.000000e+00 0.000000e+00 0.000000e+00
[122,] 1.000000e+00 0.000000e+00 0.000000e+00
[123,] 1.000000e+00 0.000000e+00 0.000000e+00
[124,] 1.000000e+00 0.000000e+00 0.000000e+00
[125,] 1.000000e+00 0.000000e+00 0.000000e+00
[126,] 1.000000e+00 0.000000e+00 0.000000e+00
[127,] 1.000000e+00 9.881313e-323 4.940656e-323
[128,] 1.000000e+00 1.917683e-312 9.588414e-313
[129,] 1.000000e+00 0.000000e+00 0.000000e+00
[130,] 1.000000e+00 9.419269e-291 4.709635e-291
[131,] 1.000000e+00 4.079564e-262 2.039782e-262
[132,] 1.000000e+00 2.200201e-248 1.100100e-248
[133,] 1.000000e+00 3.587393e-248 1.793697e-248
[134,] 1.000000e+00 0.000000e+00 0.000000e+00
[135,] 1.000000e+00 5.267680e-200 2.633840e-200
[136,] 1.000000e+00 2.667247e-185 1.333624e-185
[137,] 1.000000e+00 3.195327e-193 1.597663e-193
[138,] 1.000000e+00 5.304178e-155 2.652089e-155
[139,] 1.000000e+00 3.146695e-149 1.573348e-149
[140,] 1.000000e+00 8.628788e-127 4.314394e-127
[141,] 1.000000e+00 5.111109e-111 2.555555e-111
[142,] 1.000000e+00 6.214329e-93 3.107165e-93
[143,] 1.000000e+00 6.108982e-78 3.054491e-78
[144,] 1.000000e+00 4.996914e-63 2.498457e-63
[145,] 1.000000e+00 3.224528e-49 1.612264e-49
> postscript(file="/var/wessaorg/rcomp/tmp/1ati61355777552.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> plot(x[,1], type='l', main='Actuals and Interpolation', ylab='value of Actuals and Interpolation (dots)', xlab='time or index')
> points(x[,1]-mysum$resid)
> grid()
> dev.off()
null device
1
> postscript(file="/var/wessaorg/rcomp/tmp/23bnf1355777552.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> plot(mysum$resid, type='b', pch=19, main='Residuals', ylab='value of Residuals', xlab='time or index')
> grid()
> dev.off()
null device
1
> postscript(file="/var/wessaorg/rcomp/tmp/3a80n1355777552.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> hist(mysum$resid, main='Residual Histogram', xlab='values of Residuals')
> grid()
> dev.off()
null device
1
> postscript(file="/var/wessaorg/rcomp/tmp/4bn8f1355777552.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> densityplot(~mysum$resid,col='black',main='Residual Density Plot', xlab='values of Residuals')
> dev.off()
null device
1
> postscript(file="/var/wessaorg/rcomp/tmp/5yo6v1355777552.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 = 154
Frequency = 1
1 2 3 4 5 6 7 8
0.915493 0.915493 0.915493 0.915493 0.915493 0.915493 0.915493 0.915493
9 10 11 12 13 14 15 16
0.915493 0.915493 0.915493 0.915493 0.915493 0.915493 0.915493 0.915493
17 18 19 20 21 22 23 24
0.500000 0.915493 0.915493 0.500000 0.915493 0.915493 0.915493 0.915493
25 26 27 28 29 30 31 32
0.915493 0.915493 0.915493 0.915493 0.915493 0.915493 0.915493 0.915493
33 34 35 36 37 38 39 40
0.915493 0.915493 0.915493 0.915493 0.915493 0.915493 0.915493 0.915493
41 42 43 44 45 46 47 48
0.500000 0.915493 0.915493 0.915493 0.915493 0.915493 0.915493 0.915493
49 50 51 52 53 54 55 56
0.915493 0.915493 0.915493 0.500000 0.915493 0.500000 0.915493 0.915493
57 58 59 60 61 62 63 64
0.915493 0.915493 0.915493 0.500000 0.915493 0.915493 0.915493 0.915493
65 66 67 68 69 70 71 72
0.915493 0.915493 0.500000 0.915493 0.915493 0.915493 0.915493 0.915493
73 74 75 76 77 78 79 80
0.915493 0.915493 0.915493 0.915493 0.915493 0.915493 0.500000 0.915493
81 82 83 84 85 86 87 88
0.915493 0.915493 0.915493 0.500000 0.915493 0.915493 -1.084507 -1.084507
89 90 91 92 93 94 95 96
-1.084507 -1.084507 -1.084507 -1.084507 -1.084507 -1.084507 -1.084507 -1.084507
97 98 99 100 101 102 103 104
-1.084507 -1.084507 -1.084507 -1.084507 -1.084507 -1.084507 -1.084507 -1.084507
105 106 107 108 109 110 111 112
-1.084507 -1.084507 -1.084507 -1.084507 -1.084507 -1.084507 -1.084507 -1.084507
113 114 115 116 117 118 119 120
-1.084507 -1.084507 -1.084507 -1.084507 -1.084507 -1.084507 -1.084507 -1.084507
121 122 123 124 125 126 127 128
-1.084507 -1.084507 -1.084507 -1.084507 -1.084507 -1.084507 -1.084507 -1.084507
129 130 131 132 133 134 135 136
-1.084507 -1.084507 -1.084507 -1.084507 -1.084507 -1.084507 -1.084507 -1.084507
137 138 139 140 141 142 143 144
-1.084507 -1.084507 -1.084507 -1.084507 -1.500000 -1.084507 -1.084507 -1.084507
145 146 147 148 149 150 151 152
-1.084507 -1.084507 -1.084507 -1.084507 -1.084507 -1.084507 -1.084507 -1.500000
153 154
-1.500000 -1.084507
> postscript(file="/var/wessaorg/rcomp/tmp/6yz9b1355777552.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 = 154
Frequency = 1
lag(myerror, k = 1) myerror
0 0.915493 NA
1 0.915493 0.915493
2 0.915493 0.915493
3 0.915493 0.915493
4 0.915493 0.915493
5 0.915493 0.915493
6 0.915493 0.915493
7 0.915493 0.915493
8 0.915493 0.915493
9 0.915493 0.915493
10 0.915493 0.915493
11 0.915493 0.915493
12 0.915493 0.915493
13 0.915493 0.915493
14 0.915493 0.915493
15 0.915493 0.915493
16 0.500000 0.915493
17 0.915493 0.500000
18 0.915493 0.915493
19 0.500000 0.915493
20 0.915493 0.500000
21 0.915493 0.915493
22 0.915493 0.915493
23 0.915493 0.915493
24 0.915493 0.915493
25 0.915493 0.915493
26 0.915493 0.915493
27 0.915493 0.915493
28 0.915493 0.915493
29 0.915493 0.915493
30 0.915493 0.915493
31 0.915493 0.915493
32 0.915493 0.915493
33 0.915493 0.915493
34 0.915493 0.915493
35 0.915493 0.915493
36 0.915493 0.915493
37 0.915493 0.915493
38 0.915493 0.915493
39 0.915493 0.915493
40 0.500000 0.915493
41 0.915493 0.500000
42 0.915493 0.915493
43 0.915493 0.915493
44 0.915493 0.915493
45 0.915493 0.915493
46 0.915493 0.915493
47 0.915493 0.915493
48 0.915493 0.915493
49 0.915493 0.915493
50 0.915493 0.915493
51 0.500000 0.915493
52 0.915493 0.500000
53 0.500000 0.915493
54 0.915493 0.500000
55 0.915493 0.915493
56 0.915493 0.915493
57 0.915493 0.915493
58 0.915493 0.915493
59 0.500000 0.915493
60 0.915493 0.500000
61 0.915493 0.915493
62 0.915493 0.915493
63 0.915493 0.915493
64 0.915493 0.915493
65 0.915493 0.915493
66 0.500000 0.915493
67 0.915493 0.500000
68 0.915493 0.915493
69 0.915493 0.915493
70 0.915493 0.915493
71 0.915493 0.915493
72 0.915493 0.915493
73 0.915493 0.915493
74 0.915493 0.915493
75 0.915493 0.915493
76 0.915493 0.915493
77 0.915493 0.915493
78 0.500000 0.915493
79 0.915493 0.500000
80 0.915493 0.915493
81 0.915493 0.915493
82 0.915493 0.915493
83 0.500000 0.915493
84 0.915493 0.500000
85 0.915493 0.915493
86 -1.084507 0.915493
87 -1.084507 -1.084507
88 -1.084507 -1.084507
89 -1.084507 -1.084507
90 -1.084507 -1.084507
91 -1.084507 -1.084507
92 -1.084507 -1.084507
93 -1.084507 -1.084507
94 -1.084507 -1.084507
95 -1.084507 -1.084507
96 -1.084507 -1.084507
97 -1.084507 -1.084507
98 -1.084507 -1.084507
99 -1.084507 -1.084507
100 -1.084507 -1.084507
101 -1.084507 -1.084507
102 -1.084507 -1.084507
103 -1.084507 -1.084507
104 -1.084507 -1.084507
105 -1.084507 -1.084507
106 -1.084507 -1.084507
107 -1.084507 -1.084507
108 -1.084507 -1.084507
109 -1.084507 -1.084507
110 -1.084507 -1.084507
111 -1.084507 -1.084507
112 -1.084507 -1.084507
113 -1.084507 -1.084507
114 -1.084507 -1.084507
115 -1.084507 -1.084507
116 -1.084507 -1.084507
117 -1.084507 -1.084507
118 -1.084507 -1.084507
119 -1.084507 -1.084507
120 -1.084507 -1.084507
121 -1.084507 -1.084507
122 -1.084507 -1.084507
123 -1.084507 -1.084507
124 -1.084507 -1.084507
125 -1.084507 -1.084507
126 -1.084507 -1.084507
127 -1.084507 -1.084507
128 -1.084507 -1.084507
129 -1.084507 -1.084507
130 -1.084507 -1.084507
131 -1.084507 -1.084507
132 -1.084507 -1.084507
133 -1.084507 -1.084507
134 -1.084507 -1.084507
135 -1.084507 -1.084507
136 -1.084507 -1.084507
137 -1.084507 -1.084507
138 -1.084507 -1.084507
139 -1.084507 -1.084507
140 -1.500000 -1.084507
141 -1.084507 -1.500000
142 -1.084507 -1.084507
143 -1.084507 -1.084507
144 -1.084507 -1.084507
145 -1.084507 -1.084507
146 -1.084507 -1.084507
147 -1.084507 -1.084507
148 -1.084507 -1.084507
149 -1.084507 -1.084507
150 -1.084507 -1.084507
151 -1.500000 -1.084507
152 -1.500000 -1.500000
153 -1.084507 -1.500000
154 NA -1.084507
> dum1 <- dum[2:length(myerror),]
> dum1
lag(myerror, k = 1) myerror
[1,] 0.915493 0.915493
[2,] 0.915493 0.915493
[3,] 0.915493 0.915493
[4,] 0.915493 0.915493
[5,] 0.915493 0.915493
[6,] 0.915493 0.915493
[7,] 0.915493 0.915493
[8,] 0.915493 0.915493
[9,] 0.915493 0.915493
[10,] 0.915493 0.915493
[11,] 0.915493 0.915493
[12,] 0.915493 0.915493
[13,] 0.915493 0.915493
[14,] 0.915493 0.915493
[15,] 0.915493 0.915493
[16,] 0.500000 0.915493
[17,] 0.915493 0.500000
[18,] 0.915493 0.915493
[19,] 0.500000 0.915493
[20,] 0.915493 0.500000
[21,] 0.915493 0.915493
[22,] 0.915493 0.915493
[23,] 0.915493 0.915493
[24,] 0.915493 0.915493
[25,] 0.915493 0.915493
[26,] 0.915493 0.915493
[27,] 0.915493 0.915493
[28,] 0.915493 0.915493
[29,] 0.915493 0.915493
[30,] 0.915493 0.915493
[31,] 0.915493 0.915493
[32,] 0.915493 0.915493
[33,] 0.915493 0.915493
[34,] 0.915493 0.915493
[35,] 0.915493 0.915493
[36,] 0.915493 0.915493
[37,] 0.915493 0.915493
[38,] 0.915493 0.915493
[39,] 0.915493 0.915493
[40,] 0.500000 0.915493
[41,] 0.915493 0.500000
[42,] 0.915493 0.915493
[43,] 0.915493 0.915493
[44,] 0.915493 0.915493
[45,] 0.915493 0.915493
[46,] 0.915493 0.915493
[47,] 0.915493 0.915493
[48,] 0.915493 0.915493
[49,] 0.915493 0.915493
[50,] 0.915493 0.915493
[51,] 0.500000 0.915493
[52,] 0.915493 0.500000
[53,] 0.500000 0.915493
[54,] 0.915493 0.500000
[55,] 0.915493 0.915493
[56,] 0.915493 0.915493
[57,] 0.915493 0.915493
[58,] 0.915493 0.915493
[59,] 0.500000 0.915493
[60,] 0.915493 0.500000
[61,] 0.915493 0.915493
[62,] 0.915493 0.915493
[63,] 0.915493 0.915493
[64,] 0.915493 0.915493
[65,] 0.915493 0.915493
[66,] 0.500000 0.915493
[67,] 0.915493 0.500000
[68,] 0.915493 0.915493
[69,] 0.915493 0.915493
[70,] 0.915493 0.915493
[71,] 0.915493 0.915493
[72,] 0.915493 0.915493
[73,] 0.915493 0.915493
[74,] 0.915493 0.915493
[75,] 0.915493 0.915493
[76,] 0.915493 0.915493
[77,] 0.915493 0.915493
[78,] 0.500000 0.915493
[79,] 0.915493 0.500000
[80,] 0.915493 0.915493
[81,] 0.915493 0.915493
[82,] 0.915493 0.915493
[83,] 0.500000 0.915493
[84,] 0.915493 0.500000
[85,] 0.915493 0.915493
[86,] -1.084507 0.915493
[87,] -1.084507 -1.084507
[88,] -1.084507 -1.084507
[89,] -1.084507 -1.084507
[90,] -1.084507 -1.084507
[91,] -1.084507 -1.084507
[92,] -1.084507 -1.084507
[93,] -1.084507 -1.084507
[94,] -1.084507 -1.084507
[95,] -1.084507 -1.084507
[96,] -1.084507 -1.084507
[97,] -1.084507 -1.084507
[98,] -1.084507 -1.084507
[99,] -1.084507 -1.084507
[100,] -1.084507 -1.084507
[101,] -1.084507 -1.084507
[102,] -1.084507 -1.084507
[103,] -1.084507 -1.084507
[104,] -1.084507 -1.084507
[105,] -1.084507 -1.084507
[106,] -1.084507 -1.084507
[107,] -1.084507 -1.084507
[108,] -1.084507 -1.084507
[109,] -1.084507 -1.084507
[110,] -1.084507 -1.084507
[111,] -1.084507 -1.084507
[112,] -1.084507 -1.084507
[113,] -1.084507 -1.084507
[114,] -1.084507 -1.084507
[115,] -1.084507 -1.084507
[116,] -1.084507 -1.084507
[117,] -1.084507 -1.084507
[118,] -1.084507 -1.084507
[119,] -1.084507 -1.084507
[120,] -1.084507 -1.084507
[121,] -1.084507 -1.084507
[122,] -1.084507 -1.084507
[123,] -1.084507 -1.084507
[124,] -1.084507 -1.084507
[125,] -1.084507 -1.084507
[126,] -1.084507 -1.084507
[127,] -1.084507 -1.084507
[128,] -1.084507 -1.084507
[129,] -1.084507 -1.084507
[130,] -1.084507 -1.084507
[131,] -1.084507 -1.084507
[132,] -1.084507 -1.084507
[133,] -1.084507 -1.084507
[134,] -1.084507 -1.084507
[135,] -1.084507 -1.084507
[136,] -1.084507 -1.084507
[137,] -1.084507 -1.084507
[138,] -1.084507 -1.084507
[139,] -1.084507 -1.084507
[140,] -1.500000 -1.084507
[141,] -1.084507 -1.500000
[142,] -1.084507 -1.084507
[143,] -1.084507 -1.084507
[144,] -1.084507 -1.084507
[145,] -1.084507 -1.084507
[146,] -1.084507 -1.084507
[147,] -1.084507 -1.084507
[148,] -1.084507 -1.084507
[149,] -1.084507 -1.084507
[150,] -1.084507 -1.084507
[151,] -1.500000 -1.084507
[152,] -1.500000 -1.500000
[153,] -1.084507 -1.500000
> z <- as.data.frame(dum1)
> z
lag(myerror, k = 1) myerror
1 0.915493 0.915493
2 0.915493 0.915493
3 0.915493 0.915493
4 0.915493 0.915493
5 0.915493 0.915493
6 0.915493 0.915493
7 0.915493 0.915493
8 0.915493 0.915493
9 0.915493 0.915493
10 0.915493 0.915493
11 0.915493 0.915493
12 0.915493 0.915493
13 0.915493 0.915493
14 0.915493 0.915493
15 0.915493 0.915493
16 0.500000 0.915493
17 0.915493 0.500000
18 0.915493 0.915493
19 0.500000 0.915493
20 0.915493 0.500000
21 0.915493 0.915493
22 0.915493 0.915493
23 0.915493 0.915493
24 0.915493 0.915493
25 0.915493 0.915493
26 0.915493 0.915493
27 0.915493 0.915493
28 0.915493 0.915493
29 0.915493 0.915493
30 0.915493 0.915493
31 0.915493 0.915493
32 0.915493 0.915493
33 0.915493 0.915493
34 0.915493 0.915493
35 0.915493 0.915493
36 0.915493 0.915493
37 0.915493 0.915493
38 0.915493 0.915493
39 0.915493 0.915493
40 0.500000 0.915493
41 0.915493 0.500000
42 0.915493 0.915493
43 0.915493 0.915493
44 0.915493 0.915493
45 0.915493 0.915493
46 0.915493 0.915493
47 0.915493 0.915493
48 0.915493 0.915493
49 0.915493 0.915493
50 0.915493 0.915493
51 0.500000 0.915493
52 0.915493 0.500000
53 0.500000 0.915493
54 0.915493 0.500000
55 0.915493 0.915493
56 0.915493 0.915493
57 0.915493 0.915493
58 0.915493 0.915493
59 0.500000 0.915493
60 0.915493 0.500000
61 0.915493 0.915493
62 0.915493 0.915493
63 0.915493 0.915493
64 0.915493 0.915493
65 0.915493 0.915493
66 0.500000 0.915493
67 0.915493 0.500000
68 0.915493 0.915493
69 0.915493 0.915493
70 0.915493 0.915493
71 0.915493 0.915493
72 0.915493 0.915493
73 0.915493 0.915493
74 0.915493 0.915493
75 0.915493 0.915493
76 0.915493 0.915493
77 0.915493 0.915493
78 0.500000 0.915493
79 0.915493 0.500000
80 0.915493 0.915493
81 0.915493 0.915493
82 0.915493 0.915493
83 0.500000 0.915493
84 0.915493 0.500000
85 0.915493 0.915493
86 -1.084507 0.915493
87 -1.084507 -1.084507
88 -1.084507 -1.084507
89 -1.084507 -1.084507
90 -1.084507 -1.084507
91 -1.084507 -1.084507
92 -1.084507 -1.084507
93 -1.084507 -1.084507
94 -1.084507 -1.084507
95 -1.084507 -1.084507
96 -1.084507 -1.084507
97 -1.084507 -1.084507
98 -1.084507 -1.084507
99 -1.084507 -1.084507
100 -1.084507 -1.084507
101 -1.084507 -1.084507
102 -1.084507 -1.084507
103 -1.084507 -1.084507
104 -1.084507 -1.084507
105 -1.084507 -1.084507
106 -1.084507 -1.084507
107 -1.084507 -1.084507
108 -1.084507 -1.084507
109 -1.084507 -1.084507
110 -1.084507 -1.084507
111 -1.084507 -1.084507
112 -1.084507 -1.084507
113 -1.084507 -1.084507
114 -1.084507 -1.084507
115 -1.084507 -1.084507
116 -1.084507 -1.084507
117 -1.084507 -1.084507
118 -1.084507 -1.084507
119 -1.084507 -1.084507
120 -1.084507 -1.084507
121 -1.084507 -1.084507
122 -1.084507 -1.084507
123 -1.084507 -1.084507
124 -1.084507 -1.084507
125 -1.084507 -1.084507
126 -1.084507 -1.084507
127 -1.084507 -1.084507
128 -1.084507 -1.084507
129 -1.084507 -1.084507
130 -1.084507 -1.084507
131 -1.084507 -1.084507
132 -1.084507 -1.084507
133 -1.084507 -1.084507
134 -1.084507 -1.084507
135 -1.084507 -1.084507
136 -1.084507 -1.084507
137 -1.084507 -1.084507
138 -1.084507 -1.084507
139 -1.084507 -1.084507
140 -1.500000 -1.084507
141 -1.084507 -1.500000
142 -1.084507 -1.084507
143 -1.084507 -1.084507
144 -1.084507 -1.084507
145 -1.084507 -1.084507
146 -1.084507 -1.084507
147 -1.084507 -1.084507
148 -1.084507 -1.084507
149 -1.084507 -1.084507
150 -1.084507 -1.084507
151 -1.500000 -1.084507
152 -1.500000 -1.500000
153 -1.084507 -1.500000
> plot(z,main=paste('Residual Lag plot, lowess, and regression line'), ylab='values of Residuals', xlab='lagged values of Residuals')
> lines(lowess(z))
> abline(lm(z))
> grid()
> dev.off()
null device
1
> postscript(file="/var/wessaorg/rcomp/tmp/7qzi31355777553.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> acf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/wessaorg/rcomp/tmp/8u2rl1355777553.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> pacf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Partial Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/wessaorg/rcomp/tmp/9xqzv1355777553.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> opar <- par(mfrow = c(2,2), oma = c(0, 0, 1.1, 0))
> plot(mylm, las = 1, sub='Residual Diagnostics')
> par(opar)
> dev.off()
null device
1
> if (n > n25) {
+ postscript(file="/var/wessaorg/rcomp/tmp/10n3of1355777553.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
+ plot(kp3:nmkm3,gqarr[,2], main='Goldfeld-Quandt test',ylab='2-sided p-value',xlab='breakpoint')
+ grid()
+ dev.off()
+ }
null device
1
>
> #Note: the /var/wessaorg/rcomp/createtable file can be downloaded at http://www.wessa.net/cretab
> load(file="/var/wessaorg/rcomp/createtable")
>
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a, 'Multiple Linear Regression - Estimated Regression Equation', 1, TRUE)
> a<-table.row.end(a)
> myeq <- colnames(x)[1]
> myeq <- paste(myeq, '[t] = ', sep='')
> for (i in 1:k){
+ if (mysum$coefficients[i,1] > 0) myeq <- paste(myeq, '+', '')
+ myeq <- paste(myeq, mysum$coefficients[i,1], sep=' ')
+ if (rownames(mysum$coefficients)[i] != '(Intercept)') {
+ myeq <- paste(myeq, rownames(mysum$coefficients)[i], sep='')
+ if (rownames(mysum$coefficients)[i] != 't') myeq <- paste(myeq, '[t]', sep='')
+ }
+ }
> myeq <- paste(myeq, ' + e[t]')
> a<-table.row.start(a)
> a<-table.element(a, myeq)
> a<-table.row.end(a)
> a<-table.end(a)
> table.save(a,file="/var/wessaorg/rcomp/tmp/11fkxh1355777553.tab")
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a,hyperlink('http://www.xycoon.com/ols1.htm','Multiple Linear Regression - Ordinary Least Squares',''), 6, TRUE)
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a,'Variable',header=TRUE)
> a<-table.element(a,'Parameter',header=TRUE)
> a<-table.element(a,'S.D.',header=TRUE)
> a<-table.element(a,'T-STAT
H0: parameter = 0',header=TRUE)
> a<-table.element(a,'2-tail p-value',header=TRUE)
> a<-table.element(a,'1-tail p-value',header=TRUE)
> a<-table.row.end(a)
> for (i in 1:k){
+ a<-table.row.start(a)
+ a<-table.element(a,rownames(mysum$coefficients)[i],header=TRUE)
+ a<-table.element(a,mysum$coefficients[i,1])
+ a<-table.element(a, round(mysum$coefficients[i,2],6))
+ a<-table.element(a, round(mysum$coefficients[i,3],4))
+ a<-table.element(a, round(mysum$coefficients[i,4],6))
+ a<-table.element(a, round(mysum$coefficients[i,4]/2,6))
+ a<-table.row.end(a)
+ }
> a<-table.end(a)
> table.save(a,file="/var/wessaorg/rcomp/tmp/122guw1355777553.tab")
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a, 'Multiple Linear Regression - Regression Statistics', 2, TRUE)
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a, 'Multiple R',1,TRUE)
> a<-table.element(a, sqrt(mysum$r.squared))
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a, 'R-squared',1,TRUE)
> a<-table.element(a, mysum$r.squared)
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a, 'Adjusted R-squared',1,TRUE)
> a<-table.element(a, mysum$adj.r.squared)
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a, 'F-TEST (value)',1,TRUE)
> a<-table.element(a, mysum$fstatistic[1])
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a, 'F-TEST (DF numerator)',1,TRUE)
> a<-table.element(a, mysum$fstatistic[2])
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a, 'F-TEST (DF denominator)',1,TRUE)
> a<-table.element(a, mysum$fstatistic[3])
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a, 'p-value',1,TRUE)
> a<-table.element(a, 1-pf(mysum$fstatistic[1],mysum$fstatistic[2],mysum$fstatistic[3]))
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a, 'Multiple Linear Regression - Residual Statistics', 2, TRUE)
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a, 'Residual Standard Deviation',1,TRUE)
> a<-table.element(a, mysum$sigma)
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a, 'Sum Squared Residuals',1,TRUE)
> a<-table.element(a, sum(myerror*myerror))
> a<-table.row.end(a)
> a<-table.end(a)
> table.save(a,file="/var/wessaorg/rcomp/tmp/13yzqt1355777553.tab")
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a, 'Multiple Linear Regression - Actuals, Interpolation, and Residuals', 4, TRUE)
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a, 'Time or Index', 1, TRUE)
> a<-table.element(a, 'Actuals', 1, TRUE)
> a<-table.element(a, 'Interpolation
Forecast', 1, TRUE)
> a<-table.element(a, 'Residuals
Prediction Error', 1, TRUE)
> a<-table.row.end(a)
> for (i in 1:n) {
+ a<-table.row.start(a)
+ a<-table.element(a,i, 1, TRUE)
+ a<-table.element(a,x[i])
+ a<-table.element(a,x[i]-mysum$resid[i])
+ a<-table.element(a,mysum$resid[i])
+ a<-table.row.end(a)
+ }
> a<-table.end(a)
> table.save(a,file="/var/wessaorg/rcomp/tmp/148zcg1355777553.tab")
> if (n > n25) {
+ a<-table.start()
+ a<-table.row.start(a)
+ a<-table.element(a,'Goldfeld-Quandt test for Heteroskedasticity',4,TRUE)
+ a<-table.row.end(a)
+ a<-table.row.start(a)
+ a<-table.element(a,'p-values',header=TRUE)
+ a<-table.element(a,'Alternative Hypothesis',3,header=TRUE)
+ a<-table.row.end(a)
+ a<-table.row.start(a)
+ a<-table.element(a,'breakpoint index',header=TRUE)
+ a<-table.element(a,'greater',header=TRUE)
+ a<-table.element(a,'2-sided',header=TRUE)
+ a<-table.element(a,'less',header=TRUE)
+ a<-table.row.end(a)
+ for (mypoint in kp3:nmkm3) {
+ a<-table.row.start(a)
+ a<-table.element(a,mypoint,header=TRUE)
+ a<-table.element(a,gqarr[mypoint-kp3+1,1])
+ a<-table.element(a,gqarr[mypoint-kp3+1,2])
+ a<-table.element(a,gqarr[mypoint-kp3+1,3])
+ a<-table.row.end(a)
+ }
+ a<-table.end(a)
+ table.save(a,file="/var/wessaorg/rcomp/tmp/151he81355777553.tab")
+ a<-table.start()
+ a<-table.row.start(a)
+ a<-table.element(a,'Meta Analysis of Goldfeld-Quandt test for Heteroskedasticity',4,TRUE)
+ a<-table.row.end(a)
+ a<-table.row.start(a)
+ a<-table.element(a,'Description',header=TRUE)
+ a<-table.element(a,'# significant tests',header=TRUE)
+ a<-table.element(a,'% significant tests',header=TRUE)
+ a<-table.element(a,'OK/NOK',header=TRUE)
+ a<-table.row.end(a)
+ a<-table.row.start(a)
+ a<-table.element(a,'1% type I error level',header=TRUE)
+ a<-table.element(a,numsignificant1)
+ a<-table.element(a,numsignificant1/numgqtests)
+ if (numsignificant1/numgqtests < 0.01) dum <- 'OK' else dum <- 'NOK'
+ a<-table.element(a,dum)
+ a<-table.row.end(a)
+ a<-table.row.start(a)
+ a<-table.element(a,'5% type I error level',header=TRUE)
+ a<-table.element(a,numsignificant5)
+ a<-table.element(a,numsignificant5/numgqtests)
+ if (numsignificant5/numgqtests < 0.05) dum <- 'OK' else dum <- 'NOK'
+ a<-table.element(a,dum)
+ a<-table.row.end(a)
+ a<-table.row.start(a)
+ a<-table.element(a,'10% type I error level',header=TRUE)
+ a<-table.element(a,numsignificant10)
+ a<-table.element(a,numsignificant10/numgqtests)
+ if (numsignificant10/numgqtests < 0.1) dum <- 'OK' else dum <- 'NOK'
+ a<-table.element(a,dum)
+ a<-table.row.end(a)
+ a<-table.end(a)
+ table.save(a,file="/var/wessaorg/rcomp/tmp/16qsq91355777553.tab")
+ }
>
> try(system("convert tmp/1ati61355777552.ps tmp/1ati61355777552.png",intern=TRUE))
character(0)
> try(system("convert tmp/23bnf1355777552.ps tmp/23bnf1355777552.png",intern=TRUE))
character(0)
> try(system("convert tmp/3a80n1355777552.ps tmp/3a80n1355777552.png",intern=TRUE))
character(0)
> try(system("convert tmp/4bn8f1355777552.ps tmp/4bn8f1355777552.png",intern=TRUE))
character(0)
> try(system("convert tmp/5yo6v1355777552.ps tmp/5yo6v1355777552.png",intern=TRUE))
character(0)
> try(system("convert tmp/6yz9b1355777552.ps tmp/6yz9b1355777552.png",intern=TRUE))
character(0)
> try(system("convert tmp/7qzi31355777553.ps tmp/7qzi31355777553.png",intern=TRUE))
character(0)
> try(system("convert tmp/8u2rl1355777553.ps tmp/8u2rl1355777553.png",intern=TRUE))
character(0)
> try(system("convert tmp/9xqzv1355777553.ps tmp/9xqzv1355777553.png",intern=TRUE))
character(0)
> try(system("convert tmp/10n3of1355777553.ps tmp/10n3of1355777553.png",intern=TRUE))
character(0)
>
>
> proc.time()
user system elapsed
7.057 1.192 8.344