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.
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Type 'license()' or 'licence()' for distribution details.
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Type 'contributors()' for more information and
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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(100.01
+ ,0
+ ,103.84
+ ,0
+ ,104.48
+ ,0
+ ,95.43
+ ,0
+ ,104.80
+ ,0
+ ,108.64
+ ,0
+ ,105.65
+ ,0
+ ,108.42
+ ,0
+ ,115.35
+ ,0
+ ,113.64
+ ,0
+ ,115.24
+ ,0
+ ,100.33
+ ,0
+ ,101.29
+ ,0
+ ,104.48
+ ,0
+ ,99.26
+ ,0
+ ,100.11
+ ,0
+ ,103.52
+ ,0
+ ,101.18
+ ,0
+ ,96.39
+ ,0
+ ,97.56
+ ,0
+ ,96.39
+ ,0
+ ,85.10
+ ,0
+ ,79.77
+ ,0
+ ,79.13
+ ,0
+ ,80.84
+ ,0
+ ,82.75
+ ,0
+ ,92.55
+ ,0
+ ,96.60
+ ,0
+ ,96.92
+ ,0
+ ,95.32
+ ,0
+ ,98.52
+ ,0
+ ,100.22
+ ,0
+ ,104.91
+ ,0
+ ,103.10
+ ,0
+ ,97.13
+ ,0
+ ,103.42
+ ,0
+ ,111.72
+ ,0
+ ,118.11
+ ,0
+ ,111.62
+ ,0
+ ,100.22
+ ,0
+ ,102.03
+ ,0
+ ,105.76
+ ,0
+ ,107.68
+ ,0
+ ,110.77
+ ,0
+ ,105.44
+ ,0
+ ,112.26
+ ,0
+ ,114.07
+ ,0
+ ,117.90
+ ,0
+ ,124.72
+ ,0
+ ,126.42
+ ,0
+ ,134.73
+ ,0
+ ,135.79
+ ,0
+ ,143.36
+ ,0
+ ,140.37
+ ,0
+ ,144.74
+ ,0
+ ,151.98
+ ,0
+ ,150.92
+ ,0
+ ,163.38
+ ,0
+ ,154.43
+ ,0
+ ,146.66
+ ,0
+ ,157.95
+ ,0
+ ,162.10
+ ,0
+ ,180.42
+ ,0
+ ,179.57
+ ,0
+ ,171.58
+ ,0
+ ,185.43
+ ,0
+ ,190.64
+ ,0
+ ,203.00
+ ,0
+ ,202.36
+ ,0
+ ,193.41
+ ,0
+ ,186.17
+ ,0
+ ,192.24
+ ,0
+ ,209.60
+ ,0
+ ,206.41
+ ,0
+ ,209.82
+ ,0
+ ,230.37
+ ,0
+ ,235.80
+ ,0
+ ,232.07
+ ,0
+ ,244.64
+ ,0
+ ,242.19
+ ,0
+ ,217.48
+ ,0
+ ,209.39
+ ,0
+ ,211.73
+ ,0
+ ,221.00
+ ,0
+ ,203.11
+ ,0
+ ,214.71
+ ,0
+ ,224.19
+ ,0
+ ,238.04
+ ,0
+ ,238.36
+ ,0
+ ,246.24
+ ,0
+ ,259.87
+ ,0
+ ,249.97
+ ,0
+ ,266.48
+ ,0
+ ,282.98
+ ,0
+ ,306.31
+ ,0
+ ,301.73
+ ,1
+ ,314.62
+ ,1
+ ,332.62
+ ,1
+ ,355.51
+ ,1
+ ,370.32
+ ,1
+ ,408.13
+ ,1
+ ,433.58
+ ,1
+ ,440.51
+ ,1
+ ,386.29
+ ,1
+ ,342.84
+ ,1
+ ,254.97
+ ,1
+ ,203.42
+ ,1
+ ,170.09
+ ,1
+ ,174.03
+ ,1
+ ,167.85
+ ,1
+ ,177.01
+ ,1
+ ,188.19
+ ,1
+ ,211.20
+ ,1
+ ,240.91
+ ,1
+ ,230.26
+ ,1
+ ,251.25
+ ,1
+ ,241.66
+ ,1)
+ ,dim=c(2
+ ,117)
+ ,dimnames=list(c('Y'
+ ,'X')
+ ,1:117))
> y <- array(NA,dim=c(2,117),dimnames=list(c('Y','X'),1:117))
> 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
1 100.01 0 1 0 0 0 0 0 0 0 0 0 0
2 103.84 0 0 1 0 0 0 0 0 0 0 0 0
3 104.48 0 0 0 1 0 0 0 0 0 0 0 0
4 95.43 0 0 0 0 1 0 0 0 0 0 0 0
5 104.80 0 0 0 0 0 1 0 0 0 0 0 0
6 108.64 0 0 0 0 0 0 1 0 0 0 0 0
7 105.65 0 0 0 0 0 0 0 1 0 0 0 0
8 108.42 0 0 0 0 0 0 0 0 1 0 0 0
9 115.35 0 0 0 0 0 0 0 0 0 1 0 0
10 113.64 0 0 0 0 0 0 0 0 0 0 1 0
11 115.24 0 0 0 0 0 0 0 0 0 0 0 1
12 100.33 0 0 0 0 0 0 0 0 0 0 0 0
13 101.29 0 1 0 0 0 0 0 0 0 0 0 0
14 104.48 0 0 1 0 0 0 0 0 0 0 0 0
15 99.26 0 0 0 1 0 0 0 0 0 0 0 0
16 100.11 0 0 0 0 1 0 0 0 0 0 0 0
17 103.52 0 0 0 0 0 1 0 0 0 0 0 0
18 101.18 0 0 0 0 0 0 1 0 0 0 0 0
19 96.39 0 0 0 0 0 0 0 1 0 0 0 0
20 97.56 0 0 0 0 0 0 0 0 1 0 0 0
21 96.39 0 0 0 0 0 0 0 0 0 1 0 0
22 85.10 0 0 0 0 0 0 0 0 0 0 1 0
23 79.77 0 0 0 0 0 0 0 0 0 0 0 1
24 79.13 0 0 0 0 0 0 0 0 0 0 0 0
25 80.84 0 1 0 0 0 0 0 0 0 0 0 0
26 82.75 0 0 1 0 0 0 0 0 0 0 0 0
27 92.55 0 0 0 1 0 0 0 0 0 0 0 0
28 96.60 0 0 0 0 1 0 0 0 0 0 0 0
29 96.92 0 0 0 0 0 1 0 0 0 0 0 0
30 95.32 0 0 0 0 0 0 1 0 0 0 0 0
31 98.52 0 0 0 0 0 0 0 1 0 0 0 0
32 100.22 0 0 0 0 0 0 0 0 1 0 0 0
33 104.91 0 0 0 0 0 0 0 0 0 1 0 0
34 103.10 0 0 0 0 0 0 0 0 0 0 1 0
35 97.13 0 0 0 0 0 0 0 0 0 0 0 1
36 103.42 0 0 0 0 0 0 0 0 0 0 0 0
37 111.72 0 1 0 0 0 0 0 0 0 0 0 0
38 118.11 0 0 1 0 0 0 0 0 0 0 0 0
39 111.62 0 0 0 1 0 0 0 0 0 0 0 0
40 100.22 0 0 0 0 1 0 0 0 0 0 0 0
41 102.03 0 0 0 0 0 1 0 0 0 0 0 0
42 105.76 0 0 0 0 0 0 1 0 0 0 0 0
43 107.68 0 0 0 0 0 0 0 1 0 0 0 0
44 110.77 0 0 0 0 0 0 0 0 1 0 0 0
45 105.44 0 0 0 0 0 0 0 0 0 1 0 0
46 112.26 0 0 0 0 0 0 0 0 0 0 1 0
47 114.07 0 0 0 0 0 0 0 0 0 0 0 1
48 117.90 0 0 0 0 0 0 0 0 0 0 0 0
49 124.72 0 1 0 0 0 0 0 0 0 0 0 0
50 126.42 0 0 1 0 0 0 0 0 0 0 0 0
51 134.73 0 0 0 1 0 0 0 0 0 0 0 0
52 135.79 0 0 0 0 1 0 0 0 0 0 0 0
53 143.36 0 0 0 0 0 1 0 0 0 0 0 0
54 140.37 0 0 0 0 0 0 1 0 0 0 0 0
55 144.74 0 0 0 0 0 0 0 1 0 0 0 0
56 151.98 0 0 0 0 0 0 0 0 1 0 0 0
57 150.92 0 0 0 0 0 0 0 0 0 1 0 0
58 163.38 0 0 0 0 0 0 0 0 0 0 1 0
59 154.43 0 0 0 0 0 0 0 0 0 0 0 1
60 146.66 0 0 0 0 0 0 0 0 0 0 0 0
61 157.95 0 1 0 0 0 0 0 0 0 0 0 0
62 162.10 0 0 1 0 0 0 0 0 0 0 0 0
63 180.42 0 0 0 1 0 0 0 0 0 0 0 0
64 179.57 0 0 0 0 1 0 0 0 0 0 0 0
65 171.58 0 0 0 0 0 1 0 0 0 0 0 0
66 185.43 0 0 0 0 0 0 1 0 0 0 0 0
67 190.64 0 0 0 0 0 0 0 1 0 0 0 0
68 203.00 0 0 0 0 0 0 0 0 1 0 0 0
69 202.36 0 0 0 0 0 0 0 0 0 1 0 0
70 193.41 0 0 0 0 0 0 0 0 0 0 1 0
71 186.17 0 0 0 0 0 0 0 0 0 0 0 1
72 192.24 0 0 0 0 0 0 0 0 0 0 0 0
73 209.60 0 1 0 0 0 0 0 0 0 0 0 0
74 206.41 0 0 1 0 0 0 0 0 0 0 0 0
75 209.82 0 0 0 1 0 0 0 0 0 0 0 0
76 230.37 0 0 0 0 1 0 0 0 0 0 0 0
77 235.80 0 0 0 0 0 1 0 0 0 0 0 0
78 232.07 0 0 0 0 0 0 1 0 0 0 0 0
79 244.64 0 0 0 0 0 0 0 1 0 0 0 0
80 242.19 0 0 0 0 0 0 0 0 1 0 0 0
81 217.48 0 0 0 0 0 0 0 0 0 1 0 0
82 209.39 0 0 0 0 0 0 0 0 0 0 1 0
83 211.73 0 0 0 0 0 0 0 0 0 0 0 1
84 221.00 0 0 0 0 0 0 0 0 0 0 0 0
85 203.11 0 1 0 0 0 0 0 0 0 0 0 0
86 214.71 0 0 1 0 0 0 0 0 0 0 0 0
87 224.19 0 0 0 1 0 0 0 0 0 0 0 0
88 238.04 0 0 0 0 1 0 0 0 0 0 0 0
89 238.36 0 0 0 0 0 1 0 0 0 0 0 0
90 246.24 0 0 0 0 0 0 1 0 0 0 0 0
91 259.87 0 0 0 0 0 0 0 1 0 0 0 0
92 249.97 0 0 0 0 0 0 0 0 1 0 0 0
93 266.48 0 0 0 0 0 0 0 0 0 1 0 0
94 282.98 0 0 0 0 0 0 0 0 0 0 1 0
95 306.31 0 0 0 0 0 0 0 0 0 0 0 1
96 301.73 1 0 0 0 0 0 0 0 0 0 0 0
97 314.62 1 1 0 0 0 0 0 0 0 0 0 0
98 332.62 1 0 1 0 0 0 0 0 0 0 0 0
99 355.51 1 0 0 1 0 0 0 0 0 0 0 0
100 370.32 1 0 0 0 1 0 0 0 0 0 0 0
101 408.13 1 0 0 0 0 1 0 0 0 0 0 0
102 433.58 1 0 0 0 0 0 1 0 0 0 0 0
103 440.51 1 0 0 0 0 0 0 1 0 0 0 0
104 386.29 1 0 0 0 0 0 0 0 1 0 0 0
105 342.84 1 0 0 0 0 0 0 0 0 1 0 0
106 254.97 1 0 0 0 0 0 0 0 0 0 1 0
107 203.42 1 0 0 0 0 0 0 0 0 0 0 1
108 170.09 1 0 0 0 0 0 0 0 0 0 0 0
109 174.03 1 1 0 0 0 0 0 0 0 0 0 0
110 167.85 1 0 1 0 0 0 0 0 0 0 0 0
111 177.01 1 0 0 1 0 0 0 0 0 0 0 0
112 188.19 1 0 0 0 1 0 0 0 0 0 0 0
113 211.20 1 0 0 0 0 1 0 0 0 0 0 0
114 240.91 1 0 0 0 0 0 1 0 0 0 0 0
115 230.26 1 0 0 0 0 0 0 1 0 0 0 0
116 251.25 1 0 0 0 0 0 0 0 1 0 0 0
117 241.66 1 0 0 0 0 0 0 0 0 1 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
129.735 132.441 1.565 5.705 12.735 17.240
M5 M6 M7 M8 M9 M10
25.346 32.726 35.666 33.941 28.159 24.241
M11
18.690
> (mysum <- summary(mylm))
Call:
lm(formula = df)
Residuals:
Min 1Q Median 3Q Max
-100.03 -51.56 -20.66 59.59 157.88
Coefficients:
Estimate Std. Error t value Pr(>|t|)
(Intercept) 129.735 22.652 5.727 9.99e-08 ***
X 132.441 15.939 8.309 3.87e-13 ***
M1 1.565 30.842 0.051 0.960
M2 5.705 30.842 0.185 0.854
M3 12.735 30.842 0.413 0.681
M4 17.240 30.842 0.559 0.577
M5 25.346 30.842 0.822 0.413
M6 32.726 30.842 1.061 0.291
M7 35.666 30.842 1.156 0.250
M8 33.941 30.842 1.100 0.274
M9 28.159 30.842 0.913 0.363
M10 24.241 31.691 0.765 0.446
M11 18.690 31.691 0.590 0.557
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
Residual standard error: 67.12 on 104 degrees of freedom
Multiple R-squared: 0.4121, Adjusted R-squared: 0.3442
F-statistic: 6.074 on 12 and 104 DF, p-value: 5.795e-08
> 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,] 1.005686e-04 2.011372e-04 0.9998994
[2,] 3.666482e-06 7.332965e-06 0.9999963
[3,] 7.046308e-07 1.409262e-06 0.9999993
[4,] 1.724347e-07 3.448694e-07 0.9999998
[5,] 4.846534e-08 9.693068e-08 1.0000000
[6,] 6.538854e-08 1.307771e-07 0.9999999
[7,] 2.034307e-07 4.068614e-07 0.9999998
[8,] 5.313743e-07 1.062749e-06 0.9999995
[9,] 1.959228e-07 3.918455e-07 0.9999998
[10,] 8.133791e-08 1.626758e-07 0.9999999
[11,] 3.820523e-08 7.641046e-08 1.0000000
[12,] 8.626741e-09 1.725348e-08 1.0000000
[13,] 1.627362e-09 3.254724e-09 1.0000000
[14,] 3.482343e-10 6.964686e-10 1.0000000
[15,] 8.573287e-11 1.714657e-10 1.0000000
[16,] 1.749713e-11 3.499426e-11 1.0000000
[17,] 3.510331e-12 7.020662e-12 1.0000000
[18,] 6.475071e-13 1.295014e-12 1.0000000
[19,] 1.219301e-13 2.438602e-13 1.0000000
[20,] 2.184296e-14 4.368592e-14 1.0000000
[21,] 6.195921e-15 1.239184e-14 1.0000000
[22,] 2.827498e-15 5.654996e-15 1.0000000
[23,] 1.873493e-15 3.746987e-15 1.0000000
[24,] 5.625622e-16 1.125124e-15 1.0000000
[25,] 1.202164e-16 2.404329e-16 1.0000000
[26,] 2.715587e-17 5.431174e-17 1.0000000
[27,] 7.107721e-18 1.421544e-17 1.0000000
[28,] 2.295519e-18 4.591037e-18 1.0000000
[29,] 7.745840e-19 1.549168e-18 1.0000000
[30,] 1.995622e-19 3.991245e-19 1.0000000
[31,] 7.571496e-20 1.514299e-19 1.0000000
[32,] 4.414488e-20 8.828976e-20 1.0000000
[33,] 5.148062e-20 1.029612e-19 1.0000000
[34,] 9.017349e-20 1.803470e-19 1.0000000
[35,] 1.028044e-19 2.056088e-19 1.0000000
[36,] 3.900911e-19 7.801823e-19 1.0000000
[37,] 2.625877e-18 5.251753e-18 1.0000000
[38,] 2.237852e-17 4.475705e-17 1.0000000
[39,] 1.024158e-16 2.048317e-16 1.0000000
[40,] 7.311882e-16 1.462376e-15 1.0000000
[41,] 5.992130e-15 1.198426e-14 1.0000000
[42,] 2.541644e-14 5.083289e-14 1.0000000
[43,] 2.840089e-13 5.680177e-13 1.0000000
[44,] 1.100507e-12 2.201014e-12 1.0000000
[45,] 1.990535e-12 3.981070e-12 1.0000000
[46,] 5.698778e-12 1.139756e-11 1.0000000
[47,] 1.459405e-11 2.918809e-11 1.0000000
[48,] 9.738726e-11 1.947745e-10 1.0000000
[49,] 5.692964e-10 1.138593e-09 1.0000000
[50,] 1.621360e-09 3.242721e-09 1.0000000
[51,] 8.311497e-09 1.662299e-08 1.0000000
[52,] 4.381665e-08 8.763330e-08 1.0000000
[53,] 2.152201e-07 4.304401e-07 0.9999998
[54,] 6.832753e-07 1.366551e-06 0.9999993
[55,] 1.280984e-06 2.561968e-06 0.9999987
[56,] 1.947652e-06 3.895304e-06 0.9999981
[57,] 3.160641e-06 6.321282e-06 0.9999968
[58,] 7.193286e-06 1.438657e-05 0.9999928
[59,] 1.170157e-05 2.340314e-05 0.9999883
[60,] 1.713381e-05 3.426762e-05 0.9999829
[61,] 3.895887e-05 7.791773e-05 0.9999610
[62,] 8.148951e-05 1.629790e-04 0.9999185
[63,] 1.439589e-04 2.879179e-04 0.9998560
[64,] 2.689987e-04 5.379974e-04 0.9997310
[65,] 3.827332e-04 7.654663e-04 0.9996173
[66,] 3.870452e-04 7.740904e-04 0.9996130
[67,] 3.509150e-04 7.018300e-04 0.9996491
[68,] 3.143374e-04 6.286747e-04 0.9996857
[69,] 3.031828e-04 6.063655e-04 0.9996968
[70,] 2.269966e-04 4.539933e-04 0.9997730
[71,] 1.797029e-04 3.594057e-04 0.9998203
[72,] 1.455892e-04 2.911783e-04 0.9998544
[73,] 1.302030e-04 2.604060e-04 0.9998698
[74,] 1.173799e-04 2.347597e-04 0.9998826
[75,] 1.275398e-04 2.550795e-04 0.9998725
[76,] 1.467661e-04 2.935321e-04 0.9998532
[77,] 1.593048e-04 3.186096e-04 0.9998407
[78,] 1.781618e-04 3.563236e-04 0.9998218
[79,] 1.897367e-04 3.794734e-04 0.9998103
[80,] 2.142269e-04 4.284537e-04 0.9997858
[81,] 1.847583e-04 3.695166e-04 0.9998152
[82,] 1.757076e-04 3.514151e-04 0.9998243
[83,] 2.334928e-04 4.669855e-04 0.9997665
[84,] 4.070900e-04 8.141801e-04 0.9995929
[85,] 8.131324e-04 1.626265e-03 0.9991869
[86,] 2.504272e-03 5.008544e-03 0.9974957
> postscript(file="/var/www/html/rcomp/tmp/1gfbb1258726527.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$resid)
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/2bha21258726527.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> plot(mysum$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/3hwx21258726527.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> hist(mysum$resid, main='Residual Histogram', xlab='values of Residuals')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/46c8v1258726527.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> densityplot(~mysum$resid,col='black',main='Residual Density Plot', xlab='values of Residuals')
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/5xd2v1258726527.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 = 117
Frequency = 1
1 2 3 4 5 6
-31.290744 -31.600744 -37.990744 -51.545744 -50.281744 -53.821744
7 8 9 10 11 12
-59.751744 -55.256744 -42.544744 -40.336525 -33.185414 -29.405272
13 14 15 16 17 18
-30.010744 -30.960744 -43.210744 -46.865744 -51.561744 -61.281744
19 20 21 22 23 24
-69.011744 -66.116744 -61.504744 -68.876525 -68.655414 -50.605272
25 26 27 28 29 30
-50.460744 -52.690744 -49.920744 -50.375744 -58.161744 -67.141744
31 32 33 34 35 36
-66.881744 -63.456744 -52.984744 -50.876525 -51.295414 -26.315272
37 38 39 40 41 42
-19.580744 -17.330744 -30.850744 -46.755744 -53.051744 -56.701744
43 44 45 46 47 48
-57.721744 -52.906744 -52.454744 -41.716525 -34.355414 -11.835272
49 50 51 52 53 54
-6.580744 -9.020744 -7.740744 -11.185744 -11.721744 -22.091744
55 56 57 58 59 60
-20.661744 -11.696744 -6.974744 9.403475 6.004586 16.924728
61 62 63 64 65 66
26.649256 26.659256 37.949256 32.594256 16.498256 22.968256
67 68 69 70 71 72
25.238256 39.323256 44.465256 39.433475 37.744586 62.504728
73 74 75 76 77 78
78.299256 70.969256 67.349256 83.394256 80.718256 69.608256
79 80 81 82 83 84
79.238256 78.513256 59.585256 55.413475 63.304586 91.264728
85 86 87 88 89 90
71.809256 79.269256 81.719256 91.064256 83.278256 83.778256
91 92 93 94 95 96
94.468256 86.293256 108.585256 129.003475 157.884586 39.553450
97 98 99 100 101 102
50.877977 64.737977 80.597977 90.902977 120.606977 138.676977
103 104 105 106 107 108
142.666977 90.171977 52.503977 -31.447803 -77.446692 -92.086550
109 110 111 112 113 114
-89.712023 -100.032023 -97.902023 -91.227023 -76.323023 -53.993023
115 116 117
-67.583023 -44.868023 -48.676023
> postscript(file="/var/www/html/rcomp/tmp/63iqi1258726527.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 = 117
Frequency = 1
lag(myerror, k = 1) myerror
0 -31.290744 NA
1 -31.600744 -31.290744
2 -37.990744 -31.600744
3 -51.545744 -37.990744
4 -50.281744 -51.545744
5 -53.821744 -50.281744
6 -59.751744 -53.821744
7 -55.256744 -59.751744
8 -42.544744 -55.256744
9 -40.336525 -42.544744
10 -33.185414 -40.336525
11 -29.405272 -33.185414
12 -30.010744 -29.405272
13 -30.960744 -30.010744
14 -43.210744 -30.960744
15 -46.865744 -43.210744
16 -51.561744 -46.865744
17 -61.281744 -51.561744
18 -69.011744 -61.281744
19 -66.116744 -69.011744
20 -61.504744 -66.116744
21 -68.876525 -61.504744
22 -68.655414 -68.876525
23 -50.605272 -68.655414
24 -50.460744 -50.605272
25 -52.690744 -50.460744
26 -49.920744 -52.690744
27 -50.375744 -49.920744
28 -58.161744 -50.375744
29 -67.141744 -58.161744
30 -66.881744 -67.141744
31 -63.456744 -66.881744
32 -52.984744 -63.456744
33 -50.876525 -52.984744
34 -51.295414 -50.876525
35 -26.315272 -51.295414
36 -19.580744 -26.315272
37 -17.330744 -19.580744
38 -30.850744 -17.330744
39 -46.755744 -30.850744
40 -53.051744 -46.755744
41 -56.701744 -53.051744
42 -57.721744 -56.701744
43 -52.906744 -57.721744
44 -52.454744 -52.906744
45 -41.716525 -52.454744
46 -34.355414 -41.716525
47 -11.835272 -34.355414
48 -6.580744 -11.835272
49 -9.020744 -6.580744
50 -7.740744 -9.020744
51 -11.185744 -7.740744
52 -11.721744 -11.185744
53 -22.091744 -11.721744
54 -20.661744 -22.091744
55 -11.696744 -20.661744
56 -6.974744 -11.696744
57 9.403475 -6.974744
58 6.004586 9.403475
59 16.924728 6.004586
60 26.649256 16.924728
61 26.659256 26.649256
62 37.949256 26.659256
63 32.594256 37.949256
64 16.498256 32.594256
65 22.968256 16.498256
66 25.238256 22.968256
67 39.323256 25.238256
68 44.465256 39.323256
69 39.433475 44.465256
70 37.744586 39.433475
71 62.504728 37.744586
72 78.299256 62.504728
73 70.969256 78.299256
74 67.349256 70.969256
75 83.394256 67.349256
76 80.718256 83.394256
77 69.608256 80.718256
78 79.238256 69.608256
79 78.513256 79.238256
80 59.585256 78.513256
81 55.413475 59.585256
82 63.304586 55.413475
83 91.264728 63.304586
84 71.809256 91.264728
85 79.269256 71.809256
86 81.719256 79.269256
87 91.064256 81.719256
88 83.278256 91.064256
89 83.778256 83.278256
90 94.468256 83.778256
91 86.293256 94.468256
92 108.585256 86.293256
93 129.003475 108.585256
94 157.884586 129.003475
95 39.553450 157.884586
96 50.877977 39.553450
97 64.737977 50.877977
98 80.597977 64.737977
99 90.902977 80.597977
100 120.606977 90.902977
101 138.676977 120.606977
102 142.666977 138.676977
103 90.171977 142.666977
104 52.503977 90.171977
105 -31.447803 52.503977
106 -77.446692 -31.447803
107 -92.086550 -77.446692
108 -89.712023 -92.086550
109 -100.032023 -89.712023
110 -97.902023 -100.032023
111 -91.227023 -97.902023
112 -76.323023 -91.227023
113 -53.993023 -76.323023
114 -67.583023 -53.993023
115 -44.868023 -67.583023
116 -48.676023 -44.868023
117 NA -48.676023
> dum1 <- dum[2:length(myerror),]
> dum1
lag(myerror, k = 1) myerror
[1,] -31.600744 -31.290744
[2,] -37.990744 -31.600744
[3,] -51.545744 -37.990744
[4,] -50.281744 -51.545744
[5,] -53.821744 -50.281744
[6,] -59.751744 -53.821744
[7,] -55.256744 -59.751744
[8,] -42.544744 -55.256744
[9,] -40.336525 -42.544744
[10,] -33.185414 -40.336525
[11,] -29.405272 -33.185414
[12,] -30.010744 -29.405272
[13,] -30.960744 -30.010744
[14,] -43.210744 -30.960744
[15,] -46.865744 -43.210744
[16,] -51.561744 -46.865744
[17,] -61.281744 -51.561744
[18,] -69.011744 -61.281744
[19,] -66.116744 -69.011744
[20,] -61.504744 -66.116744
[21,] -68.876525 -61.504744
[22,] -68.655414 -68.876525
[23,] -50.605272 -68.655414
[24,] -50.460744 -50.605272
[25,] -52.690744 -50.460744
[26,] -49.920744 -52.690744
[27,] -50.375744 -49.920744
[28,] -58.161744 -50.375744
[29,] -67.141744 -58.161744
[30,] -66.881744 -67.141744
[31,] -63.456744 -66.881744
[32,] -52.984744 -63.456744
[33,] -50.876525 -52.984744
[34,] -51.295414 -50.876525
[35,] -26.315272 -51.295414
[36,] -19.580744 -26.315272
[37,] -17.330744 -19.580744
[38,] -30.850744 -17.330744
[39,] -46.755744 -30.850744
[40,] -53.051744 -46.755744
[41,] -56.701744 -53.051744
[42,] -57.721744 -56.701744
[43,] -52.906744 -57.721744
[44,] -52.454744 -52.906744
[45,] -41.716525 -52.454744
[46,] -34.355414 -41.716525
[47,] -11.835272 -34.355414
[48,] -6.580744 -11.835272
[49,] -9.020744 -6.580744
[50,] -7.740744 -9.020744
[51,] -11.185744 -7.740744
[52,] -11.721744 -11.185744
[53,] -22.091744 -11.721744
[54,] -20.661744 -22.091744
[55,] -11.696744 -20.661744
[56,] -6.974744 -11.696744
[57,] 9.403475 -6.974744
[58,] 6.004586 9.403475
[59,] 16.924728 6.004586
[60,] 26.649256 16.924728
[61,] 26.659256 26.649256
[62,] 37.949256 26.659256
[63,] 32.594256 37.949256
[64,] 16.498256 32.594256
[65,] 22.968256 16.498256
[66,] 25.238256 22.968256
[67,] 39.323256 25.238256
[68,] 44.465256 39.323256
[69,] 39.433475 44.465256
[70,] 37.744586 39.433475
[71,] 62.504728 37.744586
[72,] 78.299256 62.504728
[73,] 70.969256 78.299256
[74,] 67.349256 70.969256
[75,] 83.394256 67.349256
[76,] 80.718256 83.394256
[77,] 69.608256 80.718256
[78,] 79.238256 69.608256
[79,] 78.513256 79.238256
[80,] 59.585256 78.513256
[81,] 55.413475 59.585256
[82,] 63.304586 55.413475
[83,] 91.264728 63.304586
[84,] 71.809256 91.264728
[85,] 79.269256 71.809256
[86,] 81.719256 79.269256
[87,] 91.064256 81.719256
[88,] 83.278256 91.064256
[89,] 83.778256 83.278256
[90,] 94.468256 83.778256
[91,] 86.293256 94.468256
[92,] 108.585256 86.293256
[93,] 129.003475 108.585256
[94,] 157.884586 129.003475
[95,] 39.553450 157.884586
[96,] 50.877977 39.553450
[97,] 64.737977 50.877977
[98,] 80.597977 64.737977
[99,] 90.902977 80.597977
[100,] 120.606977 90.902977
[101,] 138.676977 120.606977
[102,] 142.666977 138.676977
[103,] 90.171977 142.666977
[104,] 52.503977 90.171977
[105,] -31.447803 52.503977
[106,] -77.446692 -31.447803
[107,] -92.086550 -77.446692
[108,] -89.712023 -92.086550
[109,] -100.032023 -89.712023
[110,] -97.902023 -100.032023
[111,] -91.227023 -97.902023
[112,] -76.323023 -91.227023
[113,] -53.993023 -76.323023
[114,] -67.583023 -53.993023
[115,] -44.868023 -67.583023
[116,] -48.676023 -44.868023
> z <- as.data.frame(dum1)
> z
lag(myerror, k = 1) myerror
1 -31.600744 -31.290744
2 -37.990744 -31.600744
3 -51.545744 -37.990744
4 -50.281744 -51.545744
5 -53.821744 -50.281744
6 -59.751744 -53.821744
7 -55.256744 -59.751744
8 -42.544744 -55.256744
9 -40.336525 -42.544744
10 -33.185414 -40.336525
11 -29.405272 -33.185414
12 -30.010744 -29.405272
13 -30.960744 -30.010744
14 -43.210744 -30.960744
15 -46.865744 -43.210744
16 -51.561744 -46.865744
17 -61.281744 -51.561744
18 -69.011744 -61.281744
19 -66.116744 -69.011744
20 -61.504744 -66.116744
21 -68.876525 -61.504744
22 -68.655414 -68.876525
23 -50.605272 -68.655414
24 -50.460744 -50.605272
25 -52.690744 -50.460744
26 -49.920744 -52.690744
27 -50.375744 -49.920744
28 -58.161744 -50.375744
29 -67.141744 -58.161744
30 -66.881744 -67.141744
31 -63.456744 -66.881744
32 -52.984744 -63.456744
33 -50.876525 -52.984744
34 -51.295414 -50.876525
35 -26.315272 -51.295414
36 -19.580744 -26.315272
37 -17.330744 -19.580744
38 -30.850744 -17.330744
39 -46.755744 -30.850744
40 -53.051744 -46.755744
41 -56.701744 -53.051744
42 -57.721744 -56.701744
43 -52.906744 -57.721744
44 -52.454744 -52.906744
45 -41.716525 -52.454744
46 -34.355414 -41.716525
47 -11.835272 -34.355414
48 -6.580744 -11.835272
49 -9.020744 -6.580744
50 -7.740744 -9.020744
51 -11.185744 -7.740744
52 -11.721744 -11.185744
53 -22.091744 -11.721744
54 -20.661744 -22.091744
55 -11.696744 -20.661744
56 -6.974744 -11.696744
57 9.403475 -6.974744
58 6.004586 9.403475
59 16.924728 6.004586
60 26.649256 16.924728
61 26.659256 26.649256
62 37.949256 26.659256
63 32.594256 37.949256
64 16.498256 32.594256
65 22.968256 16.498256
66 25.238256 22.968256
67 39.323256 25.238256
68 44.465256 39.323256
69 39.433475 44.465256
70 37.744586 39.433475
71 62.504728 37.744586
72 78.299256 62.504728
73 70.969256 78.299256
74 67.349256 70.969256
75 83.394256 67.349256
76 80.718256 83.394256
77 69.608256 80.718256
78 79.238256 69.608256
79 78.513256 79.238256
80 59.585256 78.513256
81 55.413475 59.585256
82 63.304586 55.413475
83 91.264728 63.304586
84 71.809256 91.264728
85 79.269256 71.809256
86 81.719256 79.269256
87 91.064256 81.719256
88 83.278256 91.064256
89 83.778256 83.278256
90 94.468256 83.778256
91 86.293256 94.468256
92 108.585256 86.293256
93 129.003475 108.585256
94 157.884586 129.003475
95 39.553450 157.884586
96 50.877977 39.553450
97 64.737977 50.877977
98 80.597977 64.737977
99 90.902977 80.597977
100 120.606977 90.902977
101 138.676977 120.606977
102 142.666977 138.676977
103 90.171977 142.666977
104 52.503977 90.171977
105 -31.447803 52.503977
106 -77.446692 -31.447803
107 -92.086550 -77.446692
108 -89.712023 -92.086550
109 -100.032023 -89.712023
110 -97.902023 -100.032023
111 -91.227023 -97.902023
112 -76.323023 -91.227023
113 -53.993023 -76.323023
114 -67.583023 -53.993023
115 -44.868023 -67.583023
116 -48.676023 -44.868023
> 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/7rz8u1258726527.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> acf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/86eam1258726527.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> pacf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Partial Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/96kuz1258726527.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> opar <- par(mfrow = c(2,2), oma = c(0, 0, 1.1, 0))
> plot(mylm, las = 1, sub='Residual Diagnostics')
> par(opar)
> dev.off()
null device
1
> if (n > n25) {
+ postscript(file="/var/www/html/rcomp/tmp/10gcm31258726527.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
+ plot(kp3:nmkm3,gqarr[,2], main='Goldfeld-Quandt test',ylab='2-sided p-value',xlab='breakpoint')
+ grid()
+ dev.off()
+ }
null device
1
>
> #Note: the /var/www/html/rcomp/createtable file can be downloaded at http://www.wessa.net/cretab
> load(file="/var/www/html/rcomp/createtable")
>
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a, 'Multiple Linear Regression - Estimated Regression Equation', 1, TRUE)
> a<-table.row.end(a)
> myeq <- colnames(x)[1]
> myeq <- paste(myeq, '[t] = ', sep='')
> for (i in 1:k){
+ if (mysum$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/11fzz41258726527.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/123i001258726527.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/13gbvm1258726527.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/14w3zu1258726528.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/15nm7z1258726528.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/168zyh1258726528.tab")
+ }
> system("convert tmp/1gfbb1258726527.ps tmp/1gfbb1258726527.png")
> system("convert tmp/2bha21258726527.ps tmp/2bha21258726527.png")
> system("convert tmp/3hwx21258726527.ps tmp/3hwx21258726527.png")
> system("convert tmp/46c8v1258726527.ps tmp/46c8v1258726527.png")
> system("convert tmp/5xd2v1258726527.ps tmp/5xd2v1258726527.png")
> system("convert tmp/63iqi1258726527.ps tmp/63iqi1258726527.png")
> system("convert tmp/7rz8u1258726527.ps tmp/7rz8u1258726527.png")
> system("convert tmp/86eam1258726527.ps tmp/86eam1258726527.png")
> system("convert tmp/96kuz1258726527.ps tmp/96kuz1258726527.png")
> system("convert tmp/10gcm31258726527.ps tmp/10gcm31258726527.png")
>
>
> proc.time()
user system elapsed
3.328 1.649 3.778