R version 2.8.0 (2008-10-20)
Copyright (C) 2008 The R Foundation for Statistical Computing
ISBN 3-900051-07-0
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> x <- array(list(8310,0,7649,0,7279,0,6857,0,6496,0,6280,0,8962,0,11205,0,10363,0,9175,0,8234,0,8121,0,7438,0,6876,0,6489,0,6319,0,5952,0,6055,0,9107,0,11493,0,10213,0,9238,0,8218,0,7995,0,7581,0,7051,0,6668,0,6433,0,6135,0,6365,0,10095,0,12029,0,12184,0,11331,0,9961,0,9739,0,9080,0,8507,0,8097,0,7772,0,7440,0,7902,0,13539,0,14992,0,15436,0,14156,0,12846,0,12302,0,11691,0,10648,0,10064,0,10016,0,9691,0,10260,0,16882,0,18573,0,18227,0,16346,0,14694,0,14453,0,13949,0,13277,0,12726,0,12279,0,11819,0,12207,0,18637,0,20519,0,19974,0,17802,0,15997,0,15430,0,14452,0,13614,0,13080,0,12290,0,11890,0,12292,0,18700,0,20388,1,19170,1,17530,1,15564,1,15163,1,13406,1,12763,1,12083,1,12054,1,11770,1,12266,1,17549,1,18655,1,17279,1,14788,1,13138,1,12494,1,11767,1,10928,1,10104,1,9760,1,9536,1,9978,1,14846,1,15565,1,13587,1,11804,1,10611,1,10915,1,9988,1,9376,1,9319,1,8852,1,8392,1,9050,1,13250,1,14037,1,12486,1,11182,1,10287,1),dim=c(2,119),dimnames=list(c('NWWZm','Dummy'),1:119))
> y <- array(NA,dim=c(2,119),dimnames=list(c('NWWZm','Dummy'),1:119))
> for (i in 1:dim(x)[1])
+ {
+ for (j in 1:dim(x)[2])
+ {
+ y[i,j] <- as.numeric(x[i,j])
+ }
+ }
> par3 = 'No Linear Trend'
> par2 = 'Include Monthly Dummies'
> par1 = '1'
> #'GNU S' R Code compiled by R2WASP v. 1.0.44 ()
> #Author: Prof. Dr. P. Wessa
> #To cite this work: AUTHOR(S), (YEAR), YOUR SOFTWARE TITLE (vNUMBER) in Free Statistics Software (v$_version), Office for Research Development and Education, URL http://www.wessa.net/rwasp_YOURPAGE.wasp/
> #Source of accompanying publication: Office for Research, Development, and Education
> #Technical description: Write here your technical program description (don't use hard returns!)
> library(lattice)
> library(lmtest)
Loading required package: zoo
Attaching package: 'zoo'
The following object(s) are masked from package:base :
as.Date.numeric
> n25 <- 25 #minimum number of obs. for Goldfeld-Quandt test
> par1 <- as.numeric(par1)
> x <- t(y)
> k <- length(x[1,])
> n <- length(x[,1])
> x1 <- cbind(x[,par1], x[,1:k!=par1])
> mycolnames <- c(colnames(x)[par1], colnames(x)[1:k!=par1])
> colnames(x1) <- mycolnames #colnames(x)[par1]
> x <- x1
> if (par3 == 'First Differences'){
+ x2 <- array(0, dim=c(n-1,k), dimnames=list(1:(n-1), paste('(1-B)',colnames(x),sep='')))
+ for (i in 1:n-1) {
+ for (j in 1:k) {
+ x2[i,j] <- x[i+1,j] - x[i,j]
+ }
+ }
+ x <- x2
+ }
> if (par2 == 'Include Monthly Dummies'){
+ x2 <- array(0, dim=c(n,11), dimnames=list(1:n, paste('M', seq(1:11), sep ='')))
+ for (i in 1:11){
+ x2[seq(i,n,12),i] <- 1
+ }
+ x <- cbind(x, x2)
+ }
> if (par2 == 'Include Quarterly Dummies'){
+ x2 <- array(0, dim=c(n,3), dimnames=list(1:n, paste('Q', seq(1:3), sep ='')))
+ for (i in 1:3){
+ x2[seq(i,n,4),i] <- 1
+ }
+ x <- cbind(x, x2)
+ }
> k <- length(x[1,])
> if (par3 == 'Linear Trend'){
+ x <- cbind(x, c(1:n))
+ colnames(x)[k+1] <- 't'
+ }
> x
NWWZm Dummy M1 M2 M3 M4 M5 M6 M7 M8 M9 M10 M11
1 8310 0 1 0 0 0 0 0 0 0 0 0 0
2 7649 0 0 1 0 0 0 0 0 0 0 0 0
3 7279 0 0 0 1 0 0 0 0 0 0 0 0
4 6857 0 0 0 0 1 0 0 0 0 0 0 0
5 6496 0 0 0 0 0 1 0 0 0 0 0 0
6 6280 0 0 0 0 0 0 1 0 0 0 0 0
7 8962 0 0 0 0 0 0 0 1 0 0 0 0
8 11205 0 0 0 0 0 0 0 0 1 0 0 0
9 10363 0 0 0 0 0 0 0 0 0 1 0 0
10 9175 0 0 0 0 0 0 0 0 0 0 1 0
11 8234 0 0 0 0 0 0 0 0 0 0 0 1
12 8121 0 0 0 0 0 0 0 0 0 0 0 0
13 7438 0 1 0 0 0 0 0 0 0 0 0 0
14 6876 0 0 1 0 0 0 0 0 0 0 0 0
15 6489 0 0 0 1 0 0 0 0 0 0 0 0
16 6319 0 0 0 0 1 0 0 0 0 0 0 0
17 5952 0 0 0 0 0 1 0 0 0 0 0 0
18 6055 0 0 0 0 0 0 1 0 0 0 0 0
19 9107 0 0 0 0 0 0 0 1 0 0 0 0
20 11493 0 0 0 0 0 0 0 0 1 0 0 0
21 10213 0 0 0 0 0 0 0 0 0 1 0 0
22 9238 0 0 0 0 0 0 0 0 0 0 1 0
23 8218 0 0 0 0 0 0 0 0 0 0 0 1
24 7995 0 0 0 0 0 0 0 0 0 0 0 0
25 7581 0 1 0 0 0 0 0 0 0 0 0 0
26 7051 0 0 1 0 0 0 0 0 0 0 0 0
27 6668 0 0 0 1 0 0 0 0 0 0 0 0
28 6433 0 0 0 0 1 0 0 0 0 0 0 0
29 6135 0 0 0 0 0 1 0 0 0 0 0 0
30 6365 0 0 0 0 0 0 1 0 0 0 0 0
31 10095 0 0 0 0 0 0 0 1 0 0 0 0
32 12029 0 0 0 0 0 0 0 0 1 0 0 0
33 12184 0 0 0 0 0 0 0 0 0 1 0 0
34 11331 0 0 0 0 0 0 0 0 0 0 1 0
35 9961 0 0 0 0 0 0 0 0 0 0 0 1
36 9739 0 0 0 0 0 0 0 0 0 0 0 0
37 9080 0 1 0 0 0 0 0 0 0 0 0 0
38 8507 0 0 1 0 0 0 0 0 0 0 0 0
39 8097 0 0 0 1 0 0 0 0 0 0 0 0
40 7772 0 0 0 0 1 0 0 0 0 0 0 0
41 7440 0 0 0 0 0 1 0 0 0 0 0 0
42 7902 0 0 0 0 0 0 1 0 0 0 0 0
43 13539 0 0 0 0 0 0 0 1 0 0 0 0
44 14992 0 0 0 0 0 0 0 0 1 0 0 0
45 15436 0 0 0 0 0 0 0 0 0 1 0 0
46 14156 0 0 0 0 0 0 0 0 0 0 1 0
47 12846 0 0 0 0 0 0 0 0 0 0 0 1
48 12302 0 0 0 0 0 0 0 0 0 0 0 0
49 11691 0 1 0 0 0 0 0 0 0 0 0 0
50 10648 0 0 1 0 0 0 0 0 0 0 0 0
51 10064 0 0 0 1 0 0 0 0 0 0 0 0
52 10016 0 0 0 0 1 0 0 0 0 0 0 0
53 9691 0 0 0 0 0 1 0 0 0 0 0 0
54 10260 0 0 0 0 0 0 1 0 0 0 0 0
55 16882 0 0 0 0 0 0 0 1 0 0 0 0
56 18573 0 0 0 0 0 0 0 0 1 0 0 0
57 18227 0 0 0 0 0 0 0 0 0 1 0 0
58 16346 0 0 0 0 0 0 0 0 0 0 1 0
59 14694 0 0 0 0 0 0 0 0 0 0 0 1
60 14453 0 0 0 0 0 0 0 0 0 0 0 0
61 13949 0 1 0 0 0 0 0 0 0 0 0 0
62 13277 0 0 1 0 0 0 0 0 0 0 0 0
63 12726 0 0 0 1 0 0 0 0 0 0 0 0
64 12279 0 0 0 0 1 0 0 0 0 0 0 0
65 11819 0 0 0 0 0 1 0 0 0 0 0 0
66 12207 0 0 0 0 0 0 1 0 0 0 0 0
67 18637 0 0 0 0 0 0 0 1 0 0 0 0
68 20519 0 0 0 0 0 0 0 0 1 0 0 0
69 19974 0 0 0 0 0 0 0 0 0 1 0 0
70 17802 0 0 0 0 0 0 0 0 0 0 1 0
71 15997 0 0 0 0 0 0 0 0 0 0 0 1
72 15430 0 0 0 0 0 0 0 0 0 0 0 0
73 14452 0 1 0 0 0 0 0 0 0 0 0 0
74 13614 0 0 1 0 0 0 0 0 0 0 0 0
75 13080 0 0 0 1 0 0 0 0 0 0 0 0
76 12290 0 0 0 0 1 0 0 0 0 0 0 0
77 11890 0 0 0 0 0 1 0 0 0 0 0 0
78 12292 0 0 0 0 0 0 1 0 0 0 0 0
79 18700 0 0 0 0 0 0 0 1 0 0 0 0
80 20388 1 0 0 0 0 0 0 0 1 0 0 0
81 19170 1 0 0 0 0 0 0 0 0 1 0 0
82 17530 1 0 0 0 0 0 0 0 0 0 1 0
83 15564 1 0 0 0 0 0 0 0 0 0 0 1
84 15163 1 0 0 0 0 0 0 0 0 0 0 0
85 13406 1 1 0 0 0 0 0 0 0 0 0 0
86 12763 1 0 1 0 0 0 0 0 0 0 0 0
87 12083 1 0 0 1 0 0 0 0 0 0 0 0
88 12054 1 0 0 0 1 0 0 0 0 0 0 0
89 11770 1 0 0 0 0 1 0 0 0 0 0 0
90 12266 1 0 0 0 0 0 1 0 0 0 0 0
91 17549 1 0 0 0 0 0 0 1 0 0 0 0
92 18655 1 0 0 0 0 0 0 0 1 0 0 0
93 17279 1 0 0 0 0 0 0 0 0 1 0 0
94 14788 1 0 0 0 0 0 0 0 0 0 1 0
95 13138 1 0 0 0 0 0 0 0 0 0 0 1
96 12494 1 0 0 0 0 0 0 0 0 0 0 0
97 11767 1 1 0 0 0 0 0 0 0 0 0 0
98 10928 1 0 1 0 0 0 0 0 0 0 0 0
99 10104 1 0 0 1 0 0 0 0 0 0 0 0
100 9760 1 0 0 0 1 0 0 0 0 0 0 0
101 9536 1 0 0 0 0 1 0 0 0 0 0 0
102 9978 1 0 0 0 0 0 1 0 0 0 0 0
103 14846 1 0 0 0 0 0 0 1 0 0 0 0
104 15565 1 0 0 0 0 0 0 0 1 0 0 0
105 13587 1 0 0 0 0 0 0 0 0 1 0 0
106 11804 1 0 0 0 0 0 0 0 0 0 1 0
107 10611 1 0 0 0 0 0 0 0 0 0 0 1
108 10915 1 0 0 0 0 0 0 0 0 0 0 0
109 9988 1 1 0 0 0 0 0 0 0 0 0 0
110 9376 1 0 1 0 0 0 0 0 0 0 0 0
111 9319 1 0 0 1 0 0 0 0 0 0 0 0
112 8852 1 0 0 0 1 0 0 0 0 0 0 0
113 8392 1 0 0 0 0 1 0 0 0 0 0 0
114 9050 1 0 0 0 0 0 1 0 0 0 0 0
115 13250 1 0 0 0 0 0 0 1 0 0 0 0
116 14037 1 0 0 0 0 0 0 0 1 0 0 0
117 12486 1 0 0 0 0 0 0 0 0 1 0 0
118 11182 1 0 0 0 0 0 0 0 0 0 1 0
119 10287 1 0 0 0 0 0 0 0 0 0 0 1
> k <- length(x[1,])
> df <- as.data.frame(x)
> (mylm <- lm(df))
Call:
lm(formula = df)
Coefficients:
(Intercept) Dummy M1 M2 M3 M4
11384.92 1382.56 -1033.49 -1730.79 -2208.79 -2536.49
M5 M6 M7 M8 M9 M10
-2887.59 -2534.19 2357.01 3807.65 2953.95 1397.25
M11
17.05
> (mysum <- summary(mylm))
Call:
lm(formula = df)
Residuals:
Min 1Q Median 3Q Max
-4779.9 -2388.9 -454.7 2410.0 5635.1
Coefficients:
Estimate Std. Error t value Pr(>|t|)
(Intercept) 11384.92 983.17 11.580 < 2e-16 ***
Dummy 1382.56 564.51 2.449 0.01596 *
M1 -1033.49 1330.29 -0.777 0.43895
M2 -1730.79 1330.29 -1.301 0.19606
M3 -2208.79 1330.29 -1.660 0.09979 .
M4 -2536.49 1330.29 -1.907 0.05926 .
M5 -2887.59 1330.29 -2.171 0.03219 *
M6 -2534.19 1330.29 -1.905 0.05949 .
M7 2357.01 1330.29 1.772 0.07930 .
M8 3807.65 1330.69 2.861 0.00508 **
M9 2953.95 1330.69 2.220 0.02856 *
M10 1397.25 1330.69 1.050 0.29610
M11 17.05 1330.69 0.013 0.98980
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
Residual standard error: 2895 on 106 degrees of freedom
Multiple R-squared: 0.4334, Adjusted R-squared: 0.3693
F-statistic: 6.758 on 12 and 106 DF, p-value: 6.645e-09
> 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,] 1.405849e-02 2.811698e-02 9.859415e-01
[2,] 3.234091e-03 6.468182e-03 9.967659e-01
[3,] 6.028517e-04 1.205703e-03 9.993971e-01
[4,] 1.134421e-04 2.268843e-04 9.998866e-01
[5,] 2.164958e-05 4.329917e-05 9.999784e-01
[6,] 3.926333e-06 7.852665e-06 9.999961e-01
[7,] 6.613420e-07 1.322684e-06 9.999993e-01
[8,] 1.063070e-07 2.126140e-07 9.999999e-01
[9,] 1.781352e-08 3.562704e-08 1.000000e+00
[10,] 3.538830e-09 7.077660e-09 1.000000e+00
[11,] 6.297281e-10 1.259456e-09 1.000000e+00
[12,] 1.130558e-10 2.261116e-10 1.000000e+00
[13,] 1.899268e-11 3.798536e-11 1.000000e+00
[14,] 3.039996e-12 6.079992e-12 1.000000e+00
[15,] 5.710249e-13 1.142050e-12 1.000000e+00
[16,] 4.548771e-12 9.097542e-12 1.000000e+00
[17,] 4.301522e-12 8.603045e-12 1.000000e+00
[18,] 5.922216e-10 1.184443e-09 1.000000e+00
[19,] 1.833961e-08 3.667922e-08 1.000000e+00
[20,] 6.654467e-08 1.330893e-07 9.999999e-01
[21,] 1.833613e-07 3.667226e-07 9.999998e-01
[22,] 2.702817e-07 5.405633e-07 9.999997e-01
[23,] 3.913583e-07 7.827165e-07 9.999996e-01
[24,] 5.367946e-07 1.073589e-06 9.999995e-01
[25,] 7.076105e-07 1.415221e-06 9.999993e-01
[26,] 9.759735e-07 1.951947e-06 9.999990e-01
[27,] 2.415140e-06 4.830281e-06 9.999976e-01
[28,] 3.615671e-04 7.231341e-04 9.996384e-01
[29,] 3.114337e-03 6.228673e-03 9.968857e-01
[30,] 2.708306e-02 5.416612e-02 9.729169e-01
[31,] 8.176635e-02 1.635327e-01 9.182337e-01
[32,] 1.571179e-01 3.142359e-01 8.428821e-01
[33,] 2.420166e-01 4.840332e-01 7.579834e-01
[34,] 3.303934e-01 6.607868e-01 6.696066e-01
[35,] 4.021912e-01 8.043824e-01 5.978088e-01
[36,] 4.669012e-01 9.338023e-01 5.330988e-01
[37,] 5.326511e-01 9.346978e-01 4.673489e-01
[38,] 5.952047e-01 8.095907e-01 4.047953e-01
[39,] 6.711511e-01 6.576978e-01 3.288489e-01
[40,] 8.472945e-01 3.054110e-01 1.527055e-01
[41,] 9.249848e-01 1.500304e-01 7.501521e-02
[42,] 9.604111e-01 7.917773e-02 3.958886e-02
[43,] 9.725384e-01 5.492311e-02 2.746155e-02
[44,] 9.778298e-01 4.434031e-02 2.217016e-02
[45,] 9.822470e-01 3.550591e-02 1.775295e-02
[46,] 9.857331e-01 2.853384e-02 1.426692e-02
[47,] 9.880623e-01 2.387532e-02 1.193766e-02
[48,] 9.893987e-01 2.120264e-02 1.060132e-02
[49,] 9.899339e-01 2.013221e-02 1.006611e-02
[50,] 9.900678e-01 1.986448e-02 9.932242e-03
[51,] 9.903269e-01 1.934624e-02 9.673120e-03
[52,] 9.932395e-01 1.352090e-02 6.760452e-03
[53,] 9.949036e-01 1.019279e-02 5.096394e-03
[54,] 9.961740e-01 7.651998e-03 3.825999e-03
[55,] 9.963743e-01 7.251358e-03 3.625679e-03
[56,] 9.960807e-01 7.838607e-03 3.919303e-03
[57,] 9.952963e-01 9.407372e-03 4.703686e-03
[58,] 9.942654e-01 1.146913e-02 5.734564e-03
[59,] 9.928105e-01 1.437893e-02 7.189465e-03
[60,] 9.908625e-01 1.827498e-02 9.137491e-03
[61,] 9.878827e-01 2.423455e-02 1.211727e-02
[62,] 9.840334e-01 3.193317e-02 1.596658e-02
[63,] 9.799110e-01 4.017803e-02 2.008902e-02
[64,] 9.768071e-01 4.638582e-02 2.319291e-02
[65,] 9.813187e-01 3.736267e-02 1.868133e-02
[66,] 9.878228e-01 2.435439e-02 1.217720e-02
[67,] 9.936988e-01 1.260242e-02 6.301212e-03
[68,] 9.960718e-01 7.856321e-03 3.928161e-03
[69,] 9.964813e-01 7.037301e-03 3.518651e-03
[70,] 9.957560e-01 8.487983e-03 4.243991e-03
[71,] 9.950126e-01 9.974724e-03 4.987362e-03
[72,] 9.937364e-01 1.252716e-02 6.263582e-03
[73,] 9.930221e-01 1.395581e-02 6.977905e-03
[74,] 9.924653e-01 1.506944e-02 7.534721e-03
[75,] 9.918011e-01 1.639782e-02 8.198911e-03
[76,] 9.939098e-01 1.218040e-02 6.090198e-03
[77,] 9.969312e-01 6.137633e-03 3.068817e-03
[78,] 9.993681e-01 1.263832e-03 6.319159e-04
[79,] 9.998195e-01 3.609063e-04 1.804531e-04
[80,] 9.999363e-01 1.273793e-04 6.368966e-05
[81,] 9.998914e-01 2.171411e-04 1.085705e-04
[82,] 9.998518e-01 2.964125e-04 1.482063e-04
[83,] 9.997534e-01 4.932636e-04 2.466318e-04
[84,] 9.992284e-01 1.543125e-03 7.715623e-04
[85,] 9.977663e-01 4.467341e-03 2.233671e-03
[86,] 9.944283e-01 1.114333e-02 5.571665e-03
[87,] 9.838986e-01 3.220277e-02 1.610138e-02
[88,] 9.717216e-01 5.655674e-02 2.827837e-02
> postscript(file="/var/www/html/rcomp/tmp/11b4p1229280289.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$resid)
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/2iytb1229280289.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> plot(mysum$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/34cag1229280289.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> hist(mysum$resid, main='Residual Histogram', xlab='values of Residuals')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/49rxw1229280289.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> densityplot(~mysum$resid,col='black',main='Residual Density Plot', xlab='values of Residuals')
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/5exwt1229280289.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> qqnorm(mysum$resid, main='Residual Normal Q-Q Plot')
> qqline(mysum$resid)
> grid()
> dev.off()
null device
1
> (myerror <- as.ts(mysum$resid))
Time Series:
Start = 1
End = 119
Frequency = 1
1 2 3 4 5 6
-2041.43156 -2005.13156 -1897.13156 -1991.43156 -2001.33156 -2570.73156
7 8 9 10 11 12
-4779.93156 -3987.57541 -3975.87541 -3607.17541 -3167.97541 -3263.92395
13 14 15 16 17 18
-2913.43156 -2778.13156 -2687.13156 -2529.43156 -2545.33156 -2795.73156
19 20 21 22 23 24
-4634.93156 -3699.57541 -4125.87541 -3544.17541 -3183.97541 -3389.92395
25 26 27 28 29 30
-2770.43156 -2603.13156 -2508.13156 -2415.43156 -2362.33156 -2485.73156
31 32 33 34 35 36
-3646.93156 -3163.57541 -2154.87541 -1451.17541 -1440.97541 -1645.92395
37 38 39 40 41 42
-1271.43156 -1147.13156 -1079.13156 -1076.43156 -1057.33156 -948.73156
43 44 45 46 47 48
-202.93156 -200.57541 1097.12459 1373.82459 1444.02459 917.07605
49 50 51 52 53 54
1339.56844 993.86844 887.86844 1167.56844 1193.66844 1409.26844
55 56 57 58 59 60
3140.06844 3380.42459 3888.12459 3563.82459 3292.02459 3068.07605
61 62 63 64 65 66
3597.56844 3622.86844 3549.86844 3430.56844 3321.66844 3356.26844
67 68 69 70 71 72
4895.06844 5326.42459 5635.12459 5019.82459 4595.02459 4045.07605
73 74 75 76 77 78
4100.56844 3959.86844 3903.86844 3441.56844 3392.66844 3441.26844
79 80 81 82 83 84
4958.06844 3812.86312 3448.56312 3365.26312 2779.46312 2395.51458
85 86 87 88 89 90
1672.00697 1726.30697 1524.30697 1823.00697 1890.10697 2032.70697
91 92 93 94 95 96
2424.50697 2079.86312 1557.56312 623.26312 353.46312 -273.48542
97 98 99 100 101 102
33.00697 -108.69303 -454.69303 -470.99303 -343.89303 -255.29303
103 104 105 106 107 108
-278.49303 -1010.13688 -2134.43688 -2360.73688 -2173.53688 -1852.48542
109 110 111 112 113 114
-1745.99303 -1660.69303 -1239.69303 -1378.99303 -1487.89303 -1183.29303
115 116 117 118 119
-1874.49303 -2538.13688 -3235.43688 -2982.73688 -2497.53688
> postscript(file="/var/www/html/rcomp/tmp/6uvye1229280289.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> dum <- cbind(lag(myerror,k=1),myerror)
> dum
Time Series:
Start = 0
End = 119
Frequency = 1
lag(myerror, k = 1) myerror
0 -2041.43156 NA
1 -2005.13156 -2041.43156
2 -1897.13156 -2005.13156
3 -1991.43156 -1897.13156
4 -2001.33156 -1991.43156
5 -2570.73156 -2001.33156
6 -4779.93156 -2570.73156
7 -3987.57541 -4779.93156
8 -3975.87541 -3987.57541
9 -3607.17541 -3975.87541
10 -3167.97541 -3607.17541
11 -3263.92395 -3167.97541
12 -2913.43156 -3263.92395
13 -2778.13156 -2913.43156
14 -2687.13156 -2778.13156
15 -2529.43156 -2687.13156
16 -2545.33156 -2529.43156
17 -2795.73156 -2545.33156
18 -4634.93156 -2795.73156
19 -3699.57541 -4634.93156
20 -4125.87541 -3699.57541
21 -3544.17541 -4125.87541
22 -3183.97541 -3544.17541
23 -3389.92395 -3183.97541
24 -2770.43156 -3389.92395
25 -2603.13156 -2770.43156
26 -2508.13156 -2603.13156
27 -2415.43156 -2508.13156
28 -2362.33156 -2415.43156
29 -2485.73156 -2362.33156
30 -3646.93156 -2485.73156
31 -3163.57541 -3646.93156
32 -2154.87541 -3163.57541
33 -1451.17541 -2154.87541
34 -1440.97541 -1451.17541
35 -1645.92395 -1440.97541
36 -1271.43156 -1645.92395
37 -1147.13156 -1271.43156
38 -1079.13156 -1147.13156
39 -1076.43156 -1079.13156
40 -1057.33156 -1076.43156
41 -948.73156 -1057.33156
42 -202.93156 -948.73156
43 -200.57541 -202.93156
44 1097.12459 -200.57541
45 1373.82459 1097.12459
46 1444.02459 1373.82459
47 917.07605 1444.02459
48 1339.56844 917.07605
49 993.86844 1339.56844
50 887.86844 993.86844
51 1167.56844 887.86844
52 1193.66844 1167.56844
53 1409.26844 1193.66844
54 3140.06844 1409.26844
55 3380.42459 3140.06844
56 3888.12459 3380.42459
57 3563.82459 3888.12459
58 3292.02459 3563.82459
59 3068.07605 3292.02459
60 3597.56844 3068.07605
61 3622.86844 3597.56844
62 3549.86844 3622.86844
63 3430.56844 3549.86844
64 3321.66844 3430.56844
65 3356.26844 3321.66844
66 4895.06844 3356.26844
67 5326.42459 4895.06844
68 5635.12459 5326.42459
69 5019.82459 5635.12459
70 4595.02459 5019.82459
71 4045.07605 4595.02459
72 4100.56844 4045.07605
73 3959.86844 4100.56844
74 3903.86844 3959.86844
75 3441.56844 3903.86844
76 3392.66844 3441.56844
77 3441.26844 3392.66844
78 4958.06844 3441.26844
79 3812.86312 4958.06844
80 3448.56312 3812.86312
81 3365.26312 3448.56312
82 2779.46312 3365.26312
83 2395.51458 2779.46312
84 1672.00697 2395.51458
85 1726.30697 1672.00697
86 1524.30697 1726.30697
87 1823.00697 1524.30697
88 1890.10697 1823.00697
89 2032.70697 1890.10697
90 2424.50697 2032.70697
91 2079.86312 2424.50697
92 1557.56312 2079.86312
93 623.26312 1557.56312
94 353.46312 623.26312
95 -273.48542 353.46312
96 33.00697 -273.48542
97 -108.69303 33.00697
98 -454.69303 -108.69303
99 -470.99303 -454.69303
100 -343.89303 -470.99303
101 -255.29303 -343.89303
102 -278.49303 -255.29303
103 -1010.13688 -278.49303
104 -2134.43688 -1010.13688
105 -2360.73688 -2134.43688
106 -2173.53688 -2360.73688
107 -1852.48542 -2173.53688
108 -1745.99303 -1852.48542
109 -1660.69303 -1745.99303
110 -1239.69303 -1660.69303
111 -1378.99303 -1239.69303
112 -1487.89303 -1378.99303
113 -1183.29303 -1487.89303
114 -1874.49303 -1183.29303
115 -2538.13688 -1874.49303
116 -3235.43688 -2538.13688
117 -2982.73688 -3235.43688
118 -2497.53688 -2982.73688
119 NA -2497.53688
> dum1 <- dum[2:length(myerror),]
> dum1
lag(myerror, k = 1) myerror
[1,] -2005.13156 -2041.43156
[2,] -1897.13156 -2005.13156
[3,] -1991.43156 -1897.13156
[4,] -2001.33156 -1991.43156
[5,] -2570.73156 -2001.33156
[6,] -4779.93156 -2570.73156
[7,] -3987.57541 -4779.93156
[8,] -3975.87541 -3987.57541
[9,] -3607.17541 -3975.87541
[10,] -3167.97541 -3607.17541
[11,] -3263.92395 -3167.97541
[12,] -2913.43156 -3263.92395
[13,] -2778.13156 -2913.43156
[14,] -2687.13156 -2778.13156
[15,] -2529.43156 -2687.13156
[16,] -2545.33156 -2529.43156
[17,] -2795.73156 -2545.33156
[18,] -4634.93156 -2795.73156
[19,] -3699.57541 -4634.93156
[20,] -4125.87541 -3699.57541
[21,] -3544.17541 -4125.87541
[22,] -3183.97541 -3544.17541
[23,] -3389.92395 -3183.97541
[24,] -2770.43156 -3389.92395
[25,] -2603.13156 -2770.43156
[26,] -2508.13156 -2603.13156
[27,] -2415.43156 -2508.13156
[28,] -2362.33156 -2415.43156
[29,] -2485.73156 -2362.33156
[30,] -3646.93156 -2485.73156
[31,] -3163.57541 -3646.93156
[32,] -2154.87541 -3163.57541
[33,] -1451.17541 -2154.87541
[34,] -1440.97541 -1451.17541
[35,] -1645.92395 -1440.97541
[36,] -1271.43156 -1645.92395
[37,] -1147.13156 -1271.43156
[38,] -1079.13156 -1147.13156
[39,] -1076.43156 -1079.13156
[40,] -1057.33156 -1076.43156
[41,] -948.73156 -1057.33156
[42,] -202.93156 -948.73156
[43,] -200.57541 -202.93156
[44,] 1097.12459 -200.57541
[45,] 1373.82459 1097.12459
[46,] 1444.02459 1373.82459
[47,] 917.07605 1444.02459
[48,] 1339.56844 917.07605
[49,] 993.86844 1339.56844
[50,] 887.86844 993.86844
[51,] 1167.56844 887.86844
[52,] 1193.66844 1167.56844
[53,] 1409.26844 1193.66844
[54,] 3140.06844 1409.26844
[55,] 3380.42459 3140.06844
[56,] 3888.12459 3380.42459
[57,] 3563.82459 3888.12459
[58,] 3292.02459 3563.82459
[59,] 3068.07605 3292.02459
[60,] 3597.56844 3068.07605
[61,] 3622.86844 3597.56844
[62,] 3549.86844 3622.86844
[63,] 3430.56844 3549.86844
[64,] 3321.66844 3430.56844
[65,] 3356.26844 3321.66844
[66,] 4895.06844 3356.26844
[67,] 5326.42459 4895.06844
[68,] 5635.12459 5326.42459
[69,] 5019.82459 5635.12459
[70,] 4595.02459 5019.82459
[71,] 4045.07605 4595.02459
[72,] 4100.56844 4045.07605
[73,] 3959.86844 4100.56844
[74,] 3903.86844 3959.86844
[75,] 3441.56844 3903.86844
[76,] 3392.66844 3441.56844
[77,] 3441.26844 3392.66844
[78,] 4958.06844 3441.26844
[79,] 3812.86312 4958.06844
[80,] 3448.56312 3812.86312
[81,] 3365.26312 3448.56312
[82,] 2779.46312 3365.26312
[83,] 2395.51458 2779.46312
[84,] 1672.00697 2395.51458
[85,] 1726.30697 1672.00697
[86,] 1524.30697 1726.30697
[87,] 1823.00697 1524.30697
[88,] 1890.10697 1823.00697
[89,] 2032.70697 1890.10697
[90,] 2424.50697 2032.70697
[91,] 2079.86312 2424.50697
[92,] 1557.56312 2079.86312
[93,] 623.26312 1557.56312
[94,] 353.46312 623.26312
[95,] -273.48542 353.46312
[96,] 33.00697 -273.48542
[97,] -108.69303 33.00697
[98,] -454.69303 -108.69303
[99,] -470.99303 -454.69303
[100,] -343.89303 -470.99303
[101,] -255.29303 -343.89303
[102,] -278.49303 -255.29303
[103,] -1010.13688 -278.49303
[104,] -2134.43688 -1010.13688
[105,] -2360.73688 -2134.43688
[106,] -2173.53688 -2360.73688
[107,] -1852.48542 -2173.53688
[108,] -1745.99303 -1852.48542
[109,] -1660.69303 -1745.99303
[110,] -1239.69303 -1660.69303
[111,] -1378.99303 -1239.69303
[112,] -1487.89303 -1378.99303
[113,] -1183.29303 -1487.89303
[114,] -1874.49303 -1183.29303
[115,] -2538.13688 -1874.49303
[116,] -3235.43688 -2538.13688
[117,] -2982.73688 -3235.43688
[118,] -2497.53688 -2982.73688
> z <- as.data.frame(dum1)
> z
lag(myerror, k = 1) myerror
1 -2005.13156 -2041.43156
2 -1897.13156 -2005.13156
3 -1991.43156 -1897.13156
4 -2001.33156 -1991.43156
5 -2570.73156 -2001.33156
6 -4779.93156 -2570.73156
7 -3987.57541 -4779.93156
8 -3975.87541 -3987.57541
9 -3607.17541 -3975.87541
10 -3167.97541 -3607.17541
11 -3263.92395 -3167.97541
12 -2913.43156 -3263.92395
13 -2778.13156 -2913.43156
14 -2687.13156 -2778.13156
15 -2529.43156 -2687.13156
16 -2545.33156 -2529.43156
17 -2795.73156 -2545.33156
18 -4634.93156 -2795.73156
19 -3699.57541 -4634.93156
20 -4125.87541 -3699.57541
21 -3544.17541 -4125.87541
22 -3183.97541 -3544.17541
23 -3389.92395 -3183.97541
24 -2770.43156 -3389.92395
25 -2603.13156 -2770.43156
26 -2508.13156 -2603.13156
27 -2415.43156 -2508.13156
28 -2362.33156 -2415.43156
29 -2485.73156 -2362.33156
30 -3646.93156 -2485.73156
31 -3163.57541 -3646.93156
32 -2154.87541 -3163.57541
33 -1451.17541 -2154.87541
34 -1440.97541 -1451.17541
35 -1645.92395 -1440.97541
36 -1271.43156 -1645.92395
37 -1147.13156 -1271.43156
38 -1079.13156 -1147.13156
39 -1076.43156 -1079.13156
40 -1057.33156 -1076.43156
41 -948.73156 -1057.33156
42 -202.93156 -948.73156
43 -200.57541 -202.93156
44 1097.12459 -200.57541
45 1373.82459 1097.12459
46 1444.02459 1373.82459
47 917.07605 1444.02459
48 1339.56844 917.07605
49 993.86844 1339.56844
50 887.86844 993.86844
51 1167.56844 887.86844
52 1193.66844 1167.56844
53 1409.26844 1193.66844
54 3140.06844 1409.26844
55 3380.42459 3140.06844
56 3888.12459 3380.42459
57 3563.82459 3888.12459
58 3292.02459 3563.82459
59 3068.07605 3292.02459
60 3597.56844 3068.07605
61 3622.86844 3597.56844
62 3549.86844 3622.86844
63 3430.56844 3549.86844
64 3321.66844 3430.56844
65 3356.26844 3321.66844
66 4895.06844 3356.26844
67 5326.42459 4895.06844
68 5635.12459 5326.42459
69 5019.82459 5635.12459
70 4595.02459 5019.82459
71 4045.07605 4595.02459
72 4100.56844 4045.07605
73 3959.86844 4100.56844
74 3903.86844 3959.86844
75 3441.56844 3903.86844
76 3392.66844 3441.56844
77 3441.26844 3392.66844
78 4958.06844 3441.26844
79 3812.86312 4958.06844
80 3448.56312 3812.86312
81 3365.26312 3448.56312
82 2779.46312 3365.26312
83 2395.51458 2779.46312
84 1672.00697 2395.51458
85 1726.30697 1672.00697
86 1524.30697 1726.30697
87 1823.00697 1524.30697
88 1890.10697 1823.00697
89 2032.70697 1890.10697
90 2424.50697 2032.70697
91 2079.86312 2424.50697
92 1557.56312 2079.86312
93 623.26312 1557.56312
94 353.46312 623.26312
95 -273.48542 353.46312
96 33.00697 -273.48542
97 -108.69303 33.00697
98 -454.69303 -108.69303
99 -470.99303 -454.69303
100 -343.89303 -470.99303
101 -255.29303 -343.89303
102 -278.49303 -255.29303
103 -1010.13688 -278.49303
104 -2134.43688 -1010.13688
105 -2360.73688 -2134.43688
106 -2173.53688 -2360.73688
107 -1852.48542 -2173.53688
108 -1745.99303 -1852.48542
109 -1660.69303 -1745.99303
110 -1239.69303 -1660.69303
111 -1378.99303 -1239.69303
112 -1487.89303 -1378.99303
113 -1183.29303 -1487.89303
114 -1874.49303 -1183.29303
115 -2538.13688 -1874.49303
116 -3235.43688 -2538.13688
117 -2982.73688 -3235.43688
118 -2497.53688 -2982.73688
> 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/721ty1229280289.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> acf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/8gi8x1229280289.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> pacf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Partial Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/9k7d01229280289.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> opar <- par(mfrow = c(2,2), oma = c(0, 0, 1.1, 0))
> plot(mylm, las = 1, sub='Residual Diagnostics')
> par(opar)
> dev.off()
null device
1
> if (n > n25) {
+ postscript(file="/var/www/html/rcomp/tmp/1038ls1229280289.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
+ plot(kp3:nmkm3,gqarr[,2], main='Goldfeld-Quandt test',ylab='2-sided p-value',xlab='breakpoint')
+ grid()
+ dev.off()
+ }
null device
1
>
> #Note: the /var/www/html/rcomp/createtable file can be downloaded at http://www.wessa.net/cretab
> load(file="/var/www/html/rcomp/createtable")
>
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a, 'Multiple Linear Regression - Estimated Regression Equation', 1, TRUE)
> a<-table.row.end(a)
> myeq <- colnames(x)[1]
> myeq <- paste(myeq, '[t] = ', sep='')
> for (i in 1:k){
+ if (mysum$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/11s6te1229280289.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/1232c81229280289.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/13njp51229280290.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/141i981229280290.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/1501d21229280290.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/1663lf1229280290.tab")
+ }
>
> system("convert tmp/11b4p1229280289.ps tmp/11b4p1229280289.png")
> system("convert tmp/2iytb1229280289.ps tmp/2iytb1229280289.png")
> system("convert tmp/34cag1229280289.ps tmp/34cag1229280289.png")
> system("convert tmp/49rxw1229280289.ps tmp/49rxw1229280289.png")
> system("convert tmp/5exwt1229280289.ps tmp/5exwt1229280289.png")
> system("convert tmp/6uvye1229280289.ps tmp/6uvye1229280289.png")
> system("convert tmp/721ty1229280289.ps tmp/721ty1229280289.png")
> system("convert tmp/8gi8x1229280289.ps tmp/8gi8x1229280289.png")
> system("convert tmp/9k7d01229280289.ps tmp/9k7d01229280289.png")
> system("convert tmp/1038ls1229280289.ps tmp/1038ls1229280289.png")
>
>
> proc.time()
user system elapsed
3.369 1.695 7.617