R version 2.8.0 (2008-10-20)
Copyright (C) 2008 The R Foundation for Statistical Computing
ISBN 3-900051-07-0
R is free software and comes with ABSOLUTELY NO WARRANTY.
You are welcome to redistribute it under certain conditions.
Type 'license()' or 'licence()' for distribution details.
Natural language support but running in an English locale
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(2
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+ ,4)
+ ,dim=c(4
+ ,159)
+ ,dimnames=list(c('Q1'
+ ,'Q2'
+ ,'Q3'
+ ,'Q4')
+ ,1:159))
> y <- array(NA,dim=c(4,159),dimnames=list(c('Q1','Q2','Q3','Q4'),1:159))
> 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'
> #'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
Q1 Q2 Q3 Q4
1 2 2 4 2
2 2 2 4 1
3 4 2 5 4
4 2 2 2 2
5 3 2 2 2
6 4 1 4 2
7 3 1 4 2
8 3 3 4 2
9 3 2 4 1
10 2 1 2 4
11 4 4 3 2
12 4 2 4 3
13 3 3 3 2
14 3 2 4 2
15 4 1 4 1
16 4 1 4 3
17 3 2 4 1
18 3 2 2 2
19 3 2 4 4
20 4 2 4 4
21 2 1 4 3
22 5 2 3 2
23 4 4 2 3
24 2 2 4 2
25 3 2 2 2
26 4 2 3 3
27 4 2 4 3
28 3 2 3 2
29 4 3 4 4
30 4 2 4 2
31 1 1 4 2
32 4 4 4 3
33 5 1 4 5
34 2 2 4 2
35 4 2 4 3
36 3 2 5 1
37 2 2 4 2
38 4 2 2 2
39 5 2 4 4
40 4 2 4 2
41 4 2 5 4
42 4 2 4 3
43 3 2 2 2
44 4 2 4 4
45 2 2 4 2
46 2 1 4 2
47 4 2 2 2
48 2 1 5 2
49 4 2 4 2
50 4 1 4 3
51 1 1 4 1
52 4 2 4 2
53 2 2 4 2
54 1 1 3 1
55 4 5 5 5
56 3 2 4 2
57 2 2 4 2
58 4 1 4 2
59 3 1 4 1
60 2 2 2 2
61 2 2 4 2
62 3 1 4 2
63 2 1 4 4
64 1 2 4 2
65 3 1 3 1
66 2 1 4 2
67 3 2 2 2
68 3 1 4 2
69 3 1 4 1
70 2 2 4 2
71 3 1 4 2
72 2 1 4 2
73 4 3 4 3
74 4 3 3 3
75 4 2 4 2
76 2 2 4 2
77 3 1 4 3
78 4 3 4 2
79 3 2 4 2
80 4 2 4 2
81 2 2 4 2
82 3 2 2 2
83 3 1 3 1
84 4 4 5 3
85 2 1 3 2
86 4 1 3 4
87 2 1 4 2
88 2 1 4 1
89 4 4 4 4
90 3 2 4 3
91 4 2 4 2
92 2 1 3 3
93 2 1 4 2
94 3 1 4 3
95 3 3 4 2
96 5 4 5 5
97 2 4 4 3
98 3 3 4 4
99 4 2 2 2
100 3 2 3 2
101 4 3 3 2
102 3 1 3 3
103 3 3 4 4
104 2 2 4 3
105 3 2 2 2
106 2 2 3 2
107 3 2 3 3
108 2 4 4 2
109 4 3 4 2
110 2 1 2 2
111 4 1 3 2
112 4 2 4 3
113 1 1 4 2
114 5 3 5 4
115 2 2 3 1
116 3 2 3 2
117 4 2 4 4
118 1 1 3 2
119 5 3 3 2
120 3 1 2 1
121 3 1 4 1
122 3 2 3 3
123 3 3 4 3
124 2 2 5 1
125 2 1 4 1
126 4 2 3 3
127 4 1 3 1
128 3 2 3 2
129 3 1 3 3
130 3 2 4 2
131 4 3 4 2
132 3 2 3 2
133 4 1 2 2
134 4 1 3 2
135 2 2 2 2
136 4 2 4 4
137 2 1 4 2
138 4 2 4 2
139 3 3 4 3
140 3 4 4 2
141 2 2 4 2
142 2 4 5 4
143 5 5 3 4
144 2 1 4 1
145 4 3 4 3
146 3 2 4 2
147 3 2 5 4
148 3 2 3 2
149 3 1 2 1
150 4 4 4 2
151 4 2 3 2
152 4 2 4 3
153 4 3 5 5
154 4 1 3 2
155 5 4 3 4
156 3 2 3 2
157 3 2 5 2
158 4 4 4 3
159 4 4 2 4
> k <- length(x[1,])
> df <- as.data.frame(x)
> (mylm <- lm(df))
Call:
lm(formula = df)
Coefficients:
(Intercept) Q2 Q3 Q4
2.2390 0.2438 -0.1224 0.3476
> (mysum <- summary(mylm))
Call:
lm(formula = df)
Residuals:
Min 1Q Median 3Q Max
-1.99233 -0.68821 -0.03581 0.65940 1.94557
Coefficients:
Estimate Std. Error t value Pr(>|t|)
(Intercept) 2.23897 0.33598 6.664 4.40e-10 ***
Q2 0.24379 0.07946 3.068 0.00254 **
Q3 -0.12244 0.08637 -1.418 0.15830
Q4 0.34760 0.07971 4.361 2.35e-05 ***
---
Signif. codes: 0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1
Residual standard error: 0.8561 on 155 degrees of freedom
Multiple R-squared: 0.2298, Adjusted R-squared: 0.2149
F-statistic: 15.41 on 3 and 155 DF, p-value: 7.984e-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,] 0.3747783 0.74955658 0.62522171
[2,] 0.4450239 0.89004774 0.55497613
[3,] 0.3826979 0.76539576 0.61730212
[4,] 0.4582372 0.91647450 0.54176275
[5,] 0.5293852 0.94122950 0.47061475
[6,] 0.4850342 0.97006831 0.51496585
[7,] 0.3825233 0.76504655 0.61747672
[8,] 0.2916757 0.58335135 0.70832433
[9,] 0.4173730 0.83474600 0.58262700
[10,] 0.3976490 0.79529807 0.60235096
[11,] 0.3192656 0.63853120 0.68073440
[12,] 0.2734157 0.54683139 0.72658430
[13,] 0.2369131 0.47382614 0.76308693
[14,] 0.1988802 0.39776041 0.80111980
[15,] 0.2794191 0.55883813 0.72058094
[16,] 0.6187714 0.76245728 0.38122864
[17,] 0.5824054 0.83518928 0.41759464
[18,] 0.6424898 0.71502040 0.35751020
[19,] 0.5801437 0.83971265 0.41985633
[20,] 0.5650864 0.86982721 0.43491360
[21,] 0.5333695 0.93326093 0.46663046
[22,] 0.4696970 0.93939409 0.53030296
[23,] 0.4083309 0.81666185 0.59166907
[24,] 0.4026976 0.80539527 0.59730236
[25,] 0.6300596 0.73988070 0.36994035
[26,] 0.5744861 0.85102790 0.42551395
[27,] 0.6462971 0.70740585 0.35370292
[28,] 0.6778923 0.64421534 0.32210767
[29,] 0.6484893 0.70302142 0.35151071
[30,] 0.6022700 0.79545992 0.39772996
[31,] 0.6305550 0.73888995 0.36944498
[32,] 0.6487312 0.70253762 0.35126881
[33,] 0.6948748 0.61025045 0.30512523
[34,] 0.7015795 0.59684093 0.29842046
[35,] 0.6617898 0.67642040 0.33821020
[36,] 0.6341963 0.73160741 0.36580370
[37,] 0.5848763 0.83024731 0.41512365
[38,] 0.5386197 0.92276053 0.46138027
[39,] 0.5683068 0.86338638 0.43169319
[40,] 0.5574854 0.88502922 0.44251461
[41,] 0.5658625 0.86827492 0.43413746
[42,] 0.5489434 0.90211318 0.45105659
[43,] 0.5639134 0.87217320 0.43608660
[44,] 0.5694688 0.86106244 0.43053122
[45,] 0.6335321 0.73293575 0.36646788
[46,] 0.6490468 0.70190631 0.35095316
[47,] 0.6656992 0.66860166 0.33430083
[48,] 0.7225322 0.55493559 0.27746779
[49,] 0.7478351 0.50432973 0.25216486
[50,] 0.7078626 0.58427484 0.29213742
[51,] 0.7167869 0.56642616 0.28321308
[52,] 0.7659550 0.46809004 0.23404502
[53,] 0.7505534 0.49889317 0.24944658
[54,] 0.7786330 0.44273400 0.22136700
[55,] 0.7862730 0.42745396 0.21372698
[56,] 0.7555743 0.48885147 0.24442573
[57,] 0.8140215 0.37195701 0.18597851
[58,] 0.9128312 0.17433756 0.08716878
[59,] 0.9020822 0.19583563 0.09791781
[60,] 0.8936619 0.21267625 0.10633813
[61,] 0.8723115 0.25537709 0.12768854
[62,] 0.8504500 0.29909994 0.14954997
[63,] 0.8397202 0.32055959 0.16027979
[64,] 0.8439415 0.31211696 0.15605848
[65,] 0.8192964 0.36140711 0.18070355
[66,] 0.8065161 0.38696787 0.19348393
[67,] 0.7830025 0.43399508 0.21699754
[68,] 0.7530311 0.49393786 0.24696893
[69,] 0.7721584 0.45568326 0.22784163
[70,] 0.7774638 0.44507243 0.22253622
[71,] 0.7420836 0.51583287 0.25791643
[72,] 0.7365939 0.52681213 0.26340607
[73,] 0.6979242 0.60415156 0.30207578
[74,] 0.7204548 0.55909036 0.27954518
[75,] 0.7259083 0.54818349 0.27409175
[76,] 0.6894231 0.62115381 0.31057690
[77,] 0.6659680 0.66806391 0.33403195
[78,] 0.6320162 0.73596770 0.36798385
[79,] 0.6248451 0.75030987 0.37515494
[80,] 0.5969606 0.80607888 0.40303944
[81,] 0.5768469 0.84630619 0.42315310
[82,] 0.5367113 0.92657735 0.46328868
[83,] 0.4931999 0.98639977 0.50680011
[84,] 0.4513617 0.90272342 0.54863829
[85,] 0.4783152 0.95663041 0.52168480
[86,] 0.5131741 0.97365177 0.48682588
[87,] 0.4933091 0.98661818 0.50669091
[88,] 0.4465349 0.89306988 0.55346506
[89,] 0.4026337 0.80526741 0.59736629
[90,] 0.3957380 0.79147607 0.60426196
[91,] 0.5439809 0.91203817 0.45601909
[92,] 0.5404712 0.91905762 0.45952881
[93,] 0.5311529 0.93769426 0.46884713
[94,] 0.4840742 0.96814843 0.51592578
[95,] 0.4642736 0.92854724 0.53572638
[96,] 0.4183853 0.83677068 0.58161466
[97,] 0.4159001 0.83180017 0.58409991
[98,] 0.4711933 0.94238658 0.52880671
[99,] 0.4285022 0.85700437 0.57149782
[100,] 0.4594193 0.91883866 0.54058067
[101,] 0.4262213 0.85244268 0.57377866
[102,] 0.5165473 0.96690533 0.48345266
[103,] 0.5069591 0.98608171 0.49304085
[104,] 0.5430074 0.91398525 0.45699262
[105,] 0.5742691 0.85146185 0.42573093
[106,] 0.5595755 0.88084898 0.44042449
[107,] 0.7026879 0.59462421 0.29731210
[108,] 0.7743129 0.45137421 0.22568710
[109,] 0.7841295 0.43174093 0.21587047
[110,] 0.7476282 0.50474353 0.25237177
[111,] 0.7198443 0.56031135 0.28015568
[112,] 0.8979609 0.20407819 0.10203909
[113,] 0.9482965 0.10340702 0.05170351
[114,] 0.9346760 0.13064800 0.06532400
[115,] 0.9235306 0.15293874 0.07646937
[116,] 0.9142200 0.17155997 0.08577999
[117,] 0.8986708 0.20265837 0.10132918
[118,] 0.8764688 0.24706244 0.12353122
[119,] 0.8590957 0.28180856 0.14090428
[120,] 0.8327575 0.33448494 0.16724247
[121,] 0.8757792 0.24844152 0.12422076
[122,] 0.8456269 0.30874617 0.15437308
[123,] 0.8168305 0.36633906 0.18316953
[124,] 0.7713211 0.45735781 0.22867891
[125,] 0.7753158 0.44936845 0.22468423
[126,] 0.7300550 0.53989008 0.26994504
[127,] 0.7050021 0.58999575 0.29499788
[128,] 0.7248966 0.55020684 0.27510342
[129,] 0.8691068 0.26178648 0.13089324
[130,] 0.8369142 0.32617160 0.16308580
[131,] 0.8368995 0.32620107 0.16310054
[132,] 0.8671816 0.26563672 0.13281836
[133,] 0.8371701 0.32565976 0.16282988
[134,] 0.7931317 0.41373664 0.20686832
[135,] 0.8310122 0.33797551 0.16898776
[136,] 0.9860358 0.02792838 0.01396419
[137,] 0.9757714 0.04845720 0.02422860
[138,] 0.9788930 0.04221395 0.02110698
[139,] 0.9640633 0.07187346 0.03593673
[140,] 0.9431597 0.11368069 0.05684035
[141,] 0.9414618 0.11707639 0.05853820
[142,] 0.9279425 0.14411502 0.07205751
[143,] 0.8929448 0.21411041 0.10705521
[144,] 0.8285398 0.34292042 0.17146021
[145,] 0.7424714 0.51505714 0.25752857
[146,] 0.6050762 0.78984752 0.39492376
> postscript(file="/var/www/html/freestat/rcomp/tmp/1ya1w1291225568.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$resid)
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/freestat/rcomp/tmp/2ya1w1291225568.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> plot(mysum$resid, type='b', pch=19, main='Residuals', ylab='value of Residuals', xlab='time or index')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/freestat/rcomp/tmp/391ii1291225568.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> hist(mysum$resid, main='Residual Histogram', xlab='values of Residuals')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/freestat/rcomp/tmp/491ii1291225568.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> densityplot(~mysum$resid,col='black',main='Residual Density Plot', xlab='values of Residuals')
> dev.off()
null device
1
> postscript(file="/var/www/html/freestat/rcomp/tmp/591ii1291225568.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 = 159
Frequency = 1
1 2 3 4 5 6
-0.93199385 -0.58439043 0.49523826 -1.17687179 -0.17687179 1.31179161
7 8 9 10 11 12
0.31179161 -0.17577932 0.41560957 -1.62829318 0.45799626 0.72040272
13 14 15 16 17 18
-0.29821828 0.06800615 1.65939503 0.96418818 0.41560957 -0.17687179
19 20 21 22 23 24
-0.62720071 0.37279929 -1.03581182 1.94556718 -0.01204614 -0.93199385
25 26 27 28 29 30
-0.17687179 0.59796375 0.72040272 -0.05443282 0.12901383 1.06800615
31 32 33 34 35 36
-1.68820839 0.23283180 1.26898133 -0.93199385 0.72040272 0.53804854
37 38 39 40 41 42
-0.93199385 0.82312821 1.37279929 1.06800615 0.49523826 0.72040272
43 44 45 46 47 48
-0.17687179 0.37279929 -0.93199385 -0.68820839 0.82312821 -0.56576943
49 50 51 52 53 54
1.06800615 0.96418818 -1.34060497 1.06800615 -0.93199385 -1.46304393
55 56 57 58 59 60
-0.58372155 0.06800615 -0.93199385 1.31179161 0.65939503 -1.17687179
61 62 63 64 65 66
-0.93199385 0.31179161 -1.38341525 -1.93199385 0.53695607 -0.68820839
67 68 69 70 71 72
-0.17687179 0.31179161 0.65939503 -0.93199385 0.31179161 -0.68820839
73 74 75 76 77 78
0.47661726 0.35417829 1.06800615 -0.93199385 -0.03581182 0.82422068
79 80 81 82 83 84
0.06800615 1.06800615 -0.93199385 -0.17687179 0.53695607 0.35527076
85 86 87 88 89 90
-0.81064736 0.49414579 -0.68820839 -0.34060497 -0.11477163 -0.27959728
91 92 93 94 95 96
1.06800615 -1.15825079 -0.68820839 -0.03581182 -0.17577932 0.66006391
97 98 99 100 101 102
-1.76716820 -0.87098617 0.82312821 -0.05443282 0.70178172 -0.15825079
103 104 105 106 107 108
-0.87098617 -1.27959728 -0.17687179 -1.05443282 -0.40203625 -1.41956478
109 110 111 112 113 114
0.82422068 -0.93308633 1.18935264 0.72040272 -1.68820839 1.25145280
115 116 117 118 119 120
-0.70682939 -0.05443282 0.37279929 -1.81064736 1.70178172 0.41451710
121 122 123 124 125 126
0.65939503 -0.40203625 -0.52338274 -0.46195146 -0.34060497 0.59796375
127 128 129 130 131 132
1.53695607 -0.05443282 -0.15825079 0.06800615 0.82422068 -0.05443282
133 134 135 136 137 138
1.06691367 1.18935264 -1.17687179 0.37279929 -0.68820839 1.06800615
139 140 141 142 143 144
-0.52338274 -0.41956478 -0.93199385 -1.99233266 0.51900394 -0.34060497
145 146 147 148 149 150
0.47661726 0.06800615 -0.50476174 -0.05443282 0.41451710 0.58043522
151 152 153 154 155 156
0.94556718 0.72040272 -0.09615063 1.18935264 0.76278940 -0.05443282
157 158 159
0.19044511 0.23283180 -0.35964956
> postscript(file="/var/www/html/freestat/rcomp/tmp/6ks031291225568.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 = 159
Frequency = 1
lag(myerror, k = 1) myerror
0 -0.93199385 NA
1 -0.58439043 -0.93199385
2 0.49523826 -0.58439043
3 -1.17687179 0.49523826
4 -0.17687179 -1.17687179
5 1.31179161 -0.17687179
6 0.31179161 1.31179161
7 -0.17577932 0.31179161
8 0.41560957 -0.17577932
9 -1.62829318 0.41560957
10 0.45799626 -1.62829318
11 0.72040272 0.45799626
12 -0.29821828 0.72040272
13 0.06800615 -0.29821828
14 1.65939503 0.06800615
15 0.96418818 1.65939503
16 0.41560957 0.96418818
17 -0.17687179 0.41560957
18 -0.62720071 -0.17687179
19 0.37279929 -0.62720071
20 -1.03581182 0.37279929
21 1.94556718 -1.03581182
22 -0.01204614 1.94556718
23 -0.93199385 -0.01204614
24 -0.17687179 -0.93199385
25 0.59796375 -0.17687179
26 0.72040272 0.59796375
27 -0.05443282 0.72040272
28 0.12901383 -0.05443282
29 1.06800615 0.12901383
30 -1.68820839 1.06800615
31 0.23283180 -1.68820839
32 1.26898133 0.23283180
33 -0.93199385 1.26898133
34 0.72040272 -0.93199385
35 0.53804854 0.72040272
36 -0.93199385 0.53804854
37 0.82312821 -0.93199385
38 1.37279929 0.82312821
39 1.06800615 1.37279929
40 0.49523826 1.06800615
41 0.72040272 0.49523826
42 -0.17687179 0.72040272
43 0.37279929 -0.17687179
44 -0.93199385 0.37279929
45 -0.68820839 -0.93199385
46 0.82312821 -0.68820839
47 -0.56576943 0.82312821
48 1.06800615 -0.56576943
49 0.96418818 1.06800615
50 -1.34060497 0.96418818
51 1.06800615 -1.34060497
52 -0.93199385 1.06800615
53 -1.46304393 -0.93199385
54 -0.58372155 -1.46304393
55 0.06800615 -0.58372155
56 -0.93199385 0.06800615
57 1.31179161 -0.93199385
58 0.65939503 1.31179161
59 -1.17687179 0.65939503
60 -0.93199385 -1.17687179
61 0.31179161 -0.93199385
62 -1.38341525 0.31179161
63 -1.93199385 -1.38341525
64 0.53695607 -1.93199385
65 -0.68820839 0.53695607
66 -0.17687179 -0.68820839
67 0.31179161 -0.17687179
68 0.65939503 0.31179161
69 -0.93199385 0.65939503
70 0.31179161 -0.93199385
71 -0.68820839 0.31179161
72 0.47661726 -0.68820839
73 0.35417829 0.47661726
74 1.06800615 0.35417829
75 -0.93199385 1.06800615
76 -0.03581182 -0.93199385
77 0.82422068 -0.03581182
78 0.06800615 0.82422068
79 1.06800615 0.06800615
80 -0.93199385 1.06800615
81 -0.17687179 -0.93199385
82 0.53695607 -0.17687179
83 0.35527076 0.53695607
84 -0.81064736 0.35527076
85 0.49414579 -0.81064736
86 -0.68820839 0.49414579
87 -0.34060497 -0.68820839
88 -0.11477163 -0.34060497
89 -0.27959728 -0.11477163
90 1.06800615 -0.27959728
91 -1.15825079 1.06800615
92 -0.68820839 -1.15825079
93 -0.03581182 -0.68820839
94 -0.17577932 -0.03581182
95 0.66006391 -0.17577932
96 -1.76716820 0.66006391
97 -0.87098617 -1.76716820
98 0.82312821 -0.87098617
99 -0.05443282 0.82312821
100 0.70178172 -0.05443282
101 -0.15825079 0.70178172
102 -0.87098617 -0.15825079
103 -1.27959728 -0.87098617
104 -0.17687179 -1.27959728
105 -1.05443282 -0.17687179
106 -0.40203625 -1.05443282
107 -1.41956478 -0.40203625
108 0.82422068 -1.41956478
109 -0.93308633 0.82422068
110 1.18935264 -0.93308633
111 0.72040272 1.18935264
112 -1.68820839 0.72040272
113 1.25145280 -1.68820839
114 -0.70682939 1.25145280
115 -0.05443282 -0.70682939
116 0.37279929 -0.05443282
117 -1.81064736 0.37279929
118 1.70178172 -1.81064736
119 0.41451710 1.70178172
120 0.65939503 0.41451710
121 -0.40203625 0.65939503
122 -0.52338274 -0.40203625
123 -0.46195146 -0.52338274
124 -0.34060497 -0.46195146
125 0.59796375 -0.34060497
126 1.53695607 0.59796375
127 -0.05443282 1.53695607
128 -0.15825079 -0.05443282
129 0.06800615 -0.15825079
130 0.82422068 0.06800615
131 -0.05443282 0.82422068
132 1.06691367 -0.05443282
133 1.18935264 1.06691367
134 -1.17687179 1.18935264
135 0.37279929 -1.17687179
136 -0.68820839 0.37279929
137 1.06800615 -0.68820839
138 -0.52338274 1.06800615
139 -0.41956478 -0.52338274
140 -0.93199385 -0.41956478
141 -1.99233266 -0.93199385
142 0.51900394 -1.99233266
143 -0.34060497 0.51900394
144 0.47661726 -0.34060497
145 0.06800615 0.47661726
146 -0.50476174 0.06800615
147 -0.05443282 -0.50476174
148 0.41451710 -0.05443282
149 0.58043522 0.41451710
150 0.94556718 0.58043522
151 0.72040272 0.94556718
152 -0.09615063 0.72040272
153 1.18935264 -0.09615063
154 0.76278940 1.18935264
155 -0.05443282 0.76278940
156 0.19044511 -0.05443282
157 0.23283180 0.19044511
158 -0.35964956 0.23283180
159 NA -0.35964956
> dum1 <- dum[2:length(myerror),]
> dum1
lag(myerror, k = 1) myerror
[1,] -0.58439043 -0.93199385
[2,] 0.49523826 -0.58439043
[3,] -1.17687179 0.49523826
[4,] -0.17687179 -1.17687179
[5,] 1.31179161 -0.17687179
[6,] 0.31179161 1.31179161
[7,] -0.17577932 0.31179161
[8,] 0.41560957 -0.17577932
[9,] -1.62829318 0.41560957
[10,] 0.45799626 -1.62829318
[11,] 0.72040272 0.45799626
[12,] -0.29821828 0.72040272
[13,] 0.06800615 -0.29821828
[14,] 1.65939503 0.06800615
[15,] 0.96418818 1.65939503
[16,] 0.41560957 0.96418818
[17,] -0.17687179 0.41560957
[18,] -0.62720071 -0.17687179
[19,] 0.37279929 -0.62720071
[20,] -1.03581182 0.37279929
[21,] 1.94556718 -1.03581182
[22,] -0.01204614 1.94556718
[23,] -0.93199385 -0.01204614
[24,] -0.17687179 -0.93199385
[25,] 0.59796375 -0.17687179
[26,] 0.72040272 0.59796375
[27,] -0.05443282 0.72040272
[28,] 0.12901383 -0.05443282
[29,] 1.06800615 0.12901383
[30,] -1.68820839 1.06800615
[31,] 0.23283180 -1.68820839
[32,] 1.26898133 0.23283180
[33,] -0.93199385 1.26898133
[34,] 0.72040272 -0.93199385
[35,] 0.53804854 0.72040272
[36,] -0.93199385 0.53804854
[37,] 0.82312821 -0.93199385
[38,] 1.37279929 0.82312821
[39,] 1.06800615 1.37279929
[40,] 0.49523826 1.06800615
[41,] 0.72040272 0.49523826
[42,] -0.17687179 0.72040272
[43,] 0.37279929 -0.17687179
[44,] -0.93199385 0.37279929
[45,] -0.68820839 -0.93199385
[46,] 0.82312821 -0.68820839
[47,] -0.56576943 0.82312821
[48,] 1.06800615 -0.56576943
[49,] 0.96418818 1.06800615
[50,] -1.34060497 0.96418818
[51,] 1.06800615 -1.34060497
[52,] -0.93199385 1.06800615
[53,] -1.46304393 -0.93199385
[54,] -0.58372155 -1.46304393
[55,] 0.06800615 -0.58372155
[56,] -0.93199385 0.06800615
[57,] 1.31179161 -0.93199385
[58,] 0.65939503 1.31179161
[59,] -1.17687179 0.65939503
[60,] -0.93199385 -1.17687179
[61,] 0.31179161 -0.93199385
[62,] -1.38341525 0.31179161
[63,] -1.93199385 -1.38341525
[64,] 0.53695607 -1.93199385
[65,] -0.68820839 0.53695607
[66,] -0.17687179 -0.68820839
[67,] 0.31179161 -0.17687179
[68,] 0.65939503 0.31179161
[69,] -0.93199385 0.65939503
[70,] 0.31179161 -0.93199385
[71,] -0.68820839 0.31179161
[72,] 0.47661726 -0.68820839
[73,] 0.35417829 0.47661726
[74,] 1.06800615 0.35417829
[75,] -0.93199385 1.06800615
[76,] -0.03581182 -0.93199385
[77,] 0.82422068 -0.03581182
[78,] 0.06800615 0.82422068
[79,] 1.06800615 0.06800615
[80,] -0.93199385 1.06800615
[81,] -0.17687179 -0.93199385
[82,] 0.53695607 -0.17687179
[83,] 0.35527076 0.53695607
[84,] -0.81064736 0.35527076
[85,] 0.49414579 -0.81064736
[86,] -0.68820839 0.49414579
[87,] -0.34060497 -0.68820839
[88,] -0.11477163 -0.34060497
[89,] -0.27959728 -0.11477163
[90,] 1.06800615 -0.27959728
[91,] -1.15825079 1.06800615
[92,] -0.68820839 -1.15825079
[93,] -0.03581182 -0.68820839
[94,] -0.17577932 -0.03581182
[95,] 0.66006391 -0.17577932
[96,] -1.76716820 0.66006391
[97,] -0.87098617 -1.76716820
[98,] 0.82312821 -0.87098617
[99,] -0.05443282 0.82312821
[100,] 0.70178172 -0.05443282
[101,] -0.15825079 0.70178172
[102,] -0.87098617 -0.15825079
[103,] -1.27959728 -0.87098617
[104,] -0.17687179 -1.27959728
[105,] -1.05443282 -0.17687179
[106,] -0.40203625 -1.05443282
[107,] -1.41956478 -0.40203625
[108,] 0.82422068 -1.41956478
[109,] -0.93308633 0.82422068
[110,] 1.18935264 -0.93308633
[111,] 0.72040272 1.18935264
[112,] -1.68820839 0.72040272
[113,] 1.25145280 -1.68820839
[114,] -0.70682939 1.25145280
[115,] -0.05443282 -0.70682939
[116,] 0.37279929 -0.05443282
[117,] -1.81064736 0.37279929
[118,] 1.70178172 -1.81064736
[119,] 0.41451710 1.70178172
[120,] 0.65939503 0.41451710
[121,] -0.40203625 0.65939503
[122,] -0.52338274 -0.40203625
[123,] -0.46195146 -0.52338274
[124,] -0.34060497 -0.46195146
[125,] 0.59796375 -0.34060497
[126,] 1.53695607 0.59796375
[127,] -0.05443282 1.53695607
[128,] -0.15825079 -0.05443282
[129,] 0.06800615 -0.15825079
[130,] 0.82422068 0.06800615
[131,] -0.05443282 0.82422068
[132,] 1.06691367 -0.05443282
[133,] 1.18935264 1.06691367
[134,] -1.17687179 1.18935264
[135,] 0.37279929 -1.17687179
[136,] -0.68820839 0.37279929
[137,] 1.06800615 -0.68820839
[138,] -0.52338274 1.06800615
[139,] -0.41956478 -0.52338274
[140,] -0.93199385 -0.41956478
[141,] -1.99233266 -0.93199385
[142,] 0.51900394 -1.99233266
[143,] -0.34060497 0.51900394
[144,] 0.47661726 -0.34060497
[145,] 0.06800615 0.47661726
[146,] -0.50476174 0.06800615
[147,] -0.05443282 -0.50476174
[148,] 0.41451710 -0.05443282
[149,] 0.58043522 0.41451710
[150,] 0.94556718 0.58043522
[151,] 0.72040272 0.94556718
[152,] -0.09615063 0.72040272
[153,] 1.18935264 -0.09615063
[154,] 0.76278940 1.18935264
[155,] -0.05443282 0.76278940
[156,] 0.19044511 -0.05443282
[157,] 0.23283180 0.19044511
[158,] -0.35964956 0.23283180
> z <- as.data.frame(dum1)
> z
lag(myerror, k = 1) myerror
1 -0.58439043 -0.93199385
2 0.49523826 -0.58439043
3 -1.17687179 0.49523826
4 -0.17687179 -1.17687179
5 1.31179161 -0.17687179
6 0.31179161 1.31179161
7 -0.17577932 0.31179161
8 0.41560957 -0.17577932
9 -1.62829318 0.41560957
10 0.45799626 -1.62829318
11 0.72040272 0.45799626
12 -0.29821828 0.72040272
13 0.06800615 -0.29821828
14 1.65939503 0.06800615
15 0.96418818 1.65939503
16 0.41560957 0.96418818
17 -0.17687179 0.41560957
18 -0.62720071 -0.17687179
19 0.37279929 -0.62720071
20 -1.03581182 0.37279929
21 1.94556718 -1.03581182
22 -0.01204614 1.94556718
23 -0.93199385 -0.01204614
24 -0.17687179 -0.93199385
25 0.59796375 -0.17687179
26 0.72040272 0.59796375
27 -0.05443282 0.72040272
28 0.12901383 -0.05443282
29 1.06800615 0.12901383
30 -1.68820839 1.06800615
31 0.23283180 -1.68820839
32 1.26898133 0.23283180
33 -0.93199385 1.26898133
34 0.72040272 -0.93199385
35 0.53804854 0.72040272
36 -0.93199385 0.53804854
37 0.82312821 -0.93199385
38 1.37279929 0.82312821
39 1.06800615 1.37279929
40 0.49523826 1.06800615
41 0.72040272 0.49523826
42 -0.17687179 0.72040272
43 0.37279929 -0.17687179
44 -0.93199385 0.37279929
45 -0.68820839 -0.93199385
46 0.82312821 -0.68820839
47 -0.56576943 0.82312821
48 1.06800615 -0.56576943
49 0.96418818 1.06800615
50 -1.34060497 0.96418818
51 1.06800615 -1.34060497
52 -0.93199385 1.06800615
53 -1.46304393 -0.93199385
54 -0.58372155 -1.46304393
55 0.06800615 -0.58372155
56 -0.93199385 0.06800615
57 1.31179161 -0.93199385
58 0.65939503 1.31179161
59 -1.17687179 0.65939503
60 -0.93199385 -1.17687179
61 0.31179161 -0.93199385
62 -1.38341525 0.31179161
63 -1.93199385 -1.38341525
64 0.53695607 -1.93199385
65 -0.68820839 0.53695607
66 -0.17687179 -0.68820839
67 0.31179161 -0.17687179
68 0.65939503 0.31179161
69 -0.93199385 0.65939503
70 0.31179161 -0.93199385
71 -0.68820839 0.31179161
72 0.47661726 -0.68820839
73 0.35417829 0.47661726
74 1.06800615 0.35417829
75 -0.93199385 1.06800615
76 -0.03581182 -0.93199385
77 0.82422068 -0.03581182
78 0.06800615 0.82422068
79 1.06800615 0.06800615
80 -0.93199385 1.06800615
81 -0.17687179 -0.93199385
82 0.53695607 -0.17687179
83 0.35527076 0.53695607
84 -0.81064736 0.35527076
85 0.49414579 -0.81064736
86 -0.68820839 0.49414579
87 -0.34060497 -0.68820839
88 -0.11477163 -0.34060497
89 -0.27959728 -0.11477163
90 1.06800615 -0.27959728
91 -1.15825079 1.06800615
92 -0.68820839 -1.15825079
93 -0.03581182 -0.68820839
94 -0.17577932 -0.03581182
95 0.66006391 -0.17577932
96 -1.76716820 0.66006391
97 -0.87098617 -1.76716820
98 0.82312821 -0.87098617
99 -0.05443282 0.82312821
100 0.70178172 -0.05443282
101 -0.15825079 0.70178172
102 -0.87098617 -0.15825079
103 -1.27959728 -0.87098617
104 -0.17687179 -1.27959728
105 -1.05443282 -0.17687179
106 -0.40203625 -1.05443282
107 -1.41956478 -0.40203625
108 0.82422068 -1.41956478
109 -0.93308633 0.82422068
110 1.18935264 -0.93308633
111 0.72040272 1.18935264
112 -1.68820839 0.72040272
113 1.25145280 -1.68820839
114 -0.70682939 1.25145280
115 -0.05443282 -0.70682939
116 0.37279929 -0.05443282
117 -1.81064736 0.37279929
118 1.70178172 -1.81064736
119 0.41451710 1.70178172
120 0.65939503 0.41451710
121 -0.40203625 0.65939503
122 -0.52338274 -0.40203625
123 -0.46195146 -0.52338274
124 -0.34060497 -0.46195146
125 0.59796375 -0.34060497
126 1.53695607 0.59796375
127 -0.05443282 1.53695607
128 -0.15825079 -0.05443282
129 0.06800615 -0.15825079
130 0.82422068 0.06800615
131 -0.05443282 0.82422068
132 1.06691367 -0.05443282
133 1.18935264 1.06691367
134 -1.17687179 1.18935264
135 0.37279929 -1.17687179
136 -0.68820839 0.37279929
137 1.06800615 -0.68820839
138 -0.52338274 1.06800615
139 -0.41956478 -0.52338274
140 -0.93199385 -0.41956478
141 -1.99233266 -0.93199385
142 0.51900394 -1.99233266
143 -0.34060497 0.51900394
144 0.47661726 -0.34060497
145 0.06800615 0.47661726
146 -0.50476174 0.06800615
147 -0.05443282 -0.50476174
148 0.41451710 -0.05443282
149 0.58043522 0.41451710
150 0.94556718 0.58043522
151 0.72040272 0.94556718
152 -0.09615063 0.72040272
153 1.18935264 -0.09615063
154 0.76278940 1.18935264
155 -0.05443282 0.76278940
156 0.19044511 -0.05443282
157 0.23283180 0.19044511
158 -0.35964956 0.23283180
> plot(z,main=paste('Residual Lag plot, lowess, and regression line'), ylab='values of Residuals', xlab='lagged values of Residuals')
> lines(lowess(z))
> abline(lm(z))
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/freestat/rcomp/tmp/7d1z51291225568.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> acf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/freestat/rcomp/tmp/8d1z51291225568.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> pacf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Partial Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/freestat/rcomp/tmp/9d1z51291225568.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> opar <- par(mfrow = c(2,2), oma = c(0, 0, 1.1, 0))
> plot(mylm, las = 1, sub='Residual Diagnostics')
> par(opar)
> dev.off()
null device
1
> if (n > n25) {
+ postscript(file="/var/www/html/freestat/rcomp/tmp/105ty81291225568.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
+ plot(kp3:nmkm3,gqarr[,2], main='Goldfeld-Quandt test',ylab='2-sided p-value',xlab='breakpoint')
+ grid()
+ dev.off()
+ }
null device
1
>
> #Note: the /var/www/html/freestat/rcomp/createtable file can be downloaded at http://www.wessa.net/cretab
> load(file="/var/www/html/freestat/rcomp/createtable")
>
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a, 'Multiple Linear Regression - Estimated Regression Equation', 1, TRUE)
> a<-table.row.end(a)
> myeq <- colnames(x)[1]
> myeq <- paste(myeq, '[t] = ', sep='')
> for (i in 1:k){
+ if (mysum$coefficients[i,1] > 0) myeq <- paste(myeq, '+', '')
+ myeq <- paste(myeq, mysum$coefficients[i,1], sep=' ')
+ if (rownames(mysum$coefficients)[i] != '(Intercept)') {
+ myeq <- paste(myeq, rownames(mysum$coefficients)[i], sep='')
+ if (rownames(mysum$coefficients)[i] != 't') myeq <- paste(myeq, '[t]', sep='')
+ }
+ }
> myeq <- paste(myeq, ' + e[t]')
> a<-table.row.start(a)
> a<-table.element(a, myeq)
> a<-table.row.end(a)
> a<-table.end(a)
> table.save(a,file="/var/www/html/freestat/rcomp/tmp/11rtfw1291225568.tab")
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a,hyperlink('http://www.xycoon.com/ols1.htm','Multiple Linear Regression - Ordinary Least Squares',''), 6, TRUE)
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a,'Variable',header=TRUE)
> a<-table.element(a,'Parameter',header=TRUE)
> a<-table.element(a,'S.D.',header=TRUE)
> a<-table.element(a,'T-STAT
H0: parameter = 0',header=TRUE)
> a<-table.element(a,'2-tail p-value',header=TRUE)
> a<-table.element(a,'1-tail p-value',header=TRUE)
> a<-table.row.end(a)
> for (i in 1:k){
+ a<-table.row.start(a)
+ a<-table.element(a,rownames(mysum$coefficients)[i],header=TRUE)
+ a<-table.element(a,mysum$coefficients[i,1])
+ a<-table.element(a, round(mysum$coefficients[i,2],6))
+ a<-table.element(a, round(mysum$coefficients[i,3],4))
+ a<-table.element(a, round(mysum$coefficients[i,4],6))
+ a<-table.element(a, round(mysum$coefficients[i,4]/2,6))
+ a<-table.row.end(a)
+ }
> a<-table.end(a)
> table.save(a,file="/var/www/html/freestat/rcomp/tmp/12cuvk1291225568.tab")
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a, 'Multiple Linear Regression - Regression Statistics', 2, TRUE)
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a, 'Multiple R',1,TRUE)
> a<-table.element(a, sqrt(mysum$r.squared))
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a, 'R-squared',1,TRUE)
> a<-table.element(a, mysum$r.squared)
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a, 'Adjusted R-squared',1,TRUE)
> a<-table.element(a, mysum$adj.r.squared)
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a, 'F-TEST (value)',1,TRUE)
> a<-table.element(a, mysum$fstatistic[1])
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a, 'F-TEST (DF numerator)',1,TRUE)
> a<-table.element(a, mysum$fstatistic[2])
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a, 'F-TEST (DF denominator)',1,TRUE)
> a<-table.element(a, mysum$fstatistic[3])
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a, 'p-value',1,TRUE)
> a<-table.element(a, 1-pf(mysum$fstatistic[1],mysum$fstatistic[2],mysum$fstatistic[3]))
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a, 'Multiple Linear Regression - Residual Statistics', 2, TRUE)
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a, 'Residual Standard Deviation',1,TRUE)
> a<-table.element(a, mysum$sigma)
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a, 'Sum Squared Residuals',1,TRUE)
> a<-table.element(a, sum(myerror*myerror))
> a<-table.row.end(a)
> a<-table.end(a)
> table.save(a,file="/var/www/html/freestat/rcomp/tmp/1384bb1291225568.tab")
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a, 'Multiple Linear Regression - Actuals, Interpolation, and Residuals', 4, TRUE)
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a, 'Time or Index', 1, TRUE)
> a<-table.element(a, 'Actuals', 1, TRUE)
> a<-table.element(a, 'Interpolation
Forecast', 1, TRUE)
> a<-table.element(a, 'Residuals
Prediction Error', 1, TRUE)
> a<-table.row.end(a)
> for (i in 1:n) {
+ a<-table.row.start(a)
+ a<-table.element(a,i, 1, TRUE)
+ a<-table.element(a,x[i])
+ a<-table.element(a,x[i]-mysum$resid[i])
+ a<-table.element(a,mysum$resid[i])
+ a<-table.row.end(a)
+ }
> a<-table.end(a)
> table.save(a,file="/var/www/html/freestat/rcomp/tmp/14um9z1291225568.tab")
> if (n > n25) {
+ a<-table.start()
+ a<-table.row.start(a)
+ a<-table.element(a,'Goldfeld-Quandt test for Heteroskedasticity',4,TRUE)
+ a<-table.row.end(a)
+ a<-table.row.start(a)
+ a<-table.element(a,'p-values',header=TRUE)
+ a<-table.element(a,'Alternative Hypothesis',3,header=TRUE)
+ a<-table.row.end(a)
+ a<-table.row.start(a)
+ a<-table.element(a,'breakpoint index',header=TRUE)
+ a<-table.element(a,'greater',header=TRUE)
+ a<-table.element(a,'2-sided',header=TRUE)
+ a<-table.element(a,'less',header=TRUE)
+ a<-table.row.end(a)
+ for (mypoint in kp3:nmkm3) {
+ a<-table.row.start(a)
+ a<-table.element(a,mypoint,header=TRUE)
+ a<-table.element(a,gqarr[mypoint-kp3+1,1])
+ a<-table.element(a,gqarr[mypoint-kp3+1,2])
+ a<-table.element(a,gqarr[mypoint-kp3+1,3])
+ a<-table.row.end(a)
+ }
+ a<-table.end(a)
+ table.save(a,file="/var/www/html/freestat/rcomp/tmp/15xn841291225568.tab")
+ a<-table.start()
+ a<-table.row.start(a)
+ a<-table.element(a,'Meta Analysis of Goldfeld-Quandt test for Heteroskedasticity',4,TRUE)
+ a<-table.row.end(a)
+ a<-table.row.start(a)
+ a<-table.element(a,'Description',header=TRUE)
+ a<-table.element(a,'# significant tests',header=TRUE)
+ a<-table.element(a,'% significant tests',header=TRUE)
+ a<-table.element(a,'OK/NOK',header=TRUE)
+ a<-table.row.end(a)
+ a<-table.row.start(a)
+ a<-table.element(a,'1% type I error level',header=TRUE)
+ a<-table.element(a,numsignificant1)
+ a<-table.element(a,numsignificant1/numgqtests)
+ if (numsignificant1/numgqtests < 0.01) dum <- 'OK' else dum <- 'NOK'
+ a<-table.element(a,dum)
+ a<-table.row.end(a)
+ a<-table.row.start(a)
+ a<-table.element(a,'5% type I error level',header=TRUE)
+ a<-table.element(a,numsignificant5)
+ a<-table.element(a,numsignificant5/numgqtests)
+ if (numsignificant5/numgqtests < 0.05) dum <- 'OK' else dum <- 'NOK'
+ a<-table.element(a,dum)
+ a<-table.row.end(a)
+ a<-table.row.start(a)
+ a<-table.element(a,'10% type I error level',header=TRUE)
+ a<-table.element(a,numsignificant10)
+ a<-table.element(a,numsignificant10/numgqtests)
+ if (numsignificant10/numgqtests < 0.1) dum <- 'OK' else dum <- 'NOK'
+ a<-table.element(a,dum)
+ a<-table.row.end(a)
+ a<-table.end(a)
+ table.save(a,file="/var/www/html/freestat/rcomp/tmp/16in6a1291225568.tab")
+ }
>
> try(system("convert tmp/1ya1w1291225568.ps tmp/1ya1w1291225568.png",intern=TRUE))
character(0)
> try(system("convert tmp/2ya1w1291225568.ps tmp/2ya1w1291225568.png",intern=TRUE))
character(0)
> try(system("convert tmp/391ii1291225568.ps tmp/391ii1291225568.png",intern=TRUE))
character(0)
> try(system("convert tmp/491ii1291225568.ps tmp/491ii1291225568.png",intern=TRUE))
character(0)
> try(system("convert tmp/591ii1291225568.ps tmp/591ii1291225568.png",intern=TRUE))
character(0)
> try(system("convert tmp/6ks031291225568.ps tmp/6ks031291225568.png",intern=TRUE))
character(0)
> try(system("convert tmp/7d1z51291225568.ps tmp/7d1z51291225568.png",intern=TRUE))
character(0)
> try(system("convert tmp/8d1z51291225568.ps tmp/8d1z51291225568.png",intern=TRUE))
character(0)
> try(system("convert tmp/9d1z51291225568.ps tmp/9d1z51291225568.png",intern=TRUE))
character(0)
> try(system("convert tmp/105ty81291225568.ps tmp/105ty81291225568.png",intern=TRUE))
character(0)
>
>
> proc.time()
user system elapsed
5.439 2.645 5.859