R version 2.12.1 (2010-12-16)
Copyright (C) 2010 The R Foundation for Statistical Computing
ISBN 3-900051-07-0
Platform: i486-pc-linux-gnu (32-bit)
R is free software and comes with ABSOLUTELY NO WARRANTY.
You are welcome to redistribute it under certain conditions.
Type 'license()' or 'licence()' for distribution details.
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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(10345
+ ,3010
+ ,13
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+ ,6
+ ,6)
+ ,dim=c(4
+ ,144)
+ ,dimnames=list(c('Y_t'
+ ,'X_1t'
+ ,'X_2t'
+ ,'X_3t')
+ ,1:144))
> y <- array(NA,dim=c(4,144),dimnames=list(c('Y_t','X_1t','X_2t','X_3t'),1:144))
> 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
> 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_t X_1t X_2t X_3t
1 10345 3010 13 13
2 17607 4344 27 24
3 1423 603 0 0
4 20050 6792 37 37
5 21212 7843 39 38
6 93979 13738 99 96
7 15524 4120 21 21
8 16182 4174 33 33
9 19238 6202 36 35
10 28909 8535 44 40
11 22357 5818 33 33
12 25560 9834 47 47
13 9954 4145 19 19
14 18490 4719 41 40
15 17777 3981 22 22
16 25268 3264 17 17
17 37525 11276 46 46
18 6023 1 0 0
19 25042 9480 31 31
20 35713 1953 20 20
21 7039 1801 10 10
22 40841 7352 55 55
23 9214 761 6 6
24 17446 1147 17 17
25 10295 3536 33 33
26 13206 3146 33 33
27 26093 6764 32 32
28 20744 7038 37 36
29 68013 8298 44 39
30 12840 5718 22 22
31 12672 2493 15 15
32 10872 4226 18 18
33 21325 3553 25 24
34 24542 58 7 7
35 16401 4425 35 34
36 0 0 0 0
37 12821 3705 14 7
38 14662 4968 31 31
39 22190 2320 9 9
40 37929 9820 59 52
41 18009 3606 62 60
42 11076 3987 12 11
43 24981 2138 23 20
44 30691 2299 31 31
45 29164 3308 57 56
46 13985 4721 23 23
47 7588 1369 14 14
48 20023 4118 31 30
49 25524 5396 17 17
50 14717 3704 24 24
51 6832 1801 11 11
52 9624 3814 16 16
53 24300 5010 32 30
54 21790 5369 36 35
55 16493 3952 37 37
56 9269 3264 25 25
57 20105 4177 30 30
58 11216 2352 10 9
59 15569 5624 16 16
60 21799 176 3 3
61 3772 2356 0 0
62 6057 1700 17 19
63 20828 1262 9 9
64 9976 2766 22 18
65 14055 2536 5 5
66 17455 4931 23 22
67 39553 9606 16 16
68 14818 4097 53 53
69 17065 4537 23 23
70 1536 516 0 0
71 11938 2643 51 50
72 24589 1277 25 25
73 21332 3230 51 48
74 13229 3356 46 46
75 11331 2204 16 16
76 853 342 0 0
77 19821 6783 25 25
78 34666 4213 34 33
79 15051 2822 14 14
80 27969 5199 32 30
81 17897 4780 24 23
82 6031 2341 16 16
83 7153 1825 19 19
84 13365 4653 27 27
85 11197 1524 24 24
86 25291 2685 12 12
87 28994 9230 43 43
88 10461 2490 13 13
89 16415 4718 19 19
90 8495 2937 24 24
91 18318 3599 27 27
92 25143 4487 26 26
93 20471 2149 14 14
94 14561 1921 26 26
95 16902 2896 15 15
96 12994 5815 30 29
97 29697 4679 33 33
98 3895 786 14 14
99 9807 4006 11 11
100 10711 2686 12 11
101 2325 593 8 8
102 19000 2454 22 22
103 22418 4061 12 11
104 7872 2856 6 6
105 5650 1678 10 10
106 3979 460 1 0
107 14956 5054 31 30
108 3738 999 5 5
109 0 0 0 0
110 10586 3685 35 34
111 18122 503 15 15
112 17899 3595 36 34
113 10913 3367 27 28
114 18060 1330 36 36
115 0 0 0 0
116 0 0 0 0
117 15452 6878 29 29
118 33996 3080 19 19
119 8877 1349 16 15
120 18708 3339 15 15
121 2781 4 1 1
122 20854 3446 36 36
123 8179 1467 22 22
124 7139 255 16 16
125 13798 424 1 1
126 5619 2374 10 10
127 13050 3519 31 31
128 11297 2650 22 22
129 16170 2757 22 21
130 0 0 0 0
131 0 0 0 0
132 20539 459 10 10
133 0 0 0 0
134 10056 549 9 9
135 0 0 0 0
136 2418 206 0 0
137 0 0 0 0
138 11806 2885 7 7
139 15924 1034 2 2
140 0 0 0 0
141 0 0 0 0
142 7084 2558 16 16
143 14831 5086 25 25
144 6585 1392 6 6
> k <- length(x[1,])
> df <- as.data.frame(x)
> (mylm <- lm(df))
Call:
lm(formula = df)
Coefficients:
(Intercept) X_1t X_2t X_3t
3171.068 1.963 1411.542 -1151.728
> (mysum <- summary(mylm))
Call:
lm(formula = df)
Residuals:
Min 1Q Median 3Q Max
-10824 -4720 -2495 2869 34659
Coefficients:
Estimate Std. Error t value Pr(>|t|)
(Intercept) 3171.0682 1151.1018 2.755 0.00665 **
X_1t 1.9633 0.3882 5.057 1.31e-06 ***
X_2t 1411.5421 596.7693 2.365 0.01939 *
X_3t -1151.7280 606.9874 -1.897 0.05983 .
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
Residual standard error: 7943 on 140 degrees of freedom
Multiple R-squared: 0.5811, Adjusted R-squared: 0.5721
F-statistic: 64.73 on 3 and 140 DF, p-value: < 2.2e-16
> 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,] 0.2046111 4.092222e-01 7.953889e-01
[2,] 0.7551847 4.896307e-01 2.448153e-01
[3,] 0.7083673 5.832654e-01 2.916327e-01
[4,] 0.6027115 7.945770e-01 3.972885e-01
[5,] 0.4865326 9.730651e-01 5.134674e-01
[6,] 0.3828477 7.656955e-01 6.171523e-01
[7,] 0.2953285 5.906570e-01 7.046715e-01
[8,] 0.5905535 8.188931e-01 4.094465e-01
[9,] 0.5563229 8.873542e-01 4.436771e-01
[10,] 0.8010323 3.979353e-01 1.989677e-01
[11,] 0.7843709 4.312583e-01 2.156291e-01
[12,] 0.7966489 4.067023e-01 2.033511e-01
[13,] 0.7616077 4.767846e-01 2.383923e-01
[14,] 0.9535345 9.293095e-02 4.646547e-02
[15,] 0.9341848 1.316304e-01 6.581518e-02
[16,] 0.9232382 1.535237e-01 7.676185e-02
[17,] 0.9020859 1.958282e-01 9.791408e-02
[18,] 0.8779082 2.441836e-01 1.220918e-01
[19,] 0.9402220 1.195560e-01 5.977801e-02
[20,] 0.9509448 9.811044e-02 4.905522e-02
[21,] 0.9355491 1.289018e-01 6.445091e-02
[22,] 0.9268510 1.462980e-01 7.314900e-02
[23,] 0.9990142 1.971688e-03 9.858439e-04
[24,] 0.9986270 2.746061e-03 1.373031e-03
[25,] 0.9978751 4.249713e-03 2.124857e-03
[26,] 0.9969640 6.071997e-03 3.035998e-03
[27,] 0.9956106 8.778781e-03 4.389391e-03
[28,] 0.9993885 1.223031e-03 6.115156e-04
[29,] 0.9994909 1.018285e-03 5.091423e-04
[30,] 0.9992411 1.517798e-03 7.588990e-04
[31,] 0.9996412 7.176171e-04 3.588086e-04
[32,] 0.9995830 8.340177e-04 4.170088e-04
[33,] 0.9998345 3.309158e-04 1.654579e-04
[34,] 0.9998824 2.351533e-04 1.175766e-04
[35,] 0.9999778 4.445262e-05 2.222631e-05
[36,] 0.9999651 6.984218e-05 3.492109e-05
[37,] 0.9999673 6.541479e-05 3.270740e-05
[38,] 0.9999895 2.108648e-05 1.054324e-05
[39,] 0.9999879 2.420364e-05 1.210182e-05
[40,] 0.9999818 3.633054e-05 1.816527e-05
[41,] 0.9999700 5.994141e-05 2.997070e-05
[42,] 0.9999506 9.886092e-05 4.943046e-05
[43,] 0.9999511 9.780002e-05 4.890001e-05
[44,] 0.9999212 1.575910e-04 7.879551e-05
[45,] 0.9998788 2.424339e-04 1.212169e-04
[46,] 0.9998385 3.230407e-04 1.615203e-04
[47,] 0.9997538 4.924133e-04 2.462067e-04
[48,] 0.9996282 7.435021e-04 3.717510e-04
[49,] 0.9994985 1.003025e-03 5.015127e-04
[50,] 0.9994348 1.130498e-03 5.652489e-04
[51,] 0.9991456 1.708858e-03 8.544288e-04
[52,] 0.9987120 2.576085e-03 1.288043e-03
[53,] 0.9981921 3.615807e-03 1.807903e-03
[54,] 0.9996482 7.036038e-04 3.518019e-04
[55,] 0.9995355 9.289304e-04 4.644652e-04
[56,] 0.9993585 1.283082e-03 6.415408e-04
[57,] 0.9996916 6.167751e-04 3.083876e-04
[58,] 0.9996803 6.393476e-04 3.196738e-04
[59,] 0.9995701 8.597934e-04 4.298967e-04
[60,] 0.9993595 1.281040e-03 6.405200e-04
[61,] 0.9997505 4.990992e-04 2.495496e-04
[62,] 0.9998063 3.874226e-04 1.937113e-04
[63,] 0.9996945 6.109468e-04 3.054734e-04
[64,] 0.9995541 8.918512e-04 4.459256e-04
[65,] 0.9996832 6.335049e-04 3.167525e-04
[66,] 0.9998526 2.948532e-04 1.474266e-04
[67,] 0.9997905 4.190623e-04 2.095311e-04
[68,] 0.9998130 3.739671e-04 1.869836e-04
[69,] 0.9997020 5.960252e-04 2.980126e-04
[70,] 0.9995642 8.715661e-04 4.357830e-04
[71,] 0.9993512 1.297591e-03 6.487953e-04
[72,] 0.9997895 4.209805e-04 2.104902e-04
[73,] 0.9996868 6.264975e-04 3.132488e-04
[74,] 0.9996661 6.678488e-04 3.339244e-04
[75,] 0.9994814 1.037123e-03 5.185613e-04
[76,] 0.9993841 1.231867e-03 6.159333e-04
[77,] 0.9991950 1.609918e-03 8.049590e-04
[78,] 0.9990234 1.953274e-03 9.766372e-04
[79,] 0.9985333 2.933475e-03 1.466737e-03
[80,] 0.9995312 9.376901e-04 4.688451e-04
[81,] 0.9992867 1.426550e-03 7.132752e-04
[82,] 0.9988937 2.212599e-03 1.106300e-03
[83,] 0.9983031 3.393795e-03 1.696897e-03
[84,] 0.9981906 3.618831e-03 1.809416e-03
[85,] 0.9972794 5.441218e-03 2.720609e-03
[86,] 0.9971543 5.691482e-03 2.845741e-03
[87,] 0.9979075 4.184909e-03 2.092455e-03
[88,] 0.9968290 6.342021e-03 3.171010e-03
[89,] 0.9960080 7.983915e-03 3.991958e-03
[90,] 0.9963748 7.250401e-03 3.625200e-03
[91,] 0.9974445 5.111051e-03 2.555525e-03
[92,] 0.9967165 6.567075e-03 3.283537e-03
[93,] 0.9953169 9.366157e-03 4.683078e-03
[94,] 0.9930432 1.391359e-02 6.956793e-03
[95,] 0.9910514 1.789716e-02 8.948582e-03
[96,] 0.9896996 2.060077e-02 1.030038e-02
[97,] 0.9930361 1.392783e-02 6.963917e-03
[98,] 0.9897217 2.055652e-02 1.027826e-02
[99,] 0.9858469 2.830626e-02 1.415313e-02
[100,] 0.9796011 4.079788e-02 2.039894e-02
[101,] 0.9739569 5.208615e-02 2.604308e-02
[102,] 0.9648344 7.033111e-02 3.516555e-02
[103,] 0.9550491 8.990190e-02 4.495095e-02
[104,] 0.9601182 7.976368e-02 3.988184e-02
[105,] 0.9675490 6.490201e-02 3.245100e-02
[106,] 0.9578925 8.421498e-02 4.210749e-02
[107,] 0.9476207 1.047585e-01 5.237927e-02
[108,] 0.9286017 1.427966e-01 7.139830e-02
[109,] 0.9091878 1.816243e-01 9.081217e-02
[110,] 0.8865887 2.268226e-01 1.134113e-01
[111,] 0.8949203 2.101594e-01 1.050797e-01
[112,] 0.9935234 1.295327e-02 6.476634e-03
[113,] 0.9899212 2.015770e-02 1.007885e-02
[114,] 0.9898150 2.037010e-02 1.018505e-02
[115,] 0.9833566 3.328685e-02 1.664343e-02
[116,] 0.9772775 4.544505e-02 2.272252e-02
[117,] 0.9660349 6.793022e-02 3.396511e-02
[118,] 0.9479272 1.041457e-01 5.207285e-02
[119,] 0.9671976 6.560474e-02 3.280237e-02
[120,] 0.9516572 9.668566e-02 4.834283e-02
[121,] 0.9377350 1.245300e-01 6.226502e-02
[122,] 0.9182368 1.635265e-01 8.176323e-02
[123,] 0.8746852 2.506296e-01 1.253148e-01
[124,] 0.8264251 3.471497e-01 1.735749e-01
[125,] 0.7677853 4.644293e-01 2.322147e-01
[126,] 0.9434102 1.131796e-01 5.658980e-02
[127,] 0.9071116 1.857769e-01 9.288843e-02
[128,] 0.9517341 9.653183e-02 4.826591e-02
[129,] 0.9047828 1.904343e-01 9.521716e-02
[130,] 0.8151856 3.696288e-01 1.848144e-01
[131,] 0.6866495 6.267011e-01 3.133505e-01
> postscript(file="/var/www/rcomp/tmp/1eyt81322152731.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$resid)
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/rcomp/tmp/2mfqb1322152731.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> plot(mysum$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/rcomp/tmp/3m6pw1322152731.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> hist(mysum$resid, main='Residual Histogram', xlab='values of Residuals')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/rcomp/tmp/4orjh1322152731.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> densityplot(~mysum$resid,col='black',main='Residual Density Plot', xlab='values of Residuals')
> dev.off()
null device
1
> postscript(file="/var/www/rcomp/tmp/5af691322152731.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 = 144
Frequency = 1
1 2 3 4 5 6
-2113.1886 -4562.8138 -2931.9389 -6068.9326 -8641.7186 34659.3185
7 8 9 10 11 12
-1191.9658 -3757.7531 -6614.4987 -7057.5776 -810.4207 -9129.4364
13 14 15 16 17 18
-6291.4202 -5749.9930 1074.1190 11271.8765 264.2970 2849.9685
19 20 21 22 23 24
-4795.4024 23511.3225 -2266.1149 8945.9651 2989.9750 7606.1857
25 26 27 28 29 30
-8392.1668 -4715.4792 1328.1102 -7009.6328 31359.9969 -7273.1356
31 32 33 34 35 36
709.2101 -5272.6335 3531.2418 19438.3618 -5702.8979 -3171.0682
37 38 39 40 41 42
-9323.5931 -6316.9863 12125.7458 -7912.8151 -10653.6622 -4192.2480
43 44 45 46 47 48
8181.4855 14952.0653 3537.2000 -4430.5382 -1908.2250 -438.9080
49 50 51 52 53 54
7342.1178 -1961.6747 -2732.9290 -5192.1252 675.2850 -2427.0686
55 56 57 58 59 60
-4050.1565 -6805.6361 938.7992 -322.6220 -2800.7008 17502.9485
61 62 63 64 65 66
-4024.6064 -2565.0640 12840.9187 -8948.3817 4605.9290 -2524.5595
67 68 69 70 71 72
13365.4328 -10166.8605 -989.2907 -2648.1317 -10824.3201 12415.4438
73 74 75 76 77 78
-4886.2340 -8482.3556 -324.2099 -2989.5172 -3162.4939 13238.1361
79 80 81 82 83 84
2702.0980 3973.2210 -2045.9150 -5893.1822 -4537.5609 -5956.2900
85 86 87 88 89 90
-1201.6775 13730.6985 -3470.3460 -976.2718 -955.3919 -6677.8225
91 92 93 94 95 96
1066.0297 6407.4321 9443.3999 863.2636 4147.9996 -10539.8165
97 98 99 100 101 102
8765.7797 -4456.6202 -4087.0087 -2002.9928 -4088.8186 5295.0803
103 104 105 106 107 108
7004.4677 -2465.1416 -3413.6288 -1506.7289 -7343.5582 -2693.4767
109 110 111 112 113 114
-3171.0682 -10065.0548 10066.1800 -3986.8998 -4731.7564 2924.4340
115 116 117 118 119 120
-3171.0682 -3171.0682 -8757.2639 19841.4958 -2251.3151 5084.2571
121 122 123 124 125 126
-657.7354 1564.0881 -3588.1412 -689.7353 9534.6780 -4811.0866
127 128 129 130 131 132
-5084.1625 -2792.7268 718.4720 -3171.0682 -3171.0682 13868.6357
133 134 135 136 137 138
-3171.0682 3468.7526 -3171.0682 -1157.5082 -3171.0682 1152.1086
139 140 141 142 143 144
10203.2500 -3171.0682 -3171.0682 -5266.2186 -4820.7714 -877.8683
> postscript(file="/var/www/rcomp/tmp/6iayh1322152731.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 = 144
Frequency = 1
lag(myerror, k = 1) myerror
0 -2113.1886 NA
1 -4562.8138 -2113.1886
2 -2931.9389 -4562.8138
3 -6068.9326 -2931.9389
4 -8641.7186 -6068.9326
5 34659.3185 -8641.7186
6 -1191.9658 34659.3185
7 -3757.7531 -1191.9658
8 -6614.4987 -3757.7531
9 -7057.5776 -6614.4987
10 -810.4207 -7057.5776
11 -9129.4364 -810.4207
12 -6291.4202 -9129.4364
13 -5749.9930 -6291.4202
14 1074.1190 -5749.9930
15 11271.8765 1074.1190
16 264.2970 11271.8765
17 2849.9685 264.2970
18 -4795.4024 2849.9685
19 23511.3225 -4795.4024
20 -2266.1149 23511.3225
21 8945.9651 -2266.1149
22 2989.9750 8945.9651
23 7606.1857 2989.9750
24 -8392.1668 7606.1857
25 -4715.4792 -8392.1668
26 1328.1102 -4715.4792
27 -7009.6328 1328.1102
28 31359.9969 -7009.6328
29 -7273.1356 31359.9969
30 709.2101 -7273.1356
31 -5272.6335 709.2101
32 3531.2418 -5272.6335
33 19438.3618 3531.2418
34 -5702.8979 19438.3618
35 -3171.0682 -5702.8979
36 -9323.5931 -3171.0682
37 -6316.9863 -9323.5931
38 12125.7458 -6316.9863
39 -7912.8151 12125.7458
40 -10653.6622 -7912.8151
41 -4192.2480 -10653.6622
42 8181.4855 -4192.2480
43 14952.0653 8181.4855
44 3537.2000 14952.0653
45 -4430.5382 3537.2000
46 -1908.2250 -4430.5382
47 -438.9080 -1908.2250
48 7342.1178 -438.9080
49 -1961.6747 7342.1178
50 -2732.9290 -1961.6747
51 -5192.1252 -2732.9290
52 675.2850 -5192.1252
53 -2427.0686 675.2850
54 -4050.1565 -2427.0686
55 -6805.6361 -4050.1565
56 938.7992 -6805.6361
57 -322.6220 938.7992
58 -2800.7008 -322.6220
59 17502.9485 -2800.7008
60 -4024.6064 17502.9485
61 -2565.0640 -4024.6064
62 12840.9187 -2565.0640
63 -8948.3817 12840.9187
64 4605.9290 -8948.3817
65 -2524.5595 4605.9290
66 13365.4328 -2524.5595
67 -10166.8605 13365.4328
68 -989.2907 -10166.8605
69 -2648.1317 -989.2907
70 -10824.3201 -2648.1317
71 12415.4438 -10824.3201
72 -4886.2340 12415.4438
73 -8482.3556 -4886.2340
74 -324.2099 -8482.3556
75 -2989.5172 -324.2099
76 -3162.4939 -2989.5172
77 13238.1361 -3162.4939
78 2702.0980 13238.1361
79 3973.2210 2702.0980
80 -2045.9150 3973.2210
81 -5893.1822 -2045.9150
82 -4537.5609 -5893.1822
83 -5956.2900 -4537.5609
84 -1201.6775 -5956.2900
85 13730.6985 -1201.6775
86 -3470.3460 13730.6985
87 -976.2718 -3470.3460
88 -955.3919 -976.2718
89 -6677.8225 -955.3919
90 1066.0297 -6677.8225
91 6407.4321 1066.0297
92 9443.3999 6407.4321
93 863.2636 9443.3999
94 4147.9996 863.2636
95 -10539.8165 4147.9996
96 8765.7797 -10539.8165
97 -4456.6202 8765.7797
98 -4087.0087 -4456.6202
99 -2002.9928 -4087.0087
100 -4088.8186 -2002.9928
101 5295.0803 -4088.8186
102 7004.4677 5295.0803
103 -2465.1416 7004.4677
104 -3413.6288 -2465.1416
105 -1506.7289 -3413.6288
106 -7343.5582 -1506.7289
107 -2693.4767 -7343.5582
108 -3171.0682 -2693.4767
109 -10065.0548 -3171.0682
110 10066.1800 -10065.0548
111 -3986.8998 10066.1800
112 -4731.7564 -3986.8998
113 2924.4340 -4731.7564
114 -3171.0682 2924.4340
115 -3171.0682 -3171.0682
116 -8757.2639 -3171.0682
117 19841.4958 -8757.2639
118 -2251.3151 19841.4958
119 5084.2571 -2251.3151
120 -657.7354 5084.2571
121 1564.0881 -657.7354
122 -3588.1412 1564.0881
123 -689.7353 -3588.1412
124 9534.6780 -689.7353
125 -4811.0866 9534.6780
126 -5084.1625 -4811.0866
127 -2792.7268 -5084.1625
128 718.4720 -2792.7268
129 -3171.0682 718.4720
130 -3171.0682 -3171.0682
131 13868.6357 -3171.0682
132 -3171.0682 13868.6357
133 3468.7526 -3171.0682
134 -3171.0682 3468.7526
135 -1157.5082 -3171.0682
136 -3171.0682 -1157.5082
137 1152.1086 -3171.0682
138 10203.2500 1152.1086
139 -3171.0682 10203.2500
140 -3171.0682 -3171.0682
141 -5266.2186 -3171.0682
142 -4820.7714 -5266.2186
143 -877.8683 -4820.7714
144 NA -877.8683
> dum1 <- dum[2:length(myerror),]
> dum1
lag(myerror, k = 1) myerror
[1,] -4562.8138 -2113.1886
[2,] -2931.9389 -4562.8138
[3,] -6068.9326 -2931.9389
[4,] -8641.7186 -6068.9326
[5,] 34659.3185 -8641.7186
[6,] -1191.9658 34659.3185
[7,] -3757.7531 -1191.9658
[8,] -6614.4987 -3757.7531
[9,] -7057.5776 -6614.4987
[10,] -810.4207 -7057.5776
[11,] -9129.4364 -810.4207
[12,] -6291.4202 -9129.4364
[13,] -5749.9930 -6291.4202
[14,] 1074.1190 -5749.9930
[15,] 11271.8765 1074.1190
[16,] 264.2970 11271.8765
[17,] 2849.9685 264.2970
[18,] -4795.4024 2849.9685
[19,] 23511.3225 -4795.4024
[20,] -2266.1149 23511.3225
[21,] 8945.9651 -2266.1149
[22,] 2989.9750 8945.9651
[23,] 7606.1857 2989.9750
[24,] -8392.1668 7606.1857
[25,] -4715.4792 -8392.1668
[26,] 1328.1102 -4715.4792
[27,] -7009.6328 1328.1102
[28,] 31359.9969 -7009.6328
[29,] -7273.1356 31359.9969
[30,] 709.2101 -7273.1356
[31,] -5272.6335 709.2101
[32,] 3531.2418 -5272.6335
[33,] 19438.3618 3531.2418
[34,] -5702.8979 19438.3618
[35,] -3171.0682 -5702.8979
[36,] -9323.5931 -3171.0682
[37,] -6316.9863 -9323.5931
[38,] 12125.7458 -6316.9863
[39,] -7912.8151 12125.7458
[40,] -10653.6622 -7912.8151
[41,] -4192.2480 -10653.6622
[42,] 8181.4855 -4192.2480
[43,] 14952.0653 8181.4855
[44,] 3537.2000 14952.0653
[45,] -4430.5382 3537.2000
[46,] -1908.2250 -4430.5382
[47,] -438.9080 -1908.2250
[48,] 7342.1178 -438.9080
[49,] -1961.6747 7342.1178
[50,] -2732.9290 -1961.6747
[51,] -5192.1252 -2732.9290
[52,] 675.2850 -5192.1252
[53,] -2427.0686 675.2850
[54,] -4050.1565 -2427.0686
[55,] -6805.6361 -4050.1565
[56,] 938.7992 -6805.6361
[57,] -322.6220 938.7992
[58,] -2800.7008 -322.6220
[59,] 17502.9485 -2800.7008
[60,] -4024.6064 17502.9485
[61,] -2565.0640 -4024.6064
[62,] 12840.9187 -2565.0640
[63,] -8948.3817 12840.9187
[64,] 4605.9290 -8948.3817
[65,] -2524.5595 4605.9290
[66,] 13365.4328 -2524.5595
[67,] -10166.8605 13365.4328
[68,] -989.2907 -10166.8605
[69,] -2648.1317 -989.2907
[70,] -10824.3201 -2648.1317
[71,] 12415.4438 -10824.3201
[72,] -4886.2340 12415.4438
[73,] -8482.3556 -4886.2340
[74,] -324.2099 -8482.3556
[75,] -2989.5172 -324.2099
[76,] -3162.4939 -2989.5172
[77,] 13238.1361 -3162.4939
[78,] 2702.0980 13238.1361
[79,] 3973.2210 2702.0980
[80,] -2045.9150 3973.2210
[81,] -5893.1822 -2045.9150
[82,] -4537.5609 -5893.1822
[83,] -5956.2900 -4537.5609
[84,] -1201.6775 -5956.2900
[85,] 13730.6985 -1201.6775
[86,] -3470.3460 13730.6985
[87,] -976.2718 -3470.3460
[88,] -955.3919 -976.2718
[89,] -6677.8225 -955.3919
[90,] 1066.0297 -6677.8225
[91,] 6407.4321 1066.0297
[92,] 9443.3999 6407.4321
[93,] 863.2636 9443.3999
[94,] 4147.9996 863.2636
[95,] -10539.8165 4147.9996
[96,] 8765.7797 -10539.8165
[97,] -4456.6202 8765.7797
[98,] -4087.0087 -4456.6202
[99,] -2002.9928 -4087.0087
[100,] -4088.8186 -2002.9928
[101,] 5295.0803 -4088.8186
[102,] 7004.4677 5295.0803
[103,] -2465.1416 7004.4677
[104,] -3413.6288 -2465.1416
[105,] -1506.7289 -3413.6288
[106,] -7343.5582 -1506.7289
[107,] -2693.4767 -7343.5582
[108,] -3171.0682 -2693.4767
[109,] -10065.0548 -3171.0682
[110,] 10066.1800 -10065.0548
[111,] -3986.8998 10066.1800
[112,] -4731.7564 -3986.8998
[113,] 2924.4340 -4731.7564
[114,] -3171.0682 2924.4340
[115,] -3171.0682 -3171.0682
[116,] -8757.2639 -3171.0682
[117,] 19841.4958 -8757.2639
[118,] -2251.3151 19841.4958
[119,] 5084.2571 -2251.3151
[120,] -657.7354 5084.2571
[121,] 1564.0881 -657.7354
[122,] -3588.1412 1564.0881
[123,] -689.7353 -3588.1412
[124,] 9534.6780 -689.7353
[125,] -4811.0866 9534.6780
[126,] -5084.1625 -4811.0866
[127,] -2792.7268 -5084.1625
[128,] 718.4720 -2792.7268
[129,] -3171.0682 718.4720
[130,] -3171.0682 -3171.0682
[131,] 13868.6357 -3171.0682
[132,] -3171.0682 13868.6357
[133,] 3468.7526 -3171.0682
[134,] -3171.0682 3468.7526
[135,] -1157.5082 -3171.0682
[136,] -3171.0682 -1157.5082
[137,] 1152.1086 -3171.0682
[138,] 10203.2500 1152.1086
[139,] -3171.0682 10203.2500
[140,] -3171.0682 -3171.0682
[141,] -5266.2186 -3171.0682
[142,] -4820.7714 -5266.2186
[143,] -877.8683 -4820.7714
> z <- as.data.frame(dum1)
> z
lag(myerror, k = 1) myerror
1 -4562.8138 -2113.1886
2 -2931.9389 -4562.8138
3 -6068.9326 -2931.9389
4 -8641.7186 -6068.9326
5 34659.3185 -8641.7186
6 -1191.9658 34659.3185
7 -3757.7531 -1191.9658
8 -6614.4987 -3757.7531
9 -7057.5776 -6614.4987
10 -810.4207 -7057.5776
11 -9129.4364 -810.4207
12 -6291.4202 -9129.4364
13 -5749.9930 -6291.4202
14 1074.1190 -5749.9930
15 11271.8765 1074.1190
16 264.2970 11271.8765
17 2849.9685 264.2970
18 -4795.4024 2849.9685
19 23511.3225 -4795.4024
20 -2266.1149 23511.3225
21 8945.9651 -2266.1149
22 2989.9750 8945.9651
23 7606.1857 2989.9750
24 -8392.1668 7606.1857
25 -4715.4792 -8392.1668
26 1328.1102 -4715.4792
27 -7009.6328 1328.1102
28 31359.9969 -7009.6328
29 -7273.1356 31359.9969
30 709.2101 -7273.1356
31 -5272.6335 709.2101
32 3531.2418 -5272.6335
33 19438.3618 3531.2418
34 -5702.8979 19438.3618
35 -3171.0682 -5702.8979
36 -9323.5931 -3171.0682
37 -6316.9863 -9323.5931
38 12125.7458 -6316.9863
39 -7912.8151 12125.7458
40 -10653.6622 -7912.8151
41 -4192.2480 -10653.6622
42 8181.4855 -4192.2480
43 14952.0653 8181.4855
44 3537.2000 14952.0653
45 -4430.5382 3537.2000
46 -1908.2250 -4430.5382
47 -438.9080 -1908.2250
48 7342.1178 -438.9080
49 -1961.6747 7342.1178
50 -2732.9290 -1961.6747
51 -5192.1252 -2732.9290
52 675.2850 -5192.1252
53 -2427.0686 675.2850
54 -4050.1565 -2427.0686
55 -6805.6361 -4050.1565
56 938.7992 -6805.6361
57 -322.6220 938.7992
58 -2800.7008 -322.6220
59 17502.9485 -2800.7008
60 -4024.6064 17502.9485
61 -2565.0640 -4024.6064
62 12840.9187 -2565.0640
63 -8948.3817 12840.9187
64 4605.9290 -8948.3817
65 -2524.5595 4605.9290
66 13365.4328 -2524.5595
67 -10166.8605 13365.4328
68 -989.2907 -10166.8605
69 -2648.1317 -989.2907
70 -10824.3201 -2648.1317
71 12415.4438 -10824.3201
72 -4886.2340 12415.4438
73 -8482.3556 -4886.2340
74 -324.2099 -8482.3556
75 -2989.5172 -324.2099
76 -3162.4939 -2989.5172
77 13238.1361 -3162.4939
78 2702.0980 13238.1361
79 3973.2210 2702.0980
80 -2045.9150 3973.2210
81 -5893.1822 -2045.9150
82 -4537.5609 -5893.1822
83 -5956.2900 -4537.5609
84 -1201.6775 -5956.2900
85 13730.6985 -1201.6775
86 -3470.3460 13730.6985
87 -976.2718 -3470.3460
88 -955.3919 -976.2718
89 -6677.8225 -955.3919
90 1066.0297 -6677.8225
91 6407.4321 1066.0297
92 9443.3999 6407.4321
93 863.2636 9443.3999
94 4147.9996 863.2636
95 -10539.8165 4147.9996
96 8765.7797 -10539.8165
97 -4456.6202 8765.7797
98 -4087.0087 -4456.6202
99 -2002.9928 -4087.0087
100 -4088.8186 -2002.9928
101 5295.0803 -4088.8186
102 7004.4677 5295.0803
103 -2465.1416 7004.4677
104 -3413.6288 -2465.1416
105 -1506.7289 -3413.6288
106 -7343.5582 -1506.7289
107 -2693.4767 -7343.5582
108 -3171.0682 -2693.4767
109 -10065.0548 -3171.0682
110 10066.1800 -10065.0548
111 -3986.8998 10066.1800
112 -4731.7564 -3986.8998
113 2924.4340 -4731.7564
114 -3171.0682 2924.4340
115 -3171.0682 -3171.0682
116 -8757.2639 -3171.0682
117 19841.4958 -8757.2639
118 -2251.3151 19841.4958
119 5084.2571 -2251.3151
120 -657.7354 5084.2571
121 1564.0881 -657.7354
122 -3588.1412 1564.0881
123 -689.7353 -3588.1412
124 9534.6780 -689.7353
125 -4811.0866 9534.6780
126 -5084.1625 -4811.0866
127 -2792.7268 -5084.1625
128 718.4720 -2792.7268
129 -3171.0682 718.4720
130 -3171.0682 -3171.0682
131 13868.6357 -3171.0682
132 -3171.0682 13868.6357
133 3468.7526 -3171.0682
134 -3171.0682 3468.7526
135 -1157.5082 -3171.0682
136 -3171.0682 -1157.5082
137 1152.1086 -3171.0682
138 10203.2500 1152.1086
139 -3171.0682 10203.2500
140 -3171.0682 -3171.0682
141 -5266.2186 -3171.0682
142 -4820.7714 -5266.2186
143 -877.8683 -4820.7714
> 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/rcomp/tmp/71i5a1322152731.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> acf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/rcomp/tmp/8cjsq1322152731.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> pacf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Partial Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/rcomp/tmp/9hmz41322152731.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> opar <- par(mfrow = c(2,2), oma = c(0, 0, 1.1, 0))
> plot(mylm, las = 1, sub='Residual Diagnostics')
> par(opar)
> dev.off()
null device
1
> if (n > n25) {
+ postscript(file="/var/www/rcomp/tmp/101qfo1322152731.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
+ plot(kp3:nmkm3,gqarr[,2], main='Goldfeld-Quandt test',ylab='2-sided p-value',xlab='breakpoint')
+ grid()
+ dev.off()
+ }
null device
1
>
> #Note: the /var/www/rcomp/createtable file can be downloaded at http://www.wessa.net/cretab
> load(file="/var/www/rcomp/createtable")
>
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a, 'Multiple Linear Regression - Estimated Regression Equation', 1, TRUE)
> a<-table.row.end(a)
> myeq <- colnames(x)[1]
> myeq <- paste(myeq, '[t] = ', sep='')
> for (i in 1:k){
+ if (mysum$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/rcomp/tmp/11x5ll1322152731.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/rcomp/tmp/12w4271322152731.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/rcomp/tmp/13j9g21322152731.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/rcomp/tmp/14jfkk1322152731.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/rcomp/tmp/15xpv91322152731.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/rcomp/tmp/169n0r1322152731.tab")
+ }
>
> try(system("convert tmp/1eyt81322152731.ps tmp/1eyt81322152731.png",intern=TRUE))
character(0)
> try(system("convert tmp/2mfqb1322152731.ps tmp/2mfqb1322152731.png",intern=TRUE))
character(0)
> try(system("convert tmp/3m6pw1322152731.ps tmp/3m6pw1322152731.png",intern=TRUE))
character(0)
> try(system("convert tmp/4orjh1322152731.ps tmp/4orjh1322152731.png",intern=TRUE))
character(0)
> try(system("convert tmp/5af691322152731.ps tmp/5af691322152731.png",intern=TRUE))
character(0)
> try(system("convert tmp/6iayh1322152731.ps tmp/6iayh1322152731.png",intern=TRUE))
character(0)
> try(system("convert tmp/71i5a1322152731.ps tmp/71i5a1322152731.png",intern=TRUE))
character(0)
> try(system("convert tmp/8cjsq1322152731.ps tmp/8cjsq1322152731.png",intern=TRUE))
character(0)
> try(system("convert tmp/9hmz41322152731.ps tmp/9hmz41322152731.png",intern=TRUE))
character(0)
> try(system("convert tmp/101qfo1322152731.ps tmp/101qfo1322152731.png",intern=TRUE))
character(0)
>
>
> proc.time()
user system elapsed
5.876 0.608 13.076