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(41
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+ ,2)
+ ,dim=c(5
+ ,146)
+ ,dimnames=list(c('StudyForCareer'
+ ,'PersonalStandards'
+ ,'ParentalExpectations'
+ ,'Doubts'
+ ,'LeaderPreference')
+ ,1:146))
> y <- array(NA,dim=c(5,146),dimnames=list(c('StudyForCareer','PersonalStandards','ParentalExpectations','Doubts','LeaderPreference'),1:146))
> 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
StudyForCareer PersonalStandards ParentalExpectations Doubts
1 41 25 15 9
2 38 25 15 9
3 37 19 14 9
4 36 18 10 14
5 42 18 10 8
6 44 23 9 14
7 40 23 18 15
8 43 25 14 9
9 40 23 11 11
10 45 24 11 14
11 47 32 9 14
12 45 30 17 6
13 45 32 21 10
14 40 24 16 9
15 49 17 14 14
16 48 30 24 8
17 44 25 7 11
18 29 25 9 10
19 42 26 18 16
20 45 23 11 11
21 32 25 13 11
22 32 25 13 11
23 41 35 18 7
24 29 19 14 13
25 38 20 12 10
26 41 21 12 9
27 38 21 9 9
28 24 23 11 15
29 34 24 8 13
30 38 23 5 16
31 37 19 10 12
32 46 17 11 6
33 48 27 15 4
34 42 27 16 12
35 46 25 12 10
36 43 18 14 14
37 38 22 13 9
38 39 26 10 10
39 34 26 18 14
40 39 23 17 14
41 35 16 12 10
42 41 27 13 9
43 40 25 13 14
44 43 14 11 8
45 37 19 13 9
46 41 20 12 8
47 46 26 12 10
48 26 16 12 9
49 41 18 12 9
50 37 22 9 9
51 39 25 17 9
52 44 29 18 11
53 39 21 7 15
54 36 22 17 8
55 38 22 12 10
56 38 32 12 8
57 38 23 9 14
58 32 31 9 11
59 33 18 13 10
60 46 23 10 12
61 42 24 12 9
62 42 19 10 13
63 43 26 11 14
64 41 14 13 15
65 49 20 6 8
66 45 22 7 7
67 39 24 13 10
68 45 25 11 10
69 31 21 18 13
70 30 21 18 13
71 45 28 9 11
72 48 24 9 8
73 28 15 12 14
74 35 21 11 9
75 38 23 15 10
76 39 24 11 11
77 40 21 14 10
78 38 21 14 16
79 42 13 8 11
80 36 17 12 16
81 49 29 8 6
82 41 25 11 11
83 18 16 10 12
84 36 20 11 12
85 42 25 17 14
86 41 25 16 9
87 43 21 13 11
88 46 23 15 8
89 37 22 11 8
90 38 19 12 7
91 43 26 20 13
92 41 25 16 8
93 35 19 8 20
94 39 25 7 11
95 42 24 16 16
96 36 20 11 11
97 35 21 13 12
98 33 14 15 10
99 36 22 15 14
100 48 14 12 8
101 41 20 12 10
102 47 21 24 14
103 41 22 15 10
104 31 19 8 5
105 36 28 18 12
106 46 25 17 9
107 39 17 12 16
108 44 21 15 8
109 43 27 11 16
110 32 29 12 12
111 40 19 12 13
112 40 20 14 8
113 46 17 11 14
114 45 21 12 8
115 39 22 10 8
116 44 26 11 7
117 35 19 11 10
118 38 17 9 11
119 38 17 12 11
120 36 19 8 14
121 42 17 12 10
122 39 15 6 6
123 41 27 15 9
124 41 19 13 12
125 47 21 17 11
126 39 25 14 14
127 40 19 16 12
128 44 18 16 8
129 42 15 11 8
130 35 20 16 11
131 46 29 15 12
132 43 20 11 14
133 40 29 9 16
134 44 24 12 13
135 37 24 13 11
136 46 23 11 9
137 44 23 11 11
138 35 19 13 9
139 39 22 14 12
140 40 22 12 13
141 42 25 17 14
142 37 21 11 9
143 29 22 15 14
144 33 21 13 8
145 35 18 9 8
146 42 10 12 9
LeaderPreference
1 3
2 4
3 4
4 2
5 4
6 4
7 3
8 4
9 4
10 4
11 4
12 5
13 4
14 4
15 4
16 5
17 4
18 4
19 4
20 5
21 5
22 5
23 4
24 2
25 4
26 4
27 4
28 3
29 2
30 2
31 3
32 5
33 5
34 4
35 4
36 5
37 4
38 4
39 4
40 4
41 2
42 3
43 3
44 4
45 2
46 4
47 4
48 3
49 3
50 3
51 4
52 5
53 2
54 4
55 2
56 0
57 4
58 4
59 3
60 4
61 4
62 2
63 4
64 2
65 4
66 3
67 4
68 5
69 3
70 3
71 4
72 5
73 4
74 2
75 4
76 4
77 4
78 4
79 4
80 2
81 5
82 4
83 2
84 3
85 3
86 5
87 4
88 3
89 4
90 3
91 4
92 5
93 2
94 4
95 4
96 4
97 5
98 2
99 3
100 4
101 4
102 3
103 3
104 5
105 4
106 4
107 4
108 4
109 2
110 4
111 5
112 3
113 3
114 3
115 4
116 4
117 4
118 3
119 2
120 3
121 3
122 4
123 5
124 4
125 3
126 3
127 4
128 4
129 4
130 3
131 5
132 3
133 4
134 4
135 4
136 4
137 5
138 3
139 2
140 3
141 3
142 3
143 4
144 2
145 4
146 2
> k <- length(x[1,])
> df <- as.data.frame(x)
> (mylm <- lm(df))
Call:
lm(formula = df)
Coefficients:
(Intercept) PersonalStandards ParentalExpectations
32.52021 0.17419 0.04668
Doubts LeaderPreference
-0.21737 1.39807
> (mysum <- summary(mylm))
Call:
lm(formula = df)
Residuals:
Min 1Q Median 3Q Max
-17.962 -2.227 0.633 3.246 10.316
Coefficients:
Estimate Std. Error t value Pr(>|t|)
(Intercept) 32.52021 3.25036 10.005 < 2e-16 ***
PersonalStandards 0.17419 0.10383 1.678 0.09563 .
ParentalExpectations 0.04668 0.12794 0.365 0.71578
Doubts -0.21737 0.15497 -1.403 0.16291
LeaderPreference 1.39807 0.48222 2.899 0.00434 **
---
Signif. codes: 0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1
Residual standard error: 4.982 on 141 degrees of freedom
Multiple R-squared: 0.1354, Adjusted R-squared: 0.1108
F-statistic: 5.519 on 4 and 141 DF, p-value: 0.0003713
> 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,] 0.209623361 0.419246722 0.79037664
[2,] 0.124782191 0.249564382 0.87521781
[3,] 0.068952480 0.137904960 0.93104752
[4,] 0.032772374 0.065544749 0.96722763
[5,] 0.014661957 0.029323915 0.98533804
[6,] 0.007017306 0.014034611 0.99298269
[7,] 0.002909888 0.005819775 0.99709011
[8,] 0.029745696 0.059491392 0.97025430
[9,] 0.017475334 0.034950667 0.98252467
[10,] 0.009903935 0.019807871 0.99009606
[11,] 0.265533382 0.531066763 0.73446662
[12,] 0.290141280 0.580282560 0.70985872
[13,] 0.226571794 0.453143589 0.77342821
[14,] 0.608355423 0.783289153 0.39164458
[15,] 0.793292587 0.413414826 0.20670741
[16,] 0.744127293 0.511745414 0.25587271
[17,] 0.827311131 0.345377738 0.17268887
[18,] 0.782819324 0.434361352 0.21718068
[19,] 0.739165867 0.521668267 0.26083413
[20,] 0.685206172 0.629587657 0.31479383
[21,] 0.930632256 0.138735489 0.06936774
[22,] 0.910314125 0.179371749 0.08968587
[23,] 0.896012734 0.207974532 0.10398727
[24,] 0.866578077 0.266843846 0.13342192
[25,] 0.864089683 0.271820634 0.13591032
[26,] 0.855829405 0.288341191 0.14417060
[27,] 0.821104330 0.357791341 0.17889567
[28,] 0.823875889 0.352248222 0.17612411
[29,] 0.788738223 0.422523554 0.21126178
[30,] 0.754766385 0.490467230 0.24523362
[31,] 0.712594382 0.574811236 0.28740562
[32,] 0.746914557 0.506170886 0.25308544
[33,] 0.702428372 0.595143255 0.29757163
[34,] 0.655249412 0.689501176 0.34475059
[35,] 0.612742139 0.774515721 0.38725786
[36,] 0.568466839 0.863066323 0.43153316
[37,] 0.540820204 0.918359592 0.45917980
[38,] 0.489536548 0.979073096 0.51046345
[39,] 0.436928625 0.873857250 0.56307137
[40,] 0.438239343 0.876478687 0.56176066
[41,] 0.654575836 0.690848328 0.34542416
[42,] 0.627180923 0.745638154 0.37281908
[43,] 0.582237566 0.835524868 0.41776243
[44,] 0.540199889 0.919600222 0.45980011
[45,] 0.490375182 0.980750364 0.50962482
[46,] 0.468344553 0.936689106 0.53165545
[47,] 0.460298735 0.920597470 0.53970126
[48,] 0.417628921 0.835257841 0.58237108
[49,] 0.384016018 0.768032036 0.61598398
[50,] 0.341508960 0.683017919 0.65849104
[51,] 0.475289612 0.950579224 0.52471039
[52,] 0.474338070 0.948676141 0.52566193
[53,] 0.497242505 0.994485011 0.50275749
[54,] 0.450726223 0.901452446 0.54927378
[55,] 0.469942159 0.939884318 0.53005784
[56,] 0.435636608 0.871273216 0.56436339
[57,] 0.454480525 0.908961051 0.54551947
[58,] 0.556025091 0.887949819 0.44397491
[59,] 0.564193481 0.871613039 0.43580652
[60,] 0.521913418 0.956173165 0.47808658
[61,] 0.486624851 0.973249702 0.51337515
[62,] 0.539543277 0.920913445 0.46045672
[63,] 0.623402039 0.753195921 0.37659796
[64,] 0.605607530 0.788784940 0.39439247
[65,] 0.621395610 0.757208780 0.37860439
[66,] 0.753263919 0.493472162 0.24673608
[67,] 0.722685622 0.554628756 0.27731438
[68,] 0.693891059 0.612217882 0.30610894
[69,] 0.653228401 0.693543198 0.34677160
[70,] 0.607822720 0.784354561 0.39217728
[71,] 0.563198869 0.873602263 0.43680113
[72,] 0.547389939 0.905220122 0.45261006
[73,] 0.503236418 0.993527163 0.49676358
[74,] 0.542394004 0.915211992 0.45760600
[75,] 0.496818676 0.993637351 0.50318132
[76,] 0.950784554 0.098430892 0.04921545
[77,] 0.940759803 0.118480393 0.05924020
[78,] 0.931980571 0.136038857 0.06801943
[79,] 0.915098492 0.169803017 0.08490151
[80,] 0.903230800 0.193538401 0.09676920
[81,] 0.917280560 0.165438879 0.08271944
[82,] 0.905460612 0.189078775 0.09453939
[83,] 0.883843843 0.232312314 0.11615616
[84,] 0.862690339 0.274619322 0.13730966
[85,] 0.834981228 0.330037545 0.16501877
[86,] 0.806406863 0.387186274 0.19359314
[87,] 0.774657182 0.450685636 0.22534282
[88,] 0.740818701 0.518362597 0.25918130
[89,] 0.720286411 0.559427179 0.27971359
[90,] 0.743479781 0.513040437 0.25652022
[91,] 0.776518151 0.446963698 0.22348185
[92,] 0.766633316 0.466733368 0.23336668
[93,] 0.837483291 0.325033417 0.16251671
[94,] 0.804027809 0.391944381 0.19597219
[95,] 0.824688221 0.350623557 0.17531178
[96,] 0.789841055 0.420317889 0.21015894
[97,] 0.882707716 0.234584569 0.11729228
[98,] 0.891754429 0.216491142 0.10824557
[99,] 0.888060133 0.223879734 0.11193987
[100,] 0.859952712 0.280094576 0.14004729
[101,] 0.841739925 0.316520151 0.15826008
[102,] 0.846942831 0.306114338 0.15305717
[103,] 0.909156859 0.181686283 0.09084314
[104,] 0.883386254 0.233227492 0.11661375
[105,] 0.850965717 0.298068566 0.14903428
[106,] 0.903469650 0.193060701 0.09653035
[107,] 0.911531621 0.176936758 0.08846838
[108,] 0.885207340 0.229585321 0.11479266
[109,] 0.868673241 0.262653519 0.13132676
[110,] 0.874059968 0.251880064 0.12594003
[111,] 0.836059037 0.327881927 0.16394096
[112,] 0.791391895 0.417216209 0.20860810
[113,] 0.752662659 0.494674681 0.24733734
[114,] 0.716343908 0.567312183 0.28365609
[115,] 0.653245573 0.693508855 0.34675443
[116,] 0.589029283 0.821941434 0.41097072
[117,] 0.516756898 0.966486204 0.48324310
[118,] 0.628954284 0.742091433 0.37104572
[119,] 0.552534886 0.894930228 0.44746511
[120,] 0.472949295 0.945898590 0.52705071
[121,] 0.457608919 0.915217838 0.54239108
[122,] 0.394211867 0.788423734 0.60578813
[123,] 0.334792894 0.669585787 0.66520711
[124,] 0.364780826 0.729561651 0.63521917
[125,] 0.301368013 0.602736025 0.69863199
[126,] 0.259140196 0.518280392 0.74085980
[127,] 0.207367343 0.414734686 0.79263266
[128,] 0.141586940 0.283173880 0.85841306
[129,] 0.221599840 0.443199680 0.77840016
[130,] 0.468679991 0.937359981 0.53132001
[131,] 0.314416546 0.628833093 0.68558345
> postscript(file="/var/www/html/freestat/rcomp/tmp/1rkg11292682719.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$resid)
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/freestat/rcomp/tmp/2rkg11292682719.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> plot(mysum$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/3rkg11292682719.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> hist(mysum$resid, main='Residual Histogram', xlab='values of Residuals')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/freestat/rcomp/tmp/41bfl1292682719.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> densityplot(~mysum$resid,col='black',main='Residual Density Plot', xlab='values of Residuals')
> dev.off()
null device
1
> postscript(file="/var/www/html/freestat/rcomp/tmp/51bfl1292682719.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 = 146
Frequency = 1
1 2 3 4 5 6
1.1869570 -3.2111084 -3.1192741 0.1246308 2.0242613 4.5042164
7 8 9 10 11 12
1.6995439 1.8355706 -0.2412610 5.2366658 5.9364835 0.7743862
13 14 15 16 17 18
2.5068430 -1.0835948 10.3159767 3.8823795 3.5970699 -11.7136613
19 20 21 22 23 24
1.9962741 3.3606736 -10.0810694 -10.0810694 -2.5278170 -7.4536509
25 26 27 28 29 30
-1.9827355 0.6256988 -2.2342642 -13.9737031 -3.0445396 1.9218093
31 32 33 34 35 36
-0.8823734 4.3189632 3.9555755 1.0459470 5.1463018 2.7437188
37 38 39 40 41 42
-2.5951727 -1.9345328 -6.4384722 -0.8692156 -1.4898347 0.9319299
43 44 45 46 47 48
1.3671806 3.6743525 -0.2764644 0.5825182 4.9721092 -12.1052731
49 50 51 52 53 54
2.5463418 -2.0103914 -2.3044663 0.9887654 2.9594632 -4.9992618
55 56 57 58 59 60
0.4650101 1.0844690 -1.4957836 -9.5414434 -5.2829641 6.0227911
61 62 63 64 65 66
1.1031212 5.7330651 2.8882807 5.8987371 8.8625922 5.6482203
67 68 69 70 71 72
-1.7261847 2.7949154 -7.3868173 -8.3868173 3.9811342 5.6277197
73 74 75 76 77 78
-10.2422803 -2.5314915 -2.6453501 -1.4154536 -0.2502861 -0.9460472
79 80 81 82 83 84
3.6407014 0.6402116 5.3686897 0.4103539 -17.9617304 -2.1032449
85 86 87 88 89 90
3.1804647 -1.6558527 3.0137661 6.3179689 -3.7191879 -1.0625970
91 92 93 94 95 96
2.2507967 -1.8732258 0.3480350 -1.4029301 2.4380171 -3.7186834
97 98 99 100 101 102
-6.1669261 -3.2814866 -2.2035997 8.6276735 1.0172645 8.5504819
103 104 105 106 107 108
1.9269078 -11.1067580 -5.2216036 4.6955337 0.8440809 3.2682887
109 110 111 112 113 114
5.9449652 -9.1157221 -0.5544889 0.8872256 8.8540790 5.8063910
115 116 117 118 119 120
-1.6725089 2.3666688 -4.7618640 0.2953176 1.5533459 -1.3542691
121 122 123 124 125 126
3.9379074 -0.7011914 -1.9575588 1.5795243 8.2251154 0.3205017
127 128 129 130 131 132
0.4394873 3.7441873 2.5001599 -3.5540130 3.3461755 5.3315013
133 134 135 136 137 138
-0.1061926 3.9726137 -3.5088116 5.3239927 2.3606736 -3.6745298
139 140 141 142 143 144
1.8063984 1.7190641 3.1804647 -1.9295569 -10.6016650 -4.8422226
145 146
-4.9290597 6.3379475
> postscript(file="/var/www/html/freestat/rcomp/tmp/61bfl1292682719.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 = 146
Frequency = 1
lag(myerror, k = 1) myerror
0 1.1869570 NA
1 -3.2111084 1.1869570
2 -3.1192741 -3.2111084
3 0.1246308 -3.1192741
4 2.0242613 0.1246308
5 4.5042164 2.0242613
6 1.6995439 4.5042164
7 1.8355706 1.6995439
8 -0.2412610 1.8355706
9 5.2366658 -0.2412610
10 5.9364835 5.2366658
11 0.7743862 5.9364835
12 2.5068430 0.7743862
13 -1.0835948 2.5068430
14 10.3159767 -1.0835948
15 3.8823795 10.3159767
16 3.5970699 3.8823795
17 -11.7136613 3.5970699
18 1.9962741 -11.7136613
19 3.3606736 1.9962741
20 -10.0810694 3.3606736
21 -10.0810694 -10.0810694
22 -2.5278170 -10.0810694
23 -7.4536509 -2.5278170
24 -1.9827355 -7.4536509
25 0.6256988 -1.9827355
26 -2.2342642 0.6256988
27 -13.9737031 -2.2342642
28 -3.0445396 -13.9737031
29 1.9218093 -3.0445396
30 -0.8823734 1.9218093
31 4.3189632 -0.8823734
32 3.9555755 4.3189632
33 1.0459470 3.9555755
34 5.1463018 1.0459470
35 2.7437188 5.1463018
36 -2.5951727 2.7437188
37 -1.9345328 -2.5951727
38 -6.4384722 -1.9345328
39 -0.8692156 -6.4384722
40 -1.4898347 -0.8692156
41 0.9319299 -1.4898347
42 1.3671806 0.9319299
43 3.6743525 1.3671806
44 -0.2764644 3.6743525
45 0.5825182 -0.2764644
46 4.9721092 0.5825182
47 -12.1052731 4.9721092
48 2.5463418 -12.1052731
49 -2.0103914 2.5463418
50 -2.3044663 -2.0103914
51 0.9887654 -2.3044663
52 2.9594632 0.9887654
53 -4.9992618 2.9594632
54 0.4650101 -4.9992618
55 1.0844690 0.4650101
56 -1.4957836 1.0844690
57 -9.5414434 -1.4957836
58 -5.2829641 -9.5414434
59 6.0227911 -5.2829641
60 1.1031212 6.0227911
61 5.7330651 1.1031212
62 2.8882807 5.7330651
63 5.8987371 2.8882807
64 8.8625922 5.8987371
65 5.6482203 8.8625922
66 -1.7261847 5.6482203
67 2.7949154 -1.7261847
68 -7.3868173 2.7949154
69 -8.3868173 -7.3868173
70 3.9811342 -8.3868173
71 5.6277197 3.9811342
72 -10.2422803 5.6277197
73 -2.5314915 -10.2422803
74 -2.6453501 -2.5314915
75 -1.4154536 -2.6453501
76 -0.2502861 -1.4154536
77 -0.9460472 -0.2502861
78 3.6407014 -0.9460472
79 0.6402116 3.6407014
80 5.3686897 0.6402116
81 0.4103539 5.3686897
82 -17.9617304 0.4103539
83 -2.1032449 -17.9617304
84 3.1804647 -2.1032449
85 -1.6558527 3.1804647
86 3.0137661 -1.6558527
87 6.3179689 3.0137661
88 -3.7191879 6.3179689
89 -1.0625970 -3.7191879
90 2.2507967 -1.0625970
91 -1.8732258 2.2507967
92 0.3480350 -1.8732258
93 -1.4029301 0.3480350
94 2.4380171 -1.4029301
95 -3.7186834 2.4380171
96 -6.1669261 -3.7186834
97 -3.2814866 -6.1669261
98 -2.2035997 -3.2814866
99 8.6276735 -2.2035997
100 1.0172645 8.6276735
101 8.5504819 1.0172645
102 1.9269078 8.5504819
103 -11.1067580 1.9269078
104 -5.2216036 -11.1067580
105 4.6955337 -5.2216036
106 0.8440809 4.6955337
107 3.2682887 0.8440809
108 5.9449652 3.2682887
109 -9.1157221 5.9449652
110 -0.5544889 -9.1157221
111 0.8872256 -0.5544889
112 8.8540790 0.8872256
113 5.8063910 8.8540790
114 -1.6725089 5.8063910
115 2.3666688 -1.6725089
116 -4.7618640 2.3666688
117 0.2953176 -4.7618640
118 1.5533459 0.2953176
119 -1.3542691 1.5533459
120 3.9379074 -1.3542691
121 -0.7011914 3.9379074
122 -1.9575588 -0.7011914
123 1.5795243 -1.9575588
124 8.2251154 1.5795243
125 0.3205017 8.2251154
126 0.4394873 0.3205017
127 3.7441873 0.4394873
128 2.5001599 3.7441873
129 -3.5540130 2.5001599
130 3.3461755 -3.5540130
131 5.3315013 3.3461755
132 -0.1061926 5.3315013
133 3.9726137 -0.1061926
134 -3.5088116 3.9726137
135 5.3239927 -3.5088116
136 2.3606736 5.3239927
137 -3.6745298 2.3606736
138 1.8063984 -3.6745298
139 1.7190641 1.8063984
140 3.1804647 1.7190641
141 -1.9295569 3.1804647
142 -10.6016650 -1.9295569
143 -4.8422226 -10.6016650
144 -4.9290597 -4.8422226
145 6.3379475 -4.9290597
146 NA 6.3379475
> dum1 <- dum[2:length(myerror),]
> dum1
lag(myerror, k = 1) myerror
[1,] -3.2111084 1.1869570
[2,] -3.1192741 -3.2111084
[3,] 0.1246308 -3.1192741
[4,] 2.0242613 0.1246308
[5,] 4.5042164 2.0242613
[6,] 1.6995439 4.5042164
[7,] 1.8355706 1.6995439
[8,] -0.2412610 1.8355706
[9,] 5.2366658 -0.2412610
[10,] 5.9364835 5.2366658
[11,] 0.7743862 5.9364835
[12,] 2.5068430 0.7743862
[13,] -1.0835948 2.5068430
[14,] 10.3159767 -1.0835948
[15,] 3.8823795 10.3159767
[16,] 3.5970699 3.8823795
[17,] -11.7136613 3.5970699
[18,] 1.9962741 -11.7136613
[19,] 3.3606736 1.9962741
[20,] -10.0810694 3.3606736
[21,] -10.0810694 -10.0810694
[22,] -2.5278170 -10.0810694
[23,] -7.4536509 -2.5278170
[24,] -1.9827355 -7.4536509
[25,] 0.6256988 -1.9827355
[26,] -2.2342642 0.6256988
[27,] -13.9737031 -2.2342642
[28,] -3.0445396 -13.9737031
[29,] 1.9218093 -3.0445396
[30,] -0.8823734 1.9218093
[31,] 4.3189632 -0.8823734
[32,] 3.9555755 4.3189632
[33,] 1.0459470 3.9555755
[34,] 5.1463018 1.0459470
[35,] 2.7437188 5.1463018
[36,] -2.5951727 2.7437188
[37,] -1.9345328 -2.5951727
[38,] -6.4384722 -1.9345328
[39,] -0.8692156 -6.4384722
[40,] -1.4898347 -0.8692156
[41,] 0.9319299 -1.4898347
[42,] 1.3671806 0.9319299
[43,] 3.6743525 1.3671806
[44,] -0.2764644 3.6743525
[45,] 0.5825182 -0.2764644
[46,] 4.9721092 0.5825182
[47,] -12.1052731 4.9721092
[48,] 2.5463418 -12.1052731
[49,] -2.0103914 2.5463418
[50,] -2.3044663 -2.0103914
[51,] 0.9887654 -2.3044663
[52,] 2.9594632 0.9887654
[53,] -4.9992618 2.9594632
[54,] 0.4650101 -4.9992618
[55,] 1.0844690 0.4650101
[56,] -1.4957836 1.0844690
[57,] -9.5414434 -1.4957836
[58,] -5.2829641 -9.5414434
[59,] 6.0227911 -5.2829641
[60,] 1.1031212 6.0227911
[61,] 5.7330651 1.1031212
[62,] 2.8882807 5.7330651
[63,] 5.8987371 2.8882807
[64,] 8.8625922 5.8987371
[65,] 5.6482203 8.8625922
[66,] -1.7261847 5.6482203
[67,] 2.7949154 -1.7261847
[68,] -7.3868173 2.7949154
[69,] -8.3868173 -7.3868173
[70,] 3.9811342 -8.3868173
[71,] 5.6277197 3.9811342
[72,] -10.2422803 5.6277197
[73,] -2.5314915 -10.2422803
[74,] -2.6453501 -2.5314915
[75,] -1.4154536 -2.6453501
[76,] -0.2502861 -1.4154536
[77,] -0.9460472 -0.2502861
[78,] 3.6407014 -0.9460472
[79,] 0.6402116 3.6407014
[80,] 5.3686897 0.6402116
[81,] 0.4103539 5.3686897
[82,] -17.9617304 0.4103539
[83,] -2.1032449 -17.9617304
[84,] 3.1804647 -2.1032449
[85,] -1.6558527 3.1804647
[86,] 3.0137661 -1.6558527
[87,] 6.3179689 3.0137661
[88,] -3.7191879 6.3179689
[89,] -1.0625970 -3.7191879
[90,] 2.2507967 -1.0625970
[91,] -1.8732258 2.2507967
[92,] 0.3480350 -1.8732258
[93,] -1.4029301 0.3480350
[94,] 2.4380171 -1.4029301
[95,] -3.7186834 2.4380171
[96,] -6.1669261 -3.7186834
[97,] -3.2814866 -6.1669261
[98,] -2.2035997 -3.2814866
[99,] 8.6276735 -2.2035997
[100,] 1.0172645 8.6276735
[101,] 8.5504819 1.0172645
[102,] 1.9269078 8.5504819
[103,] -11.1067580 1.9269078
[104,] -5.2216036 -11.1067580
[105,] 4.6955337 -5.2216036
[106,] 0.8440809 4.6955337
[107,] 3.2682887 0.8440809
[108,] 5.9449652 3.2682887
[109,] -9.1157221 5.9449652
[110,] -0.5544889 -9.1157221
[111,] 0.8872256 -0.5544889
[112,] 8.8540790 0.8872256
[113,] 5.8063910 8.8540790
[114,] -1.6725089 5.8063910
[115,] 2.3666688 -1.6725089
[116,] -4.7618640 2.3666688
[117,] 0.2953176 -4.7618640
[118,] 1.5533459 0.2953176
[119,] -1.3542691 1.5533459
[120,] 3.9379074 -1.3542691
[121,] -0.7011914 3.9379074
[122,] -1.9575588 -0.7011914
[123,] 1.5795243 -1.9575588
[124,] 8.2251154 1.5795243
[125,] 0.3205017 8.2251154
[126,] 0.4394873 0.3205017
[127,] 3.7441873 0.4394873
[128,] 2.5001599 3.7441873
[129,] -3.5540130 2.5001599
[130,] 3.3461755 -3.5540130
[131,] 5.3315013 3.3461755
[132,] -0.1061926 5.3315013
[133,] 3.9726137 -0.1061926
[134,] -3.5088116 3.9726137
[135,] 5.3239927 -3.5088116
[136,] 2.3606736 5.3239927
[137,] -3.6745298 2.3606736
[138,] 1.8063984 -3.6745298
[139,] 1.7190641 1.8063984
[140,] 3.1804647 1.7190641
[141,] -1.9295569 3.1804647
[142,] -10.6016650 -1.9295569
[143,] -4.8422226 -10.6016650
[144,] -4.9290597 -4.8422226
[145,] 6.3379475 -4.9290597
> z <- as.data.frame(dum1)
> z
lag(myerror, k = 1) myerror
1 -3.2111084 1.1869570
2 -3.1192741 -3.2111084
3 0.1246308 -3.1192741
4 2.0242613 0.1246308
5 4.5042164 2.0242613
6 1.6995439 4.5042164
7 1.8355706 1.6995439
8 -0.2412610 1.8355706
9 5.2366658 -0.2412610
10 5.9364835 5.2366658
11 0.7743862 5.9364835
12 2.5068430 0.7743862
13 -1.0835948 2.5068430
14 10.3159767 -1.0835948
15 3.8823795 10.3159767
16 3.5970699 3.8823795
17 -11.7136613 3.5970699
18 1.9962741 -11.7136613
19 3.3606736 1.9962741
20 -10.0810694 3.3606736
21 -10.0810694 -10.0810694
22 -2.5278170 -10.0810694
23 -7.4536509 -2.5278170
24 -1.9827355 -7.4536509
25 0.6256988 -1.9827355
26 -2.2342642 0.6256988
27 -13.9737031 -2.2342642
28 -3.0445396 -13.9737031
29 1.9218093 -3.0445396
30 -0.8823734 1.9218093
31 4.3189632 -0.8823734
32 3.9555755 4.3189632
33 1.0459470 3.9555755
34 5.1463018 1.0459470
35 2.7437188 5.1463018
36 -2.5951727 2.7437188
37 -1.9345328 -2.5951727
38 -6.4384722 -1.9345328
39 -0.8692156 -6.4384722
40 -1.4898347 -0.8692156
41 0.9319299 -1.4898347
42 1.3671806 0.9319299
43 3.6743525 1.3671806
44 -0.2764644 3.6743525
45 0.5825182 -0.2764644
46 4.9721092 0.5825182
47 -12.1052731 4.9721092
48 2.5463418 -12.1052731
49 -2.0103914 2.5463418
50 -2.3044663 -2.0103914
51 0.9887654 -2.3044663
52 2.9594632 0.9887654
53 -4.9992618 2.9594632
54 0.4650101 -4.9992618
55 1.0844690 0.4650101
56 -1.4957836 1.0844690
57 -9.5414434 -1.4957836
58 -5.2829641 -9.5414434
59 6.0227911 -5.2829641
60 1.1031212 6.0227911
61 5.7330651 1.1031212
62 2.8882807 5.7330651
63 5.8987371 2.8882807
64 8.8625922 5.8987371
65 5.6482203 8.8625922
66 -1.7261847 5.6482203
67 2.7949154 -1.7261847
68 -7.3868173 2.7949154
69 -8.3868173 -7.3868173
70 3.9811342 -8.3868173
71 5.6277197 3.9811342
72 -10.2422803 5.6277197
73 -2.5314915 -10.2422803
74 -2.6453501 -2.5314915
75 -1.4154536 -2.6453501
76 -0.2502861 -1.4154536
77 -0.9460472 -0.2502861
78 3.6407014 -0.9460472
79 0.6402116 3.6407014
80 5.3686897 0.6402116
81 0.4103539 5.3686897
82 -17.9617304 0.4103539
83 -2.1032449 -17.9617304
84 3.1804647 -2.1032449
85 -1.6558527 3.1804647
86 3.0137661 -1.6558527
87 6.3179689 3.0137661
88 -3.7191879 6.3179689
89 -1.0625970 -3.7191879
90 2.2507967 -1.0625970
91 -1.8732258 2.2507967
92 0.3480350 -1.8732258
93 -1.4029301 0.3480350
94 2.4380171 -1.4029301
95 -3.7186834 2.4380171
96 -6.1669261 -3.7186834
97 -3.2814866 -6.1669261
98 -2.2035997 -3.2814866
99 8.6276735 -2.2035997
100 1.0172645 8.6276735
101 8.5504819 1.0172645
102 1.9269078 8.5504819
103 -11.1067580 1.9269078
104 -5.2216036 -11.1067580
105 4.6955337 -5.2216036
106 0.8440809 4.6955337
107 3.2682887 0.8440809
108 5.9449652 3.2682887
109 -9.1157221 5.9449652
110 -0.5544889 -9.1157221
111 0.8872256 -0.5544889
112 8.8540790 0.8872256
113 5.8063910 8.8540790
114 -1.6725089 5.8063910
115 2.3666688 -1.6725089
116 -4.7618640 2.3666688
117 0.2953176 -4.7618640
118 1.5533459 0.2953176
119 -1.3542691 1.5533459
120 3.9379074 -1.3542691
121 -0.7011914 3.9379074
122 -1.9575588 -0.7011914
123 1.5795243 -1.9575588
124 8.2251154 1.5795243
125 0.3205017 8.2251154
126 0.4394873 0.3205017
127 3.7441873 0.4394873
128 2.5001599 3.7441873
129 -3.5540130 2.5001599
130 3.3461755 -3.5540130
131 5.3315013 3.3461755
132 -0.1061926 5.3315013
133 3.9726137 -0.1061926
134 -3.5088116 3.9726137
135 5.3239927 -3.5088116
136 2.3606736 5.3239927
137 -3.6745298 2.3606736
138 1.8063984 -3.6745298
139 1.7190641 1.8063984
140 3.1804647 1.7190641
141 -1.9295569 3.1804647
142 -10.6016650 -1.9295569
143 -4.8422226 -10.6016650
144 -4.9290597 -4.8422226
145 6.3379475 -4.9290597
> 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/7ulw71292682719.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> acf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/freestat/rcomp/tmp/85uv91292682719.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> pacf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Partial Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/freestat/rcomp/tmp/95uv91292682719.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> opar <- par(mfrow = c(2,2), oma = c(0, 0, 1.1, 0))
> plot(mylm, las = 1, sub='Residual Diagnostics')
> par(opar)
> dev.off()
null device
1
> if (n > n25) {
+ postscript(file="/var/www/html/freestat/rcomp/tmp/105uv91292682719.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
+ plot(kp3:nmkm3,gqarr[,2], main='Goldfeld-Quandt test',ylab='2-sided p-value',xlab='breakpoint')
+ grid()
+ dev.off()
+ }
null device
1
>
> #Note: the /var/www/html/freestat/rcomp/createtable file can be downloaded at http://www.wessa.net/cretab
> load(file="/var/www/html/freestat/rcomp/createtable")
>
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a, 'Multiple Linear Regression - Estimated Regression Equation', 1, TRUE)
> a<-table.row.end(a)
> myeq <- colnames(x)[1]
> myeq <- paste(myeq, '[t] = ', sep='')
> for (i in 1:k){
+ if (mysum$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/111mti1292682719.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/12uva31292682719.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/131w8f1292682719.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/14bopi1292682719.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/15x6561292682719.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/16tflw1292682719.tab")
+ }
>
> try(system("convert tmp/1rkg11292682719.ps tmp/1rkg11292682719.png",intern=TRUE))
character(0)
> try(system("convert tmp/2rkg11292682719.ps tmp/2rkg11292682719.png",intern=TRUE))
character(0)
> try(system("convert tmp/3rkg11292682719.ps tmp/3rkg11292682719.png",intern=TRUE))
character(0)
> try(system("convert tmp/41bfl1292682719.ps tmp/41bfl1292682719.png",intern=TRUE))
character(0)
> try(system("convert tmp/51bfl1292682719.ps tmp/51bfl1292682719.png",intern=TRUE))
character(0)
> try(system("convert tmp/61bfl1292682719.ps tmp/61bfl1292682719.png",intern=TRUE))
character(0)
> try(system("convert tmp/7ulw71292682719.ps tmp/7ulw71292682719.png",intern=TRUE))
character(0)
> try(system("convert tmp/85uv91292682719.ps tmp/85uv91292682719.png",intern=TRUE))
character(0)
> try(system("convert tmp/95uv91292682719.ps tmp/95uv91292682719.png",intern=TRUE))
character(0)
> try(system("convert tmp/105uv91292682719.ps tmp/105uv91292682719.png",intern=TRUE))
character(0)
>
>
> proc.time()
user system elapsed
5.354 2.709 5.704