R version 2.9.0 (2009-04-17)
Copyright (C) 2009 The R Foundation for Statistical Computing
ISBN 3-900051-07-0
R is free software and comes with ABSOLUTELY NO WARRANTY.
You are welcome to redistribute it under certain conditions.
Type 'license()' or 'licence()' for distribution details.
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(100
+ ,0
+ ,108.1560276
+ ,0
+ ,114.0150276
+ ,0
+ ,102.1880309
+ ,0
+ ,110.3672031
+ ,0
+ ,96.8602511
+ ,0
+ ,94.1944583
+ ,0
+ ,99.51621961
+ ,0
+ ,94.06333487
+ ,0
+ ,97.5541476
+ ,0
+ ,78.15062422
+ ,0
+ ,81.2434643
+ ,0
+ ,92.36262465
+ ,0
+ ,96.06324371
+ ,0
+ ,114.0523777
+ ,0
+ ,110.6616666
+ ,0
+ ,104.9171949
+ ,0
+ ,90.00187193
+ ,0
+ ,95.7008067
+ ,0
+ ,86.02741157
+ ,0
+ ,84.85287668
+ ,0
+ ,100.04328
+ ,0
+ ,80.91713823
+ ,0
+ ,74.06539709
+ ,0
+ ,77.30281369
+ ,0
+ ,97.23043249
+ ,0
+ ,90.75515676
+ ,0
+ ,100.5614455
+ ,0
+ ,92.01293267
+ ,0
+ ,99.24012138
+ ,0
+ ,105.8672755
+ ,0
+ ,90.9920463
+ ,0
+ ,93.30624423
+ ,0
+ ,91.17419413
+ ,0
+ ,77.33295039
+ ,0
+ ,91.1277721
+ ,0
+ ,85.01249943
+ ,0
+ ,83.90390242
+ ,0
+ ,104.8626302
+ ,0
+ ,110.9039108
+ ,0
+ ,95.43714373
+ ,0
+ ,111.6238727
+ ,0
+ ,108.8925403
+ ,0
+ ,96.17511682
+ ,0
+ ,101.9740205
+ ,0
+ ,99.11953031
+ ,0
+ ,86.78158147
+ ,0
+ ,118.4195003
+ ,0
+ ,118.7441447
+ ,0
+ ,106.5296192
+ ,0
+ ,134.7772694
+ ,0
+ ,104.6778714
+ ,0
+ ,105.2954304
+ ,0
+ ,139.4139849
+ ,0
+ ,103.6060491
+ ,0
+ ,99.78182974
+ ,0
+ ,103.4610301
+ ,0
+ ,120.0594945
+ ,0
+ ,96.71377168
+ ,0
+ ,107.1308929
+ ,0
+ ,105.3608372
+ ,0
+ ,111.6942359
+ ,0
+ ,132.0519998
+ ,0
+ ,126.8037879
+ ,0
+ ,154.4824253
+ ,0
+ ,141.5570984
+ ,0
+ ,109.9506882
+ ,0
+ ,127.904198
+ ,0
+ ,133.0888617
+ ,0
+ ,120.0796299
+ ,0
+ ,117.5557142
+ ,0
+ ,143.0362309
+ ,0
+ ,159.982927
+ ,1
+ ,128.5991124
+ ,1
+ ,149.7373327
+ ,1
+ ,126.8169313
+ ,1
+ ,140.9639674
+ ,1
+ ,137.6691981
+ ,1
+ ,117.9402337
+ ,1
+ ,122.3095247
+ ,1
+ ,127.7804207
+ ,1
+ ,136.1677176
+ ,1
+ ,116.2405856
+ ,1
+ ,123.1576893
+ ,1
+ ,116.3400234
+ ,1
+ ,108.6119282
+ ,1
+ ,125.8982264
+ ,1
+ ,112.8003105
+ ,1
+ ,107.5182447
+ ,1
+ ,135.0955413
+ ,1
+ ,115.5096488
+ ,1
+ ,115.8640759
+ ,1
+ ,104.5883906
+ ,1
+ ,163.7213386
+ ,1
+ ,113.4482275
+ ,1
+ ,98.0428844
+ ,1
+ ,116.7868521
+ ,1
+ ,126.5330444
+ ,1
+ ,113.0336597
+ ,1
+ ,124.3392163
+ ,1
+ ,109.8298759
+ ,1
+ ,124.4434777
+ ,1
+ ,111.5039454
+ ,1
+ ,102.0350019
+ ,1
+ ,116.8726598
+ ,1
+ ,112.2073122
+ ,1
+ ,101.1513902
+ ,1
+ ,124.4255108
+ ,1)
+ ,dim=c(2
+ ,108)
+ ,dimnames=list(c('BouwV'
+ ,'X')
+ ,1:108))
> y <- array(NA,dim=c(2,108),dimnames=list(c('BouwV','X'),1:108))
> for (i in 1:dim(x)[1])
+ {
+ for (j in 1:dim(x)[2])
+ {
+ y[i,j] <- as.numeric(x[i,j])
+ }
+ }
> par3 = 'No Linear Trend'
> par2 = 'Include Monthly Dummies'
> par1 = '1'
> #'GNU S' R Code compiled by R2WASP v. 1.0.44 ()
> #Author: Prof. Dr. P. Wessa
> #To cite this work: AUTHOR(S), (YEAR), YOUR SOFTWARE TITLE (vNUMBER) in Free Statistics Software (v$_version), Office for Research Development and Education, URL http://www.wessa.net/rwasp_YOURPAGE.wasp/
> #Source of accompanying publication: Office for Research, Development, and Education
> #Technical description: Write here your technical program description (don't use hard returns!)
> library(lattice)
> library(lmtest)
Loading required package: zoo
Attaching package: 'zoo'
The following object(s) are masked from package:base :
as.Date.numeric
> n25 <- 25 #minimum number of obs. for Goldfeld-Quandt test
> par1 <- as.numeric(par1)
> x <- t(y)
> k <- length(x[1,])
> n <- length(x[,1])
> x1 <- cbind(x[,par1], x[,1:k!=par1])
> mycolnames <- c(colnames(x)[par1], colnames(x)[1:k!=par1])
> colnames(x1) <- mycolnames #colnames(x)[par1]
> x <- x1
> if (par3 == 'First Differences'){
+ x2 <- array(0, dim=c(n-1,k), dimnames=list(1:(n-1), paste('(1-B)',colnames(x),sep='')))
+ for (i in 1:n-1) {
+ for (j in 1:k) {
+ x2[i,j] <- x[i+1,j] - x[i,j]
+ }
+ }
+ x <- x2
+ }
> if (par2 == 'Include Monthly Dummies'){
+ x2 <- array(0, dim=c(n,11), dimnames=list(1:n, paste('M', seq(1:11), sep ='')))
+ for (i in 1:11){
+ x2[seq(i,n,12),i] <- 1
+ }
+ x <- cbind(x, x2)
+ }
> if (par2 == 'Include Quarterly Dummies'){
+ x2 <- array(0, dim=c(n,3), dimnames=list(1:n, paste('Q', seq(1:3), sep ='')))
+ for (i in 1:3){
+ x2[seq(i,n,4),i] <- 1
+ }
+ x <- cbind(x, x2)
+ }
> k <- length(x[1,])
> if (par3 == 'Linear Trend'){
+ x <- cbind(x, c(1:n))
+ colnames(x)[k+1] <- 't'
+ }
> x
BouwV X M1 M2 M3 M4 M5 M6 M7 M8 M9 M10 M11
1 100.00000 0 1 0 0 0 0 0 0 0 0 0 0
2 108.15603 0 0 1 0 0 0 0 0 0 0 0 0
3 114.01503 0 0 0 1 0 0 0 0 0 0 0 0
4 102.18803 0 0 0 0 1 0 0 0 0 0 0 0
5 110.36720 0 0 0 0 0 1 0 0 0 0 0 0
6 96.86025 0 0 0 0 0 0 1 0 0 0 0 0
7 94.19446 0 0 0 0 0 0 0 1 0 0 0 0
8 99.51622 0 0 0 0 0 0 0 0 1 0 0 0
9 94.06333 0 0 0 0 0 0 0 0 0 1 0 0
10 97.55415 0 0 0 0 0 0 0 0 0 0 1 0
11 78.15062 0 0 0 0 0 0 0 0 0 0 0 1
12 81.24346 0 0 0 0 0 0 0 0 0 0 0 0
13 92.36262 0 1 0 0 0 0 0 0 0 0 0 0
14 96.06324 0 0 1 0 0 0 0 0 0 0 0 0
15 114.05238 0 0 0 1 0 0 0 0 0 0 0 0
16 110.66167 0 0 0 0 1 0 0 0 0 0 0 0
17 104.91719 0 0 0 0 0 1 0 0 0 0 0 0
18 90.00187 0 0 0 0 0 0 1 0 0 0 0 0
19 95.70081 0 0 0 0 0 0 0 1 0 0 0 0
20 86.02741 0 0 0 0 0 0 0 0 1 0 0 0
21 84.85288 0 0 0 0 0 0 0 0 0 1 0 0
22 100.04328 0 0 0 0 0 0 0 0 0 0 1 0
23 80.91714 0 0 0 0 0 0 0 0 0 0 0 1
24 74.06540 0 0 0 0 0 0 0 0 0 0 0 0
25 77.30281 0 1 0 0 0 0 0 0 0 0 0 0
26 97.23043 0 0 1 0 0 0 0 0 0 0 0 0
27 90.75516 0 0 0 1 0 0 0 0 0 0 0 0
28 100.56145 0 0 0 0 1 0 0 0 0 0 0 0
29 92.01293 0 0 0 0 0 1 0 0 0 0 0 0
30 99.24012 0 0 0 0 0 0 1 0 0 0 0 0
31 105.86728 0 0 0 0 0 0 0 1 0 0 0 0
32 90.99205 0 0 0 0 0 0 0 0 1 0 0 0
33 93.30624 0 0 0 0 0 0 0 0 0 1 0 0
34 91.17419 0 0 0 0 0 0 0 0 0 0 1 0
35 77.33295 0 0 0 0 0 0 0 0 0 0 0 1
36 91.12777 0 0 0 0 0 0 0 0 0 0 0 0
37 85.01250 0 1 0 0 0 0 0 0 0 0 0 0
38 83.90390 0 0 1 0 0 0 0 0 0 0 0 0
39 104.86263 0 0 0 1 0 0 0 0 0 0 0 0
40 110.90391 0 0 0 0 1 0 0 0 0 0 0 0
41 95.43714 0 0 0 0 0 1 0 0 0 0 0 0
42 111.62387 0 0 0 0 0 0 1 0 0 0 0 0
43 108.89254 0 0 0 0 0 0 0 1 0 0 0 0
44 96.17512 0 0 0 0 0 0 0 0 1 0 0 0
45 101.97402 0 0 0 0 0 0 0 0 0 1 0 0
46 99.11953 0 0 0 0 0 0 0 0 0 0 1 0
47 86.78158 0 0 0 0 0 0 0 0 0 0 0 1
48 118.41950 0 0 0 0 0 0 0 0 0 0 0 0
49 118.74414 0 1 0 0 0 0 0 0 0 0 0 0
50 106.52962 0 0 1 0 0 0 0 0 0 0 0 0
51 134.77727 0 0 0 1 0 0 0 0 0 0 0 0
52 104.67787 0 0 0 0 1 0 0 0 0 0 0 0
53 105.29543 0 0 0 0 0 1 0 0 0 0 0 0
54 139.41398 0 0 0 0 0 0 1 0 0 0 0 0
55 103.60605 0 0 0 0 0 0 0 1 0 0 0 0
56 99.78183 0 0 0 0 0 0 0 0 1 0 0 0
57 103.46103 0 0 0 0 0 0 0 0 0 1 0 0
58 120.05949 0 0 0 0 0 0 0 0 0 0 1 0
59 96.71377 0 0 0 0 0 0 0 0 0 0 0 1
60 107.13089 0 0 0 0 0 0 0 0 0 0 0 0
61 105.36084 0 1 0 0 0 0 0 0 0 0 0 0
62 111.69424 0 0 1 0 0 0 0 0 0 0 0 0
63 132.05200 0 0 0 1 0 0 0 0 0 0 0 0
64 126.80379 0 0 0 0 1 0 0 0 0 0 0 0
65 154.48243 0 0 0 0 0 1 0 0 0 0 0 0
66 141.55710 0 0 0 0 0 0 1 0 0 0 0 0
67 109.95069 0 0 0 0 0 0 0 1 0 0 0 0
68 127.90420 0 0 0 0 0 0 0 0 1 0 0 0
69 133.08886 0 0 0 0 0 0 0 0 0 1 0 0
70 120.07963 0 0 0 0 0 0 0 0 0 0 1 0
71 117.55571 0 0 0 0 0 0 0 0 0 0 0 1
72 143.03623 0 0 0 0 0 0 0 0 0 0 0 0
73 159.98293 1 1 0 0 0 0 0 0 0 0 0 0
74 128.59911 1 0 1 0 0 0 0 0 0 0 0 0
75 149.73733 1 0 0 1 0 0 0 0 0 0 0 0
76 126.81693 1 0 0 0 1 0 0 0 0 0 0 0
77 140.96397 1 0 0 0 0 1 0 0 0 0 0 0
78 137.66920 1 0 0 0 0 0 1 0 0 0 0 0
79 117.94023 1 0 0 0 0 0 0 1 0 0 0 0
80 122.30952 1 0 0 0 0 0 0 0 1 0 0 0
81 127.78042 1 0 0 0 0 0 0 0 0 1 0 0
82 136.16772 1 0 0 0 0 0 0 0 0 0 1 0
83 116.24059 1 0 0 0 0 0 0 0 0 0 0 1
84 123.15769 1 0 0 0 0 0 0 0 0 0 0 0
85 116.34002 1 1 0 0 0 0 0 0 0 0 0 0
86 108.61193 1 0 1 0 0 0 0 0 0 0 0 0
87 125.89823 1 0 0 1 0 0 0 0 0 0 0 0
88 112.80031 1 0 0 0 1 0 0 0 0 0 0 0
89 107.51824 1 0 0 0 0 1 0 0 0 0 0 0
90 135.09554 1 0 0 0 0 0 1 0 0 0 0 0
91 115.50965 1 0 0 0 0 0 0 1 0 0 0 0
92 115.86408 1 0 0 0 0 0 0 0 1 0 0 0
93 104.58839 1 0 0 0 0 0 0 0 0 1 0 0
94 163.72134 1 0 0 0 0 0 0 0 0 0 1 0
95 113.44823 1 0 0 0 0 0 0 0 0 0 0 1
96 98.04288 1 0 0 0 0 0 0 0 0 0 0 0
97 116.78685 1 1 0 0 0 0 0 0 0 0 0 0
98 126.53304 1 0 1 0 0 0 0 0 0 0 0 0
99 113.03366 1 0 0 1 0 0 0 0 0 0 0 0
100 124.33922 1 0 0 0 1 0 0 0 0 0 0 0
101 109.82988 1 0 0 0 0 1 0 0 0 0 0 0
102 124.44348 1 0 0 0 0 0 1 0 0 0 0 0
103 111.50395 1 0 0 0 0 0 0 1 0 0 0 0
104 102.03500 1 0 0 0 0 0 0 0 1 0 0 0
105 116.87266 1 0 0 0 0 0 0 0 0 1 0 0
106 112.20731 1 0 0 0 0 0 0 0 0 0 1 0
107 101.15139 1 0 0 0 0 0 0 0 0 0 0 1
108 124.42551 1 0 0 0 0 0 0 0 0 0 0 0
> k <- length(x[1,])
> df <- as.data.frame(x)
> (mylm <- lm(df))
Call:
lm(formula = df)
Coefficients:
(Intercept) X M1 M2 M3 M4
100.7379 18.0027 1.2493 0.7414 13.1705 6.5671
M5 M6 M7 M8 M9 M10
6.6861 12.8062 0.2796 -2.2271 -0.0735 8.8308
M11
-10.2619
> (mysum <- summary(mylm))
Call:
lm(formula = df)
Residuals:
Min 1Q Median 3Q Max
-26.673 -9.831 -1.954 6.464 47.058
Coefficients:
Estimate Std. Error t value Pr(>|t|)
(Intercept) 100.7379 5.3448 18.848 < 2e-16 ***
X 18.0027 3.2069 5.614 1.96e-07 ***
M1 1.2493 7.4059 0.169 0.8664
M2 0.7414 7.4059 0.100 0.9205
M3 13.1705 7.4059 1.778 0.0785 .
M4 6.5671 7.4059 0.887 0.3775
M5 6.6861 7.4059 0.903 0.3689
M6 12.8062 7.4059 1.729 0.0870 .
M7 0.2796 7.4059 0.038 0.9700
M8 -2.2271 7.4059 -0.301 0.7643
M9 -0.0735 7.4059 -0.010 0.9921
M10 8.8308 7.4059 1.192 0.2361
M11 -10.2619 7.4059 -1.386 0.1691
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
Residual standard error: 15.71 on 95 degrees of freedom
Multiple R-squared: 0.3432, Adjusted R-squared: 0.2602
F-statistic: 4.136 on 12 and 95 DF, p-value: 3.417e-05
> 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,] 0.0806756219 0.1613512438 0.91932438
[2,] 0.0313450064 0.0626900128 0.96865499
[3,] 0.0144620332 0.0289240665 0.98553797
[4,] 0.0045474934 0.0090949868 0.99545251
[5,] 0.0049778539 0.0099557077 0.99502215
[6,] 0.0029292034 0.0058584068 0.99707080
[7,] 0.0010562074 0.0021124149 0.99894379
[8,] 0.0003710188 0.0007420377 0.99962898
[9,] 0.0002184950 0.0004369901 0.99978150
[10,] 0.0013450311 0.0026900621 0.99865497
[11,] 0.0006246607 0.0012493214 0.99937534
[12,] 0.0042166904 0.0084333809 0.99578331
[13,] 0.0023696396 0.0047392792 0.99763036
[14,] 0.0031174766 0.0062349532 0.99688252
[15,] 0.0021503030 0.0043006061 0.99784970
[16,] 0.0016052503 0.0032105007 0.99839475
[17,] 0.0008467389 0.0016934778 0.99915326
[18,] 0.0004683795 0.0009367590 0.99953162
[19,] 0.0003905552 0.0007811103 0.99960944
[20,] 0.0002376594 0.0004753187 0.99976234
[21,] 0.0003001785 0.0006003569 0.99969982
[22,] 0.0002801133 0.0005602267 0.99971989
[23,] 0.0006496402 0.0012992804 0.99935036
[24,] 0.0004426426 0.0008852852 0.99955736
[25,] 0.0002677847 0.0005355695 0.99973222
[26,] 0.0002405517 0.0004811033 0.99975945
[27,] 0.0004516968 0.0009033936 0.99954830
[28,] 0.0003470685 0.0006941369 0.99965293
[29,] 0.0002220429 0.0004440859 0.99977796
[30,] 0.0002040217 0.0004080435 0.99979598
[31,] 0.0002111883 0.0004223766 0.99978881
[32,] 0.0001973652 0.0003947304 0.99980263
[33,] 0.0040219729 0.0080439458 0.99597803
[34,] 0.0138560778 0.0277121556 0.98614392
[35,] 0.0115108572 0.0230217143 0.98848914
[36,] 0.0253922025 0.0507844049 0.97460780
[37,] 0.0204731365 0.0409462730 0.97952686
[38,] 0.0194268713 0.0388537427 0.98057313
[39,] 0.0723486063 0.1446972125 0.92765139
[40,] 0.0561258969 0.1122517938 0.94387410
[41,] 0.0501576630 0.1003153261 0.94984234
[42,] 0.0477977338 0.0955954675 0.95220227
[43,] 0.0611689261 0.1223378522 0.93883107
[44,] 0.0656068614 0.1312137227 0.93439314
[45,] 0.0710862365 0.1421724729 0.92891376
[46,] 0.1033284854 0.2066569709 0.89667151
[47,] 0.1066653898 0.2133307796 0.89333461
[48,] 0.1084710492 0.2169420983 0.89152895
[49,] 0.1086808306 0.2173616612 0.89131917
[50,] 0.3631852562 0.7263705125 0.63681474
[51,] 0.4083505272 0.8167010544 0.59164947
[52,] 0.3760095475 0.7520190949 0.62399045
[53,] 0.4087907849 0.8175815697 0.59120922
[54,] 0.4635528036 0.9271056071 0.53644720
[55,] 0.5394035616 0.9211928769 0.46059644
[56,] 0.5793758660 0.8412482680 0.42062413
[57,] 0.6494458264 0.7011083473 0.35055417
[58,] 0.8182686298 0.3634627404 0.18173137
[59,] 0.8049100467 0.3901799067 0.19508995
[60,] 0.8615635281 0.2768729438 0.13843647
[61,] 0.8369118871 0.3261762258 0.16308811
[62,] 0.9063850368 0.1872299264 0.09361496
[63,] 0.8768273245 0.2463453509 0.12317268
[64,] 0.8398241839 0.3203516322 0.16017582
[65,] 0.8125359209 0.3749281581 0.18746408
[66,] 0.7990781346 0.4018437309 0.20092187
[67,] 0.7312389706 0.5375220588 0.26876103
[68,] 0.6679948194 0.6640103612 0.33200518
[69,] 0.6135450105 0.7729099789 0.38645499
[70,] 0.5244832041 0.9510335918 0.47551680
[71,] 0.4944127311 0.9888254623 0.50558727
[72,] 0.4284906763 0.8569813527 0.57150932
[73,] 0.3582511334 0.7165022668 0.64174887
[74,] 0.2758597592 0.5517195184 0.72414024
[75,] 0.1953857384 0.3907714769 0.80461426
[76,] 0.1184017621 0.2368035242 0.88159824
[77,] 0.0707532422 0.1415064844 0.92924676
> postscript(file="/var/www/html/rcomp/tmp/13ts81258645696.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> plot(x[,1], type='l', main='Actuals and Interpolation', ylab='value of Actuals and Interpolation (dots)', xlab='time or index')
> points(x[,1]-mysum$resid)
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/2er971258645696.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> plot(mysum$resid, type='b', pch=19, main='Residuals', ylab='value of Residuals', xlab='time or index')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/3tj561258645696.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> hist(mysum$resid, main='Residual Histogram', xlab='values of Residuals')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/4h6r91258645696.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> densityplot(~mysum$resid,col='black',main='Residual Density Plot', xlab='values of Residuals')
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/5ozxo1258645696.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> qqnorm(mysum$resid, main='Residual Normal Q-Q Plot')
> qqline(mysum$resid)
> grid()
> dev.off()
null device
1
> (myerror <- as.ts(mysum$resid))
Time Series:
Start = 1
End = 108
Frequency = 1
1 2 3 4 5 6
-1.9871939 6.6767421 0.1066161 -5.1169907 2.9431541 -16.6839090
7 8 9 10 11 12
-6.8230605 1.0053921 -6.6010943 -12.0145933 -12.3253765 -19.4944652
13 14 15 16 17 18
-9.6245693 -5.4160418 0.1439662 3.3566450 -2.5068541 -23.5422881
19 20 21 22 23 24
-5.3167121 -12.4834159 -15.8115525 -9.5254609 -9.5588625 -26.6725324
25 26 27 28 29 30
-24.6843802 -4.2488530 -23.1532547 -6.7435761 -15.4111164 -14.3040387
31 32 33 34 35 36
4.8497567 -7.5187812 -7.3581849 -18.3945468 -13.1430503 -9.6101574
37 38 39 40 41 42
-16.9746945 -17.5753831 -9.0457813 3.5988892 -11.9869053 -1.9202874
43 44 45 46 47 48
7.8750215 -2.3357107 1.3095914 -10.4492106 -3.6944193 17.6815708
49 50 51 52 53 54
16.7569508 5.0503337 20.8688579 -2.6271502 -2.1286186 25.8698248
55 56 57 58 59 60
2.5885303 1.2710022 2.7966010 10.4907536 6.2377709 6.3929634
61 62 63 64 65 66
3.3736433 10.2149504 18.1435883 19.4987663 47.0583763 28.0129383
67 68 69 70 71 72
8.9331694 29.3933705 32.4244326 10.5108890 27.0797135 42.2983014
73 74 75 76 77 78
39.9930741 9.1171679 17.8262622 1.5092507 15.5372594 6.1223791
79 80 81 82 83 84
-1.0799441 5.7960382 9.1133326 8.5963177 7.7619259 4.4171009
85 86 87 88 89 90
-3.6498295 -10.8700163 -6.0128441 -12.5073701 -17.9084633 3.5487223
91 92 93 94 95 96
-3.5105290 -0.6494106 -14.0786975 36.1499387 4.9695678 -20.6977040
97 98 99 100 101 102
-3.2030008 7.0510999 -18.8774108 -0.9684643 -15.5968321 -7.1033413
103 104 105 106 107 108
-7.5162324 -14.4784846 -1.7944283 -15.3640877 -7.3272695 5.6849224
> postscript(file="/var/www/html/rcomp/tmp/6dd371258645696.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> dum <- cbind(lag(myerror,k=1),myerror)
> dum
Time Series:
Start = 0
End = 108
Frequency = 1
lag(myerror, k = 1) myerror
0 -1.9871939 NA
1 6.6767421 -1.9871939
2 0.1066161 6.6767421
3 -5.1169907 0.1066161
4 2.9431541 -5.1169907
5 -16.6839090 2.9431541
6 -6.8230605 -16.6839090
7 1.0053921 -6.8230605
8 -6.6010943 1.0053921
9 -12.0145933 -6.6010943
10 -12.3253765 -12.0145933
11 -19.4944652 -12.3253765
12 -9.6245693 -19.4944652
13 -5.4160418 -9.6245693
14 0.1439662 -5.4160418
15 3.3566450 0.1439662
16 -2.5068541 3.3566450
17 -23.5422881 -2.5068541
18 -5.3167121 -23.5422881
19 -12.4834159 -5.3167121
20 -15.8115525 -12.4834159
21 -9.5254609 -15.8115525
22 -9.5588625 -9.5254609
23 -26.6725324 -9.5588625
24 -24.6843802 -26.6725324
25 -4.2488530 -24.6843802
26 -23.1532547 -4.2488530
27 -6.7435761 -23.1532547
28 -15.4111164 -6.7435761
29 -14.3040387 -15.4111164
30 4.8497567 -14.3040387
31 -7.5187812 4.8497567
32 -7.3581849 -7.5187812
33 -18.3945468 -7.3581849
34 -13.1430503 -18.3945468
35 -9.6101574 -13.1430503
36 -16.9746945 -9.6101574
37 -17.5753831 -16.9746945
38 -9.0457813 -17.5753831
39 3.5988892 -9.0457813
40 -11.9869053 3.5988892
41 -1.9202874 -11.9869053
42 7.8750215 -1.9202874
43 -2.3357107 7.8750215
44 1.3095914 -2.3357107
45 -10.4492106 1.3095914
46 -3.6944193 -10.4492106
47 17.6815708 -3.6944193
48 16.7569508 17.6815708
49 5.0503337 16.7569508
50 20.8688579 5.0503337
51 -2.6271502 20.8688579
52 -2.1286186 -2.6271502
53 25.8698248 -2.1286186
54 2.5885303 25.8698248
55 1.2710022 2.5885303
56 2.7966010 1.2710022
57 10.4907536 2.7966010
58 6.2377709 10.4907536
59 6.3929634 6.2377709
60 3.3736433 6.3929634
61 10.2149504 3.3736433
62 18.1435883 10.2149504
63 19.4987663 18.1435883
64 47.0583763 19.4987663
65 28.0129383 47.0583763
66 8.9331694 28.0129383
67 29.3933705 8.9331694
68 32.4244326 29.3933705
69 10.5108890 32.4244326
70 27.0797135 10.5108890
71 42.2983014 27.0797135
72 39.9930741 42.2983014
73 9.1171679 39.9930741
74 17.8262622 9.1171679
75 1.5092507 17.8262622
76 15.5372594 1.5092507
77 6.1223791 15.5372594
78 -1.0799441 6.1223791
79 5.7960382 -1.0799441
80 9.1133326 5.7960382
81 8.5963177 9.1133326
82 7.7619259 8.5963177
83 4.4171009 7.7619259
84 -3.6498295 4.4171009
85 -10.8700163 -3.6498295
86 -6.0128441 -10.8700163
87 -12.5073701 -6.0128441
88 -17.9084633 -12.5073701
89 3.5487223 -17.9084633
90 -3.5105290 3.5487223
91 -0.6494106 -3.5105290
92 -14.0786975 -0.6494106
93 36.1499387 -14.0786975
94 4.9695678 36.1499387
95 -20.6977040 4.9695678
96 -3.2030008 -20.6977040
97 7.0510999 -3.2030008
98 -18.8774108 7.0510999
99 -0.9684643 -18.8774108
100 -15.5968321 -0.9684643
101 -7.1033413 -15.5968321
102 -7.5162324 -7.1033413
103 -14.4784846 -7.5162324
104 -1.7944283 -14.4784846
105 -15.3640877 -1.7944283
106 -7.3272695 -15.3640877
107 5.6849224 -7.3272695
108 NA 5.6849224
> dum1 <- dum[2:length(myerror),]
> dum1
lag(myerror, k = 1) myerror
[1,] 6.6767421 -1.9871939
[2,] 0.1066161 6.6767421
[3,] -5.1169907 0.1066161
[4,] 2.9431541 -5.1169907
[5,] -16.6839090 2.9431541
[6,] -6.8230605 -16.6839090
[7,] 1.0053921 -6.8230605
[8,] -6.6010943 1.0053921
[9,] -12.0145933 -6.6010943
[10,] -12.3253765 -12.0145933
[11,] -19.4944652 -12.3253765
[12,] -9.6245693 -19.4944652
[13,] -5.4160418 -9.6245693
[14,] 0.1439662 -5.4160418
[15,] 3.3566450 0.1439662
[16,] -2.5068541 3.3566450
[17,] -23.5422881 -2.5068541
[18,] -5.3167121 -23.5422881
[19,] -12.4834159 -5.3167121
[20,] -15.8115525 -12.4834159
[21,] -9.5254609 -15.8115525
[22,] -9.5588625 -9.5254609
[23,] -26.6725324 -9.5588625
[24,] -24.6843802 -26.6725324
[25,] -4.2488530 -24.6843802
[26,] -23.1532547 -4.2488530
[27,] -6.7435761 -23.1532547
[28,] -15.4111164 -6.7435761
[29,] -14.3040387 -15.4111164
[30,] 4.8497567 -14.3040387
[31,] -7.5187812 4.8497567
[32,] -7.3581849 -7.5187812
[33,] -18.3945468 -7.3581849
[34,] -13.1430503 -18.3945468
[35,] -9.6101574 -13.1430503
[36,] -16.9746945 -9.6101574
[37,] -17.5753831 -16.9746945
[38,] -9.0457813 -17.5753831
[39,] 3.5988892 -9.0457813
[40,] -11.9869053 3.5988892
[41,] -1.9202874 -11.9869053
[42,] 7.8750215 -1.9202874
[43,] -2.3357107 7.8750215
[44,] 1.3095914 -2.3357107
[45,] -10.4492106 1.3095914
[46,] -3.6944193 -10.4492106
[47,] 17.6815708 -3.6944193
[48,] 16.7569508 17.6815708
[49,] 5.0503337 16.7569508
[50,] 20.8688579 5.0503337
[51,] -2.6271502 20.8688579
[52,] -2.1286186 -2.6271502
[53,] 25.8698248 -2.1286186
[54,] 2.5885303 25.8698248
[55,] 1.2710022 2.5885303
[56,] 2.7966010 1.2710022
[57,] 10.4907536 2.7966010
[58,] 6.2377709 10.4907536
[59,] 6.3929634 6.2377709
[60,] 3.3736433 6.3929634
[61,] 10.2149504 3.3736433
[62,] 18.1435883 10.2149504
[63,] 19.4987663 18.1435883
[64,] 47.0583763 19.4987663
[65,] 28.0129383 47.0583763
[66,] 8.9331694 28.0129383
[67,] 29.3933705 8.9331694
[68,] 32.4244326 29.3933705
[69,] 10.5108890 32.4244326
[70,] 27.0797135 10.5108890
[71,] 42.2983014 27.0797135
[72,] 39.9930741 42.2983014
[73,] 9.1171679 39.9930741
[74,] 17.8262622 9.1171679
[75,] 1.5092507 17.8262622
[76,] 15.5372594 1.5092507
[77,] 6.1223791 15.5372594
[78,] -1.0799441 6.1223791
[79,] 5.7960382 -1.0799441
[80,] 9.1133326 5.7960382
[81,] 8.5963177 9.1133326
[82,] 7.7619259 8.5963177
[83,] 4.4171009 7.7619259
[84,] -3.6498295 4.4171009
[85,] -10.8700163 -3.6498295
[86,] -6.0128441 -10.8700163
[87,] -12.5073701 -6.0128441
[88,] -17.9084633 -12.5073701
[89,] 3.5487223 -17.9084633
[90,] -3.5105290 3.5487223
[91,] -0.6494106 -3.5105290
[92,] -14.0786975 -0.6494106
[93,] 36.1499387 -14.0786975
[94,] 4.9695678 36.1499387
[95,] -20.6977040 4.9695678
[96,] -3.2030008 -20.6977040
[97,] 7.0510999 -3.2030008
[98,] -18.8774108 7.0510999
[99,] -0.9684643 -18.8774108
[100,] -15.5968321 -0.9684643
[101,] -7.1033413 -15.5968321
[102,] -7.5162324 -7.1033413
[103,] -14.4784846 -7.5162324
[104,] -1.7944283 -14.4784846
[105,] -15.3640877 -1.7944283
[106,] -7.3272695 -15.3640877
[107,] 5.6849224 -7.3272695
> z <- as.data.frame(dum1)
> z
lag(myerror, k = 1) myerror
1 6.6767421 -1.9871939
2 0.1066161 6.6767421
3 -5.1169907 0.1066161
4 2.9431541 -5.1169907
5 -16.6839090 2.9431541
6 -6.8230605 -16.6839090
7 1.0053921 -6.8230605
8 -6.6010943 1.0053921
9 -12.0145933 -6.6010943
10 -12.3253765 -12.0145933
11 -19.4944652 -12.3253765
12 -9.6245693 -19.4944652
13 -5.4160418 -9.6245693
14 0.1439662 -5.4160418
15 3.3566450 0.1439662
16 -2.5068541 3.3566450
17 -23.5422881 -2.5068541
18 -5.3167121 -23.5422881
19 -12.4834159 -5.3167121
20 -15.8115525 -12.4834159
21 -9.5254609 -15.8115525
22 -9.5588625 -9.5254609
23 -26.6725324 -9.5588625
24 -24.6843802 -26.6725324
25 -4.2488530 -24.6843802
26 -23.1532547 -4.2488530
27 -6.7435761 -23.1532547
28 -15.4111164 -6.7435761
29 -14.3040387 -15.4111164
30 4.8497567 -14.3040387
31 -7.5187812 4.8497567
32 -7.3581849 -7.5187812
33 -18.3945468 -7.3581849
34 -13.1430503 -18.3945468
35 -9.6101574 -13.1430503
36 -16.9746945 -9.6101574
37 -17.5753831 -16.9746945
38 -9.0457813 -17.5753831
39 3.5988892 -9.0457813
40 -11.9869053 3.5988892
41 -1.9202874 -11.9869053
42 7.8750215 -1.9202874
43 -2.3357107 7.8750215
44 1.3095914 -2.3357107
45 -10.4492106 1.3095914
46 -3.6944193 -10.4492106
47 17.6815708 -3.6944193
48 16.7569508 17.6815708
49 5.0503337 16.7569508
50 20.8688579 5.0503337
51 -2.6271502 20.8688579
52 -2.1286186 -2.6271502
53 25.8698248 -2.1286186
54 2.5885303 25.8698248
55 1.2710022 2.5885303
56 2.7966010 1.2710022
57 10.4907536 2.7966010
58 6.2377709 10.4907536
59 6.3929634 6.2377709
60 3.3736433 6.3929634
61 10.2149504 3.3736433
62 18.1435883 10.2149504
63 19.4987663 18.1435883
64 47.0583763 19.4987663
65 28.0129383 47.0583763
66 8.9331694 28.0129383
67 29.3933705 8.9331694
68 32.4244326 29.3933705
69 10.5108890 32.4244326
70 27.0797135 10.5108890
71 42.2983014 27.0797135
72 39.9930741 42.2983014
73 9.1171679 39.9930741
74 17.8262622 9.1171679
75 1.5092507 17.8262622
76 15.5372594 1.5092507
77 6.1223791 15.5372594
78 -1.0799441 6.1223791
79 5.7960382 -1.0799441
80 9.1133326 5.7960382
81 8.5963177 9.1133326
82 7.7619259 8.5963177
83 4.4171009 7.7619259
84 -3.6498295 4.4171009
85 -10.8700163 -3.6498295
86 -6.0128441 -10.8700163
87 -12.5073701 -6.0128441
88 -17.9084633 -12.5073701
89 3.5487223 -17.9084633
90 -3.5105290 3.5487223
91 -0.6494106 -3.5105290
92 -14.0786975 -0.6494106
93 36.1499387 -14.0786975
94 4.9695678 36.1499387
95 -20.6977040 4.9695678
96 -3.2030008 -20.6977040
97 7.0510999 -3.2030008
98 -18.8774108 7.0510999
99 -0.9684643 -18.8774108
100 -15.5968321 -0.9684643
101 -7.1033413 -15.5968321
102 -7.5162324 -7.1033413
103 -14.4784846 -7.5162324
104 -1.7944283 -14.4784846
105 -15.3640877 -1.7944283
106 -7.3272695 -15.3640877
107 5.6849224 -7.3272695
> plot(z,main=paste('Residual Lag plot, lowess, and regression line'), ylab='values of Residuals', xlab='lagged values of Residuals')
> lines(lowess(z))
> abline(lm(z))
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/777hu1258645696.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> acf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/8gvlt1258645696.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> pacf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Partial Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/9zkic1258645696.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> opar <- par(mfrow = c(2,2), oma = c(0, 0, 1.1, 0))
> plot(mylm, las = 1, sub='Residual Diagnostics')
> par(opar)
> dev.off()
null device
1
> if (n > n25) {
+ postscript(file="/var/www/html/rcomp/tmp/10eblv1258645696.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
+ plot(kp3:nmkm3,gqarr[,2], main='Goldfeld-Quandt test',ylab='2-sided p-value',xlab='breakpoint')
+ grid()
+ dev.off()
+ }
null device
1
>
> #Note: the /var/www/html/rcomp/createtable file can be downloaded at http://www.wessa.net/cretab
> load(file="/var/www/html/rcomp/createtable")
>
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a, 'Multiple Linear Regression - Estimated Regression Equation', 1, TRUE)
> a<-table.row.end(a)
> myeq <- colnames(x)[1]
> myeq <- paste(myeq, '[t] = ', sep='')
> for (i in 1:k){
+ if (mysum$coefficients[i,1] > 0) myeq <- paste(myeq, '+', '')
+ myeq <- paste(myeq, mysum$coefficients[i,1], sep=' ')
+ if (rownames(mysum$coefficients)[i] != '(Intercept)') {
+ myeq <- paste(myeq, rownames(mysum$coefficients)[i], sep='')
+ if (rownames(mysum$coefficients)[i] != 't') myeq <- paste(myeq, '[t]', sep='')
+ }
+ }
> myeq <- paste(myeq, ' + e[t]')
> a<-table.row.start(a)
> a<-table.element(a, myeq)
> a<-table.row.end(a)
> a<-table.end(a)
> table.save(a,file="/var/www/html/rcomp/tmp/11nuod1258645696.tab")
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a,hyperlink('http://www.xycoon.com/ols1.htm','Multiple Linear Regression - Ordinary Least Squares',''), 6, TRUE)
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a,'Variable',header=TRUE)
> a<-table.element(a,'Parameter',header=TRUE)
> a<-table.element(a,'S.D.',header=TRUE)
> a<-table.element(a,'T-STAT
H0: parameter = 0',header=TRUE)
> a<-table.element(a,'2-tail p-value',header=TRUE)
> a<-table.element(a,'1-tail p-value',header=TRUE)
> a<-table.row.end(a)
> for (i in 1:k){
+ a<-table.row.start(a)
+ a<-table.element(a,rownames(mysum$coefficients)[i],header=TRUE)
+ a<-table.element(a,mysum$coefficients[i,1])
+ a<-table.element(a, round(mysum$coefficients[i,2],6))
+ a<-table.element(a, round(mysum$coefficients[i,3],4))
+ a<-table.element(a, round(mysum$coefficients[i,4],6))
+ a<-table.element(a, round(mysum$coefficients[i,4]/2,6))
+ a<-table.row.end(a)
+ }
> a<-table.end(a)
> table.save(a,file="/var/www/html/rcomp/tmp/12vsfw1258645696.tab")
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a, 'Multiple Linear Regression - Regression Statistics', 2, TRUE)
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a, 'Multiple R',1,TRUE)
> a<-table.element(a, sqrt(mysum$r.squared))
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a, 'R-squared',1,TRUE)
> a<-table.element(a, mysum$r.squared)
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a, 'Adjusted R-squared',1,TRUE)
> a<-table.element(a, mysum$adj.r.squared)
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a, 'F-TEST (value)',1,TRUE)
> a<-table.element(a, mysum$fstatistic[1])
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a, 'F-TEST (DF numerator)',1,TRUE)
> a<-table.element(a, mysum$fstatistic[2])
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a, 'F-TEST (DF denominator)',1,TRUE)
> a<-table.element(a, mysum$fstatistic[3])
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a, 'p-value',1,TRUE)
> a<-table.element(a, 1-pf(mysum$fstatistic[1],mysum$fstatistic[2],mysum$fstatistic[3]))
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a, 'Multiple Linear Regression - Residual Statistics', 2, TRUE)
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a, 'Residual Standard Deviation',1,TRUE)
> a<-table.element(a, mysum$sigma)
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a, 'Sum Squared Residuals',1,TRUE)
> a<-table.element(a, sum(myerror*myerror))
> a<-table.row.end(a)
> a<-table.end(a)
> table.save(a,file="/var/www/html/rcomp/tmp/13hngj1258645696.tab")
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a, 'Multiple Linear Regression - Actuals, Interpolation, and Residuals', 4, TRUE)
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a, 'Time or Index', 1, TRUE)
> a<-table.element(a, 'Actuals', 1, TRUE)
> a<-table.element(a, 'Interpolation
Forecast', 1, TRUE)
> a<-table.element(a, 'Residuals
Prediction Error', 1, TRUE)
> a<-table.row.end(a)
> for (i in 1:n) {
+ a<-table.row.start(a)
+ a<-table.element(a,i, 1, TRUE)
+ a<-table.element(a,x[i])
+ a<-table.element(a,x[i]-mysum$resid[i])
+ a<-table.element(a,mysum$resid[i])
+ a<-table.row.end(a)
+ }
> a<-table.end(a)
> table.save(a,file="/var/www/html/rcomp/tmp/1487sy1258645696.tab")
> if (n > n25) {
+ a<-table.start()
+ a<-table.row.start(a)
+ a<-table.element(a,'Goldfeld-Quandt test for Heteroskedasticity',4,TRUE)
+ a<-table.row.end(a)
+ a<-table.row.start(a)
+ a<-table.element(a,'p-values',header=TRUE)
+ a<-table.element(a,'Alternative Hypothesis',3,header=TRUE)
+ a<-table.row.end(a)
+ a<-table.row.start(a)
+ a<-table.element(a,'breakpoint index',header=TRUE)
+ a<-table.element(a,'greater',header=TRUE)
+ a<-table.element(a,'2-sided',header=TRUE)
+ a<-table.element(a,'less',header=TRUE)
+ a<-table.row.end(a)
+ for (mypoint in kp3:nmkm3) {
+ a<-table.row.start(a)
+ a<-table.element(a,mypoint,header=TRUE)
+ a<-table.element(a,gqarr[mypoint-kp3+1,1])
+ a<-table.element(a,gqarr[mypoint-kp3+1,2])
+ a<-table.element(a,gqarr[mypoint-kp3+1,3])
+ a<-table.row.end(a)
+ }
+ a<-table.end(a)
+ table.save(a,file="/var/www/html/rcomp/tmp/15ualr1258645696.tab")
+ a<-table.start()
+ a<-table.row.start(a)
+ a<-table.element(a,'Meta Analysis of Goldfeld-Quandt test for Heteroskedasticity',4,TRUE)
+ a<-table.row.end(a)
+ a<-table.row.start(a)
+ a<-table.element(a,'Description',header=TRUE)
+ a<-table.element(a,'# significant tests',header=TRUE)
+ a<-table.element(a,'% significant tests',header=TRUE)
+ a<-table.element(a,'OK/NOK',header=TRUE)
+ a<-table.row.end(a)
+ a<-table.row.start(a)
+ a<-table.element(a,'1% type I error level',header=TRUE)
+ a<-table.element(a,numsignificant1)
+ a<-table.element(a,numsignificant1/numgqtests)
+ if (numsignificant1/numgqtests < 0.01) dum <- 'OK' else dum <- 'NOK'
+ a<-table.element(a,dum)
+ a<-table.row.end(a)
+ a<-table.row.start(a)
+ a<-table.element(a,'5% type I error level',header=TRUE)
+ a<-table.element(a,numsignificant5)
+ a<-table.element(a,numsignificant5/numgqtests)
+ if (numsignificant5/numgqtests < 0.05) dum <- 'OK' else dum <- 'NOK'
+ a<-table.element(a,dum)
+ a<-table.row.end(a)
+ a<-table.row.start(a)
+ a<-table.element(a,'10% type I error level',header=TRUE)
+ a<-table.element(a,numsignificant10)
+ a<-table.element(a,numsignificant10/numgqtests)
+ if (numsignificant10/numgqtests < 0.1) dum <- 'OK' else dum <- 'NOK'
+ a<-table.element(a,dum)
+ a<-table.row.end(a)
+ a<-table.end(a)
+ table.save(a,file="/var/www/html/rcomp/tmp/16n0xm1258645696.tab")
+ }
>
> system("convert tmp/13ts81258645696.ps tmp/13ts81258645696.png")
> system("convert tmp/2er971258645696.ps tmp/2er971258645696.png")
> system("convert tmp/3tj561258645696.ps tmp/3tj561258645696.png")
> system("convert tmp/4h6r91258645696.ps tmp/4h6r91258645696.png")
> system("convert tmp/5ozxo1258645696.ps tmp/5ozxo1258645696.png")
> system("convert tmp/6dd371258645696.ps tmp/6dd371258645696.png")
> system("convert tmp/777hu1258645696.ps tmp/777hu1258645696.png")
> system("convert tmp/8gvlt1258645696.ps tmp/8gvlt1258645696.png")
> system("convert tmp/9zkic1258645696.ps tmp/9zkic1258645696.png")
> system("convert tmp/10eblv1258645696.ps tmp/10eblv1258645696.png")
>
>
> proc.time()
user system elapsed
3.087 1.604 4.049