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(0
+ ,1.3954
+ ,1.0685
+ ,0
+ ,1.4790
+ ,1.1010
+ ,0
+ ,1.4619
+ ,1.0996
+ ,0
+ ,1.4670
+ ,1.0978
+ ,0
+ ,1.4799
+ ,1.0893
+ ,0
+ ,1.4508
+ ,1.1018
+ ,0
+ ,1.4678
+ ,1.0931
+ ,0
+ ,1.4824
+ ,1.0842
+ ,0
+ ,1.5189
+ ,1.0409
+ ,0
+ ,1.5348
+ ,1.0245
+ ,0
+ ,1.5666
+ ,0.9994
+ ,0
+ ,1.5446
+ ,1.0090
+ ,0
+ ,1.5803
+ ,0.9947
+ ,0
+ ,1.5718
+ ,1.0080
+ ,0
+ ,1.5832
+ ,0.9986
+ ,0
+ ,1.5801
+ ,1.0184
+ ,0
+ ,1.5605
+ ,1.0357
+ ,0
+ ,1.5416
+ ,1.0556
+ ,0
+ ,1.5479
+ ,1.0409
+ ,0
+ ,1.5580
+ ,1.0474
+ ,0
+ ,1.5790
+ ,1.0219
+ ,0
+ ,1.5554
+ ,1.0427
+ ,0
+ ,1.5761
+ ,1.0205
+ ,0
+ ,1.5360
+ ,1.0490
+ ,0
+ ,1.5621
+ ,1.0344
+ ,0
+ ,1.5773
+ ,1.0193
+ ,0
+ ,1.5710
+ ,1.0238
+ ,0
+ ,1.5925
+ ,1.0165
+ ,0
+ ,1.5844
+ ,1.0218
+ ,0
+ ,1.5696
+ ,1.0370
+ ,0
+ ,1.5540
+ ,1.0508
+ ,0
+ ,1.5012
+ ,1.0813
+ ,0
+ ,1.4676
+ ,1.0970
+ ,0
+ ,1.4770
+ ,1.0989
+ ,0
+ ,1.4660
+ ,1.1018
+ ,0
+ ,1.4241
+ ,1.1166
+ ,0
+ ,1.4214
+ ,1.1319
+ ,1
+ ,1.4469
+ ,1.1020
+ ,1
+ ,1.4618
+ ,1.0884
+ ,1
+ ,1.3834
+ ,1.1263
+ ,1
+ ,1.3412
+ ,1.1345
+ ,1
+ ,1.3437
+ ,1.1337
+ ,1
+ ,1.2630
+ ,1.1660
+ ,1
+ ,1.2759
+ ,1.1550
+ ,1
+ ,1.2743
+ ,1.1782
+ ,1
+ ,1.2797
+ ,1.1856
+ ,1
+ ,1.2573
+ ,1.2219
+ ,1
+ ,1.2705
+ ,1.2130
+ ,1
+ ,1.2680
+ ,1.2230
+ ,1
+ ,1.3371
+ ,1.1767
+ ,1
+ ,1.3885
+ ,1.1077
+ ,1
+ ,1.4060
+ ,1.0672
+ ,1
+ ,1.3855
+ ,1.0840
+ ,1
+ ,1.3431
+ ,1.1154
+ ,1
+ ,1.3257
+ ,1.1184
+ ,1
+ ,1.2978
+ ,1.1570
+ ,1
+ ,1.2793
+ ,1.1625
+ ,1
+ ,1.2945
+ ,1.1627
+ ,1
+ ,1.2890
+ ,1.1578
+ ,1
+ ,1.2848
+ ,1.1533
+ ,1
+ ,1.2694
+ ,1.1684
+ ,1
+ ,1.2636
+ ,1.1597
+ ,1
+ ,1.2900
+ ,1.1888
+ ,1
+ ,1.3559
+ ,1.1296
+ ,1
+ ,1.3305
+ ,1.1424
+ ,1
+ ,1.3482
+ ,1.1317
+ ,1
+ ,1.3146
+ ,1.1581
+ ,1
+ ,1.3027
+ ,1.1672
+ ,1
+ ,1.3247
+ ,1.1391
+ ,1
+ ,1.3267
+ ,1.1357
+ ,1
+ ,1.3621
+ ,1.1065
+ ,1
+ ,1.3479
+ ,1.1232
+ ,1
+ ,1.4011
+ ,1.0845
+ ,1
+ ,1.4135
+ ,1.0676
+ ,1
+ ,1.3964
+ ,1.0863
+ ,1
+ ,1.4010
+ ,1.0792
+ ,1
+ ,1.3955
+ ,1.0799
+ ,1
+ ,1.4077
+ ,1.0817
+ ,1
+ ,1.3975
+ ,1.0869
+ ,1
+ ,1.3949
+ ,1.0843
+ ,1
+ ,1.4138
+ ,1.0747
+ ,1
+ ,1.4210
+ ,1.0711
+ ,1
+ ,1.4253
+ ,1.0688
+ ,1
+ ,1.4169
+ ,1.0828
+ ,1
+ ,1.4174
+ ,1.0746
+ ,1
+ ,1.4346
+ ,1.0568
+ ,1
+ ,1.4296
+ ,1.0600
+ ,1
+ ,1.4311
+ ,1.0593
+ ,1
+ ,1.4594
+ ,1.0370
+ ,1
+ ,1.4722
+ ,1.0288
+ ,1
+ ,1.4669
+ ,1.0295
+ ,1
+ ,1.4571
+ ,1.0352
+ ,1
+ ,1.4709
+ ,1.0324
+ ,1
+ ,1.4893
+ ,1.0186
+ ,1
+ ,1.4997
+ ,1.0094
+ ,1
+ ,1.4713
+ ,1.0258
+ ,1
+ ,1.4846
+ ,1.0170
+ ,1
+ ,1.4914
+ ,1.0117
+ ,1
+ ,1.4859
+ ,1.0175
+ ,1
+ ,1.4957
+ ,1.0064
+ ,1
+ ,1.4843
+ ,1.0168
+ ,1
+ ,1.4619
+ ,1.0340
+ ,1
+ ,1.4340
+ ,1.0423
+ ,1
+ ,1.4426
+ ,1.0356
+ ,1
+ ,1.4318
+ ,1.0348)
+ ,dim=c(3
+ ,105)
+ ,dimnames=list(c('Crisis'
+ ,'eu/us'
+ ,'us/ch')
+ ,1:105))
> y <- array(NA,dim=c(3,105),dimnames=list(c('Crisis','eu/us','us/ch'),1:105))
> 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 = '2'
> #'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
eu/us Crisis us/ch
1 1.3954 0 1.0685
2 1.4790 0 1.1010
3 1.4619 0 1.0996
4 1.4670 0 1.0978
5 1.4799 0 1.0893
6 1.4508 0 1.1018
7 1.4678 0 1.0931
8 1.4824 0 1.0842
9 1.5189 0 1.0409
10 1.5348 0 1.0245
11 1.5666 0 0.9994
12 1.5446 0 1.0090
13 1.5803 0 0.9947
14 1.5718 0 1.0080
15 1.5832 0 0.9986
16 1.5801 0 1.0184
17 1.5605 0 1.0357
18 1.5416 0 1.0556
19 1.5479 0 1.0409
20 1.5580 0 1.0474
21 1.5790 0 1.0219
22 1.5554 0 1.0427
23 1.5761 0 1.0205
24 1.5360 0 1.0490
25 1.5621 0 1.0344
26 1.5773 0 1.0193
27 1.5710 0 1.0238
28 1.5925 0 1.0165
29 1.5844 0 1.0218
30 1.5696 0 1.0370
31 1.5540 0 1.0508
32 1.5012 0 1.0813
33 1.4676 0 1.0970
34 1.4770 0 1.0989
35 1.4660 0 1.1018
36 1.4241 0 1.1166
37 1.4214 0 1.1319
38 1.4469 1 1.1020
39 1.4618 1 1.0884
40 1.3834 1 1.1263
41 1.3412 1 1.1345
42 1.3437 1 1.1337
43 1.2630 1 1.1660
44 1.2759 1 1.1550
45 1.2743 1 1.1782
46 1.2797 1 1.1856
47 1.2573 1 1.2219
48 1.2705 1 1.2130
49 1.2680 1 1.2230
50 1.3371 1 1.1767
51 1.3885 1 1.1077
52 1.4060 1 1.0672
53 1.3855 1 1.0840
54 1.3431 1 1.1154
55 1.3257 1 1.1184
56 1.2978 1 1.1570
57 1.2793 1 1.1625
58 1.2945 1 1.1627
59 1.2890 1 1.1578
60 1.2848 1 1.1533
61 1.2694 1 1.1684
62 1.2636 1 1.1597
63 1.2900 1 1.1888
64 1.3559 1 1.1296
65 1.3305 1 1.1424
66 1.3482 1 1.1317
67 1.3146 1 1.1581
68 1.3027 1 1.1672
69 1.3247 1 1.1391
70 1.3267 1 1.1357
71 1.3621 1 1.1065
72 1.3479 1 1.1232
73 1.4011 1 1.0845
74 1.4135 1 1.0676
75 1.3964 1 1.0863
76 1.4010 1 1.0792
77 1.3955 1 1.0799
78 1.4077 1 1.0817
79 1.3975 1 1.0869
80 1.3949 1 1.0843
81 1.4138 1 1.0747
82 1.4210 1 1.0711
83 1.4253 1 1.0688
84 1.4169 1 1.0828
85 1.4174 1 1.0746
86 1.4346 1 1.0568
87 1.4296 1 1.0600
88 1.4311 1 1.0593
89 1.4594 1 1.0370
90 1.4722 1 1.0288
91 1.4669 1 1.0295
92 1.4571 1 1.0352
93 1.4709 1 1.0324
94 1.4893 1 1.0186
95 1.4997 1 1.0094
96 1.4713 1 1.0258
97 1.4846 1 1.0170
98 1.4914 1 1.0117
99 1.4859 1 1.0175
100 1.4957 1 1.0064
101 1.4843 1 1.0168
102 1.4619 1 1.0340
103 1.4340 1 1.0423
104 1.4426 1 1.0356
105 1.4318 1 1.0348
> k <- length(x[1,])
> df <- as.data.frame(x)
> (mylm <- lm(df))
Call:
lm(formula = df)
Coefficients:
(Intercept) Crisis `us/ch`
2.81719 -0.08588 -1.22772
> (mysum <- summary(mylm))
Call:
lm(formula = df)
Residuals:
Min 1Q Median 3Q Max
-0.109967 -0.009989 0.001241 0.010754 0.068543
Coefficients:
Estimate Std. Error t value Pr(>|t|)
(Intercept) 2.817188 0.044156 63.80 <2e-16 ***
Crisis -0.085881 0.004943 -17.37 <2e-16 ***
`us/ch` -1.227722 0.041776 -29.39 <2e-16 ***
---
Signif. codes: 0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1
Residual standard error: 0.02227 on 102 degrees of freedom
Multiple R-squared: 0.9477, Adjusted R-squared: 0.9466
F-statistic: 923.4 on 2 and 102 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,] 0.7744735 4.510531e-01 2.255265e-01
[2,] 0.6745683 6.508635e-01 3.254317e-01
[3,] 0.8496257 3.007485e-01 1.503743e-01
[4,] 0.9960153 7.969424e-03 3.984712e-03
[5,] 0.9965972 6.805534e-03 3.402767e-03
[6,] 0.9962246 7.550865e-03 3.775432e-03
[7,] 0.9951009 9.798115e-03 4.899058e-03
[8,] 0.9943017 1.139658e-02 5.698289e-03
[9,] 0.9930348 1.393043e-02 6.965215e-03
[10,] 0.9912012 1.759758e-02 8.798791e-03
[11,] 0.9929594 1.408125e-02 7.040625e-03
[12,] 0.9935833 1.283334e-02 6.416669e-03
[13,] 0.9946784 1.064312e-02 5.321561e-03
[14,] 0.9931566 1.368675e-02 6.843375e-03
[15,] 0.9952151 9.569811e-03 4.784905e-03
[16,] 0.9946471 1.070585e-02 5.352924e-03
[17,] 0.9940251 1.194985e-02 5.974926e-03
[18,] 0.9919896 1.602075e-02 8.010373e-03
[19,] 0.9884080 2.318393e-02 1.159197e-02
[20,] 0.9853736 2.925276e-02 1.462638e-02
[21,] 0.9803465 3.930694e-02 1.965347e-02
[22,] 0.9734895 5.302106e-02 2.651053e-02
[23,] 0.9719398 5.612049e-02 2.806025e-02
[24,] 0.9688463 6.230747e-02 3.115374e-02
[25,] 0.9696117 6.077655e-02 3.038828e-02
[26,] 0.9728753 5.424933e-02 2.712467e-02
[27,] 0.9658850 6.822991e-02 3.411496e-02
[28,] 0.9527021 9.459587e-02 4.729793e-02
[29,] 0.9413420 1.173160e-01 5.865800e-02
[30,] 0.9245647 1.508706e-01 7.543529e-02
[31,] 0.9136853 1.726294e-01 8.631468e-02
[32,] 0.8878355 2.243290e-01 1.121645e-01
[33,] 0.9542500 9.150002e-02 4.575001e-02
[34,] 0.9890349 2.193016e-02 1.096508e-02
[35,] 0.9937597 1.248054e-02 6.240271e-03
[36,] 0.9960850 7.829945e-03 3.914972e-03
[37,] 0.9962877 7.424587e-03 3.712293e-03
[38,] 0.9994197 1.160510e-03 5.802550e-04
[39,] 0.9998929 2.142723e-04 1.071362e-04
[40,] 0.9998483 3.033362e-04 1.516681e-04
[41,] 0.9997394 5.212277e-04 2.606139e-04
[42,] 0.9998030 3.940430e-04 1.970215e-04
[43,] 0.9998789 2.422449e-04 1.211224e-04
[44,] 0.9999814 3.727864e-05 1.863932e-05
[45,] 0.9999999 1.691560e-07 8.457800e-08
[46,] 0.9999999 1.166129e-07 5.830644e-08
[47,] 1.0000000 9.615316e-08 4.807658e-08
[48,] 0.9999999 1.056901e-07 5.284503e-08
[49,] 0.9999999 1.095723e-07 5.478616e-08
[50,] 1.0000000 2.267195e-08 1.133598e-08
[51,] 1.0000000 4.254555e-08 2.127277e-08
[52,] 1.0000000 3.422031e-08 1.711015e-08
[53,] 1.0000000 7.431792e-08 3.715896e-08
[54,] 1.0000000 8.373859e-08 4.186930e-08
[55,] 1.0000000 2.326027e-08 1.163014e-08
[56,] 1.0000000 7.531308e-09 3.765654e-09
[57,] 1.0000000 2.702431e-12 1.351216e-12
[58,] 1.0000000 1.683575e-12 8.417876e-13
[59,] 1.0000000 2.300362e-12 1.150181e-12
[60,] 1.0000000 7.506302e-12 3.753151e-12
[61,] 1.0000000 1.717127e-11 8.585634e-12
[62,] 1.0000000 3.828914e-11 1.914457e-11
[63,] 1.0000000 7.294540e-11 3.647270e-11
[64,] 1.0000000 2.187889e-10 1.093944e-10
[65,] 1.0000000 5.253142e-10 2.626571e-10
[66,] 1.0000000 9.928607e-10 4.964304e-10
[67,] 1.0000000 2.910660e-09 1.455330e-09
[68,] 1.0000000 8.927992e-09 4.463996e-09
[69,] 1.0000000 2.107875e-08 1.053938e-08
[70,] 1.0000000 6.306029e-08 3.153015e-08
[71,] 0.9999999 1.580844e-07 7.904219e-08
[72,] 0.9999999 2.442641e-07 1.221321e-07
[73,] 0.9999997 6.729048e-07 3.364524e-07
[74,] 0.9999990 1.900177e-06 9.500886e-07
[75,] 0.9999979 4.105890e-06 2.052945e-06
[76,] 0.9999944 1.114741e-05 5.573705e-06
[77,] 0.9999859 2.828005e-05 1.414003e-05
[78,] 0.9999675 6.496692e-05 3.248346e-05
[79,] 0.9999753 4.941548e-05 2.470774e-05
[80,] 0.9999656 6.889638e-05 3.444819e-05
[81,] 0.9999287 1.425918e-04 7.129590e-05
[82,] 0.9998743 2.514904e-04 1.257452e-04
[83,] 0.9998862 2.276097e-04 1.138048e-04
[84,] 0.9998030 3.939036e-04 1.969518e-04
[85,] 0.9996289 7.421663e-04 3.710832e-04
[86,] 0.9991115 1.776997e-03 8.884983e-04
[87,] 0.9980651 3.869883e-03 1.934941e-03
[88,] 0.9987708 2.458389e-03 1.229194e-03
[89,] 0.9978949 4.210240e-03 2.105120e-03
[90,] 0.9940681 1.186383e-02 5.931913e-03
[91,] 0.9866387 2.672251e-02 1.336126e-02
[92,] 0.9659768 6.804638e-02 3.402319e-02
[93,] 0.9155470 1.689059e-01 8.445295e-02
[94,] 0.8302852 3.394296e-01 1.697148e-01
> postscript(file="/var/www/html/freestat/rcomp/tmp/19ggy1290506277.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$resid)
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/freestat/rcomp/tmp/29ggy1290506277.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> plot(mysum$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/freestat/rcomp/tmp/39ggy1290506277.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> hist(mysum$resid, main='Residual Histogram', xlab='values of Residuals')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/freestat/rcomp/tmp/42pf11290506277.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> densityplot(~mysum$resid,col='black',main='Residual Density Plot', xlab='values of Residuals')
> dev.off()
null device
1
> postscript(file="/var/www/html/freestat/rcomp/tmp/52pf11290506277.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 = 105
Frequency = 1
1 2 3 4 5
-1.099668e-01 1.353421e-02 -5.284601e-03 -2.394501e-03 6.985770e-05
6 7 8 9 10
-1.368361e-02 -7.364797e-03 -3.691527e-03 -2.035191e-02 -2.458656e-02
11 12 13 14 15
-2.360239e-02 -3.381626e-02 -1.567269e-02 -7.843978e-03 -7.984570e-03
16 17 18 19 20
1.322434e-02 1.486393e-02 2.039561e-02 8.648091e-03 2.672829e-02
21 22 23 24 25
1.642136e-02 1.835799e-02 1.180255e-02 6.692643e-03 1.486789e-02
26 27 28 29 30
1.152929e-02 1.075404e-02 2.329166e-02 2.169859e-02 2.555997e-02
31 32 33 34 35
2.690254e-02 1.154808e-02 -2.776679e-03 8.955993e-03 1.516388e-03
36 37 38 39 40
-2.221332e-02 -6.129165e-03 6.854333e-02 6.674631e-02 3.487699e-02
41 42 43 44 45
2.744311e-03 4.262133e-03 -3.678243e-02 -3.738738e-02 -1.050422e-02
46 47 48 49 50
3.980928e-03 2.614725e-02 2.842052e-02 3.819775e-02 5.045420e-02
51 52 53 54 55
1.714135e-02 -1.508141e-02 -1.495567e-02 -1.880519e-02 -3.252202e-02
56 57 58 59 60
-1.303193e-02 -2.477946e-02 -9.333916e-03 -2.084976e-02 -3.057451e-02
61 62 63 64 65
-2.743590e-02 -4.391708e-02 1.820964e-02 1.142847e-02 1.743318e-03
66 67 68 69 70
6.306688e-03 5.118561e-03 4.390835e-03 -8.108166e-03 -1.028242e-02
71 72 73 74 75
-1.073192e-02 -4.428953e-03 1.258188e-03 -7.090322e-03 -1.231912e-03
76 77 78 79 80
-5.348741e-03 -9.989336e-03 4.420565e-03 6.047215e-04 -5.187357e-03
81 82 83 84 85
1.926507e-03 4.706707e-03 6.182945e-03 1.497106e-02 5.403735e-03
86 87 88 89 90
7.502754e-04 -3.210127e-04 3.195815e-04 1.241371e-03 3.974046e-03
91 92 93 94 95
-4.665478e-04 -3.268530e-03 7.093847e-03 8.551277e-03 7.656231e-03
96 97 98 99 100
-6.091209e-04 1.886921e-03 2.179992e-03 3.800783e-03 -2.693667e-05
101 102 103 104 105
1.341377e-03 5.820326e-05 -1.765170e-02 -1.727744e-02 -2.905962e-02
> postscript(file="/var/www/html/freestat/rcomp/tmp/62pf11290506277.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 = 105
Frequency = 1
lag(myerror, k = 1) myerror
0 -1.099668e-01 NA
1 1.353421e-02 -1.099668e-01
2 -5.284601e-03 1.353421e-02
3 -2.394501e-03 -5.284601e-03
4 6.985770e-05 -2.394501e-03
5 -1.368361e-02 6.985770e-05
6 -7.364797e-03 -1.368361e-02
7 -3.691527e-03 -7.364797e-03
8 -2.035191e-02 -3.691527e-03
9 -2.458656e-02 -2.035191e-02
10 -2.360239e-02 -2.458656e-02
11 -3.381626e-02 -2.360239e-02
12 -1.567269e-02 -3.381626e-02
13 -7.843978e-03 -1.567269e-02
14 -7.984570e-03 -7.843978e-03
15 1.322434e-02 -7.984570e-03
16 1.486393e-02 1.322434e-02
17 2.039561e-02 1.486393e-02
18 8.648091e-03 2.039561e-02
19 2.672829e-02 8.648091e-03
20 1.642136e-02 2.672829e-02
21 1.835799e-02 1.642136e-02
22 1.180255e-02 1.835799e-02
23 6.692643e-03 1.180255e-02
24 1.486789e-02 6.692643e-03
25 1.152929e-02 1.486789e-02
26 1.075404e-02 1.152929e-02
27 2.329166e-02 1.075404e-02
28 2.169859e-02 2.329166e-02
29 2.555997e-02 2.169859e-02
30 2.690254e-02 2.555997e-02
31 1.154808e-02 2.690254e-02
32 -2.776679e-03 1.154808e-02
33 8.955993e-03 -2.776679e-03
34 1.516388e-03 8.955993e-03
35 -2.221332e-02 1.516388e-03
36 -6.129165e-03 -2.221332e-02
37 6.854333e-02 -6.129165e-03
38 6.674631e-02 6.854333e-02
39 3.487699e-02 6.674631e-02
40 2.744311e-03 3.487699e-02
41 4.262133e-03 2.744311e-03
42 -3.678243e-02 4.262133e-03
43 -3.738738e-02 -3.678243e-02
44 -1.050422e-02 -3.738738e-02
45 3.980928e-03 -1.050422e-02
46 2.614725e-02 3.980928e-03
47 2.842052e-02 2.614725e-02
48 3.819775e-02 2.842052e-02
49 5.045420e-02 3.819775e-02
50 1.714135e-02 5.045420e-02
51 -1.508141e-02 1.714135e-02
52 -1.495567e-02 -1.508141e-02
53 -1.880519e-02 -1.495567e-02
54 -3.252202e-02 -1.880519e-02
55 -1.303193e-02 -3.252202e-02
56 -2.477946e-02 -1.303193e-02
57 -9.333916e-03 -2.477946e-02
58 -2.084976e-02 -9.333916e-03
59 -3.057451e-02 -2.084976e-02
60 -2.743590e-02 -3.057451e-02
61 -4.391708e-02 -2.743590e-02
62 1.820964e-02 -4.391708e-02
63 1.142847e-02 1.820964e-02
64 1.743318e-03 1.142847e-02
65 6.306688e-03 1.743318e-03
66 5.118561e-03 6.306688e-03
67 4.390835e-03 5.118561e-03
68 -8.108166e-03 4.390835e-03
69 -1.028242e-02 -8.108166e-03
70 -1.073192e-02 -1.028242e-02
71 -4.428953e-03 -1.073192e-02
72 1.258188e-03 -4.428953e-03
73 -7.090322e-03 1.258188e-03
74 -1.231912e-03 -7.090322e-03
75 -5.348741e-03 -1.231912e-03
76 -9.989336e-03 -5.348741e-03
77 4.420565e-03 -9.989336e-03
78 6.047215e-04 4.420565e-03
79 -5.187357e-03 6.047215e-04
80 1.926507e-03 -5.187357e-03
81 4.706707e-03 1.926507e-03
82 6.182945e-03 4.706707e-03
83 1.497106e-02 6.182945e-03
84 5.403735e-03 1.497106e-02
85 7.502754e-04 5.403735e-03
86 -3.210127e-04 7.502754e-04
87 3.195815e-04 -3.210127e-04
88 1.241371e-03 3.195815e-04
89 3.974046e-03 1.241371e-03
90 -4.665478e-04 3.974046e-03
91 -3.268530e-03 -4.665478e-04
92 7.093847e-03 -3.268530e-03
93 8.551277e-03 7.093847e-03
94 7.656231e-03 8.551277e-03
95 -6.091209e-04 7.656231e-03
96 1.886921e-03 -6.091209e-04
97 2.179992e-03 1.886921e-03
98 3.800783e-03 2.179992e-03
99 -2.693667e-05 3.800783e-03
100 1.341377e-03 -2.693667e-05
101 5.820326e-05 1.341377e-03
102 -1.765170e-02 5.820326e-05
103 -1.727744e-02 -1.765170e-02
104 -2.905962e-02 -1.727744e-02
105 NA -2.905962e-02
> dum1 <- dum[2:length(myerror),]
> dum1
lag(myerror, k = 1) myerror
[1,] 1.353421e-02 -1.099668e-01
[2,] -5.284601e-03 1.353421e-02
[3,] -2.394501e-03 -5.284601e-03
[4,] 6.985770e-05 -2.394501e-03
[5,] -1.368361e-02 6.985770e-05
[6,] -7.364797e-03 -1.368361e-02
[7,] -3.691527e-03 -7.364797e-03
[8,] -2.035191e-02 -3.691527e-03
[9,] -2.458656e-02 -2.035191e-02
[10,] -2.360239e-02 -2.458656e-02
[11,] -3.381626e-02 -2.360239e-02
[12,] -1.567269e-02 -3.381626e-02
[13,] -7.843978e-03 -1.567269e-02
[14,] -7.984570e-03 -7.843978e-03
[15,] 1.322434e-02 -7.984570e-03
[16,] 1.486393e-02 1.322434e-02
[17,] 2.039561e-02 1.486393e-02
[18,] 8.648091e-03 2.039561e-02
[19,] 2.672829e-02 8.648091e-03
[20,] 1.642136e-02 2.672829e-02
[21,] 1.835799e-02 1.642136e-02
[22,] 1.180255e-02 1.835799e-02
[23,] 6.692643e-03 1.180255e-02
[24,] 1.486789e-02 6.692643e-03
[25,] 1.152929e-02 1.486789e-02
[26,] 1.075404e-02 1.152929e-02
[27,] 2.329166e-02 1.075404e-02
[28,] 2.169859e-02 2.329166e-02
[29,] 2.555997e-02 2.169859e-02
[30,] 2.690254e-02 2.555997e-02
[31,] 1.154808e-02 2.690254e-02
[32,] -2.776679e-03 1.154808e-02
[33,] 8.955993e-03 -2.776679e-03
[34,] 1.516388e-03 8.955993e-03
[35,] -2.221332e-02 1.516388e-03
[36,] -6.129165e-03 -2.221332e-02
[37,] 6.854333e-02 -6.129165e-03
[38,] 6.674631e-02 6.854333e-02
[39,] 3.487699e-02 6.674631e-02
[40,] 2.744311e-03 3.487699e-02
[41,] 4.262133e-03 2.744311e-03
[42,] -3.678243e-02 4.262133e-03
[43,] -3.738738e-02 -3.678243e-02
[44,] -1.050422e-02 -3.738738e-02
[45,] 3.980928e-03 -1.050422e-02
[46,] 2.614725e-02 3.980928e-03
[47,] 2.842052e-02 2.614725e-02
[48,] 3.819775e-02 2.842052e-02
[49,] 5.045420e-02 3.819775e-02
[50,] 1.714135e-02 5.045420e-02
[51,] -1.508141e-02 1.714135e-02
[52,] -1.495567e-02 -1.508141e-02
[53,] -1.880519e-02 -1.495567e-02
[54,] -3.252202e-02 -1.880519e-02
[55,] -1.303193e-02 -3.252202e-02
[56,] -2.477946e-02 -1.303193e-02
[57,] -9.333916e-03 -2.477946e-02
[58,] -2.084976e-02 -9.333916e-03
[59,] -3.057451e-02 -2.084976e-02
[60,] -2.743590e-02 -3.057451e-02
[61,] -4.391708e-02 -2.743590e-02
[62,] 1.820964e-02 -4.391708e-02
[63,] 1.142847e-02 1.820964e-02
[64,] 1.743318e-03 1.142847e-02
[65,] 6.306688e-03 1.743318e-03
[66,] 5.118561e-03 6.306688e-03
[67,] 4.390835e-03 5.118561e-03
[68,] -8.108166e-03 4.390835e-03
[69,] -1.028242e-02 -8.108166e-03
[70,] -1.073192e-02 -1.028242e-02
[71,] -4.428953e-03 -1.073192e-02
[72,] 1.258188e-03 -4.428953e-03
[73,] -7.090322e-03 1.258188e-03
[74,] -1.231912e-03 -7.090322e-03
[75,] -5.348741e-03 -1.231912e-03
[76,] -9.989336e-03 -5.348741e-03
[77,] 4.420565e-03 -9.989336e-03
[78,] 6.047215e-04 4.420565e-03
[79,] -5.187357e-03 6.047215e-04
[80,] 1.926507e-03 -5.187357e-03
[81,] 4.706707e-03 1.926507e-03
[82,] 6.182945e-03 4.706707e-03
[83,] 1.497106e-02 6.182945e-03
[84,] 5.403735e-03 1.497106e-02
[85,] 7.502754e-04 5.403735e-03
[86,] -3.210127e-04 7.502754e-04
[87,] 3.195815e-04 -3.210127e-04
[88,] 1.241371e-03 3.195815e-04
[89,] 3.974046e-03 1.241371e-03
[90,] -4.665478e-04 3.974046e-03
[91,] -3.268530e-03 -4.665478e-04
[92,] 7.093847e-03 -3.268530e-03
[93,] 8.551277e-03 7.093847e-03
[94,] 7.656231e-03 8.551277e-03
[95,] -6.091209e-04 7.656231e-03
[96,] 1.886921e-03 -6.091209e-04
[97,] 2.179992e-03 1.886921e-03
[98,] 3.800783e-03 2.179992e-03
[99,] -2.693667e-05 3.800783e-03
[100,] 1.341377e-03 -2.693667e-05
[101,] 5.820326e-05 1.341377e-03
[102,] -1.765170e-02 5.820326e-05
[103,] -1.727744e-02 -1.765170e-02
[104,] -2.905962e-02 -1.727744e-02
> z <- as.data.frame(dum1)
> z
lag(myerror, k = 1) myerror
1 1.353421e-02 -1.099668e-01
2 -5.284601e-03 1.353421e-02
3 -2.394501e-03 -5.284601e-03
4 6.985770e-05 -2.394501e-03
5 -1.368361e-02 6.985770e-05
6 -7.364797e-03 -1.368361e-02
7 -3.691527e-03 -7.364797e-03
8 -2.035191e-02 -3.691527e-03
9 -2.458656e-02 -2.035191e-02
10 -2.360239e-02 -2.458656e-02
11 -3.381626e-02 -2.360239e-02
12 -1.567269e-02 -3.381626e-02
13 -7.843978e-03 -1.567269e-02
14 -7.984570e-03 -7.843978e-03
15 1.322434e-02 -7.984570e-03
16 1.486393e-02 1.322434e-02
17 2.039561e-02 1.486393e-02
18 8.648091e-03 2.039561e-02
19 2.672829e-02 8.648091e-03
20 1.642136e-02 2.672829e-02
21 1.835799e-02 1.642136e-02
22 1.180255e-02 1.835799e-02
23 6.692643e-03 1.180255e-02
24 1.486789e-02 6.692643e-03
25 1.152929e-02 1.486789e-02
26 1.075404e-02 1.152929e-02
27 2.329166e-02 1.075404e-02
28 2.169859e-02 2.329166e-02
29 2.555997e-02 2.169859e-02
30 2.690254e-02 2.555997e-02
31 1.154808e-02 2.690254e-02
32 -2.776679e-03 1.154808e-02
33 8.955993e-03 -2.776679e-03
34 1.516388e-03 8.955993e-03
35 -2.221332e-02 1.516388e-03
36 -6.129165e-03 -2.221332e-02
37 6.854333e-02 -6.129165e-03
38 6.674631e-02 6.854333e-02
39 3.487699e-02 6.674631e-02
40 2.744311e-03 3.487699e-02
41 4.262133e-03 2.744311e-03
42 -3.678243e-02 4.262133e-03
43 -3.738738e-02 -3.678243e-02
44 -1.050422e-02 -3.738738e-02
45 3.980928e-03 -1.050422e-02
46 2.614725e-02 3.980928e-03
47 2.842052e-02 2.614725e-02
48 3.819775e-02 2.842052e-02
49 5.045420e-02 3.819775e-02
50 1.714135e-02 5.045420e-02
51 -1.508141e-02 1.714135e-02
52 -1.495567e-02 -1.508141e-02
53 -1.880519e-02 -1.495567e-02
54 -3.252202e-02 -1.880519e-02
55 -1.303193e-02 -3.252202e-02
56 -2.477946e-02 -1.303193e-02
57 -9.333916e-03 -2.477946e-02
58 -2.084976e-02 -9.333916e-03
59 -3.057451e-02 -2.084976e-02
60 -2.743590e-02 -3.057451e-02
61 -4.391708e-02 -2.743590e-02
62 1.820964e-02 -4.391708e-02
63 1.142847e-02 1.820964e-02
64 1.743318e-03 1.142847e-02
65 6.306688e-03 1.743318e-03
66 5.118561e-03 6.306688e-03
67 4.390835e-03 5.118561e-03
68 -8.108166e-03 4.390835e-03
69 -1.028242e-02 -8.108166e-03
70 -1.073192e-02 -1.028242e-02
71 -4.428953e-03 -1.073192e-02
72 1.258188e-03 -4.428953e-03
73 -7.090322e-03 1.258188e-03
74 -1.231912e-03 -7.090322e-03
75 -5.348741e-03 -1.231912e-03
76 -9.989336e-03 -5.348741e-03
77 4.420565e-03 -9.989336e-03
78 6.047215e-04 4.420565e-03
79 -5.187357e-03 6.047215e-04
80 1.926507e-03 -5.187357e-03
81 4.706707e-03 1.926507e-03
82 6.182945e-03 4.706707e-03
83 1.497106e-02 6.182945e-03
84 5.403735e-03 1.497106e-02
85 7.502754e-04 5.403735e-03
86 -3.210127e-04 7.502754e-04
87 3.195815e-04 -3.210127e-04
88 1.241371e-03 3.195815e-04
89 3.974046e-03 1.241371e-03
90 -4.665478e-04 3.974046e-03
91 -3.268530e-03 -4.665478e-04
92 7.093847e-03 -3.268530e-03
93 8.551277e-03 7.093847e-03
94 7.656231e-03 8.551277e-03
95 -6.091209e-04 7.656231e-03
96 1.886921e-03 -6.091209e-04
97 2.179992e-03 1.886921e-03
98 3.800783e-03 2.179992e-03
99 -2.693667e-05 3.800783e-03
100 1.341377e-03 -2.693667e-05
101 5.820326e-05 1.341377e-03
102 -1.765170e-02 5.820326e-05
103 -1.727744e-02 -1.765170e-02
104 -2.905962e-02 -1.727744e-02
> 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/7cyem1290506277.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> acf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/freestat/rcomp/tmp/858e71290506277.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> pacf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Partial Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/freestat/rcomp/tmp/958e71290506277.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> opar <- par(mfrow = c(2,2), oma = c(0, 0, 1.1, 0))
> plot(mylm, las = 1, sub='Residual Diagnostics')
> par(opar)
> dev.off()
null device
1
> if (n > n25) {
+ postscript(file="/var/www/html/freestat/rcomp/tmp/1058e71290506277.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
+ plot(kp3:nmkm3,gqarr[,2], main='Goldfeld-Quandt test',ylab='2-sided p-value',xlab='breakpoint')
+ grid()
+ dev.off()
+ }
null device
1
>
> #Note: the /var/www/html/freestat/rcomp/createtable file can be downloaded at http://www.wessa.net/cretab
> load(file="/var/www/html/freestat/rcomp/createtable")
>
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a, 'Multiple Linear Regression - Estimated Regression Equation', 1, TRUE)
> a<-table.row.end(a)
> myeq <- colnames(x)[1]
> myeq <- paste(myeq, '[t] = ', sep='')
> for (i in 1:k){
+ if (mysum$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/111hcg1290506277.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/1250a41290506277.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/1319qc1290506277.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/14ma6i1290506277.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/15pbno1290506277.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/16bt3c1290506277.tab")
+ }
>
> try(system("convert tmp/19ggy1290506277.ps tmp/19ggy1290506277.png",intern=TRUE))
character(0)
> try(system("convert tmp/29ggy1290506277.ps tmp/29ggy1290506277.png",intern=TRUE))
character(0)
> try(system("convert tmp/39ggy1290506277.ps tmp/39ggy1290506277.png",intern=TRUE))
character(0)
> try(system("convert tmp/42pf11290506277.ps tmp/42pf11290506277.png",intern=TRUE))
character(0)
> try(system("convert tmp/52pf11290506277.ps tmp/52pf11290506277.png",intern=TRUE))
character(0)
> try(system("convert tmp/62pf11290506277.ps tmp/62pf11290506277.png",intern=TRUE))
character(0)
> try(system("convert tmp/7cyem1290506277.ps tmp/7cyem1290506277.png",intern=TRUE))
character(0)
> try(system("convert tmp/858e71290506277.ps tmp/858e71290506277.png",intern=TRUE))
character(0)
> try(system("convert tmp/958e71290506277.ps tmp/958e71290506277.png",intern=TRUE))
character(0)
> try(system("convert tmp/1058e71290506277.ps tmp/1058e71290506277.png",intern=TRUE))
character(0)
>
>
> proc.time()
user system elapsed
4.492 2.545 5.233