R version 2.9.0 (2009-04-17)
Copyright (C) 2009 The R Foundation for Statistical Computing
ISBN 3-900051-07-0
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Type 'demo()' for some demos, 'help()' for on-line help, or
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> x <- array(list(3,101.2,3.21,101.1,3.37,100.7,3.51,100.1,3.75,99.9,4.11,99.7,4.25,99.5,4.25,99.2,4.5,99,4.7,99,4.75,99.3,4.75,99.5,4.75,99.7,4.75,100,4.75,100.4,4.75,100.6,4.58,100.7,4.5,100.7,4.5,100.6,4.49,100.5,4.03,100.6,3.75,100.5,3.39,100.4,3.25,100.3,3.25,100.4,3.25,100.4,3.25,100.4,3.25,100.4,3.25,100.4,3.25,100.5,3.25,100.6,3.25,100.6,3.25,100.5,3.25,100.5,3.25,100.7,2.85,101.1,2.75,101.5,2.75,101.9,2.55,102.1,2.5,102.1,2.5,102.1,2.1,102.4,2,102.8,2,103.1,2,103.1,2,102.9,2,102.4,2,101.9,2,101.3,2,100.7,2,100.6,2,101,2,101.5,2,101.9,2,102.1,2,102.3,2,102.5,2,102.9,2,103.6,2,104.3),dim=c(2,60),dimnames=list(c('Rente','Tprod'),1:60))
> y <- array(NA,dim=c(2,60),dimnames=list(c('Rente','Tprod'),1:60))
> for (i in 1:dim(x)[1])
+ {
+ for (j in 1:dim(x)[2])
+ {
+ y[i,j] <- as.numeric(x[i,j])
+ }
+ }
> par3 = '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
Tprod Rente t
1 101.2 3.00 1
2 101.1 3.21 2
3 100.7 3.37 3
4 100.1 3.51 4
5 99.9 3.75 5
6 99.7 4.11 6
7 99.5 4.25 7
8 99.2 4.25 8
9 99.0 4.50 9
10 99.0 4.70 10
11 99.3 4.75 11
12 99.5 4.75 12
13 99.7 4.75 13
14 100.0 4.75 14
15 100.4 4.75 15
16 100.6 4.75 16
17 100.7 4.58 17
18 100.7 4.50 18
19 100.6 4.50 19
20 100.5 4.49 20
21 100.6 4.03 21
22 100.5 3.75 22
23 100.4 3.39 23
24 100.3 3.25 24
25 100.4 3.25 25
26 100.4 3.25 26
27 100.4 3.25 27
28 100.4 3.25 28
29 100.4 3.25 29
30 100.5 3.25 30
31 100.6 3.25 31
32 100.6 3.25 32
33 100.5 3.25 33
34 100.5 3.25 34
35 100.7 3.25 35
36 101.1 2.85 36
37 101.5 2.75 37
38 101.9 2.75 38
39 102.1 2.55 39
40 102.1 2.50 40
41 102.1 2.50 41
42 102.4 2.10 42
43 102.8 2.00 43
44 103.1 2.00 44
45 103.1 2.00 45
46 102.9 2.00 46
47 102.4 2.00 47
48 101.9 2.00 48
49 101.3 2.00 49
50 100.7 2.00 50
51 100.6 2.00 51
52 101.0 2.00 52
53 101.5 2.00 53
54 101.9 2.00 54
55 102.1 2.00 55
56 102.3 2.00 56
57 102.5 2.00 57
58 102.9 2.00 58
59 103.6 2.00 59
60 104.3 2.00 60
> k <- length(x[1,])
> df <- as.data.frame(x)
> (mylm <- lm(df))
Call:
lm(formula = df)
Coefficients:
(Intercept) Rente t
102.22643 -0.60179 0.02354
> (mysum <- summary(mylm))
Call:
lm(formula = df)
Residuals:
Min 1Q Median 3Q Max
-1.6236 -0.4784 -0.1294 0.4936 1.8645
Coefficients:
Estimate Std. Error t value Pr(>|t|)
(Intercept) 102.226427 0.828026 123.458 < 2e-16 ***
Rente -0.601786 0.173837 -3.462 0.00102 **
t 0.023545 0.009938 2.369 0.02124 *
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
Residual standard error: 0.689 on 57 degrees of freedom
Multiple R-squared: 0.6751, Adjusted R-squared: 0.6637
F-statistic: 59.22 on 2 and 57 DF, p-value: 1.216e-14
> 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,] 8.082504e-03 0.0161650077 0.991917496
[2,] 2.267216e-03 0.0045344327 0.997732784
[3,] 1.315694e-03 0.0026313877 0.998684306
[4,] 4.346518e-04 0.0008693035 0.999565348
[5,] 6.102924e-04 0.0012205847 0.999389708
[6,] 3.965728e-03 0.0079314563 0.996034272
[7,] 3.087458e-03 0.0061749160 0.996912542
[8,] 1.246677e-03 0.0024933537 0.998753323
[9,] 4.510435e-04 0.0009020871 0.999548956
[10,] 1.722732e-04 0.0003445465 0.999827727
[11,] 5.945918e-05 0.0001189184 0.999940541
[12,] 1.122622e-04 0.0002245244 0.999887738
[13,] 3.225030e-04 0.0006450060 0.999677497
[14,] 6.958128e-04 0.0013916257 0.999304187
[15,] 1.498937e-03 0.0029978731 0.998501063
[16,] 1.080225e-02 0.0216044963 0.989197752
[17,] 3.295226e-02 0.0659045199 0.967047740
[18,] 6.187255e-02 0.1237451091 0.938127445
[19,] 7.484718e-02 0.1496943530 0.925152823
[20,] 6.282097e-02 0.1256419326 0.937179034
[21,] 4.809018e-02 0.0961803681 0.951909816
[22,] 3.474499e-02 0.0694899805 0.965255010
[23,] 2.405191e-02 0.0481038231 0.975948088
[24,] 1.609853e-02 0.0321970624 0.983901469
[25,] 9.963049e-03 0.0199260974 0.990036951
[26,] 5.824796e-03 0.0116495921 0.994175204
[27,] 3.315835e-03 0.0066316698 0.996684165
[28,] 1.947306e-03 0.0038946113 0.998052694
[29,] 1.180640e-03 0.0023612809 0.998819360
[30,] 7.109704e-04 0.0014219409 0.999289030
[31,] 4.693414e-04 0.0009386828 0.999530659
[32,] 3.695090e-04 0.0007390179 0.999630491
[33,] 4.232391e-04 0.0008464781 0.999576761
[34,] 4.321529e-04 0.0008643058 0.999567847
[35,] 3.403626e-04 0.0006807252 0.999659637
[36,] 2.495634e-04 0.0004991268 0.999750437
[37,] 1.604999e-04 0.0003209998 0.999839500
[38,] 2.199695e-04 0.0004399390 0.999780030
[39,] 7.964569e-04 0.0015929139 0.999203543
[40,] 4.755242e-03 0.0095104838 0.995244758
[41,] 4.012573e-02 0.0802514513 0.959874274
[42,] 2.408743e-01 0.4817486745 0.759125663
[43,] 7.707595e-01 0.4584810818 0.229240541
[44,] 9.858237e-01 0.0283525636 0.014176282
[45,] 9.910857e-01 0.0178286337 0.008914317
[46,] 9.834951e-01 0.0330098617 0.016504931
[47,] 9.621266e-01 0.0757468285 0.037873414
[48,] 9.218431e-01 0.1563137305 0.078156865
[49,] 8.910413e-01 0.2179174518 0.108958726
> postscript(file="/var/www/html/rcomp/tmp/1eft91258663264.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$resid)
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/2o9t71258663264.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> plot(mysum$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/3i2gw1258663264.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> hist(mysum$resid, main='Residual Histogram', xlab='values of Residuals')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/4g2x71258663264.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> densityplot(~mysum$resid,col='black',main='Residual Density Plot', xlab='values of Residuals')
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/59d901258663264.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 = 60
Frequency = 1
1 2 3 4 5 6
0.75538515 0.75821559 0.43095674 -0.10833783 -0.18745383 -0.19435554
7 8 9 10 11 12
-0.33365010 -0.65719467 -0.73029280 -0.63348023 -0.32693551 -0.15048007
13 14 15 16 17 18
0.02597537 0.30243080 0.67888624 0.85534168 0.82949355 0.75780613
19 20 21 22 23 24
0.63426156 0.50469914 0.30433316 0.01228860 -0.32789882 -0.53569338
25 26 27 28 29 30
-0.45923794 -0.48278250 -0.50632707 -0.52987163 -0.55341619 -0.47696076
31 32 33 34 35 36
-0.40050532 -0.42404988 -0.54759445 -0.57113901 -0.39468357 -0.25894241
37 38 39 40 41 42
0.05733445 0.43378989 0.48988819 0.43625434 0.41270977 0.44845093
43 44 45 46 47 48
0.76472780 1.04118324 1.01763867 0.79409411 0.27054955 -0.25299502
49 50 51 52 53 54
-0.87653958 -1.50008414 -1.62362871 -1.24717327 -0.77071783 -0.39426240
55 56 57 58 59 60
-0.21780696 -0.04135152 0.13510391 0.51155935 1.18801479 1.86447022
> postscript(file="/var/www/html/rcomp/tmp/6bxys1258663264.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 = 60
Frequency = 1
lag(myerror, k = 1) myerror
0 0.75538515 NA
1 0.75821559 0.75538515
2 0.43095674 0.75821559
3 -0.10833783 0.43095674
4 -0.18745383 -0.10833783
5 -0.19435554 -0.18745383
6 -0.33365010 -0.19435554
7 -0.65719467 -0.33365010
8 -0.73029280 -0.65719467
9 -0.63348023 -0.73029280
10 -0.32693551 -0.63348023
11 -0.15048007 -0.32693551
12 0.02597537 -0.15048007
13 0.30243080 0.02597537
14 0.67888624 0.30243080
15 0.85534168 0.67888624
16 0.82949355 0.85534168
17 0.75780613 0.82949355
18 0.63426156 0.75780613
19 0.50469914 0.63426156
20 0.30433316 0.50469914
21 0.01228860 0.30433316
22 -0.32789882 0.01228860
23 -0.53569338 -0.32789882
24 -0.45923794 -0.53569338
25 -0.48278250 -0.45923794
26 -0.50632707 -0.48278250
27 -0.52987163 -0.50632707
28 -0.55341619 -0.52987163
29 -0.47696076 -0.55341619
30 -0.40050532 -0.47696076
31 -0.42404988 -0.40050532
32 -0.54759445 -0.42404988
33 -0.57113901 -0.54759445
34 -0.39468357 -0.57113901
35 -0.25894241 -0.39468357
36 0.05733445 -0.25894241
37 0.43378989 0.05733445
38 0.48988819 0.43378989
39 0.43625434 0.48988819
40 0.41270977 0.43625434
41 0.44845093 0.41270977
42 0.76472780 0.44845093
43 1.04118324 0.76472780
44 1.01763867 1.04118324
45 0.79409411 1.01763867
46 0.27054955 0.79409411
47 -0.25299502 0.27054955
48 -0.87653958 -0.25299502
49 -1.50008414 -0.87653958
50 -1.62362871 -1.50008414
51 -1.24717327 -1.62362871
52 -0.77071783 -1.24717327
53 -0.39426240 -0.77071783
54 -0.21780696 -0.39426240
55 -0.04135152 -0.21780696
56 0.13510391 -0.04135152
57 0.51155935 0.13510391
58 1.18801479 0.51155935
59 1.86447022 1.18801479
60 NA 1.86447022
> dum1 <- dum[2:length(myerror),]
> dum1
lag(myerror, k = 1) myerror
[1,] 0.75821559 0.75538515
[2,] 0.43095674 0.75821559
[3,] -0.10833783 0.43095674
[4,] -0.18745383 -0.10833783
[5,] -0.19435554 -0.18745383
[6,] -0.33365010 -0.19435554
[7,] -0.65719467 -0.33365010
[8,] -0.73029280 -0.65719467
[9,] -0.63348023 -0.73029280
[10,] -0.32693551 -0.63348023
[11,] -0.15048007 -0.32693551
[12,] 0.02597537 -0.15048007
[13,] 0.30243080 0.02597537
[14,] 0.67888624 0.30243080
[15,] 0.85534168 0.67888624
[16,] 0.82949355 0.85534168
[17,] 0.75780613 0.82949355
[18,] 0.63426156 0.75780613
[19,] 0.50469914 0.63426156
[20,] 0.30433316 0.50469914
[21,] 0.01228860 0.30433316
[22,] -0.32789882 0.01228860
[23,] -0.53569338 -0.32789882
[24,] -0.45923794 -0.53569338
[25,] -0.48278250 -0.45923794
[26,] -0.50632707 -0.48278250
[27,] -0.52987163 -0.50632707
[28,] -0.55341619 -0.52987163
[29,] -0.47696076 -0.55341619
[30,] -0.40050532 -0.47696076
[31,] -0.42404988 -0.40050532
[32,] -0.54759445 -0.42404988
[33,] -0.57113901 -0.54759445
[34,] -0.39468357 -0.57113901
[35,] -0.25894241 -0.39468357
[36,] 0.05733445 -0.25894241
[37,] 0.43378989 0.05733445
[38,] 0.48988819 0.43378989
[39,] 0.43625434 0.48988819
[40,] 0.41270977 0.43625434
[41,] 0.44845093 0.41270977
[42,] 0.76472780 0.44845093
[43,] 1.04118324 0.76472780
[44,] 1.01763867 1.04118324
[45,] 0.79409411 1.01763867
[46,] 0.27054955 0.79409411
[47,] -0.25299502 0.27054955
[48,] -0.87653958 -0.25299502
[49,] -1.50008414 -0.87653958
[50,] -1.62362871 -1.50008414
[51,] -1.24717327 -1.62362871
[52,] -0.77071783 -1.24717327
[53,] -0.39426240 -0.77071783
[54,] -0.21780696 -0.39426240
[55,] -0.04135152 -0.21780696
[56,] 0.13510391 -0.04135152
[57,] 0.51155935 0.13510391
[58,] 1.18801479 0.51155935
[59,] 1.86447022 1.18801479
> z <- as.data.frame(dum1)
> z
lag(myerror, k = 1) myerror
1 0.75821559 0.75538515
2 0.43095674 0.75821559
3 -0.10833783 0.43095674
4 -0.18745383 -0.10833783
5 -0.19435554 -0.18745383
6 -0.33365010 -0.19435554
7 -0.65719467 -0.33365010
8 -0.73029280 -0.65719467
9 -0.63348023 -0.73029280
10 -0.32693551 -0.63348023
11 -0.15048007 -0.32693551
12 0.02597537 -0.15048007
13 0.30243080 0.02597537
14 0.67888624 0.30243080
15 0.85534168 0.67888624
16 0.82949355 0.85534168
17 0.75780613 0.82949355
18 0.63426156 0.75780613
19 0.50469914 0.63426156
20 0.30433316 0.50469914
21 0.01228860 0.30433316
22 -0.32789882 0.01228860
23 -0.53569338 -0.32789882
24 -0.45923794 -0.53569338
25 -0.48278250 -0.45923794
26 -0.50632707 -0.48278250
27 -0.52987163 -0.50632707
28 -0.55341619 -0.52987163
29 -0.47696076 -0.55341619
30 -0.40050532 -0.47696076
31 -0.42404988 -0.40050532
32 -0.54759445 -0.42404988
33 -0.57113901 -0.54759445
34 -0.39468357 -0.57113901
35 -0.25894241 -0.39468357
36 0.05733445 -0.25894241
37 0.43378989 0.05733445
38 0.48988819 0.43378989
39 0.43625434 0.48988819
40 0.41270977 0.43625434
41 0.44845093 0.41270977
42 0.76472780 0.44845093
43 1.04118324 0.76472780
44 1.01763867 1.04118324
45 0.79409411 1.01763867
46 0.27054955 0.79409411
47 -0.25299502 0.27054955
48 -0.87653958 -0.25299502
49 -1.50008414 -0.87653958
50 -1.62362871 -1.50008414
51 -1.24717327 -1.62362871
52 -0.77071783 -1.24717327
53 -0.39426240 -0.77071783
54 -0.21780696 -0.39426240
55 -0.04135152 -0.21780696
56 0.13510391 -0.04135152
57 0.51155935 0.13510391
58 1.18801479 0.51155935
59 1.86447022 1.18801479
> 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/7eq7a1258663264.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> acf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/8t9pl1258663264.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> pacf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Partial Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/9rkxw1258663264.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> opar <- par(mfrow = c(2,2), oma = c(0, 0, 1.1, 0))
> plot(mylm, las = 1, sub='Residual Diagnostics')
> par(opar)
> dev.off()
null device
1
> if (n > n25) {
+ postscript(file="/var/www/html/rcomp/tmp/10gpql1258663264.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
+ plot(kp3:nmkm3,gqarr[,2], main='Goldfeld-Quandt test',ylab='2-sided p-value',xlab='breakpoint')
+ grid()
+ dev.off()
+ }
null device
1
>
> #Note: the /var/www/html/rcomp/createtable file can be downloaded at http://www.wessa.net/cretab
> load(file="/var/www/html/rcomp/createtable")
>
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a, 'Multiple Linear Regression - Estimated Regression Equation', 1, TRUE)
> a<-table.row.end(a)
> myeq <- colnames(x)[1]
> myeq <- paste(myeq, '[t] = ', sep='')
> for (i in 1:k){
+ if (mysum$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/11k96h1258663264.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/126vey1258663264.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/13zyyf1258663265.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/14qcoe1258663265.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/15nsbb1258663265.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/16n6ei1258663265.tab")
+ }
> system("convert tmp/1eft91258663264.ps tmp/1eft91258663264.png")
> system("convert tmp/2o9t71258663264.ps tmp/2o9t71258663264.png")
> system("convert tmp/3i2gw1258663264.ps tmp/3i2gw1258663264.png")
> system("convert tmp/4g2x71258663264.ps tmp/4g2x71258663264.png")
> system("convert tmp/59d901258663264.ps tmp/59d901258663264.png")
> system("convert tmp/6bxys1258663264.ps tmp/6bxys1258663264.png")
> system("convert tmp/7eq7a1258663264.ps tmp/7eq7a1258663264.png")
> system("convert tmp/8t9pl1258663264.ps tmp/8t9pl1258663264.png")
> system("convert tmp/9rkxw1258663264.ps tmp/9rkxw1258663264.png")
> system("convert tmp/10gpql1258663264.ps tmp/10gpql1258663264.png")
>
>
> proc.time()
user system elapsed
2.467 1.552 2.873