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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> x <- array(list(2.09,0,2.11,2.05,0,2.09,2.08,0,2.05,2.06,0,2.08,2.06,0,2.06,2.08,0,2.06,2.07,0,2.08,2.06,0,2.07,2.07,0,2.06,2.06,0,2.07,2.09,0,2.06,2.07,0,2.09,2.09,0,2.07,2.28,0,2.09,2.33,0,2.28,2.35,0,2.33,2.52,0,2.35,2.63,0,2.52,2.58,0,2.63,2.70,0,2.58,2.81,0,2.70,2.97,0,2.81,3.04,0,2.97,3.28,0,3.04,3.33,0,3.28,3.50,0,3.33,3.56,0,3.50,3.57,0,3.56,3.69,0,3.57,3.82,0,3.69,3.79,0,3.82,3.96,0,3.79,4.06,0,3.96,4.05,0,4.06,4.03,0,4.05,3.94,0,4.03,4.02,0,3.94,3.88,0,4.02,4.02,0,3.88,4.03,0,4.02,4.09,0,4.03,3.99,0,4.09,4.01,0,3.99,4.01,0,4.01,4.19,0,4.01,4.30,0,4.19,4.27,0,4.30,3.82,0,4.27,3.15,1,3.82,2.49,1,3.15,1.81,1,2.49,1.26,1,1.81,1.06,1,1.26,0.84,1,1.06,0.78,1,0.84,0.70,1,0.78,0.36,1,0.70,0.35,1,0.36,0.36,1,0.35),dim=c(3,59),dimnames=list(c('Y','X','Y1'),1:59))
> y <- array(NA,dim=c(3,59),dimnames=list(c('Y','X','Y1'),1:59))
> 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 = '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
Y X Y1 t
1 2.09 0 2.11 1
2 2.05 0 2.09 2
3 2.08 0 2.05 3
4 2.06 0 2.08 4
5 2.06 0 2.06 5
6 2.08 0 2.06 6
7 2.07 0 2.08 7
8 2.06 0 2.07 8
9 2.07 0 2.06 9
10 2.06 0 2.07 10
11 2.09 0 2.06 11
12 2.07 0 2.09 12
13 2.09 0 2.07 13
14 2.28 0 2.09 14
15 2.33 0 2.28 15
16 2.35 0 2.33 16
17 2.52 0 2.35 17
18 2.63 0 2.52 18
19 2.58 0 2.63 19
20 2.70 0 2.58 20
21 2.81 0 2.70 21
22 2.97 0 2.81 22
23 3.04 0 2.97 23
24 3.28 0 3.04 24
25 3.33 0 3.28 25
26 3.50 0 3.33 26
27 3.56 0 3.50 27
28 3.57 0 3.56 28
29 3.69 0 3.57 29
30 3.82 0 3.69 30
31 3.79 0 3.82 31
32 3.96 0 3.79 32
33 4.06 0 3.96 33
34 4.05 0 4.06 34
35 4.03 0 4.05 35
36 3.94 0 4.03 36
37 4.02 0 3.94 37
38 3.88 0 4.02 38
39 4.02 0 3.88 39
40 4.03 0 4.02 40
41 4.09 0 4.03 41
42 3.99 0 4.09 42
43 4.01 0 3.99 43
44 4.01 0 4.01 44
45 4.19 0 4.01 45
46 4.30 0 4.19 46
47 4.27 0 4.30 47
48 3.82 0 4.27 48
49 3.15 1 3.82 49
50 2.49 1 3.15 50
51 1.81 1 2.49 51
52 1.26 1 1.81 52
53 1.06 1 1.26 53
54 0.84 1 1.06 54
55 0.78 1 0.84 55
56 0.70 1 0.78 56
57 0.36 1 0.70 57
58 0.35 1 0.36 58
59 0.36 1 0.35 59
> k <- length(x[1,])
> df <- as.data.frame(x)
> (mylm <- lm(df))
Call:
lm(formula = df)
Coefficients:
(Intercept) X Y1 t
0.33565 -0.89864 0.82882 0.00939
> (mysum <- summary(mylm))
Call:
lm(formula = df)
Residuals:
Min 1Q Median 3Q Max
-0.50545 -0.05996 0.01710 0.07793 0.19937
Coefficients:
Estimate Std. Error t value Pr(>|t|)
(Intercept) 0.335653 0.056319 5.960 1.87e-07 ***
X -0.898645 0.096710 -9.292 7.23e-13 ***
Y1 0.828817 0.025505 32.496 < 2e-16 ***
t 0.009391 0.001831 5.129 3.91e-06 ***
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
Residual standard error: 0.1157 on 55 degrees of freedom
Multiple R-squared: 0.9903, Adjusted R-squared: 0.9898
F-statistic: 1873 on 3 and 55 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,] 5.783861e-03 1.156772e-02 0.9942161
[2,] 7.988417e-04 1.597683e-03 0.9992012
[3,] 1.029792e-04 2.059584e-04 0.9998970
[4,] 1.232422e-05 2.464845e-05 0.9999877
[5,] 4.556036e-06 9.112073e-06 0.9999954
[6,] 6.202088e-07 1.240418e-06 0.9999994
[7,] 1.500531e-07 3.001061e-07 0.9999998
[8,] 3.580205e-03 7.160410e-03 0.9964198
[9,] 1.582664e-03 3.165327e-03 0.9984173
[10,] 8.318060e-04 1.663612e-03 0.9991682
[11,] 1.509113e-03 3.018226e-03 0.9984909
[12,] 6.483236e-04 1.296647e-03 0.9993517
[13,] 3.226195e-03 6.452391e-03 0.9967738
[14,] 2.355098e-03 4.710196e-03 0.9976449
[15,] 1.460064e-03 2.920127e-03 0.9985399
[16,] 1.080152e-03 2.160304e-03 0.9989198
[17,] 7.316868e-04 1.463374e-03 0.9992683
[18,] 1.264194e-03 2.528388e-03 0.9987358
[19,] 1.305645e-03 2.611290e-03 0.9986944
[20,] 7.187814e-04 1.437563e-03 0.9992812
[21,] 5.385171e-04 1.077034e-03 0.9994615
[22,] 7.192771e-04 1.438554e-03 0.9992807
[23,] 3.478259e-04 6.956517e-04 0.9996522
[24,] 1.652049e-04 3.304098e-04 0.9998348
[25,] 3.597856e-04 7.195712e-04 0.9996402
[26,] 2.575371e-04 5.150742e-04 0.9997425
[27,] 1.300761e-04 2.601521e-04 0.9998699
[28,] 1.300187e-04 2.600374e-04 0.9998700
[29,] 1.347010e-04 2.694020e-04 0.9998653
[30,] 4.833018e-04 9.666036e-04 0.9995167
[31,] 2.368805e-04 4.737611e-04 0.9997631
[32,] 2.249980e-03 4.499960e-03 0.9977500
[33,] 1.261292e-03 2.522584e-03 0.9987387
[34,] 8.296448e-04 1.659290e-03 0.9991704
[35,] 4.166778e-04 8.333556e-04 0.9995833
[36,] 9.597269e-04 1.919454e-03 0.9990403
[37,] 5.722147e-04 1.144429e-03 0.9994278
[38,] 3.809718e-04 7.619435e-04 0.9996190
[39,] 4.143920e-04 8.287839e-04 0.9995856
[40,] 1.497244e-03 2.994489e-03 0.9985028
[41,] 2.708363e-02 5.416727e-02 0.9729164
[42,] 1.707000e-01 3.414001e-01 0.8293000
[43,] 2.255601e-01 4.511202e-01 0.7744399
[44,] 3.729708e-01 7.459416e-01 0.6270292
[45,] 4.289710e-01 8.579420e-01 0.5710290
[46,] 3.147052e-01 6.294104e-01 0.6852948
> postscript(file="/var/www/html/rcomp/tmp/1utvz1258724329.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$resid)
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/24hoa1258724329.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> plot(mysum$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/3j1bp1258724329.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> hist(mysum$resid, main='Residual Histogram', xlab='values of Residuals')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/4336d1258724329.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> densityplot(~mysum$resid,col='black',main='Residual Density Plot', xlab='values of Residuals')
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/5h2nh1258724329.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 = 59
Frequency = 1
1 2 3 4 5 6
-0.003848319 -0.036662486 0.017099693 -0.037155335 -0.029969502 -0.019360013
7 8 9 10 11 12
-0.055326868 -0.066429207 -0.057531546 -0.085210229 -0.056312568 -0.110567596
13 14 15 16 17 18
-0.083381762 0.080651382 -0.036214404 -0.067045776 0.076987368 0.036697927
19 20 21 22 23 24
-0.113862480 0.038187871 0.039339292 0.098778885 0.026777616 0.199369899
25 26 27 28 29 30
0.041063251 0.160231879 0.069942438 0.020822893 0.123144209 0.144295630
31 32 33 34 35 36
-0.002841121 0.182632885 0.132343444 0.030071209 0.008968871 -0.073845296
37 38 39 40 41 42
0.071357744 -0.144338146 0.102305756 -0.013119168 0.029202149 -0.129917396
43 44 45 46 47 48
-0.036426184 -0.062393039 0.108216450 0.059638836 -0.070921570 -0.505447564
49 50 51 52 53 54
0.086774577 -0.027308387 -0.169679523 -0.165474314 0.080984654 0.017357589
55 56 57 58 59
0.130306870 0.090645393 -0.192439739 0.069967610 0.078865271
> postscript(file="/var/www/html/rcomp/tmp/6v48o1258724329.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 = 59
Frequency = 1
lag(myerror, k = 1) myerror
0 -0.003848319 NA
1 -0.036662486 -0.003848319
2 0.017099693 -0.036662486
3 -0.037155335 0.017099693
4 -0.029969502 -0.037155335
5 -0.019360013 -0.029969502
6 -0.055326868 -0.019360013
7 -0.066429207 -0.055326868
8 -0.057531546 -0.066429207
9 -0.085210229 -0.057531546
10 -0.056312568 -0.085210229
11 -0.110567596 -0.056312568
12 -0.083381762 -0.110567596
13 0.080651382 -0.083381762
14 -0.036214404 0.080651382
15 -0.067045776 -0.036214404
16 0.076987368 -0.067045776
17 0.036697927 0.076987368
18 -0.113862480 0.036697927
19 0.038187871 -0.113862480
20 0.039339292 0.038187871
21 0.098778885 0.039339292
22 0.026777616 0.098778885
23 0.199369899 0.026777616
24 0.041063251 0.199369899
25 0.160231879 0.041063251
26 0.069942438 0.160231879
27 0.020822893 0.069942438
28 0.123144209 0.020822893
29 0.144295630 0.123144209
30 -0.002841121 0.144295630
31 0.182632885 -0.002841121
32 0.132343444 0.182632885
33 0.030071209 0.132343444
34 0.008968871 0.030071209
35 -0.073845296 0.008968871
36 0.071357744 -0.073845296
37 -0.144338146 0.071357744
38 0.102305756 -0.144338146
39 -0.013119168 0.102305756
40 0.029202149 -0.013119168
41 -0.129917396 0.029202149
42 -0.036426184 -0.129917396
43 -0.062393039 -0.036426184
44 0.108216450 -0.062393039
45 0.059638836 0.108216450
46 -0.070921570 0.059638836
47 -0.505447564 -0.070921570
48 0.086774577 -0.505447564
49 -0.027308387 0.086774577
50 -0.169679523 -0.027308387
51 -0.165474314 -0.169679523
52 0.080984654 -0.165474314
53 0.017357589 0.080984654
54 0.130306870 0.017357589
55 0.090645393 0.130306870
56 -0.192439739 0.090645393
57 0.069967610 -0.192439739
58 0.078865271 0.069967610
59 NA 0.078865271
> dum1 <- dum[2:length(myerror),]
> dum1
lag(myerror, k = 1) myerror
[1,] -0.036662486 -0.003848319
[2,] 0.017099693 -0.036662486
[3,] -0.037155335 0.017099693
[4,] -0.029969502 -0.037155335
[5,] -0.019360013 -0.029969502
[6,] -0.055326868 -0.019360013
[7,] -0.066429207 -0.055326868
[8,] -0.057531546 -0.066429207
[9,] -0.085210229 -0.057531546
[10,] -0.056312568 -0.085210229
[11,] -0.110567596 -0.056312568
[12,] -0.083381762 -0.110567596
[13,] 0.080651382 -0.083381762
[14,] -0.036214404 0.080651382
[15,] -0.067045776 -0.036214404
[16,] 0.076987368 -0.067045776
[17,] 0.036697927 0.076987368
[18,] -0.113862480 0.036697927
[19,] 0.038187871 -0.113862480
[20,] 0.039339292 0.038187871
[21,] 0.098778885 0.039339292
[22,] 0.026777616 0.098778885
[23,] 0.199369899 0.026777616
[24,] 0.041063251 0.199369899
[25,] 0.160231879 0.041063251
[26,] 0.069942438 0.160231879
[27,] 0.020822893 0.069942438
[28,] 0.123144209 0.020822893
[29,] 0.144295630 0.123144209
[30,] -0.002841121 0.144295630
[31,] 0.182632885 -0.002841121
[32,] 0.132343444 0.182632885
[33,] 0.030071209 0.132343444
[34,] 0.008968871 0.030071209
[35,] -0.073845296 0.008968871
[36,] 0.071357744 -0.073845296
[37,] -0.144338146 0.071357744
[38,] 0.102305756 -0.144338146
[39,] -0.013119168 0.102305756
[40,] 0.029202149 -0.013119168
[41,] -0.129917396 0.029202149
[42,] -0.036426184 -0.129917396
[43,] -0.062393039 -0.036426184
[44,] 0.108216450 -0.062393039
[45,] 0.059638836 0.108216450
[46,] -0.070921570 0.059638836
[47,] -0.505447564 -0.070921570
[48,] 0.086774577 -0.505447564
[49,] -0.027308387 0.086774577
[50,] -0.169679523 -0.027308387
[51,] -0.165474314 -0.169679523
[52,] 0.080984654 -0.165474314
[53,] 0.017357589 0.080984654
[54,] 0.130306870 0.017357589
[55,] 0.090645393 0.130306870
[56,] -0.192439739 0.090645393
[57,] 0.069967610 -0.192439739
[58,] 0.078865271 0.069967610
> z <- as.data.frame(dum1)
> z
lag(myerror, k = 1) myerror
1 -0.036662486 -0.003848319
2 0.017099693 -0.036662486
3 -0.037155335 0.017099693
4 -0.029969502 -0.037155335
5 -0.019360013 -0.029969502
6 -0.055326868 -0.019360013
7 -0.066429207 -0.055326868
8 -0.057531546 -0.066429207
9 -0.085210229 -0.057531546
10 -0.056312568 -0.085210229
11 -0.110567596 -0.056312568
12 -0.083381762 -0.110567596
13 0.080651382 -0.083381762
14 -0.036214404 0.080651382
15 -0.067045776 -0.036214404
16 0.076987368 -0.067045776
17 0.036697927 0.076987368
18 -0.113862480 0.036697927
19 0.038187871 -0.113862480
20 0.039339292 0.038187871
21 0.098778885 0.039339292
22 0.026777616 0.098778885
23 0.199369899 0.026777616
24 0.041063251 0.199369899
25 0.160231879 0.041063251
26 0.069942438 0.160231879
27 0.020822893 0.069942438
28 0.123144209 0.020822893
29 0.144295630 0.123144209
30 -0.002841121 0.144295630
31 0.182632885 -0.002841121
32 0.132343444 0.182632885
33 0.030071209 0.132343444
34 0.008968871 0.030071209
35 -0.073845296 0.008968871
36 0.071357744 -0.073845296
37 -0.144338146 0.071357744
38 0.102305756 -0.144338146
39 -0.013119168 0.102305756
40 0.029202149 -0.013119168
41 -0.129917396 0.029202149
42 -0.036426184 -0.129917396
43 -0.062393039 -0.036426184
44 0.108216450 -0.062393039
45 0.059638836 0.108216450
46 -0.070921570 0.059638836
47 -0.505447564 -0.070921570
48 0.086774577 -0.505447564
49 -0.027308387 0.086774577
50 -0.169679523 -0.027308387
51 -0.165474314 -0.169679523
52 0.080984654 -0.165474314
53 0.017357589 0.080984654
54 0.130306870 0.017357589
55 0.090645393 0.130306870
56 -0.192439739 0.090645393
57 0.069967610 -0.192439739
58 0.078865271 0.069967610
> 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/7raup1258724329.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> acf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/8iyyp1258724329.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> pacf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Partial Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/964xr1258724329.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> opar <- par(mfrow = c(2,2), oma = c(0, 0, 1.1, 0))
> plot(mylm, las = 1, sub='Residual Diagnostics')
> par(opar)
> dev.off()
null device
1
> if (n > n25) {
+ postscript(file="/var/www/html/rcomp/tmp/101m9v1258724329.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
+ plot(kp3:nmkm3,gqarr[,2], main='Goldfeld-Quandt test',ylab='2-sided p-value',xlab='breakpoint')
+ grid()
+ dev.off()
+ }
null device
1
>
> #Note: the /var/www/html/rcomp/createtable file can be downloaded at http://www.wessa.net/cretab
> load(file="/var/www/html/rcomp/createtable")
>
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a, 'Multiple Linear Regression - Estimated Regression Equation', 1, TRUE)
> a<-table.row.end(a)
> myeq <- colnames(x)[1]
> myeq <- paste(myeq, '[t] = ', sep='')
> for (i in 1:k){
+ if (mysum$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/11my1m1258724329.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/12impf1258724329.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/13o4ld1258724329.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/142ta11258724329.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/15xkt81258724329.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/16mx911258724329.tab")
+ }
>
> system("convert tmp/1utvz1258724329.ps tmp/1utvz1258724329.png")
> system("convert tmp/24hoa1258724329.ps tmp/24hoa1258724329.png")
> system("convert tmp/3j1bp1258724329.ps tmp/3j1bp1258724329.png")
> system("convert tmp/4336d1258724329.ps tmp/4336d1258724329.png")
> system("convert tmp/5h2nh1258724329.ps tmp/5h2nh1258724329.png")
> system("convert tmp/6v48o1258724329.ps tmp/6v48o1258724329.png")
> system("convert tmp/7raup1258724329.ps tmp/7raup1258724329.png")
> system("convert tmp/8iyyp1258724329.ps tmp/8iyyp1258724329.png")
> system("convert tmp/964xr1258724329.ps tmp/964xr1258724329.png")
> system("convert tmp/101m9v1258724329.ps tmp/101m9v1258724329.png")
>
>
> proc.time()
user system elapsed
2.465 1.576 2.836