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(16198.9
+ ,16896.2
+ ,0
+ ,16554.2
+ ,16698
+ ,0
+ ,19554.2
+ ,19691.6
+ ,0
+ ,15903.8
+ ,15930.7
+ ,0
+ ,18003.8
+ ,17444.6
+ ,0
+ ,18329.6
+ ,17699.4
+ ,0
+ ,16260.7
+ ,15189.8
+ ,0
+ ,14851.9
+ ,15672.7
+ ,0
+ ,18174.1
+ ,17180.8
+ ,0
+ ,18406.6
+ ,17664.9
+ ,0
+ ,18466.5
+ ,17862.9
+ ,0
+ ,16016.5
+ ,16162.3
+ ,0
+ ,17428.5
+ ,17463.6
+ ,0
+ ,17167.2
+ ,16772.1
+ ,0
+ ,19630
+ ,19106.9
+ ,0
+ ,17183.6
+ ,16721.3
+ ,0
+ ,18344.7
+ ,18161.3
+ ,0
+ ,19301.4
+ ,18509.9
+ ,0
+ ,18147.5
+ ,17802.7
+ ,0
+ ,16192.9
+ ,16409.9
+ ,0
+ ,18374.4
+ ,17967.7
+ ,0
+ ,20515.2
+ ,20286.6
+ ,0
+ ,18957.2
+ ,19537.3
+ ,0
+ ,16471.5
+ ,18021.9
+ ,0
+ ,18746.8
+ ,20194.3
+ ,0
+ ,19009.5
+ ,19049.6
+ ,0
+ ,19211.2
+ ,20244.7
+ ,0
+ ,20547.7
+ ,21473.3
+ ,0
+ ,19325.8
+ ,19673.6
+ ,0
+ ,20605.5
+ ,21053.2
+ ,0
+ ,20056.9
+ ,20159.5
+ ,0
+ ,16141.4
+ ,18203.6
+ ,0
+ ,20359.8
+ ,21289.5
+ ,0
+ ,19711.6
+ ,20432.3
+ ,1
+ ,15638.6
+ ,17180.4
+ ,1
+ ,14384.5
+ ,15816.8
+ ,1
+ ,13855.6
+ ,15071.8
+ ,1
+ ,14308.3
+ ,14521.1
+ ,1
+ ,15290.6
+ ,15668.8
+ ,1
+ ,14423.8
+ ,14346.9
+ ,1
+ ,13779.7
+ ,13881
+ ,1
+ ,15686.3
+ ,15465.9
+ ,1
+ ,14733.8
+ ,14238.2
+ ,1
+ ,12522.5
+ ,13557.7
+ ,1
+ ,16189.4
+ ,16127.6
+ ,1
+ ,16059.1
+ ,16793.9
+ ,1
+ ,16007.1
+ ,16014
+ ,1
+ ,15806.8
+ ,16867.9
+ ,1
+ ,15160
+ ,16014.6
+ ,0
+ ,15692.1
+ ,15878.6
+ ,0
+ ,18908.9
+ ,18664.9
+ ,0
+ ,16969.9
+ ,17962.5
+ ,0
+ ,16997.5
+ ,17332.7
+ ,0
+ ,19858.9
+ ,19542.1
+ ,0
+ ,17681.2
+ ,17203.6
+ ,0)
+ ,dim=c(3
+ ,55)
+ ,dimnames=list(c('uitvoer'
+ ,'invoer'
+ ,'crisis')
+ ,1:55))
> y <- array(NA,dim=c(3,55),dimnames=list(c('uitvoer','invoer','crisis'),1:55))
> for (i in 1:dim(x)[1])
+ {
+ for (j in 1:dim(x)[2])
+ {
+ y[i,j] <- as.numeric(x[i,j])
+ }
+ }
> par20 = ''
> par19 = ''
> par18 = ''
> par17 = ''
> par16 = ''
> par15 = ''
> par14 = ''
> par13 = ''
> par12 = ''
> par11 = ''
> par10 = ''
> par9 = ''
> par8 = ''
> par7 = ''
> par6 = ''
> par5 = ''
> par4 = ''
> par3 = 'No Linear Trend'
> par2 = 'Do not include Seasonal Dummies'
> par1 = '1'
> ylab = ''
> xlab = ''
> main = ''
> #'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
uitvoer invoer crisis
1 16198.9 16896.2 0
2 16554.2 16698.0 0
3 19554.2 19691.6 0
4 15903.8 15930.7 0
5 18003.8 17444.6 0
6 18329.6 17699.4 0
7 16260.7 15189.8 0
8 14851.9 15672.7 0
9 18174.1 17180.8 0
10 18406.6 17664.9 0
11 18466.5 17862.9 0
12 16016.5 16162.3 0
13 17428.5 17463.6 0
14 17167.2 16772.1 0
15 19630.0 19106.9 0
16 17183.6 16721.3 0
17 18344.7 18161.3 0
18 19301.4 18509.9 0
19 18147.5 17802.7 0
20 16192.9 16409.9 0
21 18374.4 17967.7 0
22 20515.2 20286.6 0
23 18957.2 19537.3 0
24 16471.5 18021.9 0
25 18746.8 20194.3 0
26 19009.5 19049.6 0
27 19211.2 20244.7 0
28 20547.7 21473.3 0
29 19325.8 19673.6 0
30 20605.5 21053.2 0
31 20056.9 20159.5 0
32 16141.4 18203.6 0
33 20359.8 21289.5 0
34 19711.6 20432.3 1
35 15638.6 17180.4 1
36 14384.5 15816.8 1
37 13855.6 15071.8 1
38 14308.3 14521.1 1
39 15290.6 15668.8 1
40 14423.8 14346.9 1
41 13779.7 13881.0 1
42 15686.3 15465.9 1
43 14733.8 14238.2 1
44 12522.5 13557.7 1
45 16189.4 16127.6 1
46 16059.1 16793.9 1
47 16007.1 16014.0 1
48 15806.8 16867.9 1
49 15160.0 16014.6 0
50 15692.1 15878.6 0
51 18908.9 18664.9 0
52 16969.9 17962.5 0
53 16997.5 17332.7 0
54 19858.9 19542.1 0
55 17681.2 17203.6 0
> k <- length(x[1,])
> df <- as.data.frame(x)
> (mylm <- lm(df))
Call:
lm(formula = df)
Coefficients:
(Intercept) invoer crisis
2113.9401 0.8763 -673.8941
> (mysum <- summary(mylm))
Call:
lm(formula = df)
Residuals:
Min 1Q Median 3Q Max
-1924.7 -397.1 143.2 524.4 1004.3
Coefficients:
Estimate Std. Error t value Pr(>|t|)
(Intercept) 2113.94009 1023.76892 2.065 0.04394 *
invoer 0.87632 0.05619 15.596 < 2e-16 ***
crisis -673.89410 245.81904 -2.741 0.00837 **
---
Signif. codes: 0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1
Residual standard error: 680.3 on 52 degrees of freedom
Multiple R-squared: 0.8907, Adjusted R-squared: 0.8865
F-statistic: 211.8 on 2 and 52 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,] 0.5122358 0.9755284 0.4877642
[2,] 0.5875490 0.8249020 0.4124510
[3,] 0.7080543 0.5838915 0.2919457
[4,] 0.7550401 0.4899198 0.2449599
[5,] 0.7236508 0.5526985 0.2763492
[6,] 0.6637127 0.6725747 0.3362873
[7,] 0.5801873 0.8396254 0.4198127
[8,] 0.4885323 0.9770647 0.5114677
[9,] 0.4045077 0.8090155 0.5954923
[10,] 0.3498001 0.6996002 0.6501999
[11,] 0.2892480 0.5784959 0.7107520
[12,] 0.2253534 0.4507069 0.7746466
[13,] 0.2390494 0.4780988 0.7609506
[14,] 0.1950004 0.3900008 0.8049996
[15,] 0.1566870 0.3133740 0.8433130
[16,] 0.1331213 0.2662426 0.8668787
[17,] 0.1228754 0.2457507 0.8771246
[18,] 0.1527855 0.3055710 0.8472145
[19,] 0.4868681 0.9737362 0.5131319
[20,] 0.6574124 0.6851752 0.3425876
[21,] 0.5975250 0.8049501 0.4024750
[22,] 0.5880110 0.8239779 0.4119890
[23,] 0.5273742 0.9452516 0.4726258
[24,] 0.4483804 0.8967609 0.5516196
[25,] 0.3717842 0.7435684 0.6282158
[26,] 0.3235043 0.6470086 0.6764957
[27,] 0.7756534 0.4486932 0.2243466
[28,] 0.7313892 0.5372215 0.2686108
[29,] 0.6573292 0.6853417 0.3426708
[30,] 0.7412625 0.5174751 0.2587375
[31,] 0.8137855 0.3724289 0.1862145
[32,] 0.8510292 0.2979416 0.1489708
[33,] 0.8027251 0.3945498 0.1972749
[34,] 0.7416698 0.5166603 0.2583302
[35,] 0.6940552 0.6118896 0.3059448
[36,] 0.6167348 0.7665304 0.3832652
[37,] 0.5993080 0.8013841 0.4006920
[38,] 0.7572512 0.4854977 0.2427488
[39,] 0.6891314 0.6217372 0.3108686
[40,] 0.6788738 0.6422525 0.3211262
[41,] 0.5670590 0.8658821 0.4329410
[42,] 0.6375620 0.7248760 0.3624380
[43,] 0.4900987 0.9801974 0.5099013
[44,] 0.4170778 0.8341556 0.5829222
> postscript(file="/var/www/html/freestat/rcomp/tmp/1xl4k1290541912.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$resid)
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/freestat/rcomp/tmp/2xl4k1290541912.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> plot(mysum$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/38umn1290541912.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> hist(mysum$resid, main='Residual Histogram', xlab='values of Residuals')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/freestat/rcomp/tmp/48umn1290541912.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> densityplot(~mysum$resid,col='black',main='Residual Density Plot', xlab='values of Residuals')
> dev.off()
null device
1
> postscript(file="/var/www/html/freestat/rcomp/tmp/58umn1290541912.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 = 55
Frequency = 1
1 2 3 4 5 6
-721.46426 -192.47827 184.17972 -170.48037 602.86360 705.37808
7 8 9 10 11 12
835.68275 -996.29064 1004.33598 812.61101 699.00028 -260.73535
13 14 15 16 17 18
10.91358 355.58666 772.36216 416.50355 315.70734 966.92330
19 20 21 22 23 24
432.75455 -301.31139 515.06227 623.77121 -277.60460 -1435.33410
25 26 27 28 29 30
-1063.74475 202.07511 -643.51111 -383.65395 -28.44658 42.28674
31 32 33 34 35 36
276.85108 -1924.66086 -410.48692 366.38595 -856.91940 -916.07379
37 38 39 40 41 42
-792.11776 143.16991 119.72110 411.32430 175.50030 693.22578
43 44 45 46 47 48
816.57994 -798.38647 616.46695 -97.72295 533.71654 -414.87039
49 50 51 52 53 54
-987.80335 -336.52427 438.59419 -884.88088 -305.37655 619.88908
55
491.45595
> postscript(file="/var/www/html/freestat/rcomp/tmp/61llq1290541912.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 = 55
Frequency = 1
lag(myerror, k = 1) myerror
0 -721.46426 NA
1 -192.47827 -721.46426
2 184.17972 -192.47827
3 -170.48037 184.17972
4 602.86360 -170.48037
5 705.37808 602.86360
6 835.68275 705.37808
7 -996.29064 835.68275
8 1004.33598 -996.29064
9 812.61101 1004.33598
10 699.00028 812.61101
11 -260.73535 699.00028
12 10.91358 -260.73535
13 355.58666 10.91358
14 772.36216 355.58666
15 416.50355 772.36216
16 315.70734 416.50355
17 966.92330 315.70734
18 432.75455 966.92330
19 -301.31139 432.75455
20 515.06227 -301.31139
21 623.77121 515.06227
22 -277.60460 623.77121
23 -1435.33410 -277.60460
24 -1063.74475 -1435.33410
25 202.07511 -1063.74475
26 -643.51111 202.07511
27 -383.65395 -643.51111
28 -28.44658 -383.65395
29 42.28674 -28.44658
30 276.85108 42.28674
31 -1924.66086 276.85108
32 -410.48692 -1924.66086
33 366.38595 -410.48692
34 -856.91940 366.38595
35 -916.07379 -856.91940
36 -792.11776 -916.07379
37 143.16991 -792.11776
38 119.72110 143.16991
39 411.32430 119.72110
40 175.50030 411.32430
41 693.22578 175.50030
42 816.57994 693.22578
43 -798.38647 816.57994
44 616.46695 -798.38647
45 -97.72295 616.46695
46 533.71654 -97.72295
47 -414.87039 533.71654
48 -987.80335 -414.87039
49 -336.52427 -987.80335
50 438.59419 -336.52427
51 -884.88088 438.59419
52 -305.37655 -884.88088
53 619.88908 -305.37655
54 491.45595 619.88908
55 NA 491.45595
> dum1 <- dum[2:length(myerror),]
> dum1
lag(myerror, k = 1) myerror
[1,] -192.47827 -721.46426
[2,] 184.17972 -192.47827
[3,] -170.48037 184.17972
[4,] 602.86360 -170.48037
[5,] 705.37808 602.86360
[6,] 835.68275 705.37808
[7,] -996.29064 835.68275
[8,] 1004.33598 -996.29064
[9,] 812.61101 1004.33598
[10,] 699.00028 812.61101
[11,] -260.73535 699.00028
[12,] 10.91358 -260.73535
[13,] 355.58666 10.91358
[14,] 772.36216 355.58666
[15,] 416.50355 772.36216
[16,] 315.70734 416.50355
[17,] 966.92330 315.70734
[18,] 432.75455 966.92330
[19,] -301.31139 432.75455
[20,] 515.06227 -301.31139
[21,] 623.77121 515.06227
[22,] -277.60460 623.77121
[23,] -1435.33410 -277.60460
[24,] -1063.74475 -1435.33410
[25,] 202.07511 -1063.74475
[26,] -643.51111 202.07511
[27,] -383.65395 -643.51111
[28,] -28.44658 -383.65395
[29,] 42.28674 -28.44658
[30,] 276.85108 42.28674
[31,] -1924.66086 276.85108
[32,] -410.48692 -1924.66086
[33,] 366.38595 -410.48692
[34,] -856.91940 366.38595
[35,] -916.07379 -856.91940
[36,] -792.11776 -916.07379
[37,] 143.16991 -792.11776
[38,] 119.72110 143.16991
[39,] 411.32430 119.72110
[40,] 175.50030 411.32430
[41,] 693.22578 175.50030
[42,] 816.57994 693.22578
[43,] -798.38647 816.57994
[44,] 616.46695 -798.38647
[45,] -97.72295 616.46695
[46,] 533.71654 -97.72295
[47,] -414.87039 533.71654
[48,] -987.80335 -414.87039
[49,] -336.52427 -987.80335
[50,] 438.59419 -336.52427
[51,] -884.88088 438.59419
[52,] -305.37655 -884.88088
[53,] 619.88908 -305.37655
[54,] 491.45595 619.88908
> z <- as.data.frame(dum1)
> z
lag(myerror, k = 1) myerror
1 -192.47827 -721.46426
2 184.17972 -192.47827
3 -170.48037 184.17972
4 602.86360 -170.48037
5 705.37808 602.86360
6 835.68275 705.37808
7 -996.29064 835.68275
8 1004.33598 -996.29064
9 812.61101 1004.33598
10 699.00028 812.61101
11 -260.73535 699.00028
12 10.91358 -260.73535
13 355.58666 10.91358
14 772.36216 355.58666
15 416.50355 772.36216
16 315.70734 416.50355
17 966.92330 315.70734
18 432.75455 966.92330
19 -301.31139 432.75455
20 515.06227 -301.31139
21 623.77121 515.06227
22 -277.60460 623.77121
23 -1435.33410 -277.60460
24 -1063.74475 -1435.33410
25 202.07511 -1063.74475
26 -643.51111 202.07511
27 -383.65395 -643.51111
28 -28.44658 -383.65395
29 42.28674 -28.44658
30 276.85108 42.28674
31 -1924.66086 276.85108
32 -410.48692 -1924.66086
33 366.38595 -410.48692
34 -856.91940 366.38595
35 -916.07379 -856.91940
36 -792.11776 -916.07379
37 143.16991 -792.11776
38 119.72110 143.16991
39 411.32430 119.72110
40 175.50030 411.32430
41 693.22578 175.50030
42 816.57994 693.22578
43 -798.38647 816.57994
44 616.46695 -798.38647
45 -97.72295 616.46695
46 533.71654 -97.72295
47 -414.87039 533.71654
48 -987.80335 -414.87039
49 -336.52427 -987.80335
50 438.59419 -336.52427
51 -884.88088 438.59419
52 -305.37655 -884.88088
53 619.88908 -305.37655
54 491.45595 619.88908
> 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/71llq1290541912.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> acf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/freestat/rcomp/tmp/8tdks1290541912.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> pacf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Partial Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/freestat/rcomp/tmp/9tdks1290541912.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> opar <- par(mfrow = c(2,2), oma = c(0, 0, 1.1, 0))
> plot(mylm, las = 1, sub='Residual Diagnostics')
> par(opar)
> dev.off()
null device
1
> if (n > n25) {
+ postscript(file="/var/www/html/freestat/rcomp/tmp/10mm2d1290541912.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
+ plot(kp3:nmkm3,gqarr[,2], main='Goldfeld-Quandt test',ylab='2-sided p-value',xlab='breakpoint')
+ grid()
+ dev.off()
+ }
null device
1
>
> #Note: the /var/www/html/freestat/rcomp/createtable file can be downloaded at http://www.wessa.net/cretab
> load(file="/var/www/html/freestat/rcomp/createtable")
>
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a, 'Multiple Linear Regression - Estimated Regression Equation', 1, TRUE)
> a<-table.row.end(a)
> myeq <- colnames(x)[1]
> myeq <- paste(myeq, '[t] = ', sep='')
> for (i in 1:k){
+ if (mysum$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/117mi11290541912.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/120ehm1290541912.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/137xwg1290541912.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/14afv41290541912.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/15eyts1290541912.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/16zysy1290541912.tab")
+ }
>
> try(system("convert tmp/1xl4k1290541912.ps tmp/1xl4k1290541912.png",intern=TRUE))
character(0)
> try(system("convert tmp/2xl4k1290541912.ps tmp/2xl4k1290541912.png",intern=TRUE))
character(0)
> try(system("convert tmp/38umn1290541912.ps tmp/38umn1290541912.png",intern=TRUE))
character(0)
> try(system("convert tmp/48umn1290541912.ps tmp/48umn1290541912.png",intern=TRUE))
character(0)
> try(system("convert tmp/58umn1290541912.ps tmp/58umn1290541912.png",intern=TRUE))
character(0)
> try(system("convert tmp/61llq1290541912.ps tmp/61llq1290541912.png",intern=TRUE))
character(0)
> try(system("convert tmp/71llq1290541912.ps tmp/71llq1290541912.png",intern=TRUE))
character(0)
> try(system("convert tmp/8tdks1290541912.ps tmp/8tdks1290541912.png",intern=TRUE))
character(0)
> try(system("convert tmp/9tdks1290541912.ps tmp/9tdks1290541912.png",intern=TRUE))
character(0)
> try(system("convert tmp/10mm2d1290541912.ps tmp/10mm2d1290541912.png",intern=TRUE))
character(0)
>
>
> proc.time()
user system elapsed
3.913 2.556 10.535