R version 2.6.1 (2007-11-26)
Copyright (C) 2007 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.
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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(115.4
+ ,126.6
+ ,117
+ ,106.9
+ ,93.9
+ ,103.8
+ ,107.1
+ ,89.8
+ ,100.8
+ ,99.3
+ ,93.4
+ ,110.6
+ ,99.2
+ ,101.5
+ ,104
+ ,108.3
+ ,110.4
+ ,112.6
+ ,105.6
+ ,105.9
+ ,107.3
+ ,99.5
+ ,108.4
+ ,98.9
+ ,107.4
+ ,113.9
+ ,109.8
+ ,93.1
+ ,86.1
+ ,104.9
+ ,88.1
+ ,69.4
+ ,102.2
+ ,110.7
+ ,101.2
+ ,123.9
+ ,113.1
+ ,100.5
+ ,124.9
+ ,99.6
+ ,98
+ ,112.7
+ ,93.6
+ ,106.6
+ ,121.9
+ ,98.6
+ ,90.1
+ ,100.6
+ ,99.6
+ ,96.9
+ ,104.3
+ ,114.3
+ ,125.9
+ ,120.4
+ ,107.8
+ ,112
+ ,107.5
+ ,101.2
+ ,100
+ ,102.9
+ ,112.5
+ ,123.9
+ ,125.6
+ ,100.5
+ ,79.8
+ ,107.5
+ ,93.9
+ ,83.4
+ ,108.8
+ ,116.2
+ ,113.6
+ ,128.4
+ ,112
+ ,112.9
+ ,121.1
+ ,106.4
+ ,104
+ ,119.5
+ ,95.7
+ ,109.9
+ ,128.7
+ ,96
+ ,99
+ ,108.7
+ ,95.8
+ ,106.3
+ ,105.5
+ ,103
+ ,128.9
+ ,119.8
+ ,102.2
+ ,111.1
+ ,111.3
+ ,98.4
+ ,102.9
+ ,110.6
+ ,111.4
+ ,130
+ ,120.1
+ ,86.6
+ ,87
+ ,97.5
+ ,91.3
+ ,87.5
+ ,107.7
+ ,107.9
+ ,117.6
+ ,127.3
+ ,101.8
+ ,103.4
+ ,117.2
+ ,104.4
+ ,110.8
+ ,119.8
+ ,93.4
+ ,112.6
+ ,116.2
+ ,100.1
+ ,102.5
+ ,111
+ ,98.5
+ ,112.4
+ ,112.4
+ ,112.9
+ ,135.6
+ ,130.6
+ ,101.4
+ ,105.1
+ ,109.1
+ ,107.1
+ ,127.7
+ ,118.8
+ ,110.8
+ ,137
+ ,123.9
+ ,90.3
+ ,91
+ ,101.6
+ ,95.5
+ ,90.5
+ ,112.8
+ ,111.4
+ ,122.4
+ ,128
+ ,113
+ ,123.3
+ ,129.6
+ ,107.5
+ ,124.3
+ ,125.8
+ ,95.9
+ ,120
+ ,119.5
+ ,106.3
+ ,118.1
+ ,115.7
+ ,105.2
+ ,119
+ ,113.6
+ ,117.2
+ ,142.7
+ ,129.7
+ ,106.9
+ ,123.6
+ ,112
+ ,108.2
+ ,129.6
+ ,116.8
+ ,113
+ ,151.6
+ ,127
+ ,96.1
+ ,108.7
+ ,112.9
+ ,100.2
+ ,99.3
+ ,113.3
+ ,108.1
+ ,126.4
+ ,121.7)
+ ,dim=c(3
+ ,60)
+ ,dimnames=list(c('Interm'
+ ,'Invest'
+ ,'Consum')
+ ,1:60))
> y <- array(NA,dim=c(3,60),dimnames=list(c('Interm','Invest','Consum'),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 = 'No Linear Trend'
> par2 = 'Include Monthly Dummies'
> par1 = '3'
> #'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)
> 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
Consum Interm Invest M1 M2 M3 M4 M5 M6 M7 M8 M9 M10 M11
1 117.0 115.4 126.6 1 0 0 0 0 0 0 0 0 0 0
2 103.8 106.9 93.9 0 1 0 0 0 0 0 0 0 0 0
3 100.8 107.1 89.8 0 0 1 0 0 0 0 0 0 0 0
4 110.6 99.3 93.4 0 0 0 1 0 0 0 0 0 0 0
5 104.0 99.2 101.5 0 0 0 0 1 0 0 0 0 0 0
6 112.6 108.3 110.4 0 0 0 0 0 1 0 0 0 0 0
7 107.3 105.6 105.9 0 0 0 0 0 0 1 0 0 0 0
8 98.9 99.5 108.4 0 0 0 0 0 0 0 1 0 0 0
9 109.8 107.4 113.9 0 0 0 0 0 0 0 0 1 0 0
10 104.9 93.1 86.1 0 0 0 0 0 0 0 0 0 1 0
11 102.2 88.1 69.4 0 0 0 0 0 0 0 0 0 0 1
12 123.9 110.7 101.2 0 0 0 0 0 0 0 0 0 0 0
13 124.9 113.1 100.5 1 0 0 0 0 0 0 0 0 0 0
14 112.7 99.6 98.0 0 1 0 0 0 0 0 0 0 0 0
15 121.9 93.6 106.6 0 0 1 0 0 0 0 0 0 0 0
16 100.6 98.6 90.1 0 0 0 1 0 0 0 0 0 0 0
17 104.3 99.6 96.9 0 0 0 0 1 0 0 0 0 0 0
18 120.4 114.3 125.9 0 0 0 0 0 1 0 0 0 0 0
19 107.5 107.8 112.0 0 0 0 0 0 0 1 0 0 0 0
20 102.9 101.2 100.0 0 0 0 0 0 0 0 1 0 0 0
21 125.6 112.5 123.9 0 0 0 0 0 0 0 0 1 0 0
22 107.5 100.5 79.8 0 0 0 0 0 0 0 0 0 1 0
23 108.8 93.9 83.4 0 0 0 0 0 0 0 0 0 0 1
24 128.4 116.2 113.6 0 0 0 0 0 0 0 0 0 0 0
25 121.1 112.0 112.9 1 0 0 0 0 0 0 0 0 0 0
26 119.5 106.4 104.0 0 1 0 0 0 0 0 0 0 0 0
27 128.7 95.7 109.9 0 0 1 0 0 0 0 0 0 0 0
28 108.7 96.0 99.0 0 0 0 1 0 0 0 0 0 0 0
29 105.5 95.8 106.3 0 0 0 0 1 0 0 0 0 0 0
30 119.8 103.0 128.9 0 0 0 0 0 1 0 0 0 0 0
31 111.3 102.2 111.1 0 0 0 0 0 0 1 0 0 0 0
32 110.6 98.4 102.9 0 0 0 0 0 0 0 1 0 0 0
33 120.1 111.4 130.0 0 0 0 0 0 0 0 0 1 0 0
34 97.5 86.6 87.0 0 0 0 0 0 0 0 0 0 1 0
35 107.7 91.3 87.5 0 0 0 0 0 0 0 0 0 0 1
36 127.3 107.9 117.6 0 0 0 0 0 0 0 0 0 0 0
37 117.2 101.8 103.4 1 0 0 0 0 0 0 0 0 0 0
38 119.8 104.4 110.8 0 1 0 0 0 0 0 0 0 0 0
39 116.2 93.4 112.6 0 0 1 0 0 0 0 0 0 0 0
40 111.0 100.1 102.5 0 0 0 1 0 0 0 0 0 0 0
41 112.4 98.5 112.4 0 0 0 0 1 0 0 0 0 0 0
42 130.6 112.9 135.6 0 0 0 0 0 1 0 0 0 0 0
43 109.1 101.4 105.1 0 0 0 0 0 0 1 0 0 0 0
44 118.8 107.1 127.7 0 0 0 0 0 0 0 1 0 0 0
45 123.9 110.8 137.0 0 0 0 0 0 0 0 0 1 0 0
46 101.6 90.3 91.0 0 0 0 0 0 0 0 0 0 1 0
47 112.8 95.5 90.5 0 0 0 0 0 0 0 0 0 0 1
48 128.0 111.4 122.4 0 0 0 0 0 0 0 0 0 0 0
49 129.6 113.0 123.3 1 0 0 0 0 0 0 0 0 0 0
50 125.8 107.5 124.3 0 1 0 0 0 0 0 0 0 0 0
51 119.5 95.9 120.0 0 0 1 0 0 0 0 0 0 0 0
52 115.7 106.3 118.1 0 0 0 1 0 0 0 0 0 0 0
53 113.6 105.2 119.0 0 0 0 0 1 0 0 0 0 0 0
54 129.7 117.2 142.7 0 0 0 0 0 1 0 0 0 0 0
55 112.0 106.9 123.6 0 0 0 0 0 0 1 0 0 0 0
56 116.8 108.2 129.6 0 0 0 0 0 0 0 1 0 0 0
57 127.0 113.0 151.6 0 0 0 0 0 0 0 0 1 0 0
58 112.9 96.1 108.7 0 0 0 0 0 0 0 0 0 1 0
59 113.3 100.2 99.3 0 0 0 0 0 0 0 0 0 0 1
60 121.7 108.1 126.4 0 0 0 0 0 0 0 0 0 0 0
> k <- length(x[1,])
> df <- as.data.frame(x)
> (mylm <- lm(df))
Call:
lm(formula = df)
Coefficients:
(Intercept) Interm Invest M1 M2 M3
67.4292 0.1226 0.3857 -2.8060 -4.9439 -3.4942
M4 M5 M6 M7 M8 M9
-9.1907 -13.0473 -8.0802 -13.8615 -14.3093 -10.4006
M10 M11
-8.9085 -3.1517
> (mysum <- summary(mylm))
Call:
lm(formula = df)
Residuals:
Min 1Q Median 3Q Max
-10.9067 -2.0120 0.3386 2.3992 10.6389
Coefficients:
Estimate Std. Error t value Pr(>|t|)
(Intercept) 67.42920 17.63962 3.823 0.000395 ***
Interm 0.12265 0.16926 0.725 0.472358
Invest 0.38570 0.06445 5.985 3.05e-07 ***
M1 -2.80600 2.98025 -0.942 0.351352
M2 -4.94393 3.12901 -1.580 0.120953
M3 -3.49422 3.69017 -0.947 0.348637
M4 -9.19073 3.44496 -2.668 0.010505 *
M5 -13.04730 3.46083 -3.770 0.000464 ***
M6 -8.08018 3.07585 -2.627 0.011664 *
M7 -13.86150 3.12523 -4.435 5.68e-05 ***
M8 -14.30929 3.24556 -4.409 6.19e-05 ***
M9 -10.40057 3.12451 -3.329 0.001724 **
M10 -8.90850 4.10489 -2.170 0.035190 *
M11 -3.15171 4.11248 -0.766 0.447367
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
Residual standard error: 4.701 on 46 degrees of freedom
Multiple R-Squared: 0.787, Adjusted R-squared: 0.7268
F-statistic: 13.07 on 13 and 46 DF, p-value: 2.239e-11
> postscript(file="/var/www/html/rcomp/tmp/17so81198181092.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/2x7ol1198181092.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> plot(mysum$resid, type='b', pch=19, main='Residuals', ylab='value of Residuals', xlab='time or index')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/3u2i81198181092.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> hist(mysum$resid, main='Residual Histogram', xlab='values of Residuals')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/4ce2f1198181092.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> densityplot(~mysum$resid,col='black',main='Residual Density Plot', xlab='values of Residuals')
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/5v4pp1198181092.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> qqnorm(mysum$resid, main='Residual Normal Q-Q Plot')
> 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
-10.60669821 -8.01381031 -10.90666990 4.15797805 -1.69736888 -2.61333954
7 8 9 10 11 12
-0.06521559 -8.23351471 -4.33251878 1.75178342 0.34945778 3.86057450
13 14 15 16 17 18
7.64220361 0.20015045 5.36930488 -4.48335275 0.32779850 -1.52760629
19 20 21 22 23 24
-2.48782236 -1.20212516 6.98495676 5.87410108 0.83827306 2.90330687
25 26 27 28 29 30
-0.80558130 3.85192891 10.63892721 0.50279097 -1.63172987 -1.89877828
31 32 33 34 35 36
2.34614282 5.72275737 -0.73290865 -5.19813010 -1.52421599 1.27848668
37 38 39 40 41 42
0.20960178 1.77445645 -2.62037439 0.94997521 2.58433891 5.10279754
43 44 45 46 47 48
2.55847098 3.29031457 0.44077013 -3.09473705 1.90355412 -0.30215169
49 50 51 52 53 54
3.56047412 2.18727451 -2.48118779 -1.12739148 0.41696135 0.93692657
55 56 57 58 59 60
-2.35157585 0.42256792 -2.36029946 0.66698265 -1.56706897 -7.74021636
> postscript(file="/var/www/html/rcomp/tmp/6i2731198181092.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 -10.60669821 NA
1 -8.01381031 -10.60669821
2 -10.90666990 -8.01381031
3 4.15797805 -10.90666990
4 -1.69736888 4.15797805
5 -2.61333954 -1.69736888
6 -0.06521559 -2.61333954
7 -8.23351471 -0.06521559
8 -4.33251878 -8.23351471
9 1.75178342 -4.33251878
10 0.34945778 1.75178342
11 3.86057450 0.34945778
12 7.64220361 3.86057450
13 0.20015045 7.64220361
14 5.36930488 0.20015045
15 -4.48335275 5.36930488
16 0.32779850 -4.48335275
17 -1.52760629 0.32779850
18 -2.48782236 -1.52760629
19 -1.20212516 -2.48782236
20 6.98495676 -1.20212516
21 5.87410108 6.98495676
22 0.83827306 5.87410108
23 2.90330687 0.83827306
24 -0.80558130 2.90330687
25 3.85192891 -0.80558130
26 10.63892721 3.85192891
27 0.50279097 10.63892721
28 -1.63172987 0.50279097
29 -1.89877828 -1.63172987
30 2.34614282 -1.89877828
31 5.72275737 2.34614282
32 -0.73290865 5.72275737
33 -5.19813010 -0.73290865
34 -1.52421599 -5.19813010
35 1.27848668 -1.52421599
36 0.20960178 1.27848668
37 1.77445645 0.20960178
38 -2.62037439 1.77445645
39 0.94997521 -2.62037439
40 2.58433891 0.94997521
41 5.10279754 2.58433891
42 2.55847098 5.10279754
43 3.29031457 2.55847098
44 0.44077013 3.29031457
45 -3.09473705 0.44077013
46 1.90355412 -3.09473705
47 -0.30215169 1.90355412
48 3.56047412 -0.30215169
49 2.18727451 3.56047412
50 -2.48118779 2.18727451
51 -1.12739148 -2.48118779
52 0.41696135 -1.12739148
53 0.93692657 0.41696135
54 -2.35157585 0.93692657
55 0.42256792 -2.35157585
56 -2.36029946 0.42256792
57 0.66698265 -2.36029946
58 -1.56706897 0.66698265
59 -7.74021636 -1.56706897
60 NA -7.74021636
> dum1 <- dum[2:length(myerror),]
> dum1
lag(myerror, k = 1) myerror
[1,] -8.01381031 -10.60669821
[2,] -10.90666990 -8.01381031
[3,] 4.15797805 -10.90666990
[4,] -1.69736888 4.15797805
[5,] -2.61333954 -1.69736888
[6,] -0.06521559 -2.61333954
[7,] -8.23351471 -0.06521559
[8,] -4.33251878 -8.23351471
[9,] 1.75178342 -4.33251878
[10,] 0.34945778 1.75178342
[11,] 3.86057450 0.34945778
[12,] 7.64220361 3.86057450
[13,] 0.20015045 7.64220361
[14,] 5.36930488 0.20015045
[15,] -4.48335275 5.36930488
[16,] 0.32779850 -4.48335275
[17,] -1.52760629 0.32779850
[18,] -2.48782236 -1.52760629
[19,] -1.20212516 -2.48782236
[20,] 6.98495676 -1.20212516
[21,] 5.87410108 6.98495676
[22,] 0.83827306 5.87410108
[23,] 2.90330687 0.83827306
[24,] -0.80558130 2.90330687
[25,] 3.85192891 -0.80558130
[26,] 10.63892721 3.85192891
[27,] 0.50279097 10.63892721
[28,] -1.63172987 0.50279097
[29,] -1.89877828 -1.63172987
[30,] 2.34614282 -1.89877828
[31,] 5.72275737 2.34614282
[32,] -0.73290865 5.72275737
[33,] -5.19813010 -0.73290865
[34,] -1.52421599 -5.19813010
[35,] 1.27848668 -1.52421599
[36,] 0.20960178 1.27848668
[37,] 1.77445645 0.20960178
[38,] -2.62037439 1.77445645
[39,] 0.94997521 -2.62037439
[40,] 2.58433891 0.94997521
[41,] 5.10279754 2.58433891
[42,] 2.55847098 5.10279754
[43,] 3.29031457 2.55847098
[44,] 0.44077013 3.29031457
[45,] -3.09473705 0.44077013
[46,] 1.90355412 -3.09473705
[47,] -0.30215169 1.90355412
[48,] 3.56047412 -0.30215169
[49,] 2.18727451 3.56047412
[50,] -2.48118779 2.18727451
[51,] -1.12739148 -2.48118779
[52,] 0.41696135 -1.12739148
[53,] 0.93692657 0.41696135
[54,] -2.35157585 0.93692657
[55,] 0.42256792 -2.35157585
[56,] -2.36029946 0.42256792
[57,] 0.66698265 -2.36029946
[58,] -1.56706897 0.66698265
[59,] -7.74021636 -1.56706897
> z <- as.data.frame(dum1)
> z
lag(myerror, k = 1) myerror
1 -8.01381031 -10.60669821
2 -10.90666990 -8.01381031
3 4.15797805 -10.90666990
4 -1.69736888 4.15797805
5 -2.61333954 -1.69736888
6 -0.06521559 -2.61333954
7 -8.23351471 -0.06521559
8 -4.33251878 -8.23351471
9 1.75178342 -4.33251878
10 0.34945778 1.75178342
11 3.86057450 0.34945778
12 7.64220361 3.86057450
13 0.20015045 7.64220361
14 5.36930488 0.20015045
15 -4.48335275 5.36930488
16 0.32779850 -4.48335275
17 -1.52760629 0.32779850
18 -2.48782236 -1.52760629
19 -1.20212516 -2.48782236
20 6.98495676 -1.20212516
21 5.87410108 6.98495676
22 0.83827306 5.87410108
23 2.90330687 0.83827306
24 -0.80558130 2.90330687
25 3.85192891 -0.80558130
26 10.63892721 3.85192891
27 0.50279097 10.63892721
28 -1.63172987 0.50279097
29 -1.89877828 -1.63172987
30 2.34614282 -1.89877828
31 5.72275737 2.34614282
32 -0.73290865 5.72275737
33 -5.19813010 -0.73290865
34 -1.52421599 -5.19813010
35 1.27848668 -1.52421599
36 0.20960178 1.27848668
37 1.77445645 0.20960178
38 -2.62037439 1.77445645
39 0.94997521 -2.62037439
40 2.58433891 0.94997521
41 5.10279754 2.58433891
42 2.55847098 5.10279754
43 3.29031457 2.55847098
44 0.44077013 3.29031457
45 -3.09473705 0.44077013
46 1.90355412 -3.09473705
47 -0.30215169 1.90355412
48 3.56047412 -0.30215169
49 2.18727451 3.56047412
50 -2.48118779 2.18727451
51 -1.12739148 -2.48118779
52 0.41696135 -1.12739148
53 0.93692657 0.41696135
54 -2.35157585 0.93692657
55 0.42256792 -2.35157585
56 -2.36029946 0.42256792
57 0.66698265 -2.36029946
58 -1.56706897 0.66698265
59 -7.74021636 -1.56706897
> 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/7rr661198181092.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> acf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/8k6gw1198181092.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> pacf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Partial Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/91u491198181092.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> opar <- par(mfrow = c(2,2), oma = c(0, 0, 1.1, 0))
> plot(mylm, las = 1, sub='Residual Diagnostics')
> par(opar)
> dev.off()
null device
1
> load(file='/var/www/html/rcomp/createtable')
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a, 'Multiple Linear Regression - Estimated Regression Equation', 1, TRUE)
> a<-table.row.end(a)
> myeq <- colnames(x)[1]
> myeq <- paste(myeq, '[t] = ', sep='')
> for (i in 1:k){
+ if (mysum$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/10hjzb1198181092.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/11cyop1198181092.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/123a8q1198181092.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/13paf91198181092.tab")
>
> system("convert tmp/17so81198181092.ps tmp/17so81198181092.png")
> system("convert tmp/2x7ol1198181092.ps tmp/2x7ol1198181092.png")
> system("convert tmp/3u2i81198181092.ps tmp/3u2i81198181092.png")
> system("convert tmp/4ce2f1198181092.ps tmp/4ce2f1198181092.png")
> system("convert tmp/5v4pp1198181092.ps tmp/5v4pp1198181092.png")
> system("convert tmp/6i2731198181092.ps tmp/6i2731198181092.png")
> system("convert tmp/7rr661198181092.ps tmp/7rr661198181092.png")
> system("convert tmp/8k6gw1198181092.ps tmp/8k6gw1198181092.png")
> system("convert tmp/91u491198181092.ps tmp/91u491198181092.png")
>
>
> proc.time()
user system elapsed
4.025 2.456 4.348