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.
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(102.7
+ ,0
+ ,0
+ ,103.2
+ ,0
+ ,0
+ ,105.6
+ ,0
+ ,0
+ ,103.9
+ ,0
+ ,0
+ ,107.2
+ ,0
+ ,0
+ ,100.7
+ ,0
+ ,0
+ ,92.1
+ ,0
+ ,0
+ ,90.3
+ ,0
+ ,0
+ ,93.4
+ ,0
+ ,0
+ ,98.5
+ ,0
+ ,0
+ ,100.8
+ ,0
+ ,0
+ ,102.3
+ ,0
+ ,0
+ ,104.7
+ ,0
+ ,0
+ ,101.1
+ ,0
+ ,0
+ ,101.4
+ ,0
+ ,0
+ ,99.5
+ ,0
+ ,0
+ ,98.4
+ ,0
+ ,0
+ ,96.3
+ ,0
+ ,0
+ ,100.7
+ ,0
+ ,0
+ ,101.2
+ ,0
+ ,0
+ ,100.3
+ ,0
+ ,0
+ ,97.8
+ ,0
+ ,0
+ ,97.4
+ ,0
+ ,0
+ ,98.6
+ ,0
+ ,0
+ ,99.7
+ ,0
+ ,0
+ ,99.0
+ ,0
+ ,0
+ ,98.1
+ ,0
+ ,0
+ ,97.0
+ ,0
+ ,0
+ ,98.5
+ ,0
+ ,0
+ ,103.8
+ ,0
+ ,0
+ ,114.4
+ ,0
+ ,0
+ ,124.5
+ ,0
+ ,0
+ ,134.2
+ ,0
+ ,0
+ ,131.8
+ ,0
+ ,0
+ ,125.6
+ ,0
+ ,0
+ ,119.9
+ ,0
+ ,0
+ ,114.9
+ ,0
+ ,0
+ ,115.5
+ ,0
+ ,0
+ ,112.5
+ ,0
+ ,0
+ ,111.4
+ ,0
+ ,0
+ ,115.3
+ ,0
+ ,0
+ ,110.8
+ ,0
+ ,0
+ ,103.7
+ ,0
+ ,0
+ ,111.1
+ ,0
+ ,1
+ ,113.0
+ ,0
+ ,1
+ ,111.2
+ ,0
+ ,1
+ ,117.6
+ ,0
+ ,1
+ ,121.7
+ ,0
+ ,1
+ ,127.3
+ ,0
+ ,1
+ ,129.8
+ ,0
+ ,1
+ ,137.1
+ ,0
+ ,1
+ ,141.4
+ ,0
+ ,1
+ ,137.4
+ ,0
+ ,1
+ ,130.7
+ ,0
+ ,1
+ ,117.2
+ ,0
+ ,1
+ ,110.8
+ ,0
+ ,-1
+ ,111.4
+ ,0
+ ,-1
+ ,108.2
+ ,0
+ ,-1
+ ,108.8
+ ,0
+ ,-1
+ ,110.2
+ ,0
+ ,-1
+ ,109.5
+ ,0
+ ,-1
+ ,109.5
+ ,0
+ ,-1
+ ,116.0
+ ,0
+ ,-1
+ ,111.2
+ ,0
+ ,-1
+ ,112.1
+ ,0
+ ,-1
+ ,114.0
+ ,0
+ ,-1
+ ,119.1
+ ,0
+ ,-1
+ ,114.1
+ ,1
+ ,-1
+ ,115.1
+ ,1
+ ,-1
+ ,115.4
+ ,1
+ ,-1
+ ,110.8
+ ,1
+ ,0
+ ,116.0
+ ,1
+ ,0
+ ,119.2
+ ,1
+ ,0
+ ,126.5
+ ,1
+ ,0
+ ,127.8
+ ,1
+ ,0
+ ,131.3
+ ,1
+ ,0
+ ,140.3
+ ,1
+ ,0
+ ,137.3
+ ,1
+ ,0
+ ,143.0
+ ,1
+ ,0
+ ,134.5
+ ,1
+ ,0
+ ,139.9
+ ,1
+ ,0
+ ,159.3
+ ,1
+ ,0
+ ,170.4
+ ,1
+ ,0
+ ,175.0
+ ,1
+ ,0
+ ,175.8
+ ,1
+ ,0
+ ,180.9
+ ,1
+ ,0
+ ,180.3
+ ,1
+ ,0
+ ,169.6
+ ,1
+ ,0
+ ,172.3
+ ,1
+ ,0
+ ,184.8
+ ,1
+ ,0
+ ,177.7
+ ,1
+ ,0
+ ,184.6
+ ,1
+ ,0
+ ,211.4
+ ,1
+ ,0
+ ,215.3
+ ,1
+ ,0
+ ,215.9
+ ,1
+ ,0)
+ ,dim=c(3
+ ,95)
+ ,dimnames=list(c('prijsindex'
+ ,'ontkoppelde_bedrijfstoeslag'
+ ,'oogstomvang')
+ ,1:95))
> y <- array(NA,dim=c(3,95),dimnames=list(c('prijsindex','ontkoppelde_bedrijfstoeslag','oogstomvang'),1:95))
> for (i in 1:dim(x)[1])
+ {
+ for (j in 1:dim(x)[2])
+ {
+ y[i,j] <- as.numeric(x[i,j])
+ }
+ }
> par3 = 'No Linear Trend'
> par2 = 'Do not include Seasonal Dummies'
> par1 = '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)
> 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
prijsindex ontkoppelde_bedrijfstoeslag oogstomvang
1 102.7 0 0
2 103.2 0 0
3 105.6 0 0
4 103.9 0 0
5 107.2 0 0
6 100.7 0 0
7 92.1 0 0
8 90.3 0 0
9 93.4 0 0
10 98.5 0 0
11 100.8 0 0
12 102.3 0 0
13 104.7 0 0
14 101.1 0 0
15 101.4 0 0
16 99.5 0 0
17 98.4 0 0
18 96.3 0 0
19 100.7 0 0
20 101.2 0 0
21 100.3 0 0
22 97.8 0 0
23 97.4 0 0
24 98.6 0 0
25 99.7 0 0
26 99.0 0 0
27 98.1 0 0
28 97.0 0 0
29 98.5 0 0
30 103.8 0 0
31 114.4 0 0
32 124.5 0 0
33 134.2 0 0
34 131.8 0 0
35 125.6 0 0
36 119.9 0 0
37 114.9 0 0
38 115.5 0 0
39 112.5 0 0
40 111.4 0 0
41 115.3 0 0
42 110.8 0 0
43 103.7 0 0
44 111.1 0 1
45 113.0 0 1
46 111.2 0 1
47 117.6 0 1
48 121.7 0 1
49 127.3 0 1
50 129.8 0 1
51 137.1 0 1
52 141.4 0 1
53 137.4 0 1
54 130.7 0 1
55 117.2 0 1
56 110.8 0 -1
57 111.4 0 -1
58 108.2 0 -1
59 108.8 0 -1
60 110.2 0 -1
61 109.5 0 -1
62 109.5 0 -1
63 116.0 0 -1
64 111.2 0 -1
65 112.1 0 -1
66 114.0 0 -1
67 119.1 0 -1
68 114.1 1 -1
69 115.1 1 -1
70 115.4 1 -1
71 110.8 1 0
72 116.0 1 0
73 119.2 1 0
74 126.5 1 0
75 127.8 1 0
76 131.3 1 0
77 140.3 1 0
78 137.3 1 0
79 143.0 1 0
80 134.5 1 0
81 139.9 1 0
82 159.3 1 0
83 170.4 1 0
84 175.0 1 0
85 175.8 1 0
86 180.9 1 0
87 180.3 1 0
88 169.6 1 0
89 172.3 1 0
90 184.8 1 0
91 177.7 1 0
92 184.6 1 0
93 211.4 1 0
94 215.3 1 0
95 215.9 1 0
> k <- length(x[1,])
> df <- as.data.frame(x)
> (mylm <- lm(df))
Call:
lm(formula = df)
Coefficients:
(Intercept) ontkoppelde_bedrijfstoeslag
109.93 46.34
oogstomvang
10.33
> (mysum <- summary(mylm))
Call:
lm(formula = df)
Residuals:
Min 1Q Median 3Q Max
-45.467 -11.425 -3.055 12.154 59.633
Coefficients:
Estimate Std. Error t value Pr(>|t|)
(Intercept) 109.925 2.389 46.011 < 2e-16 ***
ontkoppelde_bedrijfstoeslag 46.342 4.419 10.486 < 2e-16 ***
oogstomvang 10.330 3.786 2.728 0.00762 **
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
Residual standard error: 19.56 on 92 degrees of freedom
Multiple R-Squared: 0.5515, Adjusted R-squared: 0.5417
F-statistic: 56.55 on 2 and 92 DF, p-value: < 2.2e-16
> postscript(file="/var/www/html/rcomp/tmp/1b99m1199885127.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/2tmc31199885127.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> plot(mysum$resid, type='b', pch=19, main='Residuals', ylab='value of Residuals', xlab='time or index')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/37nr81199885127.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> hist(mysum$resid, main='Residual Histogram', xlab='values of Residuals')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/4qtek1199885127.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> densityplot(~mysum$resid,col='black',main='Residual Density Plot', xlab='values of Residuals')
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/548yr1199885127.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> qqnorm(mysum$resid, main='Residual Normal Q-Q Plot')
> grid()
> dev.off()
null device
1
> (myerror <- as.ts(mysum$resid))
Time Series:
Start = 1
End = 95
Frequency = 1
1 2 3 4 5 6
-7.2253731 -6.7253731 -4.3253731 -6.0253731 -2.7253731 -9.2253731
7 8 9 10 11 12
-17.8253731 -19.6253731 -16.5253731 -11.4253731 -9.1253731 -7.6253731
13 14 15 16 17 18
-5.2253731 -8.8253731 -8.5253731 -10.4253731 -11.5253731 -13.6253731
19 20 21 22 23 24
-9.2253731 -8.7253731 -9.6253731 -12.1253731 -12.5253731 -11.3253731
25 26 27 28 29 30
-10.2253731 -10.9253731 -11.8253731 -12.9253731 -11.4253731 -6.1253731
31 32 33 34 35 36
4.4746269 14.5746269 24.2746269 21.8746269 15.6746269 9.9746269
37 38 39 40 41 42
4.9746269 5.5746269 2.5746269 1.4746269 5.3746269 0.8746269
43 44 45 46 47 48
-6.2253731 -9.1550920 -7.2550920 -9.0550920 -2.6550920 1.4449080
49 50 51 52 53 54
7.0449080 9.5449080 16.8449080 21.1449080 17.1449080 10.4449080
55 56 57 58 59 60
-3.0550920 11.2043457 11.8043457 8.6043457 9.2043457 10.6043457
61 62 63 64 65 66
9.9043457 9.9043457 16.4043457 11.6043457 12.5043457 14.4043457
67 68 69 70 71 72
19.5043457 -31.8377510 -30.8377510 -30.5377510 -45.4674699 -40.2674699
73 74 75 76 77 78
-37.0674699 -29.7674699 -28.4674699 -24.9674699 -15.9674699 -18.9674699
79 80 81 82 83 84
-13.2674699 -21.7674699 -16.3674699 3.0325301 14.1325301 18.7325301
85 86 87 88 89 90
19.5325301 24.6325301 24.0325301 13.3325301 16.0325301 28.5325301
91 92 93 94 95
21.4325301 28.3325301 55.1325301 59.0325301 59.6325301
> postscript(file="/var/www/html/rcomp/tmp/6lz0w1199885128.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 = 95
Frequency = 1
lag(myerror, k = 1) myerror
0 -7.2253731 NA
1 -6.7253731 -7.2253731
2 -4.3253731 -6.7253731
3 -6.0253731 -4.3253731
4 -2.7253731 -6.0253731
5 -9.2253731 -2.7253731
6 -17.8253731 -9.2253731
7 -19.6253731 -17.8253731
8 -16.5253731 -19.6253731
9 -11.4253731 -16.5253731
10 -9.1253731 -11.4253731
11 -7.6253731 -9.1253731
12 -5.2253731 -7.6253731
13 -8.8253731 -5.2253731
14 -8.5253731 -8.8253731
15 -10.4253731 -8.5253731
16 -11.5253731 -10.4253731
17 -13.6253731 -11.5253731
18 -9.2253731 -13.6253731
19 -8.7253731 -9.2253731
20 -9.6253731 -8.7253731
21 -12.1253731 -9.6253731
22 -12.5253731 -12.1253731
23 -11.3253731 -12.5253731
24 -10.2253731 -11.3253731
25 -10.9253731 -10.2253731
26 -11.8253731 -10.9253731
27 -12.9253731 -11.8253731
28 -11.4253731 -12.9253731
29 -6.1253731 -11.4253731
30 4.4746269 -6.1253731
31 14.5746269 4.4746269
32 24.2746269 14.5746269
33 21.8746269 24.2746269
34 15.6746269 21.8746269
35 9.9746269 15.6746269
36 4.9746269 9.9746269
37 5.5746269 4.9746269
38 2.5746269 5.5746269
39 1.4746269 2.5746269
40 5.3746269 1.4746269
41 0.8746269 5.3746269
42 -6.2253731 0.8746269
43 -9.1550920 -6.2253731
44 -7.2550920 -9.1550920
45 -9.0550920 -7.2550920
46 -2.6550920 -9.0550920
47 1.4449080 -2.6550920
48 7.0449080 1.4449080
49 9.5449080 7.0449080
50 16.8449080 9.5449080
51 21.1449080 16.8449080
52 17.1449080 21.1449080
53 10.4449080 17.1449080
54 -3.0550920 10.4449080
55 11.2043457 -3.0550920
56 11.8043457 11.2043457
57 8.6043457 11.8043457
58 9.2043457 8.6043457
59 10.6043457 9.2043457
60 9.9043457 10.6043457
61 9.9043457 9.9043457
62 16.4043457 9.9043457
63 11.6043457 16.4043457
64 12.5043457 11.6043457
65 14.4043457 12.5043457
66 19.5043457 14.4043457
67 -31.8377510 19.5043457
68 -30.8377510 -31.8377510
69 -30.5377510 -30.8377510
70 -45.4674699 -30.5377510
71 -40.2674699 -45.4674699
72 -37.0674699 -40.2674699
73 -29.7674699 -37.0674699
74 -28.4674699 -29.7674699
75 -24.9674699 -28.4674699
76 -15.9674699 -24.9674699
77 -18.9674699 -15.9674699
78 -13.2674699 -18.9674699
79 -21.7674699 -13.2674699
80 -16.3674699 -21.7674699
81 3.0325301 -16.3674699
82 14.1325301 3.0325301
83 18.7325301 14.1325301
84 19.5325301 18.7325301
85 24.6325301 19.5325301
86 24.0325301 24.6325301
87 13.3325301 24.0325301
88 16.0325301 13.3325301
89 28.5325301 16.0325301
90 21.4325301 28.5325301
91 28.3325301 21.4325301
92 55.1325301 28.3325301
93 59.0325301 55.1325301
94 59.6325301 59.0325301
95 NA 59.6325301
> dum1 <- dum[2:length(myerror),]
> dum1
lag(myerror, k = 1) myerror
[1,] -6.7253731 -7.2253731
[2,] -4.3253731 -6.7253731
[3,] -6.0253731 -4.3253731
[4,] -2.7253731 -6.0253731
[5,] -9.2253731 -2.7253731
[6,] -17.8253731 -9.2253731
[7,] -19.6253731 -17.8253731
[8,] -16.5253731 -19.6253731
[9,] -11.4253731 -16.5253731
[10,] -9.1253731 -11.4253731
[11,] -7.6253731 -9.1253731
[12,] -5.2253731 -7.6253731
[13,] -8.8253731 -5.2253731
[14,] -8.5253731 -8.8253731
[15,] -10.4253731 -8.5253731
[16,] -11.5253731 -10.4253731
[17,] -13.6253731 -11.5253731
[18,] -9.2253731 -13.6253731
[19,] -8.7253731 -9.2253731
[20,] -9.6253731 -8.7253731
[21,] -12.1253731 -9.6253731
[22,] -12.5253731 -12.1253731
[23,] -11.3253731 -12.5253731
[24,] -10.2253731 -11.3253731
[25,] -10.9253731 -10.2253731
[26,] -11.8253731 -10.9253731
[27,] -12.9253731 -11.8253731
[28,] -11.4253731 -12.9253731
[29,] -6.1253731 -11.4253731
[30,] 4.4746269 -6.1253731
[31,] 14.5746269 4.4746269
[32,] 24.2746269 14.5746269
[33,] 21.8746269 24.2746269
[34,] 15.6746269 21.8746269
[35,] 9.9746269 15.6746269
[36,] 4.9746269 9.9746269
[37,] 5.5746269 4.9746269
[38,] 2.5746269 5.5746269
[39,] 1.4746269 2.5746269
[40,] 5.3746269 1.4746269
[41,] 0.8746269 5.3746269
[42,] -6.2253731 0.8746269
[43,] -9.1550920 -6.2253731
[44,] -7.2550920 -9.1550920
[45,] -9.0550920 -7.2550920
[46,] -2.6550920 -9.0550920
[47,] 1.4449080 -2.6550920
[48,] 7.0449080 1.4449080
[49,] 9.5449080 7.0449080
[50,] 16.8449080 9.5449080
[51,] 21.1449080 16.8449080
[52,] 17.1449080 21.1449080
[53,] 10.4449080 17.1449080
[54,] -3.0550920 10.4449080
[55,] 11.2043457 -3.0550920
[56,] 11.8043457 11.2043457
[57,] 8.6043457 11.8043457
[58,] 9.2043457 8.6043457
[59,] 10.6043457 9.2043457
[60,] 9.9043457 10.6043457
[61,] 9.9043457 9.9043457
[62,] 16.4043457 9.9043457
[63,] 11.6043457 16.4043457
[64,] 12.5043457 11.6043457
[65,] 14.4043457 12.5043457
[66,] 19.5043457 14.4043457
[67,] -31.8377510 19.5043457
[68,] -30.8377510 -31.8377510
[69,] -30.5377510 -30.8377510
[70,] -45.4674699 -30.5377510
[71,] -40.2674699 -45.4674699
[72,] -37.0674699 -40.2674699
[73,] -29.7674699 -37.0674699
[74,] -28.4674699 -29.7674699
[75,] -24.9674699 -28.4674699
[76,] -15.9674699 -24.9674699
[77,] -18.9674699 -15.9674699
[78,] -13.2674699 -18.9674699
[79,] -21.7674699 -13.2674699
[80,] -16.3674699 -21.7674699
[81,] 3.0325301 -16.3674699
[82,] 14.1325301 3.0325301
[83,] 18.7325301 14.1325301
[84,] 19.5325301 18.7325301
[85,] 24.6325301 19.5325301
[86,] 24.0325301 24.6325301
[87,] 13.3325301 24.0325301
[88,] 16.0325301 13.3325301
[89,] 28.5325301 16.0325301
[90,] 21.4325301 28.5325301
[91,] 28.3325301 21.4325301
[92,] 55.1325301 28.3325301
[93,] 59.0325301 55.1325301
[94,] 59.6325301 59.0325301
> z <- as.data.frame(dum1)
> z
lag(myerror, k = 1) myerror
1 -6.7253731 -7.2253731
2 -4.3253731 -6.7253731
3 -6.0253731 -4.3253731
4 -2.7253731 -6.0253731
5 -9.2253731 -2.7253731
6 -17.8253731 -9.2253731
7 -19.6253731 -17.8253731
8 -16.5253731 -19.6253731
9 -11.4253731 -16.5253731
10 -9.1253731 -11.4253731
11 -7.6253731 -9.1253731
12 -5.2253731 -7.6253731
13 -8.8253731 -5.2253731
14 -8.5253731 -8.8253731
15 -10.4253731 -8.5253731
16 -11.5253731 -10.4253731
17 -13.6253731 -11.5253731
18 -9.2253731 -13.6253731
19 -8.7253731 -9.2253731
20 -9.6253731 -8.7253731
21 -12.1253731 -9.6253731
22 -12.5253731 -12.1253731
23 -11.3253731 -12.5253731
24 -10.2253731 -11.3253731
25 -10.9253731 -10.2253731
26 -11.8253731 -10.9253731
27 -12.9253731 -11.8253731
28 -11.4253731 -12.9253731
29 -6.1253731 -11.4253731
30 4.4746269 -6.1253731
31 14.5746269 4.4746269
32 24.2746269 14.5746269
33 21.8746269 24.2746269
34 15.6746269 21.8746269
35 9.9746269 15.6746269
36 4.9746269 9.9746269
37 5.5746269 4.9746269
38 2.5746269 5.5746269
39 1.4746269 2.5746269
40 5.3746269 1.4746269
41 0.8746269 5.3746269
42 -6.2253731 0.8746269
43 -9.1550920 -6.2253731
44 -7.2550920 -9.1550920
45 -9.0550920 -7.2550920
46 -2.6550920 -9.0550920
47 1.4449080 -2.6550920
48 7.0449080 1.4449080
49 9.5449080 7.0449080
50 16.8449080 9.5449080
51 21.1449080 16.8449080
52 17.1449080 21.1449080
53 10.4449080 17.1449080
54 -3.0550920 10.4449080
55 11.2043457 -3.0550920
56 11.8043457 11.2043457
57 8.6043457 11.8043457
58 9.2043457 8.6043457
59 10.6043457 9.2043457
60 9.9043457 10.6043457
61 9.9043457 9.9043457
62 16.4043457 9.9043457
63 11.6043457 16.4043457
64 12.5043457 11.6043457
65 14.4043457 12.5043457
66 19.5043457 14.4043457
67 -31.8377510 19.5043457
68 -30.8377510 -31.8377510
69 -30.5377510 -30.8377510
70 -45.4674699 -30.5377510
71 -40.2674699 -45.4674699
72 -37.0674699 -40.2674699
73 -29.7674699 -37.0674699
74 -28.4674699 -29.7674699
75 -24.9674699 -28.4674699
76 -15.9674699 -24.9674699
77 -18.9674699 -15.9674699
78 -13.2674699 -18.9674699
79 -21.7674699 -13.2674699
80 -16.3674699 -21.7674699
81 3.0325301 -16.3674699
82 14.1325301 3.0325301
83 18.7325301 14.1325301
84 19.5325301 18.7325301
85 24.6325301 19.5325301
86 24.0325301 24.6325301
87 13.3325301 24.0325301
88 16.0325301 13.3325301
89 28.5325301 16.0325301
90 21.4325301 28.5325301
91 28.3325301 21.4325301
92 55.1325301 28.3325301
93 59.0325301 55.1325301
94 59.6325301 59.0325301
> 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/7skib1199885128.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> acf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/833ao1199885128.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> pacf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Partial Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/957bo1199885128.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> opar <- par(mfrow = c(2,2), oma = c(0, 0, 1.1, 0))
> plot(mylm, las = 1, sub='Residual Diagnostics')
> par(opar)
> dev.off()
null device
1
> load(file='/var/www/html/rcomp/createtable')
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a, 'Multiple Linear Regression - Estimated Regression Equation', 1, TRUE)
> a<-table.row.end(a)
> myeq <- colnames(x)[1]
> myeq <- paste(myeq, '[t] = ', sep='')
> for (i in 1:k){
+ if (mysum$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/109lvz1199885128.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/11bckl1199885128.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/12gmjq1199885128.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/13ahoh1199885128.tab")
>
> system("convert tmp/1b99m1199885127.ps tmp/1b99m1199885127.png")
> system("convert tmp/2tmc31199885127.ps tmp/2tmc31199885127.png")
> system("convert tmp/37nr81199885127.ps tmp/37nr81199885127.png")
> system("convert tmp/4qtek1199885127.ps tmp/4qtek1199885127.png")
> system("convert tmp/548yr1199885127.ps tmp/548yr1199885127.png")
> system("convert tmp/6lz0w1199885128.ps tmp/6lz0w1199885128.png")
> system("convert tmp/7skib1199885128.ps tmp/7skib1199885128.png")
> system("convert tmp/833ao1199885128.ps tmp/833ao1199885128.png")
> system("convert tmp/957bo1199885128.ps tmp/957bo1199885128.png")
>
>
> proc.time()
user system elapsed
2.437 1.559 2.884