R version 2.6.0 (2007-10-03)
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(97.3,0,101,0,113.2,0,101,0,105.7,0,113.9,0,86.4,0,96.5,0,103.3,0,114.9,0,105.8,0,94.2,0,98.4,0,99.4,0,108.8,0,112.6,0,104.4,0,112.2,0,81.1,0,97.1,0,112.6,0,113.8,0,107.8,0,103.2,0,103.3,0,101.2,0,107.7,0,110.4,0,101.9,0,115.9,0,89.9,0,88.6,0,117.2,0,123.9,0,100,0,103.6,0,94.1,0,98.7,0,119.5,0,112.7,0,104.4,0,124.7,0,89.1,0,97,0,121.6,0,118.8,0,114,0,111.5,0,97.2,0,102.5,0,113.4,0,109.8,0,104.9,0,126.1,0,80,0,96.8,0,117.2,1,112.3,1,117.3,1,111.1,1,102.2,1,104.3,1,122.9,1,107.6,1,121.3,1,131.5,1,89,1,104.4,1,128.9,1,135.9,1,133.3,1,121.3,1,120.5,1,120.4,1,137.9,1,126.1,1,133.2,1,146.6,1,103.4,1,117.2,1),dim=c(2,80),dimnames=list(c('y','x
'),1:80))
> y <- array(NA,dim=c(2,80),dimnames=list(c('y','x
'),1:80))
> 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 = '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
y x\r M1 M2 M3 M4 M5 M6 M7 M8 M9 M10 M11
1 97.3 0 1 0 0 0 0 0 0 0 0 0 0
2 101.0 0 0 1 0 0 0 0 0 0 0 0 0
3 113.2 0 0 0 1 0 0 0 0 0 0 0 0
4 101.0 0 0 0 0 1 0 0 0 0 0 0 0
5 105.7 0 0 0 0 0 1 0 0 0 0 0 0
6 113.9 0 0 0 0 0 0 1 0 0 0 0 0
7 86.4 0 0 0 0 0 0 0 1 0 0 0 0
8 96.5 0 0 0 0 0 0 0 0 1 0 0 0
9 103.3 0 0 0 0 0 0 0 0 0 1 0 0
10 114.9 0 0 0 0 0 0 0 0 0 0 1 0
11 105.8 0 0 0 0 0 0 0 0 0 0 0 1
12 94.2 0 0 0 0 0 0 0 0 0 0 0 0
13 98.4 0 1 0 0 0 0 0 0 0 0 0 0
14 99.4 0 0 1 0 0 0 0 0 0 0 0 0
15 108.8 0 0 0 1 0 0 0 0 0 0 0 0
16 112.6 0 0 0 0 1 0 0 0 0 0 0 0
17 104.4 0 0 0 0 0 1 0 0 0 0 0 0
18 112.2 0 0 0 0 0 0 1 0 0 0 0 0
19 81.1 0 0 0 0 0 0 0 1 0 0 0 0
20 97.1 0 0 0 0 0 0 0 0 1 0 0 0
21 112.6 0 0 0 0 0 0 0 0 0 1 0 0
22 113.8 0 0 0 0 0 0 0 0 0 0 1 0
23 107.8 0 0 0 0 0 0 0 0 0 0 0 1
24 103.2 0 0 0 0 0 0 0 0 0 0 0 0
25 103.3 0 1 0 0 0 0 0 0 0 0 0 0
26 101.2 0 0 1 0 0 0 0 0 0 0 0 0
27 107.7 0 0 0 1 0 0 0 0 0 0 0 0
28 110.4 0 0 0 0 1 0 0 0 0 0 0 0
29 101.9 0 0 0 0 0 1 0 0 0 0 0 0
30 115.9 0 0 0 0 0 0 1 0 0 0 0 0
31 89.9 0 0 0 0 0 0 0 1 0 0 0 0
32 88.6 0 0 0 0 0 0 0 0 1 0 0 0
33 117.2 0 0 0 0 0 0 0 0 0 1 0 0
34 123.9 0 0 0 0 0 0 0 0 0 0 1 0
35 100.0 0 0 0 0 0 0 0 0 0 0 0 1
36 103.6 0 0 0 0 0 0 0 0 0 0 0 0
37 94.1 0 1 0 0 0 0 0 0 0 0 0 0
38 98.7 0 0 1 0 0 0 0 0 0 0 0 0
39 119.5 0 0 0 1 0 0 0 0 0 0 0 0
40 112.7 0 0 0 0 1 0 0 0 0 0 0 0
41 104.4 0 0 0 0 0 1 0 0 0 0 0 0
42 124.7 0 0 0 0 0 0 1 0 0 0 0 0
43 89.1 0 0 0 0 0 0 0 1 0 0 0 0
44 97.0 0 0 0 0 0 0 0 0 1 0 0 0
45 121.6 0 0 0 0 0 0 0 0 0 1 0 0
46 118.8 0 0 0 0 0 0 0 0 0 0 1 0
47 114.0 0 0 0 0 0 0 0 0 0 0 0 1
48 111.5 0 0 0 0 0 0 0 0 0 0 0 0
49 97.2 0 1 0 0 0 0 0 0 0 0 0 0
50 102.5 0 0 1 0 0 0 0 0 0 0 0 0
51 113.4 0 0 0 1 0 0 0 0 0 0 0 0
52 109.8 0 0 0 0 1 0 0 0 0 0 0 0
53 104.9 0 0 0 0 0 1 0 0 0 0 0 0
54 126.1 0 0 0 0 0 0 1 0 0 0 0 0
55 80.0 0 0 0 0 0 0 0 1 0 0 0 0
56 96.8 0 0 0 0 0 0 0 0 1 0 0 0
57 117.2 1 0 0 0 0 0 0 0 0 1 0 0
58 112.3 1 0 0 0 0 0 0 0 0 0 1 0
59 117.3 1 0 0 0 0 0 0 0 0 0 0 1
60 111.1 1 0 0 0 0 0 0 0 0 0 0 0
61 102.2 1 1 0 0 0 0 0 0 0 0 0 0
62 104.3 1 0 1 0 0 0 0 0 0 0 0 0
63 122.9 1 0 0 1 0 0 0 0 0 0 0 0
64 107.6 1 0 0 0 1 0 0 0 0 0 0 0
65 121.3 1 0 0 0 0 1 0 0 0 0 0 0
66 131.5 1 0 0 0 0 0 1 0 0 0 0 0
67 89.0 1 0 0 0 0 0 0 1 0 0 0 0
68 104.4 1 0 0 0 0 0 0 0 1 0 0 0
69 128.9 1 0 0 0 0 0 0 0 0 1 0 0
70 135.9 1 0 0 0 0 0 0 0 0 0 1 0
71 133.3 1 0 0 0 0 0 0 0 0 0 0 1
72 121.3 1 0 0 0 0 0 0 0 0 0 0 0
73 120.5 1 1 0 0 0 0 0 0 0 0 0 0
74 120.4 1 0 1 0 0 0 0 0 0 0 0 0
75 137.9 1 0 0 1 0 0 0 0 0 0 0 0
76 126.1 1 0 0 0 1 0 0 0 0 0 0 0
77 133.2 1 0 0 0 0 1 0 0 0 0 0 0
78 146.6 1 0 0 0 0 0 1 0 0 0 0 0
79 103.4 1 0 0 0 0 0 0 1 0 0 0 0
80 117.2 1 0 0 0 0 0 0 0 1 0 0 0
> k <- length(x[1,])
> df <- as.data.frame(x)
> (mylm <- lm(df))
Call:
lm(formula = df)
Coefficients:
(Intercept) `x\r` M1 M2 M3 M4
102.811 14.016 -4.959 -2.887 10.813 4.641
M5 M6 M7 M8 M9 M10
4.013 17.598 -18.402 -7.159 9.317 12.450
M11
5.550
> (mysum <- summary(mylm))
Call:
lm(formula = df)
Residuals:
Min 1Q Median 3Q Max
-16.9771 -4.5673 0.4244 4.7613 12.3603
Coefficients:
Estimate Std. Error t value Pr(>|t|)
(Intercept) 102.811 2.755 37.317 < 2e-16 ***
`x\r` 14.016 1.616 8.670 1.49e-12 ***
M1 -4.959 3.683 -1.346 0.18269
M2 -2.887 3.683 -0.784 0.43580
M3 10.813 3.683 2.936 0.00455 **
M4 4.641 3.683 1.260 0.21195
M5 4.013 3.683 1.090 0.27981
M6 17.598 3.683 4.779 1.00e-05 ***
M7 -18.402 3.683 -4.997 4.43e-06 ***
M8 -7.159 3.683 -1.944 0.05612 .
M9 9.317 3.821 2.438 0.01742 *
M10 12.450 3.821 3.258 0.00176 **
M11 5.550 3.821 1.453 0.15103
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
Residual standard error: 6.618 on 67 degrees of freedom
Multiple R-Squared: 0.7869, Adjusted R-squared: 0.7488
F-statistic: 20.62 on 12 and 67 DF, p-value: < 2.2e-16
> postscript(file="/var/www/html/rcomp/tmp/1ueml1196781355.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/2o3931196781355.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> plot(mysum$resid, type='b', pch=19, main='Residuals', ylab='value of Residuals', xlab='time or index')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/3qzys1196781355.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> hist(mysum$resid, main='Residual Histogram', xlab='values of Residuals')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/4mo4s1196781355.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> densityplot(~mysum$resid,col='black',main='Residual Density Plot', xlab='values of Residuals')
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/5f4be1196781355.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> qqnorm(mysum$resid, main='Residual Normal Q-Q Plot')
> grid()
> dev.off()
null device
1
> (myerror <- as.ts(mysum$resid))
Time Series:
Start = 1
End = 80
Frequency = 1
1 2 3 4 5 6
-0.5526786 1.0758929 -0.4241071 -6.4526786 -1.1241071 -6.5098214
7 8 9 10 11 12
1.9901786 0.8473214 -8.8281250 -0.3614583 -2.5614583 -8.6114583
13 14 15 16 17 18
0.5473214 -0.5241071 -4.8241071 5.1473214 -2.4241071 -8.2098214
19 20 21 22 23 24
-3.3098214 1.4473214 0.4718750 -1.4614583 -0.5614583 0.3885417
25 26 27 28 29 30
5.4473214 1.2758929 -5.9241071 2.9473214 -4.9241071 -4.5098214
31 32 33 34 35 36
5.4901786 -7.0526786 5.0718750 8.6385417 -8.3614583 0.7885417
37 38 39 40 41 42
-3.7526786 -1.2241071 5.8758929 5.2473214 -2.4241071 4.2901786
43 44 45 46 47 48
4.6901786 1.3473214 9.4718750 3.5385417 5.6385417 8.6885417
49 50 51 52 53 54
-0.6526786 2.5758929 -0.2241071 2.3473214 -1.9241071 5.6901786
55 56 57 58 59 60
-4.4098214 1.1473214 -8.9437500 -16.9770833 -5.0770833 -5.7270833
61 62 63 64 65 66
-9.6683036 -9.6397321 -4.7397321 -13.8683036 0.4602679 -2.9254464
67 68 69 70 71 72
-9.4254464 -5.2683036 2.7562500 6.6229167 10.9229167 4.4729167
73 74 75 76 77 78
8.6316964 6.4602679 10.2602679 4.6316964 12.3602679 12.1745536
79 80
4.9745536 7.5316964
> postscript(file="/var/www/html/rcomp/tmp/6ebdp1196781355.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 = 80
Frequency = 1
lag(myerror, k = 1) myerror
0 -0.5526786 NA
1 1.0758929 -0.5526786
2 -0.4241071 1.0758929
3 -6.4526786 -0.4241071
4 -1.1241071 -6.4526786
5 -6.5098214 -1.1241071
6 1.9901786 -6.5098214
7 0.8473214 1.9901786
8 -8.8281250 0.8473214
9 -0.3614583 -8.8281250
10 -2.5614583 -0.3614583
11 -8.6114583 -2.5614583
12 0.5473214 -8.6114583
13 -0.5241071 0.5473214
14 -4.8241071 -0.5241071
15 5.1473214 -4.8241071
16 -2.4241071 5.1473214
17 -8.2098214 -2.4241071
18 -3.3098214 -8.2098214
19 1.4473214 -3.3098214
20 0.4718750 1.4473214
21 -1.4614583 0.4718750
22 -0.5614583 -1.4614583
23 0.3885417 -0.5614583
24 5.4473214 0.3885417
25 1.2758929 5.4473214
26 -5.9241071 1.2758929
27 2.9473214 -5.9241071
28 -4.9241071 2.9473214
29 -4.5098214 -4.9241071
30 5.4901786 -4.5098214
31 -7.0526786 5.4901786
32 5.0718750 -7.0526786
33 8.6385417 5.0718750
34 -8.3614583 8.6385417
35 0.7885417 -8.3614583
36 -3.7526786 0.7885417
37 -1.2241071 -3.7526786
38 5.8758929 -1.2241071
39 5.2473214 5.8758929
40 -2.4241071 5.2473214
41 4.2901786 -2.4241071
42 4.6901786 4.2901786
43 1.3473214 4.6901786
44 9.4718750 1.3473214
45 3.5385417 9.4718750
46 5.6385417 3.5385417
47 8.6885417 5.6385417
48 -0.6526786 8.6885417
49 2.5758929 -0.6526786
50 -0.2241071 2.5758929
51 2.3473214 -0.2241071
52 -1.9241071 2.3473214
53 5.6901786 -1.9241071
54 -4.4098214 5.6901786
55 1.1473214 -4.4098214
56 -8.9437500 1.1473214
57 -16.9770833 -8.9437500
58 -5.0770833 -16.9770833
59 -5.7270833 -5.0770833
60 -9.6683036 -5.7270833
61 -9.6397321 -9.6683036
62 -4.7397321 -9.6397321
63 -13.8683036 -4.7397321
64 0.4602679 -13.8683036
65 -2.9254464 0.4602679
66 -9.4254464 -2.9254464
67 -5.2683036 -9.4254464
68 2.7562500 -5.2683036
69 6.6229167 2.7562500
70 10.9229167 6.6229167
71 4.4729167 10.9229167
72 8.6316964 4.4729167
73 6.4602679 8.6316964
74 10.2602679 6.4602679
75 4.6316964 10.2602679
76 12.3602679 4.6316964
77 12.1745536 12.3602679
78 4.9745536 12.1745536
79 7.5316964 4.9745536
80 NA 7.5316964
> dum1 <- dum[2:length(myerror),]
> dum1
lag(myerror, k = 1) myerror
[1,] 1.0758929 -0.5526786
[2,] -0.4241071 1.0758929
[3,] -6.4526786 -0.4241071
[4,] -1.1241071 -6.4526786
[5,] -6.5098214 -1.1241071
[6,] 1.9901786 -6.5098214
[7,] 0.8473214 1.9901786
[8,] -8.8281250 0.8473214
[9,] -0.3614583 -8.8281250
[10,] -2.5614583 -0.3614583
[11,] -8.6114583 -2.5614583
[12,] 0.5473214 -8.6114583
[13,] -0.5241071 0.5473214
[14,] -4.8241071 -0.5241071
[15,] 5.1473214 -4.8241071
[16,] -2.4241071 5.1473214
[17,] -8.2098214 -2.4241071
[18,] -3.3098214 -8.2098214
[19,] 1.4473214 -3.3098214
[20,] 0.4718750 1.4473214
[21,] -1.4614583 0.4718750
[22,] -0.5614583 -1.4614583
[23,] 0.3885417 -0.5614583
[24,] 5.4473214 0.3885417
[25,] 1.2758929 5.4473214
[26,] -5.9241071 1.2758929
[27,] 2.9473214 -5.9241071
[28,] -4.9241071 2.9473214
[29,] -4.5098214 -4.9241071
[30,] 5.4901786 -4.5098214
[31,] -7.0526786 5.4901786
[32,] 5.0718750 -7.0526786
[33,] 8.6385417 5.0718750
[34,] -8.3614583 8.6385417
[35,] 0.7885417 -8.3614583
[36,] -3.7526786 0.7885417
[37,] -1.2241071 -3.7526786
[38,] 5.8758929 -1.2241071
[39,] 5.2473214 5.8758929
[40,] -2.4241071 5.2473214
[41,] 4.2901786 -2.4241071
[42,] 4.6901786 4.2901786
[43,] 1.3473214 4.6901786
[44,] 9.4718750 1.3473214
[45,] 3.5385417 9.4718750
[46,] 5.6385417 3.5385417
[47,] 8.6885417 5.6385417
[48,] -0.6526786 8.6885417
[49,] 2.5758929 -0.6526786
[50,] -0.2241071 2.5758929
[51,] 2.3473214 -0.2241071
[52,] -1.9241071 2.3473214
[53,] 5.6901786 -1.9241071
[54,] -4.4098214 5.6901786
[55,] 1.1473214 -4.4098214
[56,] -8.9437500 1.1473214
[57,] -16.9770833 -8.9437500
[58,] -5.0770833 -16.9770833
[59,] -5.7270833 -5.0770833
[60,] -9.6683036 -5.7270833
[61,] -9.6397321 -9.6683036
[62,] -4.7397321 -9.6397321
[63,] -13.8683036 -4.7397321
[64,] 0.4602679 -13.8683036
[65,] -2.9254464 0.4602679
[66,] -9.4254464 -2.9254464
[67,] -5.2683036 -9.4254464
[68,] 2.7562500 -5.2683036
[69,] 6.6229167 2.7562500
[70,] 10.9229167 6.6229167
[71,] 4.4729167 10.9229167
[72,] 8.6316964 4.4729167
[73,] 6.4602679 8.6316964
[74,] 10.2602679 6.4602679
[75,] 4.6316964 10.2602679
[76,] 12.3602679 4.6316964
[77,] 12.1745536 12.3602679
[78,] 4.9745536 12.1745536
[79,] 7.5316964 4.9745536
> z <- as.data.frame(dum1)
> z
lag(myerror, k = 1) myerror
1 1.0758929 -0.5526786
2 -0.4241071 1.0758929
3 -6.4526786 -0.4241071
4 -1.1241071 -6.4526786
5 -6.5098214 -1.1241071
6 1.9901786 -6.5098214
7 0.8473214 1.9901786
8 -8.8281250 0.8473214
9 -0.3614583 -8.8281250
10 -2.5614583 -0.3614583
11 -8.6114583 -2.5614583
12 0.5473214 -8.6114583
13 -0.5241071 0.5473214
14 -4.8241071 -0.5241071
15 5.1473214 -4.8241071
16 -2.4241071 5.1473214
17 -8.2098214 -2.4241071
18 -3.3098214 -8.2098214
19 1.4473214 -3.3098214
20 0.4718750 1.4473214
21 -1.4614583 0.4718750
22 -0.5614583 -1.4614583
23 0.3885417 -0.5614583
24 5.4473214 0.3885417
25 1.2758929 5.4473214
26 -5.9241071 1.2758929
27 2.9473214 -5.9241071
28 -4.9241071 2.9473214
29 -4.5098214 -4.9241071
30 5.4901786 -4.5098214
31 -7.0526786 5.4901786
32 5.0718750 -7.0526786
33 8.6385417 5.0718750
34 -8.3614583 8.6385417
35 0.7885417 -8.3614583
36 -3.7526786 0.7885417
37 -1.2241071 -3.7526786
38 5.8758929 -1.2241071
39 5.2473214 5.8758929
40 -2.4241071 5.2473214
41 4.2901786 -2.4241071
42 4.6901786 4.2901786
43 1.3473214 4.6901786
44 9.4718750 1.3473214
45 3.5385417 9.4718750
46 5.6385417 3.5385417
47 8.6885417 5.6385417
48 -0.6526786 8.6885417
49 2.5758929 -0.6526786
50 -0.2241071 2.5758929
51 2.3473214 -0.2241071
52 -1.9241071 2.3473214
53 5.6901786 -1.9241071
54 -4.4098214 5.6901786
55 1.1473214 -4.4098214
56 -8.9437500 1.1473214
57 -16.9770833 -8.9437500
58 -5.0770833 -16.9770833
59 -5.7270833 -5.0770833
60 -9.6683036 -5.7270833
61 -9.6397321 -9.6683036
62 -4.7397321 -9.6397321
63 -13.8683036 -4.7397321
64 0.4602679 -13.8683036
65 -2.9254464 0.4602679
66 -9.4254464 -2.9254464
67 -5.2683036 -9.4254464
68 2.7562500 -5.2683036
69 6.6229167 2.7562500
70 10.9229167 6.6229167
71 4.4729167 10.9229167
72 8.6316964 4.4729167
73 6.4602679 8.6316964
74 10.2602679 6.4602679
75 4.6316964 10.2602679
76 12.3602679 4.6316964
77 12.1745536 12.3602679
78 4.9745536 12.1745536
79 7.5316964 4.9745536
> 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/7pkhq1196781355.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> acf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/86iqz1196781355.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> pacf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Partial Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/9z0851196781355.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> opar <- par(mfrow = c(2,2), oma = c(0, 0, 1.1, 0))
> plot(mylm, las = 1, sub='Residual Diagnostics')
> par(opar)
> dev.off()
null device
1
> load(file='/var/www/html/rcomp/createtable')
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a, 'Multiple Linear Regression - Estimated Regression Equation', 1, TRUE)
> a<-table.row.end(a)
> myeq <- colnames(x)[1]
> myeq <- paste(myeq, '[t] = ', sep='')
> for (i in 1:k){
+ if (mysum$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/10apni1196781356.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/119ufq1196781356.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/12j6ne1196781356.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/13wq4h1196781356.tab")
>
> system("convert tmp/1ueml1196781355.ps tmp/1ueml1196781355.png")
> system("convert tmp/2o3931196781355.ps tmp/2o3931196781355.png")
> system("convert tmp/3qzys1196781355.ps tmp/3qzys1196781355.png")
> system("convert tmp/4mo4s1196781355.ps tmp/4mo4s1196781355.png")
> system("convert tmp/5f4be1196781355.ps tmp/5f4be1196781355.png")
> system("convert tmp/6ebdp1196781355.ps tmp/6ebdp1196781355.png")
> system("convert tmp/7pkhq1196781355.ps tmp/7pkhq1196781355.png")
> system("convert tmp/86iqz1196781355.ps tmp/86iqz1196781355.png")
> system("convert tmp/9z0851196781355.ps tmp/9z0851196781355.png")
>
>
> proc.time()
user system elapsed
2.368 1.471 2.731