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.
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(10.400,1,10.800,1,10.600,1,11.200,1,11.800,1,11.300,1,10.800,1,10.600,1,10.900,1,10.200,1,10.100,1,10.100,1,10.000,1,10.100,0,10.300,0,10.900,0,10.700,0,10.500,0,10.600,0,10.600,0,10.800,0,10.700,0,10.400,0,10.400,0,10.600,0,10.900,0,10.900,0,10.500,0,10.100,0,10.200,0,10.300,0,10.600,0,10.800,0,10.500,0,10.500,0,10.500,0,10.400,0,10.500,0,10.700,0,11.000,0,11.600,0,11.600,0,11.700,0,11.700,0,11.800,0,12.100,0,11.800,0,11.300,0,11.200,0,11.700,0,11.900,0,12.600,0,12.500,0,12.800,0,13.500,0,13.900,0,14.500,0,14.100,0,13.200,0,13.100,0,13.300,0,13.200,0,13.200,0,14.000,0,14.300,0,14.300,0,14.500,0,14.500,1,13.300,1,12.700,1,12.700,1,12.900,1,12.500,1,12.600,0,13.200,0,13.600,0,14.000,0,14.100,0,14.200,0,13.900,0,13.800,0,14.100,0,14.700,0,14.400,0,14.700,0,14.500,0,14.700,0,14.900,0,15.400,0,16.100,0,16.300,0),dim=c(2,91),dimnames=list(c('Y','D'),1:91))
> y <- array(NA,dim=c(2,91),dimnames=list(c('Y','D'),1:91))
> 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
Y D
1 10.4 1
2 10.8 1
3 10.6 1
4 11.2 1
5 11.8 1
6 11.3 1
7 10.8 1
8 10.6 1
9 10.9 1
10 10.2 1
11 10.1 1
12 10.1 1
13 10.0 1
14 10.1 0
15 10.3 0
16 10.9 0
17 10.7 0
18 10.5 0
19 10.6 0
20 10.6 0
21 10.8 0
22 10.7 0
23 10.4 0
24 10.4 0
25 10.6 0
26 10.9 0
27 10.9 0
28 10.5 0
29 10.1 0
30 10.2 0
31 10.3 0
32 10.6 0
33 10.8 0
34 10.5 0
35 10.5 0
36 10.5 0
37 10.4 0
38 10.5 0
39 10.7 0
40 11.0 0
41 11.6 0
42 11.6 0
43 11.7 0
44 11.7 0
45 11.8 0
46 12.1 0
47 11.8 0
48 11.3 0
49 11.2 0
50 11.7 0
51 11.9 0
52 12.6 0
53 12.5 0
54 12.8 0
55 13.5 0
56 13.9 0
57 14.5 0
58 14.1 0
59 13.2 0
60 13.1 0
61 13.3 0
62 13.2 0
63 13.2 0
64 14.0 0
65 14.3 0
66 14.3 0
67 14.5 0
68 14.5 1
69 13.3 1
70 12.7 1
71 12.7 1
72 12.9 1
73 12.5 1
74 12.6 0
75 13.2 0
76 13.6 0
77 14.0 0
78 14.1 0
79 14.2 0
80 13.9 0
81 13.8 0
82 14.1 0
83 14.7 0
84 14.4 0
85 14.7 0
86 14.5 0
87 14.7 0
88 14.9 0
89 15.4 0
90 16.1 0
91 16.3 0
> k <- length(x[1,])
> df <- as.data.frame(x)
> (mylm <- lm(df))
Call:
lm(formula = df)
Coefficients:
(Intercept) D
12.3556 -0.9135
> (mysum <- summary(mylm))
Call:
lm(formula = df)
Residuals:
Min 1Q Median 3Q Max
-2.2556 -1.5056 -0.5421 1.5012 3.9444
Coefficients:
Estimate Std. Error t value Pr(>|t|)
(Intercept) 12.3556 0.1954 63.232 <2e-16 ***
D -0.9135 0.4276 -2.136 0.0354 *
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
Residual standard error: 1.658 on 89 degrees of freedom
Multiple R-squared: 0.04877, Adjusted R-squared: 0.03808
F-statistic: 4.563 on 1 and 89 DF, p-value: 0.03542
> postscript(file="/var/www/html/rcomp/tmp/1xey11227572372.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/2sx4r1227572372.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> plot(mysum$resid, type='b', pch=19, main='Residuals', ylab='value of Residuals', xlab='time or index')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/3q70s1227572372.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> hist(mysum$resid, main='Residual Histogram', xlab='values of Residuals')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/4dxk01227572372.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> densityplot(~mysum$resid,col='black',main='Residual Density Plot', xlab='values of Residuals')
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/5bzf41227572372.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> qqnorm(mysum$resid, main='Residual Normal Q-Q Plot')
> grid()
> dev.off()
null device
1
> (myerror <- as.ts(mysum$resid))
Time Series:
Start = 1
End = 91
Frequency = 1
1 2 3 4 5 6 7
-1.0421053 -0.6421053 -0.8421053 -0.2421053 0.3578947 -0.1421053 -0.6421053
8 9 10 11 12 13 14
-0.8421053 -0.5421053 -1.2421053 -1.3421053 -1.3421053 -1.4421053 -2.2555556
15 16 17 18 19 20 21
-2.0555556 -1.4555556 -1.6555556 -1.8555556 -1.7555556 -1.7555556 -1.5555556
22 23 24 25 26 27 28
-1.6555556 -1.9555556 -1.9555556 -1.7555556 -1.4555556 -1.4555556 -1.8555556
29 30 31 32 33 34 35
-2.2555556 -2.1555556 -2.0555556 -1.7555556 -1.5555556 -1.8555556 -1.8555556
36 37 38 39 40 41 42
-1.8555556 -1.9555556 -1.8555556 -1.6555556 -1.3555556 -0.7555556 -0.7555556
43 44 45 46 47 48 49
-0.6555556 -0.6555556 -0.5555556 -0.2555556 -0.5555556 -1.0555556 -1.1555556
50 51 52 53 54 55 56
-0.6555556 -0.4555556 0.2444444 0.1444444 0.4444444 1.1444444 1.5444444
57 58 59 60 61 62 63
2.1444444 1.7444444 0.8444444 0.7444444 0.9444444 0.8444444 0.8444444
64 65 66 67 68 69 70
1.6444444 1.9444444 1.9444444 2.1444444 3.0578947 1.8578947 1.2578947
71 72 73 74 75 76 77
1.2578947 1.4578947 1.0578947 0.2444444 0.8444444 1.2444444 1.6444444
78 79 80 81 82 83 84
1.7444444 1.8444444 1.5444444 1.4444444 1.7444444 2.3444444 2.0444444
85 86 87 88 89 90 91
2.3444444 2.1444444 2.3444444 2.5444444 3.0444444 3.7444444 3.9444444
> postscript(file="/var/www/html/rcomp/tmp/6prpk1227572372.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 = 91
Frequency = 1
lag(myerror, k = 1) myerror
0 -1.0421053 NA
1 -0.6421053 -1.0421053
2 -0.8421053 -0.6421053
3 -0.2421053 -0.8421053
4 0.3578947 -0.2421053
5 -0.1421053 0.3578947
6 -0.6421053 -0.1421053
7 -0.8421053 -0.6421053
8 -0.5421053 -0.8421053
9 -1.2421053 -0.5421053
10 -1.3421053 -1.2421053
11 -1.3421053 -1.3421053
12 -1.4421053 -1.3421053
13 -2.2555556 -1.4421053
14 -2.0555556 -2.2555556
15 -1.4555556 -2.0555556
16 -1.6555556 -1.4555556
17 -1.8555556 -1.6555556
18 -1.7555556 -1.8555556
19 -1.7555556 -1.7555556
20 -1.5555556 -1.7555556
21 -1.6555556 -1.5555556
22 -1.9555556 -1.6555556
23 -1.9555556 -1.9555556
24 -1.7555556 -1.9555556
25 -1.4555556 -1.7555556
26 -1.4555556 -1.4555556
27 -1.8555556 -1.4555556
28 -2.2555556 -1.8555556
29 -2.1555556 -2.2555556
30 -2.0555556 -2.1555556
31 -1.7555556 -2.0555556
32 -1.5555556 -1.7555556
33 -1.8555556 -1.5555556
34 -1.8555556 -1.8555556
35 -1.8555556 -1.8555556
36 -1.9555556 -1.8555556
37 -1.8555556 -1.9555556
38 -1.6555556 -1.8555556
39 -1.3555556 -1.6555556
40 -0.7555556 -1.3555556
41 -0.7555556 -0.7555556
42 -0.6555556 -0.7555556
43 -0.6555556 -0.6555556
44 -0.5555556 -0.6555556
45 -0.2555556 -0.5555556
46 -0.5555556 -0.2555556
47 -1.0555556 -0.5555556
48 -1.1555556 -1.0555556
49 -0.6555556 -1.1555556
50 -0.4555556 -0.6555556
51 0.2444444 -0.4555556
52 0.1444444 0.2444444
53 0.4444444 0.1444444
54 1.1444444 0.4444444
55 1.5444444 1.1444444
56 2.1444444 1.5444444
57 1.7444444 2.1444444
58 0.8444444 1.7444444
59 0.7444444 0.8444444
60 0.9444444 0.7444444
61 0.8444444 0.9444444
62 0.8444444 0.8444444
63 1.6444444 0.8444444
64 1.9444444 1.6444444
65 1.9444444 1.9444444
66 2.1444444 1.9444444
67 3.0578947 2.1444444
68 1.8578947 3.0578947
69 1.2578947 1.8578947
70 1.2578947 1.2578947
71 1.4578947 1.2578947
72 1.0578947 1.4578947
73 0.2444444 1.0578947
74 0.8444444 0.2444444
75 1.2444444 0.8444444
76 1.6444444 1.2444444
77 1.7444444 1.6444444
78 1.8444444 1.7444444
79 1.5444444 1.8444444
80 1.4444444 1.5444444
81 1.7444444 1.4444444
82 2.3444444 1.7444444
83 2.0444444 2.3444444
84 2.3444444 2.0444444
85 2.1444444 2.3444444
86 2.3444444 2.1444444
87 2.5444444 2.3444444
88 3.0444444 2.5444444
89 3.7444444 3.0444444
90 3.9444444 3.7444444
91 NA 3.9444444
> dum1 <- dum[2:length(myerror),]
> dum1
lag(myerror, k = 1) myerror
[1,] -0.6421053 -1.0421053
[2,] -0.8421053 -0.6421053
[3,] -0.2421053 -0.8421053
[4,] 0.3578947 -0.2421053
[5,] -0.1421053 0.3578947
[6,] -0.6421053 -0.1421053
[7,] -0.8421053 -0.6421053
[8,] -0.5421053 -0.8421053
[9,] -1.2421053 -0.5421053
[10,] -1.3421053 -1.2421053
[11,] -1.3421053 -1.3421053
[12,] -1.4421053 -1.3421053
[13,] -2.2555556 -1.4421053
[14,] -2.0555556 -2.2555556
[15,] -1.4555556 -2.0555556
[16,] -1.6555556 -1.4555556
[17,] -1.8555556 -1.6555556
[18,] -1.7555556 -1.8555556
[19,] -1.7555556 -1.7555556
[20,] -1.5555556 -1.7555556
[21,] -1.6555556 -1.5555556
[22,] -1.9555556 -1.6555556
[23,] -1.9555556 -1.9555556
[24,] -1.7555556 -1.9555556
[25,] -1.4555556 -1.7555556
[26,] -1.4555556 -1.4555556
[27,] -1.8555556 -1.4555556
[28,] -2.2555556 -1.8555556
[29,] -2.1555556 -2.2555556
[30,] -2.0555556 -2.1555556
[31,] -1.7555556 -2.0555556
[32,] -1.5555556 -1.7555556
[33,] -1.8555556 -1.5555556
[34,] -1.8555556 -1.8555556
[35,] -1.8555556 -1.8555556
[36,] -1.9555556 -1.8555556
[37,] -1.8555556 -1.9555556
[38,] -1.6555556 -1.8555556
[39,] -1.3555556 -1.6555556
[40,] -0.7555556 -1.3555556
[41,] -0.7555556 -0.7555556
[42,] -0.6555556 -0.7555556
[43,] -0.6555556 -0.6555556
[44,] -0.5555556 -0.6555556
[45,] -0.2555556 -0.5555556
[46,] -0.5555556 -0.2555556
[47,] -1.0555556 -0.5555556
[48,] -1.1555556 -1.0555556
[49,] -0.6555556 -1.1555556
[50,] -0.4555556 -0.6555556
[51,] 0.2444444 -0.4555556
[52,] 0.1444444 0.2444444
[53,] 0.4444444 0.1444444
[54,] 1.1444444 0.4444444
[55,] 1.5444444 1.1444444
[56,] 2.1444444 1.5444444
[57,] 1.7444444 2.1444444
[58,] 0.8444444 1.7444444
[59,] 0.7444444 0.8444444
[60,] 0.9444444 0.7444444
[61,] 0.8444444 0.9444444
[62,] 0.8444444 0.8444444
[63,] 1.6444444 0.8444444
[64,] 1.9444444 1.6444444
[65,] 1.9444444 1.9444444
[66,] 2.1444444 1.9444444
[67,] 3.0578947 2.1444444
[68,] 1.8578947 3.0578947
[69,] 1.2578947 1.8578947
[70,] 1.2578947 1.2578947
[71,] 1.4578947 1.2578947
[72,] 1.0578947 1.4578947
[73,] 0.2444444 1.0578947
[74,] 0.8444444 0.2444444
[75,] 1.2444444 0.8444444
[76,] 1.6444444 1.2444444
[77,] 1.7444444 1.6444444
[78,] 1.8444444 1.7444444
[79,] 1.5444444 1.8444444
[80,] 1.4444444 1.5444444
[81,] 1.7444444 1.4444444
[82,] 2.3444444 1.7444444
[83,] 2.0444444 2.3444444
[84,] 2.3444444 2.0444444
[85,] 2.1444444 2.3444444
[86,] 2.3444444 2.1444444
[87,] 2.5444444 2.3444444
[88,] 3.0444444 2.5444444
[89,] 3.7444444 3.0444444
[90,] 3.9444444 3.7444444
> z <- as.data.frame(dum1)
> z
lag(myerror, k = 1) myerror
1 -0.6421053 -1.0421053
2 -0.8421053 -0.6421053
3 -0.2421053 -0.8421053
4 0.3578947 -0.2421053
5 -0.1421053 0.3578947
6 -0.6421053 -0.1421053
7 -0.8421053 -0.6421053
8 -0.5421053 -0.8421053
9 -1.2421053 -0.5421053
10 -1.3421053 -1.2421053
11 -1.3421053 -1.3421053
12 -1.4421053 -1.3421053
13 -2.2555556 -1.4421053
14 -2.0555556 -2.2555556
15 -1.4555556 -2.0555556
16 -1.6555556 -1.4555556
17 -1.8555556 -1.6555556
18 -1.7555556 -1.8555556
19 -1.7555556 -1.7555556
20 -1.5555556 -1.7555556
21 -1.6555556 -1.5555556
22 -1.9555556 -1.6555556
23 -1.9555556 -1.9555556
24 -1.7555556 -1.9555556
25 -1.4555556 -1.7555556
26 -1.4555556 -1.4555556
27 -1.8555556 -1.4555556
28 -2.2555556 -1.8555556
29 -2.1555556 -2.2555556
30 -2.0555556 -2.1555556
31 -1.7555556 -2.0555556
32 -1.5555556 -1.7555556
33 -1.8555556 -1.5555556
34 -1.8555556 -1.8555556
35 -1.8555556 -1.8555556
36 -1.9555556 -1.8555556
37 -1.8555556 -1.9555556
38 -1.6555556 -1.8555556
39 -1.3555556 -1.6555556
40 -0.7555556 -1.3555556
41 -0.7555556 -0.7555556
42 -0.6555556 -0.7555556
43 -0.6555556 -0.6555556
44 -0.5555556 -0.6555556
45 -0.2555556 -0.5555556
46 -0.5555556 -0.2555556
47 -1.0555556 -0.5555556
48 -1.1555556 -1.0555556
49 -0.6555556 -1.1555556
50 -0.4555556 -0.6555556
51 0.2444444 -0.4555556
52 0.1444444 0.2444444
53 0.4444444 0.1444444
54 1.1444444 0.4444444
55 1.5444444 1.1444444
56 2.1444444 1.5444444
57 1.7444444 2.1444444
58 0.8444444 1.7444444
59 0.7444444 0.8444444
60 0.9444444 0.7444444
61 0.8444444 0.9444444
62 0.8444444 0.8444444
63 1.6444444 0.8444444
64 1.9444444 1.6444444
65 1.9444444 1.9444444
66 2.1444444 1.9444444
67 3.0578947 2.1444444
68 1.8578947 3.0578947
69 1.2578947 1.8578947
70 1.2578947 1.2578947
71 1.4578947 1.2578947
72 1.0578947 1.4578947
73 0.2444444 1.0578947
74 0.8444444 0.2444444
75 1.2444444 0.8444444
76 1.6444444 1.2444444
77 1.7444444 1.6444444
78 1.8444444 1.7444444
79 1.5444444 1.8444444
80 1.4444444 1.5444444
81 1.7444444 1.4444444
82 2.3444444 1.7444444
83 2.0444444 2.3444444
84 2.3444444 2.0444444
85 2.1444444 2.3444444
86 2.3444444 2.1444444
87 2.5444444 2.3444444
88 3.0444444 2.5444444
89 3.7444444 3.0444444
90 3.9444444 3.7444444
> 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/7dvkz1227572372.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> acf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/864741227572372.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> pacf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Partial Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/9gzz61227572372.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> opar <- par(mfrow = c(2,2), oma = c(0, 0, 1.1, 0))
> plot(mylm, las = 1, sub='Residual Diagnostics')
> par(opar)
> dev.off()
null device
1
>
> #Note: the /var/www/html/rcomp/createtable file can be downloaded at http://www.wessa.net/cretab
> load(file="/var/www/html/rcomp/createtable")
>
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a, 'Multiple Linear Regression - Estimated Regression Equation', 1, TRUE)
> a<-table.row.end(a)
> myeq <- colnames(x)[1]
> myeq <- paste(myeq, '[t] = ', sep='')
> for (i in 1:k){
+ if (mysum$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/108plj1227572372.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/11y4ag1227572372.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/12h3hm1227572372.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/139vme1227572372.tab")
>
> system("convert tmp/1xey11227572372.ps tmp/1xey11227572372.png")
> system("convert tmp/2sx4r1227572372.ps tmp/2sx4r1227572372.png")
> system("convert tmp/3q70s1227572372.ps tmp/3q70s1227572372.png")
> system("convert tmp/4dxk01227572372.ps tmp/4dxk01227572372.png")
> system("convert tmp/5bzf41227572372.ps tmp/5bzf41227572372.png")
> system("convert tmp/6prpk1227572372.ps tmp/6prpk1227572372.png")
> system("convert tmp/7dvkz1227572372.ps tmp/7dvkz1227572372.png")
> system("convert tmp/864741227572372.ps tmp/864741227572372.png")
> system("convert tmp/9gzz61227572372.ps tmp/9gzz61227572372.png")
>
>
> proc.time()
user system elapsed
1.950 1.463 2.360