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(36409,0,33163,0,34122,0,35225,0,28249,0,30374,0,26311,0,22069,0,23651,0,28628,0,23187,0,14727,0,43080,0,32519,0,39657,0,33614,0,28671,0,34243,0,27336,0,22916,0,24537,0,26128,0,22602,0,15744,0,41086,0,39690,0,43129,0,37863,0,35953,0,29133,0,24693,0,22205,0,21725,0,27192,0,21790,0,13253,0,37702,0,30364,0,32609,0,30212,0,29965,0,28352,0,25814,0,22414,0,20506,0,28806,0,22228,0,13971,0,36845,0,35338,0,35022,0,34777,0,26887,0,23970,0,22780,0,17351,0,21382,0,24561,0,17409,0,11514,0,31514,0,27071,0,29462,0,26105,0,22397,0,23843,0,21705,0,18089,0,20764,0,25316,0,17704,0,15548,0,28029,0,29383,0,36438,0,32034,0,22679,0,24319,0,18004,0,17537,0,20366,0,22782,0,19169,0,13807,0,29743,0,25591,0,29096,1,26482,1,22405,1,27044,1,17970,1,18730,1,19684,1,19785,1,18479,1,10698,1),dim=c(2,96),dimnames=list(c('Y(t)','X1dum'),1:96))
> y <- array(NA,dim=c(2,96),dimnames=list(c('Y(t)','X1dum'),1:96))
> 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(t) X1dum
1 36409 0
2 33163 0
3 34122 0
4 35225 0
5 28249 0
6 30374 0
7 26311 0
8 22069 0
9 23651 0
10 28628 0
11 23187 0
12 14727 0
13 43080 0
14 32519 0
15 39657 0
16 33614 0
17 28671 0
18 34243 0
19 27336 0
20 22916 0
21 24537 0
22 26128 0
23 22602 0
24 15744 0
25 41086 0
26 39690 0
27 43129 0
28 37863 0
29 35953 0
30 29133 0
31 24693 0
32 22205 0
33 21725 0
34 27192 0
35 21790 0
36 13253 0
37 37702 0
38 30364 0
39 32609 0
40 30212 0
41 29965 0
42 28352 0
43 25814 0
44 22414 0
45 20506 0
46 28806 0
47 22228 0
48 13971 0
49 36845 0
50 35338 0
51 35022 0
52 34777 0
53 26887 0
54 23970 0
55 22780 0
56 17351 0
57 21382 0
58 24561 0
59 17409 0
60 11514 0
61 31514 0
62 27071 0
63 29462 0
64 26105 0
65 22397 0
66 23843 0
67 21705 0
68 18089 0
69 20764 0
70 25316 0
71 17704 0
72 15548 0
73 28029 0
74 29383 0
75 36438 0
76 32034 0
77 22679 0
78 24319 0
79 18004 0
80 17537 0
81 20366 0
82 22782 0
83 19169 0
84 13807 0
85 29743 0
86 25591 0
87 29096 1
88 26482 1
89 22405 1
90 27044 1
91 17970 1
92 18730 1
93 19684 1
94 19785 1
95 18479 1
96 10698 1
> k <- length(x[1,])
> df <- as.data.frame(x)
> (mylm <- lm(df))
Call:
lm(formula = df)
Coefficients:
(Intercept) X1dum
26687 -5649
> (mysum <- summary(mylm))
Call:
lm(formula = df)
Residuals:
Min 1Q Median 3Q Max
-15172.7 -4464.4 -727.2 5371.7 16442.3
Coefficients:
Estimate Std. Error t value Pr(>|t|)
(Intercept) 26686.7 770.4 34.638 <2e-16 ***
X1dum -5649.4 2387.1 -2.367 0.02 *
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
Residual standard error: 7145 on 94 degrees of freedom
Multiple R-Squared: 0.05623, Adjusted R-squared: 0.04619
F-statistic: 5.601 on 1 and 94 DF, p-value: 0.02000
> postscript(file="/var/www/html/rcomp/tmp/14p3r1199523961.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/2lhw61199523961.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> plot(mysum$resid, type='b', pch=19, main='Residuals', ylab='value of Residuals', xlab='time or index')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/3apfi1199523961.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> hist(mysum$resid, main='Residual Histogram', xlab='values of Residuals')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/4mykp1199523961.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> densityplot(~mysum$resid,col='black',main='Residual Density Plot', xlab='values of Residuals')
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/5gbyh1199523961.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> qqnorm(mysum$resid, main='Residual Normal Q-Q Plot')
> grid()
> dev.off()
null device
1
> (myerror <- as.ts(mysum$resid))
Time Series:
Start = 1
End = 96
Frequency = 1
1 2 3 4 5 6
9722.3488 6476.3488 7435.3488 8538.3488 1562.3488 3687.3488
7 8 9 10 11 12
-375.6512 -4617.6512 -3035.6512 1941.3488 -3499.6512 -11959.6512
13 14 15 16 17 18
16393.3488 5832.3488 12970.3488 6927.3488 1984.3488 7556.3488
19 20 21 22 23 24
649.3488 -3770.6512 -2149.6512 -558.6512 -4084.6512 -10942.6512
25 26 27 28 29 30
14399.3488 13003.3488 16442.3488 11176.3488 9266.3488 2446.3488
31 32 33 34 35 36
-1993.6512 -4481.6512 -4961.6512 505.3488 -4896.6512 -13433.6512
37 38 39 40 41 42
11015.3488 3677.3488 5922.3488 3525.3488 3278.3488 1665.3488
43 44 45 46 47 48
-872.6512 -4272.6512 -6180.6512 2119.3488 -4458.6512 -12715.6512
49 50 51 52 53 54
10158.3488 8651.3488 8335.3488 8090.3488 200.3488 -2716.6512
55 56 57 58 59 60
-3906.6512 -9335.6512 -5304.6512 -2125.6512 -9277.6512 -15172.6512
61 62 63 64 65 66
4827.3488 384.3488 2775.3488 -581.6512 -4289.6512 -2843.6512
67 68 69 70 71 72
-4981.6512 -8597.6512 -5922.6512 -1370.6512 -8982.6512 -11138.6512
73 74 75 76 77 78
1342.3488 2696.3488 9751.3488 5347.3488 -4007.6512 -2367.6512
79 80 81 82 83 84
-8682.6512 -9149.6512 -6320.6512 -3904.6512 -7517.6512 -12879.6512
85 86 87 88 89 90
3056.3488 -1095.6512 8058.7000 5444.7000 1367.7000 6006.7000
91 92 93 94 95 96
-3067.3000 -2307.3000 -1353.3000 -1252.3000 -2558.3000 -10339.3000
> postscript(file="/var/www/html/rcomp/tmp/6qmzh1199523961.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 = 96
Frequency = 1
lag(myerror, k = 1) myerror
0 9722.3488 NA
1 6476.3488 9722.3488
2 7435.3488 6476.3488
3 8538.3488 7435.3488
4 1562.3488 8538.3488
5 3687.3488 1562.3488
6 -375.6512 3687.3488
7 -4617.6512 -375.6512
8 -3035.6512 -4617.6512
9 1941.3488 -3035.6512
10 -3499.6512 1941.3488
11 -11959.6512 -3499.6512
12 16393.3488 -11959.6512
13 5832.3488 16393.3488
14 12970.3488 5832.3488
15 6927.3488 12970.3488
16 1984.3488 6927.3488
17 7556.3488 1984.3488
18 649.3488 7556.3488
19 -3770.6512 649.3488
20 -2149.6512 -3770.6512
21 -558.6512 -2149.6512
22 -4084.6512 -558.6512
23 -10942.6512 -4084.6512
24 14399.3488 -10942.6512
25 13003.3488 14399.3488
26 16442.3488 13003.3488
27 11176.3488 16442.3488
28 9266.3488 11176.3488
29 2446.3488 9266.3488
30 -1993.6512 2446.3488
31 -4481.6512 -1993.6512
32 -4961.6512 -4481.6512
33 505.3488 -4961.6512
34 -4896.6512 505.3488
35 -13433.6512 -4896.6512
36 11015.3488 -13433.6512
37 3677.3488 11015.3488
38 5922.3488 3677.3488
39 3525.3488 5922.3488
40 3278.3488 3525.3488
41 1665.3488 3278.3488
42 -872.6512 1665.3488
43 -4272.6512 -872.6512
44 -6180.6512 -4272.6512
45 2119.3488 -6180.6512
46 -4458.6512 2119.3488
47 -12715.6512 -4458.6512
48 10158.3488 -12715.6512
49 8651.3488 10158.3488
50 8335.3488 8651.3488
51 8090.3488 8335.3488
52 200.3488 8090.3488
53 -2716.6512 200.3488
54 -3906.6512 -2716.6512
55 -9335.6512 -3906.6512
56 -5304.6512 -9335.6512
57 -2125.6512 -5304.6512
58 -9277.6512 -2125.6512
59 -15172.6512 -9277.6512
60 4827.3488 -15172.6512
61 384.3488 4827.3488
62 2775.3488 384.3488
63 -581.6512 2775.3488
64 -4289.6512 -581.6512
65 -2843.6512 -4289.6512
66 -4981.6512 -2843.6512
67 -8597.6512 -4981.6512
68 -5922.6512 -8597.6512
69 -1370.6512 -5922.6512
70 -8982.6512 -1370.6512
71 -11138.6512 -8982.6512
72 1342.3488 -11138.6512
73 2696.3488 1342.3488
74 9751.3488 2696.3488
75 5347.3488 9751.3488
76 -4007.6512 5347.3488
77 -2367.6512 -4007.6512
78 -8682.6512 -2367.6512
79 -9149.6512 -8682.6512
80 -6320.6512 -9149.6512
81 -3904.6512 -6320.6512
82 -7517.6512 -3904.6512
83 -12879.6512 -7517.6512
84 3056.3488 -12879.6512
85 -1095.6512 3056.3488
86 8058.7000 -1095.6512
87 5444.7000 8058.7000
88 1367.7000 5444.7000
89 6006.7000 1367.7000
90 -3067.3000 6006.7000
91 -2307.3000 -3067.3000
92 -1353.3000 -2307.3000
93 -1252.3000 -1353.3000
94 -2558.3000 -1252.3000
95 -10339.3000 -2558.3000
96 NA -10339.3000
> dum1 <- dum[2:length(myerror),]
> dum1
lag(myerror, k = 1) myerror
[1,] 6476.3488 9722.3488
[2,] 7435.3488 6476.3488
[3,] 8538.3488 7435.3488
[4,] 1562.3488 8538.3488
[5,] 3687.3488 1562.3488
[6,] -375.6512 3687.3488
[7,] -4617.6512 -375.6512
[8,] -3035.6512 -4617.6512
[9,] 1941.3488 -3035.6512
[10,] -3499.6512 1941.3488
[11,] -11959.6512 -3499.6512
[12,] 16393.3488 -11959.6512
[13,] 5832.3488 16393.3488
[14,] 12970.3488 5832.3488
[15,] 6927.3488 12970.3488
[16,] 1984.3488 6927.3488
[17,] 7556.3488 1984.3488
[18,] 649.3488 7556.3488
[19,] -3770.6512 649.3488
[20,] -2149.6512 -3770.6512
[21,] -558.6512 -2149.6512
[22,] -4084.6512 -558.6512
[23,] -10942.6512 -4084.6512
[24,] 14399.3488 -10942.6512
[25,] 13003.3488 14399.3488
[26,] 16442.3488 13003.3488
[27,] 11176.3488 16442.3488
[28,] 9266.3488 11176.3488
[29,] 2446.3488 9266.3488
[30,] -1993.6512 2446.3488
[31,] -4481.6512 -1993.6512
[32,] -4961.6512 -4481.6512
[33,] 505.3488 -4961.6512
[34,] -4896.6512 505.3488
[35,] -13433.6512 -4896.6512
[36,] 11015.3488 -13433.6512
[37,] 3677.3488 11015.3488
[38,] 5922.3488 3677.3488
[39,] 3525.3488 5922.3488
[40,] 3278.3488 3525.3488
[41,] 1665.3488 3278.3488
[42,] -872.6512 1665.3488
[43,] -4272.6512 -872.6512
[44,] -6180.6512 -4272.6512
[45,] 2119.3488 -6180.6512
[46,] -4458.6512 2119.3488
[47,] -12715.6512 -4458.6512
[48,] 10158.3488 -12715.6512
[49,] 8651.3488 10158.3488
[50,] 8335.3488 8651.3488
[51,] 8090.3488 8335.3488
[52,] 200.3488 8090.3488
[53,] -2716.6512 200.3488
[54,] -3906.6512 -2716.6512
[55,] -9335.6512 -3906.6512
[56,] -5304.6512 -9335.6512
[57,] -2125.6512 -5304.6512
[58,] -9277.6512 -2125.6512
[59,] -15172.6512 -9277.6512
[60,] 4827.3488 -15172.6512
[61,] 384.3488 4827.3488
[62,] 2775.3488 384.3488
[63,] -581.6512 2775.3488
[64,] -4289.6512 -581.6512
[65,] -2843.6512 -4289.6512
[66,] -4981.6512 -2843.6512
[67,] -8597.6512 -4981.6512
[68,] -5922.6512 -8597.6512
[69,] -1370.6512 -5922.6512
[70,] -8982.6512 -1370.6512
[71,] -11138.6512 -8982.6512
[72,] 1342.3488 -11138.6512
[73,] 2696.3488 1342.3488
[74,] 9751.3488 2696.3488
[75,] 5347.3488 9751.3488
[76,] -4007.6512 5347.3488
[77,] -2367.6512 -4007.6512
[78,] -8682.6512 -2367.6512
[79,] -9149.6512 -8682.6512
[80,] -6320.6512 -9149.6512
[81,] -3904.6512 -6320.6512
[82,] -7517.6512 -3904.6512
[83,] -12879.6512 -7517.6512
[84,] 3056.3488 -12879.6512
[85,] -1095.6512 3056.3488
[86,] 8058.7000 -1095.6512
[87,] 5444.7000 8058.7000
[88,] 1367.7000 5444.7000
[89,] 6006.7000 1367.7000
[90,] -3067.3000 6006.7000
[91,] -2307.3000 -3067.3000
[92,] -1353.3000 -2307.3000
[93,] -1252.3000 -1353.3000
[94,] -2558.3000 -1252.3000
[95,] -10339.3000 -2558.3000
> z <- as.data.frame(dum1)
> z
lag(myerror, k = 1) myerror
1 6476.3488 9722.3488
2 7435.3488 6476.3488
3 8538.3488 7435.3488
4 1562.3488 8538.3488
5 3687.3488 1562.3488
6 -375.6512 3687.3488
7 -4617.6512 -375.6512
8 -3035.6512 -4617.6512
9 1941.3488 -3035.6512
10 -3499.6512 1941.3488
11 -11959.6512 -3499.6512
12 16393.3488 -11959.6512
13 5832.3488 16393.3488
14 12970.3488 5832.3488
15 6927.3488 12970.3488
16 1984.3488 6927.3488
17 7556.3488 1984.3488
18 649.3488 7556.3488
19 -3770.6512 649.3488
20 -2149.6512 -3770.6512
21 -558.6512 -2149.6512
22 -4084.6512 -558.6512
23 -10942.6512 -4084.6512
24 14399.3488 -10942.6512
25 13003.3488 14399.3488
26 16442.3488 13003.3488
27 11176.3488 16442.3488
28 9266.3488 11176.3488
29 2446.3488 9266.3488
30 -1993.6512 2446.3488
31 -4481.6512 -1993.6512
32 -4961.6512 -4481.6512
33 505.3488 -4961.6512
34 -4896.6512 505.3488
35 -13433.6512 -4896.6512
36 11015.3488 -13433.6512
37 3677.3488 11015.3488
38 5922.3488 3677.3488
39 3525.3488 5922.3488
40 3278.3488 3525.3488
41 1665.3488 3278.3488
42 -872.6512 1665.3488
43 -4272.6512 -872.6512
44 -6180.6512 -4272.6512
45 2119.3488 -6180.6512
46 -4458.6512 2119.3488
47 -12715.6512 -4458.6512
48 10158.3488 -12715.6512
49 8651.3488 10158.3488
50 8335.3488 8651.3488
51 8090.3488 8335.3488
52 200.3488 8090.3488
53 -2716.6512 200.3488
54 -3906.6512 -2716.6512
55 -9335.6512 -3906.6512
56 -5304.6512 -9335.6512
57 -2125.6512 -5304.6512
58 -9277.6512 -2125.6512
59 -15172.6512 -9277.6512
60 4827.3488 -15172.6512
61 384.3488 4827.3488
62 2775.3488 384.3488
63 -581.6512 2775.3488
64 -4289.6512 -581.6512
65 -2843.6512 -4289.6512
66 -4981.6512 -2843.6512
67 -8597.6512 -4981.6512
68 -5922.6512 -8597.6512
69 -1370.6512 -5922.6512
70 -8982.6512 -1370.6512
71 -11138.6512 -8982.6512
72 1342.3488 -11138.6512
73 2696.3488 1342.3488
74 9751.3488 2696.3488
75 5347.3488 9751.3488
76 -4007.6512 5347.3488
77 -2367.6512 -4007.6512
78 -8682.6512 -2367.6512
79 -9149.6512 -8682.6512
80 -6320.6512 -9149.6512
81 -3904.6512 -6320.6512
82 -7517.6512 -3904.6512
83 -12879.6512 -7517.6512
84 3056.3488 -12879.6512
85 -1095.6512 3056.3488
86 8058.7000 -1095.6512
87 5444.7000 8058.7000
88 1367.7000 5444.7000
89 6006.7000 1367.7000
90 -3067.3000 6006.7000
91 -2307.3000 -3067.3000
92 -1353.3000 -2307.3000
93 -1252.3000 -1353.3000
94 -2558.3000 -1252.3000
95 -10339.3000 -2558.3000
> 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/7cjg01199523961.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> acf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/8dwf41199523961.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> pacf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Partial Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/9xric1199523961.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> opar <- par(mfrow = c(2,2), oma = c(0, 0, 1.1, 0))
> plot(mylm, las = 1, sub='Residual Diagnostics')
> par(opar)
> dev.off()
null device
1
> load(file='/var/www/html/rcomp/createtable')
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a, 'Multiple Linear Regression - Estimated Regression Equation', 1, TRUE)
> a<-table.row.end(a)
> myeq <- colnames(x)[1]
> myeq <- paste(myeq, '[t] = ', sep='')
> for (i in 1:k){
+ if (mysum$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/106ect1199523962.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/11nq6n1199523962.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/12n3731199523962.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/13jn171199523962.tab")
>
> system("convert tmp/14p3r1199523961.ps tmp/14p3r1199523961.png")
> system("convert tmp/2lhw61199523961.ps tmp/2lhw61199523961.png")
> system("convert tmp/3apfi1199523961.ps tmp/3apfi1199523961.png")
> system("convert tmp/4mykp1199523961.ps tmp/4mykp1199523961.png")
> system("convert tmp/5gbyh1199523961.ps tmp/5gbyh1199523961.png")
> system("convert tmp/6qmzh1199523961.ps tmp/6qmzh1199523961.png")
> system("convert tmp/7cjg01199523961.ps tmp/7cjg01199523961.png")
> system("convert tmp/8dwf41199523961.ps tmp/8dwf41199523961.png")
> system("convert tmp/9xric1199523961.ps tmp/9xric1199523961.png")
>
>
> proc.time()
user system elapsed
2.449 1.558 4.056