R version 2.9.0 (2009-04-17)
Copyright (C) 2009 The R Foundation for Statistical Computing
ISBN 3-900051-07-0
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> x <- array(list(1.39,1.08,1.34,1.12,1.33,1.12,1.3,1.16,1.28,1.16,1.29,1.16,1.29,1.16,1.28,1.15,1.27,1.17,1.26,1.16,1.29,1.19,1.36,1.13,1.33,1.14,1.35,1.13,1.31,1.16,1.3,1.17,1.32,1.14,1.33,1.14,1.36,1.11,1.35,1.12,1.4,1.08,1.41,1.07,1.4,1.09,1.4,1.08,1.4,1.08,1.41,1.08,1.4,1.09,1.39,1.08,1.41,1.07,1.42,1.07,1.43,1.07,1.42,1.08,1.42,1.07,1.43,1.06,1.43,1.06,1.43,1.06,1.46,1.04,1.47,1.03,1.47,1.03,1.46,1.04,1.47,1.03,1.49,1.02,1.5,1.01,1.47,1.03,1.48,1.02,1.49,1.01,1.49,1.02,1.5,1.01,1.48,1.02,1.46,1.03,1.43,1.04,1.44,1.04,1.43,1.03),dim=c(2,53),dimnames=list(c('eu/us','us/ch'),1:53))
> y <- array(NA,dim=c(2,53),dimnames=list(c('eu/us','us/ch'),1:53))
> for (i in 1:dim(x)[1])
+ {
+ for (j in 1:dim(x)[2])
+ {
+ y[i,j] <- as.numeric(x[i,j])
+ }
+ }
> par3 = 'Linear Trend'
> par2 = 'Include Monthly Dummies'
> par1 = '2'
> #'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
us/ch eu/us M1 M2 M3 M4 M5 M6 M7 M8 M9 M10 M11 t
1 1.08 1.39 1 0 0 0 0 0 0 0 0 0 0 1
2 1.12 1.34 0 1 0 0 0 0 0 0 0 0 0 2
3 1.12 1.33 0 0 1 0 0 0 0 0 0 0 0 3
4 1.16 1.30 0 0 0 1 0 0 0 0 0 0 0 4
5 1.16 1.28 0 0 0 0 1 0 0 0 0 0 0 5
6 1.16 1.29 0 0 0 0 0 1 0 0 0 0 0 6
7 1.16 1.29 0 0 0 0 0 0 1 0 0 0 0 7
8 1.15 1.28 0 0 0 0 0 0 0 1 0 0 0 8
9 1.17 1.27 0 0 0 0 0 0 0 0 1 0 0 9
10 1.16 1.26 0 0 0 0 0 0 0 0 0 1 0 10
11 1.19 1.29 0 0 0 0 0 0 0 0 0 0 1 11
12 1.13 1.36 0 0 0 0 0 0 0 0 0 0 0 12
13 1.14 1.33 1 0 0 0 0 0 0 0 0 0 0 13
14 1.13 1.35 0 1 0 0 0 0 0 0 0 0 0 14
15 1.16 1.31 0 0 1 0 0 0 0 0 0 0 0 15
16 1.17 1.30 0 0 0 1 0 0 0 0 0 0 0 16
17 1.14 1.32 0 0 0 0 1 0 0 0 0 0 0 17
18 1.14 1.33 0 0 0 0 0 1 0 0 0 0 0 18
19 1.11 1.36 0 0 0 0 0 0 1 0 0 0 0 19
20 1.12 1.35 0 0 0 0 0 0 0 1 0 0 0 20
21 1.08 1.40 0 0 0 0 0 0 0 0 1 0 0 21
22 1.07 1.41 0 0 0 0 0 0 0 0 0 1 0 22
23 1.09 1.40 0 0 0 0 0 0 0 0 0 0 1 23
24 1.08 1.40 0 0 0 0 0 0 0 0 0 0 0 24
25 1.08 1.40 1 0 0 0 0 0 0 0 0 0 0 25
26 1.08 1.41 0 1 0 0 0 0 0 0 0 0 0 26
27 1.09 1.40 0 0 1 0 0 0 0 0 0 0 0 27
28 1.08 1.39 0 0 0 1 0 0 0 0 0 0 0 28
29 1.07 1.41 0 0 0 0 1 0 0 0 0 0 0 29
30 1.07 1.42 0 0 0 0 0 1 0 0 0 0 0 30
31 1.07 1.43 0 0 0 0 0 0 1 0 0 0 0 31
32 1.08 1.42 0 0 0 0 0 0 0 1 0 0 0 32
33 1.07 1.42 0 0 0 0 0 0 0 0 1 0 0 33
34 1.06 1.43 0 0 0 0 0 0 0 0 0 1 0 34
35 1.06 1.43 0 0 0 0 0 0 0 0 0 0 1 35
36 1.06 1.43 0 0 0 0 0 0 0 0 0 0 0 36
37 1.04 1.46 1 0 0 0 0 0 0 0 0 0 0 37
38 1.03 1.47 0 1 0 0 0 0 0 0 0 0 0 38
39 1.03 1.47 0 0 1 0 0 0 0 0 0 0 0 39
40 1.04 1.46 0 0 0 1 0 0 0 0 0 0 0 40
41 1.03 1.47 0 0 0 0 1 0 0 0 0 0 0 41
42 1.02 1.49 0 0 0 0 0 1 0 0 0 0 0 42
43 1.01 1.50 0 0 0 0 0 0 1 0 0 0 0 43
44 1.03 1.47 0 0 0 0 0 0 0 1 0 0 0 44
45 1.02 1.48 0 0 0 0 0 0 0 0 1 0 0 45
46 1.01 1.49 0 0 0 0 0 0 0 0 0 1 0 46
47 1.02 1.49 0 0 0 0 0 0 0 0 0 0 1 47
48 1.01 1.50 0 0 0 0 0 0 0 0 0 0 0 48
49 1.02 1.48 1 0 0 0 0 0 0 0 0 0 0 49
50 1.03 1.46 0 1 0 0 0 0 0 0 0 0 0 50
51 1.04 1.43 0 0 1 0 0 0 0 0 0 0 0 51
52 1.04 1.44 0 0 0 1 0 0 0 0 0 0 0 52
53 1.03 1.43 0 0 0 0 1 0 0 0 0 0 0 53
> k <- length(x[1,])
> df <- as.data.frame(x)
> (mylm <- lm(df))
Call:
lm(formula = df)
Coefficients:
(Intercept) `eu/us` M1 M2 M3 M4
2.0298501 -0.6671546 -0.0068089 -0.0044511 -0.0060991 -0.0024099
M5 M6 M7 M8 M9 M10
-0.0113805 -0.0013507 -0.0026505 -0.0047971 -0.0060969 -0.0124004
M11 t
0.0062962 -0.0003608
> (mysum <- summary(mylm))
Call:
lm(formula = df)
Residuals:
Min 1Q Median 3Q Max
-1.821e-02 -4.045e-03 -5.855e-06 5.310e-03 1.845e-02
Coefficients:
Estimate Std. Error t value Pr(>|t|)
(Intercept) 2.0298501 0.0604960 33.553 <2e-16 ***
`eu/us` -0.6671546 0.0463267 -14.401 <2e-16 ***
M1 -0.0068089 0.0066091 -1.030 0.3092
M2 -0.0044511 0.0065879 -0.676 0.5033
M3 -0.0060991 0.0066642 -0.915 0.3657
M4 -0.0024099 0.0067928 -0.355 0.7247
M5 -0.0113805 0.0067920 -1.676 0.1018
M6 -0.0013507 0.0069918 -0.193 0.8478
M7 -0.0026505 0.0069562 -0.381 0.7052
M8 -0.0047971 0.0070486 -0.681 0.5002
M9 -0.0060969 0.0069880 -0.872 0.3883
M10 -0.0124004 0.0069803 -1.776 0.0835 .
M11 0.0062962 0.0069739 0.903 0.3722
t -0.0003608 0.0002085 -1.730 0.0915 .
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
Residual standard error: 0.009806 on 39 degrees of freedom
Multiple R-squared: 0.974, Adjusted R-squared: 0.9653
F-statistic: 112.3 on 13 and 39 DF, p-value: < 2.2e-16
> postscript(file="/var/www/html/rcomp/tmp/1sejd1290349607.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/2loig1290349607.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> plot(mysum$resid, type='b', pch=19, main='Residuals', ylab='value of Residuals', xlab='time or index')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/3loig1290349607.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> hist(mysum$resid, main='Residual Histogram', xlab='values of Residuals')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/4vfz11290349607.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> densityplot(~mysum$resid,col='black',main='Residual Density Plot', xlab='values of Residuals')
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/5vfz11290349607.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> qqnorm(mysum$resid, main='Residual Normal Q-Q Plot')
> grid()
> dev.off()
null device
1
> (myerror <- as.ts(mysum$resid))
Time Series:
Start = 1
End = 53
Frequency = 1
1 2 3 4 5
-1.533558e-02 -1.069038e-02 -1.535315e-02 1.303761e-03 -2.707949e-03
6 7 8 9 10
-5.705435e-03 -4.044867e-03 -1.820909e-02 -3.220072e-03 -1.322739e-02
11 12 13 14 15
1.845147e-02 1.180920e-02 8.964234e-03 1.031025e-02 1.563285e-02
16 17 18 19 20
1.563285e-02 8.307325e-03 5.309839e-03 -3.014956e-03 2.820817e-03
21 22 23 24 25
-2.160886e-03 1.174887e-03 -3.832432e-03 -7.175523e-03 -5.854939e-06
26 27 28 29 30
4.668618e-03 1.000585e-02 -9.994145e-03 2.680328e-03 -3.171579e-04
31 32 33 34 35
8.014956e-03 1.385073e-02 5.511296e-03 8.847069e-03 -9.488704e-03
36 37 38 39 40
-2.831795e-03 4.352511e-03 -9.730161e-04 1.035766e-03 1.035766e-03
41 42 43 44 45
7.038694e-03 7.127535e-04 -9.551329e-04 1.537548e-03 -1.303380e-04
46 47 48 49 50
3.205435e-03 -5.130338e-03 -1.801884e-03 2.024693e-03 -3.315471e-03
51 52 53
-1.132133e-02 -7.978234e-03 -1.531840e-02
> postscript(file="/var/www/html/rcomp/tmp/6vfz11290349607.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 = 53
Frequency = 1
lag(myerror, k = 1) myerror
0 -1.533558e-02 NA
1 -1.069038e-02 -1.533558e-02
2 -1.535315e-02 -1.069038e-02
3 1.303761e-03 -1.535315e-02
4 -2.707949e-03 1.303761e-03
5 -5.705435e-03 -2.707949e-03
6 -4.044867e-03 -5.705435e-03
7 -1.820909e-02 -4.044867e-03
8 -3.220072e-03 -1.820909e-02
9 -1.322739e-02 -3.220072e-03
10 1.845147e-02 -1.322739e-02
11 1.180920e-02 1.845147e-02
12 8.964234e-03 1.180920e-02
13 1.031025e-02 8.964234e-03
14 1.563285e-02 1.031025e-02
15 1.563285e-02 1.563285e-02
16 8.307325e-03 1.563285e-02
17 5.309839e-03 8.307325e-03
18 -3.014956e-03 5.309839e-03
19 2.820817e-03 -3.014956e-03
20 -2.160886e-03 2.820817e-03
21 1.174887e-03 -2.160886e-03
22 -3.832432e-03 1.174887e-03
23 -7.175523e-03 -3.832432e-03
24 -5.854939e-06 -7.175523e-03
25 4.668618e-03 -5.854939e-06
26 1.000585e-02 4.668618e-03
27 -9.994145e-03 1.000585e-02
28 2.680328e-03 -9.994145e-03
29 -3.171579e-04 2.680328e-03
30 8.014956e-03 -3.171579e-04
31 1.385073e-02 8.014956e-03
32 5.511296e-03 1.385073e-02
33 8.847069e-03 5.511296e-03
34 -9.488704e-03 8.847069e-03
35 -2.831795e-03 -9.488704e-03
36 4.352511e-03 -2.831795e-03
37 -9.730161e-04 4.352511e-03
38 1.035766e-03 -9.730161e-04
39 1.035766e-03 1.035766e-03
40 7.038694e-03 1.035766e-03
41 7.127535e-04 7.038694e-03
42 -9.551329e-04 7.127535e-04
43 1.537548e-03 -9.551329e-04
44 -1.303380e-04 1.537548e-03
45 3.205435e-03 -1.303380e-04
46 -5.130338e-03 3.205435e-03
47 -1.801884e-03 -5.130338e-03
48 2.024693e-03 -1.801884e-03
49 -3.315471e-03 2.024693e-03
50 -1.132133e-02 -3.315471e-03
51 -7.978234e-03 -1.132133e-02
52 -1.531840e-02 -7.978234e-03
53 NA -1.531840e-02
> dum1 <- dum[2:length(myerror),]
> dum1
lag(myerror, k = 1) myerror
[1,] -1.069038e-02 -1.533558e-02
[2,] -1.535315e-02 -1.069038e-02
[3,] 1.303761e-03 -1.535315e-02
[4,] -2.707949e-03 1.303761e-03
[5,] -5.705435e-03 -2.707949e-03
[6,] -4.044867e-03 -5.705435e-03
[7,] -1.820909e-02 -4.044867e-03
[8,] -3.220072e-03 -1.820909e-02
[9,] -1.322739e-02 -3.220072e-03
[10,] 1.845147e-02 -1.322739e-02
[11,] 1.180920e-02 1.845147e-02
[12,] 8.964234e-03 1.180920e-02
[13,] 1.031025e-02 8.964234e-03
[14,] 1.563285e-02 1.031025e-02
[15,] 1.563285e-02 1.563285e-02
[16,] 8.307325e-03 1.563285e-02
[17,] 5.309839e-03 8.307325e-03
[18,] -3.014956e-03 5.309839e-03
[19,] 2.820817e-03 -3.014956e-03
[20,] -2.160886e-03 2.820817e-03
[21,] 1.174887e-03 -2.160886e-03
[22,] -3.832432e-03 1.174887e-03
[23,] -7.175523e-03 -3.832432e-03
[24,] -5.854939e-06 -7.175523e-03
[25,] 4.668618e-03 -5.854939e-06
[26,] 1.000585e-02 4.668618e-03
[27,] -9.994145e-03 1.000585e-02
[28,] 2.680328e-03 -9.994145e-03
[29,] -3.171579e-04 2.680328e-03
[30,] 8.014956e-03 -3.171579e-04
[31,] 1.385073e-02 8.014956e-03
[32,] 5.511296e-03 1.385073e-02
[33,] 8.847069e-03 5.511296e-03
[34,] -9.488704e-03 8.847069e-03
[35,] -2.831795e-03 -9.488704e-03
[36,] 4.352511e-03 -2.831795e-03
[37,] -9.730161e-04 4.352511e-03
[38,] 1.035766e-03 -9.730161e-04
[39,] 1.035766e-03 1.035766e-03
[40,] 7.038694e-03 1.035766e-03
[41,] 7.127535e-04 7.038694e-03
[42,] -9.551329e-04 7.127535e-04
[43,] 1.537548e-03 -9.551329e-04
[44,] -1.303380e-04 1.537548e-03
[45,] 3.205435e-03 -1.303380e-04
[46,] -5.130338e-03 3.205435e-03
[47,] -1.801884e-03 -5.130338e-03
[48,] 2.024693e-03 -1.801884e-03
[49,] -3.315471e-03 2.024693e-03
[50,] -1.132133e-02 -3.315471e-03
[51,] -7.978234e-03 -1.132133e-02
[52,] -1.531840e-02 -7.978234e-03
> z <- as.data.frame(dum1)
> z
lag(myerror, k = 1) myerror
1 -1.069038e-02 -1.533558e-02
2 -1.535315e-02 -1.069038e-02
3 1.303761e-03 -1.535315e-02
4 -2.707949e-03 1.303761e-03
5 -5.705435e-03 -2.707949e-03
6 -4.044867e-03 -5.705435e-03
7 -1.820909e-02 -4.044867e-03
8 -3.220072e-03 -1.820909e-02
9 -1.322739e-02 -3.220072e-03
10 1.845147e-02 -1.322739e-02
11 1.180920e-02 1.845147e-02
12 8.964234e-03 1.180920e-02
13 1.031025e-02 8.964234e-03
14 1.563285e-02 1.031025e-02
15 1.563285e-02 1.563285e-02
16 8.307325e-03 1.563285e-02
17 5.309839e-03 8.307325e-03
18 -3.014956e-03 5.309839e-03
19 2.820817e-03 -3.014956e-03
20 -2.160886e-03 2.820817e-03
21 1.174887e-03 -2.160886e-03
22 -3.832432e-03 1.174887e-03
23 -7.175523e-03 -3.832432e-03
24 -5.854939e-06 -7.175523e-03
25 4.668618e-03 -5.854939e-06
26 1.000585e-02 4.668618e-03
27 -9.994145e-03 1.000585e-02
28 2.680328e-03 -9.994145e-03
29 -3.171579e-04 2.680328e-03
30 8.014956e-03 -3.171579e-04
31 1.385073e-02 8.014956e-03
32 5.511296e-03 1.385073e-02
33 8.847069e-03 5.511296e-03
34 -9.488704e-03 8.847069e-03
35 -2.831795e-03 -9.488704e-03
36 4.352511e-03 -2.831795e-03
37 -9.730161e-04 4.352511e-03
38 1.035766e-03 -9.730161e-04
39 1.035766e-03 1.035766e-03
40 7.038694e-03 1.035766e-03
41 7.127535e-04 7.038694e-03
42 -9.551329e-04 7.127535e-04
43 1.537548e-03 -9.551329e-04
44 -1.303380e-04 1.537548e-03
45 3.205435e-03 -1.303380e-04
46 -5.130338e-03 3.205435e-03
47 -1.801884e-03 -5.130338e-03
48 2.024693e-03 -1.801884e-03
49 -3.315471e-03 2.024693e-03
50 -1.132133e-02 -3.315471e-03
51 -7.978234e-03 -1.132133e-02
52 -1.531840e-02 -7.978234e-03
> 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/7o6y41290349607.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> acf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/8o6y41290349607.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> pacf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Partial Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/9o6y41290349607.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> opar <- par(mfrow = c(2,2), oma = c(0, 0, 1.1, 0))
> plot(mylm, las = 1, sub='Residual Diagnostics')
> par(opar)
> dev.off()
null device
1
>
> #Note: the /var/www/html/rcomp/createtable file can be downloaded at http://www.wessa.net/cretab
> load(file="/var/www/html/rcomp/createtable")
>
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a, 'Multiple Linear Regression - Estimated Regression Equation', 1, TRUE)
> a<-table.row.end(a)
> myeq <- colnames(x)[1]
> myeq <- paste(myeq, '[t] = ', sep='')
> for (i in 1:k){
+ if (mysum$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/10rpxs1290349607.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/11dpvx1290349607.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/12kqs91290349607.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/13uhsc1290349607.tab")
>
> try(system("convert tmp/1sejd1290349607.ps tmp/1sejd1290349607.png",intern=TRUE))
character(0)
> try(system("convert tmp/2loig1290349607.ps tmp/2loig1290349607.png",intern=TRUE))
character(0)
> try(system("convert tmp/3loig1290349607.ps tmp/3loig1290349607.png",intern=TRUE))
character(0)
> try(system("convert tmp/4vfz11290349607.ps tmp/4vfz11290349607.png",intern=TRUE))
character(0)
> try(system("convert tmp/5vfz11290349607.ps tmp/5vfz11290349607.png",intern=TRUE))
character(0)
> try(system("convert tmp/6vfz11290349607.ps tmp/6vfz11290349607.png",intern=TRUE))
character(0)
> try(system("convert tmp/7o6y41290349607.ps tmp/7o6y41290349607.png",intern=TRUE))
character(0)
> try(system("convert tmp/8o6y41290349607.ps tmp/8o6y41290349607.png",intern=TRUE))
character(0)
> try(system("convert tmp/9o6y41290349607.ps tmp/9o6y41290349607.png",intern=TRUE))
character(0)
>
>
> proc.time()
user system elapsed
1.877 1.395 4.394