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(513,0,503,0,471,0,471,0,476,0,475,0,470,0,461,0,455,0,456,0,517,0,525,0,523,1,519,1,509,1,512,1,519,1,517,1,510,1,509,1,501,1,507,1,569,1,580,1,578,1,565,1,547,1,555,1,562,1,561,1,555,1,544,1,537,1,543,1,594,1,611,1,613,1,611,1,594,1,595,1,591,1,589,1,584,1,573,1,567,1,569,1,621,1,629,1,628,1,612,1,595,1,597,1,593,1,590,1,580,1,574,1,573,1,573,1,620,1,626,1,620,1,588,1,566,1,557,1,561,1,549,1,532,1,526,1,511,1,499,1,555,1,565,1,542,1),dim=c(2,73),dimnames=list(c('werk','actbel'),1:73))
> y <- array(NA,dim=c(2,73),dimnames=list(c('werk','actbel'),1:73))
> 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 = '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
werk actbel M1 M2 M3 M4 M5 M6 M7 M8 M9 M10 M11 t
1 513 0 1 0 0 0 0 0 0 0 0 0 0 1
2 503 0 0 1 0 0 0 0 0 0 0 0 0 2
3 471 0 0 0 1 0 0 0 0 0 0 0 0 3
4 471 0 0 0 0 1 0 0 0 0 0 0 0 4
5 476 0 0 0 0 0 1 0 0 0 0 0 0 5
6 475 0 0 0 0 0 0 1 0 0 0 0 0 6
7 470 0 0 0 0 0 0 0 1 0 0 0 0 7
8 461 0 0 0 0 0 0 0 0 1 0 0 0 8
9 455 0 0 0 0 0 0 0 0 0 1 0 0 9
10 456 0 0 0 0 0 0 0 0 0 0 1 0 10
11 517 0 0 0 0 0 0 0 0 0 0 0 1 11
12 525 0 0 0 0 0 0 0 0 0 0 0 0 12
13 523 1 1 0 0 0 0 0 0 0 0 0 0 13
14 519 1 0 1 0 0 0 0 0 0 0 0 0 14
15 509 1 0 0 1 0 0 0 0 0 0 0 0 15
16 512 1 0 0 0 1 0 0 0 0 0 0 0 16
17 519 1 0 0 0 0 1 0 0 0 0 0 0 17
18 517 1 0 0 0 0 0 1 0 0 0 0 0 18
19 510 1 0 0 0 0 0 0 1 0 0 0 0 19
20 509 1 0 0 0 0 0 0 0 1 0 0 0 20
21 501 1 0 0 0 0 0 0 0 0 1 0 0 21
22 507 1 0 0 0 0 0 0 0 0 0 1 0 22
23 569 1 0 0 0 0 0 0 0 0 0 0 1 23
24 580 1 0 0 0 0 0 0 0 0 0 0 0 24
25 578 1 1 0 0 0 0 0 0 0 0 0 0 25
26 565 1 0 1 0 0 0 0 0 0 0 0 0 26
27 547 1 0 0 1 0 0 0 0 0 0 0 0 27
28 555 1 0 0 0 1 0 0 0 0 0 0 0 28
29 562 1 0 0 0 0 1 0 0 0 0 0 0 29
30 561 1 0 0 0 0 0 1 0 0 0 0 0 30
31 555 1 0 0 0 0 0 0 1 0 0 0 0 31
32 544 1 0 0 0 0 0 0 0 1 0 0 0 32
33 537 1 0 0 0 0 0 0 0 0 1 0 0 33
34 543 1 0 0 0 0 0 0 0 0 0 1 0 34
35 594 1 0 0 0 0 0 0 0 0 0 0 1 35
36 611 1 0 0 0 0 0 0 0 0 0 0 0 36
37 613 1 1 0 0 0 0 0 0 0 0 0 0 37
38 611 1 0 1 0 0 0 0 0 0 0 0 0 38
39 594 1 0 0 1 0 0 0 0 0 0 0 0 39
40 595 1 0 0 0 1 0 0 0 0 0 0 0 40
41 591 1 0 0 0 0 1 0 0 0 0 0 0 41
42 589 1 0 0 0 0 0 1 0 0 0 0 0 42
43 584 1 0 0 0 0 0 0 1 0 0 0 0 43
44 573 1 0 0 0 0 0 0 0 1 0 0 0 44
45 567 1 0 0 0 0 0 0 0 0 1 0 0 45
46 569 1 0 0 0 0 0 0 0 0 0 1 0 46
47 621 1 0 0 0 0 0 0 0 0 0 0 1 47
48 629 1 0 0 0 0 0 0 0 0 0 0 0 48
49 628 1 1 0 0 0 0 0 0 0 0 0 0 49
50 612 1 0 1 0 0 0 0 0 0 0 0 0 50
51 595 1 0 0 1 0 0 0 0 0 0 0 0 51
52 597 1 0 0 0 1 0 0 0 0 0 0 0 52
53 593 1 0 0 0 0 1 0 0 0 0 0 0 53
54 590 1 0 0 0 0 0 1 0 0 0 0 0 54
55 580 1 0 0 0 0 0 0 1 0 0 0 0 55
56 574 1 0 0 0 0 0 0 0 1 0 0 0 56
57 573 1 0 0 0 0 0 0 0 0 1 0 0 57
58 573 1 0 0 0 0 0 0 0 0 0 1 0 58
59 620 1 0 0 0 0 0 0 0 0 0 0 1 59
60 626 1 0 0 0 0 0 0 0 0 0 0 0 60
61 620 1 1 0 0 0 0 0 0 0 0 0 0 61
62 588 1 0 1 0 0 0 0 0 0 0 0 0 62
63 566 1 0 0 1 0 0 0 0 0 0 0 0 63
64 557 1 0 0 0 1 0 0 0 0 0 0 0 64
65 561 1 0 0 0 0 1 0 0 0 0 0 0 65
66 549 1 0 0 0 0 0 1 0 0 0 0 0 66
67 532 1 0 0 0 0 0 0 1 0 0 0 0 67
68 526 1 0 0 0 0 0 0 0 1 0 0 0 68
69 511 1 0 0 0 0 0 0 0 0 1 0 0 69
70 499 1 0 0 0 0 0 0 0 0 0 1 0 70
71 555 1 0 0 0 0 0 0 0 0 0 0 1 71
72 565 1 0 0 0 0 0 0 0 0 0 0 0 72
73 542 1 1 0 0 0 0 0 0 0 0 0 0 73
> k <- length(x[1,])
> df <- as.data.frame(x)
> (mylm <- lm(df))
Call:
lm(formula = df)
Coefficients:
(Intercept) actbel M1 M2 M3 M4
513.2143 58.9090 -13.6611 -16.5647 -36.5416 -36.3518
M5 M6 M7 M8 M9 M10
-34.4953 -38.6388 -47.6157 -55.5926 -63.4027 -63.5463
M11 t
-9.3565 0.6435
> (mysum <- summary(mylm))
Call:
lm(formula = df)
Residuals:
Min 1Q Median 3Q Max
-63.440 -18.457 4.063 22.283 38.005
Coefficients:
Estimate Std. Error t value Pr(>|t|)
(Intercept) 513.2143 14.1575 36.250 < 2e-16 ***
actbel 58.9090 11.9145 4.944 6.67e-06 ***
M1 -13.6611 16.0204 -0.853 0.39726
M2 -16.5647 16.7083 -0.991 0.32553
M3 -36.5416 16.6828 -2.190 0.03246 *
M4 -36.3518 16.6599 -2.182 0.03310 *
M5 -34.4953 16.6397 -2.073 0.04254 *
M6 -38.6388 16.6222 -2.325 0.02356 *
M7 -47.6157 16.6074 -2.867 0.00573 **
M8 -55.5926 16.5952 -3.350 0.00141 **
M9 -63.4027 16.5858 -3.823 0.00032 ***
M10 -63.5463 16.5790 -3.833 0.00031 ***
M11 -9.3565 16.5750 -0.564 0.57456
t 0.6435 0.2117 3.040 0.00353 **
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
Residual standard error: 28.71 on 59 degrees of freedom
Multiple R-Squared: 0.6865, Adjusted R-squared: 0.6174
F-statistic: 9.939 on 13 and 59 DF, p-value: 1.406e-10
> postscript(file="/var/www/html/rcomp/tmp/1zasd1195124106.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/2lx7g1195124106.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> plot(mysum$resid, type='b', pch=19, main='Residuals', ylab='value of Residuals', xlab='time or index')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/3rhys1195124106.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> hist(mysum$resid, main='Residual Histogram', xlab='values of Residuals')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/4xu9s1195124106.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> densityplot(~mysum$resid,col='black',main='Residual Density Plot', xlab='values of Residuals')
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/5bmic1195124106.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> qqnorm(mysum$resid, main='Residual Normal Q-Q Plot')
> grid()
> dev.off()
null device
1
> (myerror <- as.ts(mysum$resid))
Time Series:
Start = 1
End = 73
Frequency = 1
1 2 3 4 5 6
12.8032924 5.0633371 -7.6033296 -8.4366629 -5.9366629 -3.4366629
7 8 9 10 11 12
-0.1033296 -1.7699963 -0.6033296 -0.1033296 6.0633371 4.0633371
13 14 15 16 17 18
-43.8280320 -45.5679874 -36.2346540 -34.0679874 -29.5679874 -28.0679874
19 20 21 22 23 24
-26.7346540 -20.4013207 -21.2346540 -15.7346540 -8.5679874 -7.5679874
25 26 27 28 29 30
3.4496280 -7.2903274 -5.9569940 1.2096726 5.7096726 8.2096726
31 32 33 34 35 36
10.5430060 6.8763393 7.0430060 12.5430060 8.7096726 15.7096726
37 38 39 40 41 42
30.7272879 30.9873326 33.3206659 33.4873326 26.9873326 28.4873326
43 44 45 46 47 48
31.8206659 28.1539993 29.3206659 30.8206659 27.9873326 25.9873326
49 50 51 52 53 54
38.0049479 24.2649926 26.5983259 27.7649926 21.2649926 21.7649926
55 56 57 58 59 60
20.0983259 21.4316592 27.5983259 27.0983259 19.2649926 15.2649926
61 62 63 64 65 66
22.2826079 -7.4573475 -10.1240141 -19.9573475 -18.4573475 -26.9573475
67 68 69 70 71 72
-35.6240141 -34.2906808 -42.1240141 -54.6240141 -53.4573475 -53.4573475
73
-63.4397321
> postscript(file="/var/www/html/rcomp/tmp/69rwb1195124106.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 = 73
Frequency = 1
lag(myerror, k = 1) myerror
0 12.8032924 NA
1 5.0633371 12.8032924
2 -7.6033296 5.0633371
3 -8.4366629 -7.6033296
4 -5.9366629 -8.4366629
5 -3.4366629 -5.9366629
6 -0.1033296 -3.4366629
7 -1.7699963 -0.1033296
8 -0.6033296 -1.7699963
9 -0.1033296 -0.6033296
10 6.0633371 -0.1033296
11 4.0633371 6.0633371
12 -43.8280320 4.0633371
13 -45.5679874 -43.8280320
14 -36.2346540 -45.5679874
15 -34.0679874 -36.2346540
16 -29.5679874 -34.0679874
17 -28.0679874 -29.5679874
18 -26.7346540 -28.0679874
19 -20.4013207 -26.7346540
20 -21.2346540 -20.4013207
21 -15.7346540 -21.2346540
22 -8.5679874 -15.7346540
23 -7.5679874 -8.5679874
24 3.4496280 -7.5679874
25 -7.2903274 3.4496280
26 -5.9569940 -7.2903274
27 1.2096726 -5.9569940
28 5.7096726 1.2096726
29 8.2096726 5.7096726
30 10.5430060 8.2096726
31 6.8763393 10.5430060
32 7.0430060 6.8763393
33 12.5430060 7.0430060
34 8.7096726 12.5430060
35 15.7096726 8.7096726
36 30.7272879 15.7096726
37 30.9873326 30.7272879
38 33.3206659 30.9873326
39 33.4873326 33.3206659
40 26.9873326 33.4873326
41 28.4873326 26.9873326
42 31.8206659 28.4873326
43 28.1539993 31.8206659
44 29.3206659 28.1539993
45 30.8206659 29.3206659
46 27.9873326 30.8206659
47 25.9873326 27.9873326
48 38.0049479 25.9873326
49 24.2649926 38.0049479
50 26.5983259 24.2649926
51 27.7649926 26.5983259
52 21.2649926 27.7649926
53 21.7649926 21.2649926
54 20.0983259 21.7649926
55 21.4316592 20.0983259
56 27.5983259 21.4316592
57 27.0983259 27.5983259
58 19.2649926 27.0983259
59 15.2649926 19.2649926
60 22.2826079 15.2649926
61 -7.4573475 22.2826079
62 -10.1240141 -7.4573475
63 -19.9573475 -10.1240141
64 -18.4573475 -19.9573475
65 -26.9573475 -18.4573475
66 -35.6240141 -26.9573475
67 -34.2906808 -35.6240141
68 -42.1240141 -34.2906808
69 -54.6240141 -42.1240141
70 -53.4573475 -54.6240141
71 -53.4573475 -53.4573475
72 -63.4397321 -53.4573475
73 NA -63.4397321
> dum1 <- dum[2:length(myerror),]
> dum1
lag(myerror, k = 1) myerror
[1,] 5.0633371 12.8032924
[2,] -7.6033296 5.0633371
[3,] -8.4366629 -7.6033296
[4,] -5.9366629 -8.4366629
[5,] -3.4366629 -5.9366629
[6,] -0.1033296 -3.4366629
[7,] -1.7699963 -0.1033296
[8,] -0.6033296 -1.7699963
[9,] -0.1033296 -0.6033296
[10,] 6.0633371 -0.1033296
[11,] 4.0633371 6.0633371
[12,] -43.8280320 4.0633371
[13,] -45.5679874 -43.8280320
[14,] -36.2346540 -45.5679874
[15,] -34.0679874 -36.2346540
[16,] -29.5679874 -34.0679874
[17,] -28.0679874 -29.5679874
[18,] -26.7346540 -28.0679874
[19,] -20.4013207 -26.7346540
[20,] -21.2346540 -20.4013207
[21,] -15.7346540 -21.2346540
[22,] -8.5679874 -15.7346540
[23,] -7.5679874 -8.5679874
[24,] 3.4496280 -7.5679874
[25,] -7.2903274 3.4496280
[26,] -5.9569940 -7.2903274
[27,] 1.2096726 -5.9569940
[28,] 5.7096726 1.2096726
[29,] 8.2096726 5.7096726
[30,] 10.5430060 8.2096726
[31,] 6.8763393 10.5430060
[32,] 7.0430060 6.8763393
[33,] 12.5430060 7.0430060
[34,] 8.7096726 12.5430060
[35,] 15.7096726 8.7096726
[36,] 30.7272879 15.7096726
[37,] 30.9873326 30.7272879
[38,] 33.3206659 30.9873326
[39,] 33.4873326 33.3206659
[40,] 26.9873326 33.4873326
[41,] 28.4873326 26.9873326
[42,] 31.8206659 28.4873326
[43,] 28.1539993 31.8206659
[44,] 29.3206659 28.1539993
[45,] 30.8206659 29.3206659
[46,] 27.9873326 30.8206659
[47,] 25.9873326 27.9873326
[48,] 38.0049479 25.9873326
[49,] 24.2649926 38.0049479
[50,] 26.5983259 24.2649926
[51,] 27.7649926 26.5983259
[52,] 21.2649926 27.7649926
[53,] 21.7649926 21.2649926
[54,] 20.0983259 21.7649926
[55,] 21.4316592 20.0983259
[56,] 27.5983259 21.4316592
[57,] 27.0983259 27.5983259
[58,] 19.2649926 27.0983259
[59,] 15.2649926 19.2649926
[60,] 22.2826079 15.2649926
[61,] -7.4573475 22.2826079
[62,] -10.1240141 -7.4573475
[63,] -19.9573475 -10.1240141
[64,] -18.4573475 -19.9573475
[65,] -26.9573475 -18.4573475
[66,] -35.6240141 -26.9573475
[67,] -34.2906808 -35.6240141
[68,] -42.1240141 -34.2906808
[69,] -54.6240141 -42.1240141
[70,] -53.4573475 -54.6240141
[71,] -53.4573475 -53.4573475
[72,] -63.4397321 -53.4573475
> z <- as.data.frame(dum1)
> z
lag(myerror, k = 1) myerror
1 5.0633371 12.8032924
2 -7.6033296 5.0633371
3 -8.4366629 -7.6033296
4 -5.9366629 -8.4366629
5 -3.4366629 -5.9366629
6 -0.1033296 -3.4366629
7 -1.7699963 -0.1033296
8 -0.6033296 -1.7699963
9 -0.1033296 -0.6033296
10 6.0633371 -0.1033296
11 4.0633371 6.0633371
12 -43.8280320 4.0633371
13 -45.5679874 -43.8280320
14 -36.2346540 -45.5679874
15 -34.0679874 -36.2346540
16 -29.5679874 -34.0679874
17 -28.0679874 -29.5679874
18 -26.7346540 -28.0679874
19 -20.4013207 -26.7346540
20 -21.2346540 -20.4013207
21 -15.7346540 -21.2346540
22 -8.5679874 -15.7346540
23 -7.5679874 -8.5679874
24 3.4496280 -7.5679874
25 -7.2903274 3.4496280
26 -5.9569940 -7.2903274
27 1.2096726 -5.9569940
28 5.7096726 1.2096726
29 8.2096726 5.7096726
30 10.5430060 8.2096726
31 6.8763393 10.5430060
32 7.0430060 6.8763393
33 12.5430060 7.0430060
34 8.7096726 12.5430060
35 15.7096726 8.7096726
36 30.7272879 15.7096726
37 30.9873326 30.7272879
38 33.3206659 30.9873326
39 33.4873326 33.3206659
40 26.9873326 33.4873326
41 28.4873326 26.9873326
42 31.8206659 28.4873326
43 28.1539993 31.8206659
44 29.3206659 28.1539993
45 30.8206659 29.3206659
46 27.9873326 30.8206659
47 25.9873326 27.9873326
48 38.0049479 25.9873326
49 24.2649926 38.0049479
50 26.5983259 24.2649926
51 27.7649926 26.5983259
52 21.2649926 27.7649926
53 21.7649926 21.2649926
54 20.0983259 21.7649926
55 21.4316592 20.0983259
56 27.5983259 21.4316592
57 27.0983259 27.5983259
58 19.2649926 27.0983259
59 15.2649926 19.2649926
60 22.2826079 15.2649926
61 -7.4573475 22.2826079
62 -10.1240141 -7.4573475
63 -19.9573475 -10.1240141
64 -18.4573475 -19.9573475
65 -26.9573475 -18.4573475
66 -35.6240141 -26.9573475
67 -34.2906808 -35.6240141
68 -42.1240141 -34.2906808
69 -54.6240141 -42.1240141
70 -53.4573475 -54.6240141
71 -53.4573475 -53.4573475
72 -63.4397321 -53.4573475
> 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/7zgnt1195124106.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> acf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/8sgxj1195124106.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> pacf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Partial Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/9p8bf1195124106.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> opar <- par(mfrow = c(2,2), oma = c(0, 0, 1.1, 0))
> plot(mylm, las = 1, sub='Residual Diagnostics')
> par(opar)
> dev.off()
null device
1
> load(file='/var/www/html/rcomp/createtable')
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a, 'Multiple Linear Regression - Estimated Regression Equation', 1, TRUE)
> a<-table.row.end(a)
> myeq <- colnames(x)[1]
> myeq <- paste(myeq, '[t] = ', sep='')
> for (i in 1:k){
+ if (mysum$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/10s6g01195124106.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/11h84n1195124106.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/12luay1195124106.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/13cqfz1195124106.tab")
>
> system("convert tmp/1zasd1195124106.ps tmp/1zasd1195124106.png")
> system("convert tmp/2lx7g1195124106.ps tmp/2lx7g1195124106.png")
> system("convert tmp/3rhys1195124106.ps tmp/3rhys1195124106.png")
> system("convert tmp/4xu9s1195124106.ps tmp/4xu9s1195124106.png")
> system("convert tmp/5bmic1195124106.ps tmp/5bmic1195124106.png")
> system("convert tmp/69rwb1195124106.ps tmp/69rwb1195124106.png")
> system("convert tmp/7zgnt1195124106.ps tmp/7zgnt1195124106.png")
> system("convert tmp/8sgxj1195124106.ps tmp/8sgxj1195124106.png")
> system("convert tmp/9p8bf1195124106.ps tmp/9p8bf1195124106.png")
>
>
> proc.time()
user system elapsed
2.452 1.513 2.957