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(519,0,517,0,510,0,509,0,501,0,507,0,569,0,580,0,578,0,565,0,547,0,555,0,562,0,561,0,555,0,544,0,537,0,543,0,594,0,611,0,613,0,611,0,594,0,595,0,591,0,589,0,584,0,573,0,567,0,569,0,621,0,629,0,628,0,612,0,595,0,597,0,593,0,590,0,580,0,574,0,573,0,573,0,620,0,626,0,620,0,588,1,566,1,557,1,561,1,549,1,532,1,526,1,511,1,499,1,555,1,565,1,542,1,527,1,510,1,514,1,517,1,508,1,493,1,490,1,469,1,478,1,528,1,534,1,518,1,506,1),dim=c(2,70),dimnames=list(c('W','D'),1:70))
> y <- array(NA,dim=c(2,70),dimnames=list(c('W','D'),1:70))
> 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)
> library(lmtest)
Loading required package: zoo
Attaching package: 'zoo'
The following object(s) are masked from package:base :
as.Date.numeric
> n25 <- 25 #minimum number of obs. for Goldfeld-Quandt test
> 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
W D
1 519 0
2 517 0
3 510 0
4 509 0
5 501 0
6 507 0
7 569 0
8 580 0
9 578 0
10 565 0
11 547 0
12 555 0
13 562 0
14 561 0
15 555 0
16 544 0
17 537 0
18 543 0
19 594 0
20 611 0
21 613 0
22 611 0
23 594 0
24 595 0
25 591 0
26 589 0
27 584 0
28 573 0
29 567 0
30 569 0
31 621 0
32 629 0
33 628 0
34 612 0
35 595 0
36 597 0
37 593 0
38 590 0
39 580 0
40 574 0
41 573 0
42 573 0
43 620 0
44 626 0
45 620 0
46 588 1
47 566 1
48 557 1
49 561 1
50 549 1
51 532 1
52 526 1
53 511 1
54 499 1
55 555 1
56 565 1
57 542 1
58 527 1
59 510 1
60 514 1
61 517 1
62 508 1
63 493 1
64 490 1
65 469 1
66 478 1
67 528 1
68 534 1
69 518 1
70 506 1
> k <- length(x[1,])
> df <- as.data.frame(x)
> (mylm <- lm(df))
Call:
lm(formula = df)
Coefficients:
(Intercept) D
575.13 -49.41
> (mysum <- summary(mylm))
Call:
lm(formula = df)
Residuals:
Min 1Q Median 3Q Max
-74.13 -19.22 0.78 21.37 62.28
Coefficients:
Estimate Std. Error t value Pr(>|t|)
(Intercept) 575.133 4.947 116.255 < 2e-16 ***
D -49.413 8.278 -5.969 9.63e-08 ***
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
Residual standard error: 33.19 on 68 degrees of freedom
Multiple R-squared: 0.3438, Adjusted R-squared: 0.3342
F-statistic: 35.63 on 1 and 68 DF, p-value: 9.63e-08
> if (n > n25) {
+ kp3 <- k + 3
+ nmkm3 <- n - k - 3
+ gqarr <- array(NA, dim=c(nmkm3-kp3+1,3))
+ numgqtests <- 0
+ numsignificant1 <- 0
+ numsignificant5 <- 0
+ numsignificant10 <- 0
+ for (mypoint in kp3:nmkm3) {
+ j <- 0
+ numgqtests <- numgqtests + 1
+ for (myalt in c('greater', 'two.sided', 'less')) {
+ j <- j + 1
+ gqarr[mypoint-kp3+1,j] <- gqtest(mylm, point=mypoint, alternative=myalt)$p.value
+ }
+ if (gqarr[mypoint-kp3+1,2] < 0.01) numsignificant1 <- numsignificant1 + 1
+ if (gqarr[mypoint-kp3+1,2] < 0.05) numsignificant5 <- numsignificant5 + 1
+ if (gqarr[mypoint-kp3+1,2] < 0.10) numsignificant10 <- numsignificant10 + 1
+ }
+ gqarr
+ }
[,1] [,2] [,3]
[1,] 0.03104549 0.06209099 0.96895451
[2,] 0.01028207 0.02056413 0.98971793
[3,] 0.47719339 0.95438678 0.52280661
[4,] 0.77549027 0.44901945 0.22450973
[5,] 0.85534065 0.28931870 0.14465935
[6,] 0.84683516 0.30632968 0.15316484
[7,] 0.80763376 0.38473248 0.19236624
[8,] 0.77204121 0.45591758 0.22795879
[9,] 0.74494833 0.51010334 0.25505167
[10,] 0.71247821 0.57504357 0.28752179
[11,] 0.67272486 0.65455028 0.32727514
[12,] 0.64603788 0.70792424 0.35396212
[13,] 0.65216789 0.69566422 0.34783211
[14,] 0.65534715 0.68930570 0.34465285
[15,] 0.76255090 0.47489820 0.23744910
[16,] 0.89008962 0.21982077 0.10991038
[17,] 0.94590953 0.10818094 0.05409047
[18,] 0.96704647 0.06590707 0.03295353
[19,] 0.96547069 0.06905861 0.03452931
[20,] 0.96287172 0.07425657 0.03712828
[21,] 0.95646623 0.08706755 0.04353377
[22,] 0.94719837 0.10560326 0.05280163
[23,] 0.93382366 0.13235268 0.06617634
[24,] 0.91865462 0.16269077 0.08134538
[25,] 0.90689411 0.18621178 0.09310589
[26,] 0.89510935 0.20978131 0.10489065
[27,] 0.92108751 0.15782499 0.07891249
[28,] 0.95041740 0.09916521 0.04958260
[29,] 0.96693630 0.06612741 0.03306370
[30,] 0.96525734 0.06948532 0.03474266
[31,] 0.95346240 0.09307520 0.04653760
[32,] 0.93909124 0.12181753 0.06090876
[33,] 0.91915077 0.16169847 0.08084923
[34,] 0.89331253 0.21337494 0.10668747
[35,] 0.86414241 0.27171518 0.13585759
[36,] 0.84026147 0.31947707 0.15973853
[37,] 0.82660030 0.34679940 0.17339970
[38,] 0.83662867 0.32674266 0.16337133
[39,] 0.82238697 0.35522607 0.17761303
[40,] 0.81223025 0.37553950 0.18776975
[41,] 0.78843897 0.42312206 0.21156103
[42,] 0.87679517 0.24640966 0.12320483
[43,] 0.89876011 0.20247977 0.10123989
[44,] 0.90559671 0.18880658 0.09440329
[45,] 0.92587474 0.14825051 0.07412526
[46,] 0.92764398 0.14471205 0.07235602
[47,] 0.90955567 0.18088865 0.09044433
[48,] 0.88194706 0.23610588 0.11805294
[49,] 0.84855770 0.30288460 0.15144230
[50,] 0.82653090 0.34693821 0.17346910
[51,] 0.85797180 0.28405640 0.14202820
[52,] 0.94647933 0.10704133 0.05352067
[53,] 0.95866444 0.08267112 0.04133556
[54,] 0.94873408 0.10253183 0.05126592
[55,] 0.91699338 0.16601323 0.08300662
[56,] 0.87282246 0.25435508 0.12717754
[57,] 0.81840280 0.36319441 0.18159720
[58,] 0.72949065 0.54101870 0.27050935
[59,] 0.62968278 0.74063444 0.37031722
[60,] 0.52289722 0.95420555 0.47710278
[61,] 0.63422000 0.73155999 0.36578000
> postscript(file="/var/www/html/rcomp/tmp/14yjx1227528274.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$resid)
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/2gbcp1227528274.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> plot(mysum$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/32cwz1227528274.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> hist(mysum$resid, main='Residual Histogram', xlab='values of Residuals')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/4gn3v1227528274.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> densityplot(~mysum$resid,col='black',main='Residual Density Plot', xlab='values of Residuals')
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/5flqs1227528274.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> qqnorm(mysum$resid, main='Residual Normal Q-Q Plot')
> qqline(mysum$resid)
> grid()
> dev.off()
null device
1
> (myerror <- as.ts(mysum$resid))
Time Series:
Start = 1
End = 70
Frequency = 1
1 2 3 4 5 6 7
-56.133333 -58.133333 -65.133333 -66.133333 -74.133333 -68.133333 -6.133333
8 9 10 11 12 13 14
4.866667 2.866667 -10.133333 -28.133333 -20.133333 -13.133333 -14.133333
15 16 17 18 19 20 21
-20.133333 -31.133333 -38.133333 -32.133333 18.866667 35.866667 37.866667
22 23 24 25 26 27 28
35.866667 18.866667 19.866667 15.866667 13.866667 8.866667 -2.133333
29 30 31 32 33 34 35
-8.133333 -6.133333 45.866667 53.866667 52.866667 36.866667 19.866667
36 37 38 39 40 41 42
21.866667 17.866667 14.866667 4.866667 -1.133333 -2.133333 -2.133333
43 44 45 46 47 48 49
44.866667 50.866667 44.866667 62.280000 40.280000 31.280000 35.280000
50 51 52 53 54 55 56
23.280000 6.280000 0.280000 -14.720000 -26.720000 29.280000 39.280000
57 58 59 60 61 62 63
16.280000 1.280000 -15.720000 -11.720000 -8.720000 -17.720000 -32.720000
64 65 66 67 68 69 70
-35.720000 -56.720000 -47.720000 2.280000 8.280000 -7.720000 -19.720000
> postscript(file="/var/www/html/rcomp/tmp/6ztye1227528275.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 = 70
Frequency = 1
lag(myerror, k = 1) myerror
0 -56.133333 NA
1 -58.133333 -56.133333
2 -65.133333 -58.133333
3 -66.133333 -65.133333
4 -74.133333 -66.133333
5 -68.133333 -74.133333
6 -6.133333 -68.133333
7 4.866667 -6.133333
8 2.866667 4.866667
9 -10.133333 2.866667
10 -28.133333 -10.133333
11 -20.133333 -28.133333
12 -13.133333 -20.133333
13 -14.133333 -13.133333
14 -20.133333 -14.133333
15 -31.133333 -20.133333
16 -38.133333 -31.133333
17 -32.133333 -38.133333
18 18.866667 -32.133333
19 35.866667 18.866667
20 37.866667 35.866667
21 35.866667 37.866667
22 18.866667 35.866667
23 19.866667 18.866667
24 15.866667 19.866667
25 13.866667 15.866667
26 8.866667 13.866667
27 -2.133333 8.866667
28 -8.133333 -2.133333
29 -6.133333 -8.133333
30 45.866667 -6.133333
31 53.866667 45.866667
32 52.866667 53.866667
33 36.866667 52.866667
34 19.866667 36.866667
35 21.866667 19.866667
36 17.866667 21.866667
37 14.866667 17.866667
38 4.866667 14.866667
39 -1.133333 4.866667
40 -2.133333 -1.133333
41 -2.133333 -2.133333
42 44.866667 -2.133333
43 50.866667 44.866667
44 44.866667 50.866667
45 62.280000 44.866667
46 40.280000 62.280000
47 31.280000 40.280000
48 35.280000 31.280000
49 23.280000 35.280000
50 6.280000 23.280000
51 0.280000 6.280000
52 -14.720000 0.280000
53 -26.720000 -14.720000
54 29.280000 -26.720000
55 39.280000 29.280000
56 16.280000 39.280000
57 1.280000 16.280000
58 -15.720000 1.280000
59 -11.720000 -15.720000
60 -8.720000 -11.720000
61 -17.720000 -8.720000
62 -32.720000 -17.720000
63 -35.720000 -32.720000
64 -56.720000 -35.720000
65 -47.720000 -56.720000
66 2.280000 -47.720000
67 8.280000 2.280000
68 -7.720000 8.280000
69 -19.720000 -7.720000
70 NA -19.720000
> dum1 <- dum[2:length(myerror),]
> dum1
lag(myerror, k = 1) myerror
[1,] -58.133333 -56.133333
[2,] -65.133333 -58.133333
[3,] -66.133333 -65.133333
[4,] -74.133333 -66.133333
[5,] -68.133333 -74.133333
[6,] -6.133333 -68.133333
[7,] 4.866667 -6.133333
[8,] 2.866667 4.866667
[9,] -10.133333 2.866667
[10,] -28.133333 -10.133333
[11,] -20.133333 -28.133333
[12,] -13.133333 -20.133333
[13,] -14.133333 -13.133333
[14,] -20.133333 -14.133333
[15,] -31.133333 -20.133333
[16,] -38.133333 -31.133333
[17,] -32.133333 -38.133333
[18,] 18.866667 -32.133333
[19,] 35.866667 18.866667
[20,] 37.866667 35.866667
[21,] 35.866667 37.866667
[22,] 18.866667 35.866667
[23,] 19.866667 18.866667
[24,] 15.866667 19.866667
[25,] 13.866667 15.866667
[26,] 8.866667 13.866667
[27,] -2.133333 8.866667
[28,] -8.133333 -2.133333
[29,] -6.133333 -8.133333
[30,] 45.866667 -6.133333
[31,] 53.866667 45.866667
[32,] 52.866667 53.866667
[33,] 36.866667 52.866667
[34,] 19.866667 36.866667
[35,] 21.866667 19.866667
[36,] 17.866667 21.866667
[37,] 14.866667 17.866667
[38,] 4.866667 14.866667
[39,] -1.133333 4.866667
[40,] -2.133333 -1.133333
[41,] -2.133333 -2.133333
[42,] 44.866667 -2.133333
[43,] 50.866667 44.866667
[44,] 44.866667 50.866667
[45,] 62.280000 44.866667
[46,] 40.280000 62.280000
[47,] 31.280000 40.280000
[48,] 35.280000 31.280000
[49,] 23.280000 35.280000
[50,] 6.280000 23.280000
[51,] 0.280000 6.280000
[52,] -14.720000 0.280000
[53,] -26.720000 -14.720000
[54,] 29.280000 -26.720000
[55,] 39.280000 29.280000
[56,] 16.280000 39.280000
[57,] 1.280000 16.280000
[58,] -15.720000 1.280000
[59,] -11.720000 -15.720000
[60,] -8.720000 -11.720000
[61,] -17.720000 -8.720000
[62,] -32.720000 -17.720000
[63,] -35.720000 -32.720000
[64,] -56.720000 -35.720000
[65,] -47.720000 -56.720000
[66,] 2.280000 -47.720000
[67,] 8.280000 2.280000
[68,] -7.720000 8.280000
[69,] -19.720000 -7.720000
> z <- as.data.frame(dum1)
> z
lag(myerror, k = 1) myerror
1 -58.133333 -56.133333
2 -65.133333 -58.133333
3 -66.133333 -65.133333
4 -74.133333 -66.133333
5 -68.133333 -74.133333
6 -6.133333 -68.133333
7 4.866667 -6.133333
8 2.866667 4.866667
9 -10.133333 2.866667
10 -28.133333 -10.133333
11 -20.133333 -28.133333
12 -13.133333 -20.133333
13 -14.133333 -13.133333
14 -20.133333 -14.133333
15 -31.133333 -20.133333
16 -38.133333 -31.133333
17 -32.133333 -38.133333
18 18.866667 -32.133333
19 35.866667 18.866667
20 37.866667 35.866667
21 35.866667 37.866667
22 18.866667 35.866667
23 19.866667 18.866667
24 15.866667 19.866667
25 13.866667 15.866667
26 8.866667 13.866667
27 -2.133333 8.866667
28 -8.133333 -2.133333
29 -6.133333 -8.133333
30 45.866667 -6.133333
31 53.866667 45.866667
32 52.866667 53.866667
33 36.866667 52.866667
34 19.866667 36.866667
35 21.866667 19.866667
36 17.866667 21.866667
37 14.866667 17.866667
38 4.866667 14.866667
39 -1.133333 4.866667
40 -2.133333 -1.133333
41 -2.133333 -2.133333
42 44.866667 -2.133333
43 50.866667 44.866667
44 44.866667 50.866667
45 62.280000 44.866667
46 40.280000 62.280000
47 31.280000 40.280000
48 35.280000 31.280000
49 23.280000 35.280000
50 6.280000 23.280000
51 0.280000 6.280000
52 -14.720000 0.280000
53 -26.720000 -14.720000
54 29.280000 -26.720000
55 39.280000 29.280000
56 16.280000 39.280000
57 1.280000 16.280000
58 -15.720000 1.280000
59 -11.720000 -15.720000
60 -8.720000 -11.720000
61 -17.720000 -8.720000
62 -32.720000 -17.720000
63 -35.720000 -32.720000
64 -56.720000 -35.720000
65 -47.720000 -56.720000
66 2.280000 -47.720000
67 8.280000 2.280000
68 -7.720000 8.280000
69 -19.720000 -7.720000
> 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/7v3kx1227528275.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> acf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/8dzq31227528275.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> pacf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Partial Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/9vtcw1227528275.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> opar <- par(mfrow = c(2,2), oma = c(0, 0, 1.1, 0))
> plot(mylm, las = 1, sub='Residual Diagnostics')
> par(opar)
> dev.off()
null device
1
> if (n > n25) {
+ postscript(file="/var/www/html/rcomp/tmp/10cddo1227528275.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
+ plot(kp3:nmkm3,gqarr[,2], main='Goldfeld-Quandt test',ylab='2-sided p-value',xlab='breakpoint')
+ grid()
+ dev.off()
+ }
null device
1
>
> #Note: the /var/www/html/rcomp/createtable file can be downloaded at http://www.wessa.net/cretab
> load(file="/var/www/html/rcomp/createtable")
>
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a, 'Multiple Linear Regression - Estimated Regression Equation', 1, TRUE)
> a<-table.row.end(a)
> myeq <- colnames(x)[1]
> myeq <- paste(myeq, '[t] = ', sep='')
> for (i in 1:k){
+ if (mysum$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/11zddh1227528275.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/12lvl71227528275.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/1326j11227528275.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/14d8kt1227528275.tab")
> if (n > n25) {
+ a<-table.start()
+ a<-table.row.start(a)
+ a<-table.element(a,'Goldfeld-Quandt test for Heteroskedasticity',4,TRUE)
+ a<-table.row.end(a)
+ a<-table.row.start(a)
+ a<-table.element(a,'p-values',header=TRUE)
+ a<-table.element(a,'Alternative Hypothesis',3,header=TRUE)
+ a<-table.row.end(a)
+ a<-table.row.start(a)
+ a<-table.element(a,'breakpoint index',header=TRUE)
+ a<-table.element(a,'greater',header=TRUE)
+ a<-table.element(a,'2-sided',header=TRUE)
+ a<-table.element(a,'less',header=TRUE)
+ a<-table.row.end(a)
+ for (mypoint in kp3:nmkm3) {
+ a<-table.row.start(a)
+ a<-table.element(a,mypoint,header=TRUE)
+ a<-table.element(a,gqarr[mypoint-kp3+1,1])
+ a<-table.element(a,gqarr[mypoint-kp3+1,2])
+ a<-table.element(a,gqarr[mypoint-kp3+1,3])
+ a<-table.row.end(a)
+ }
+ a<-table.end(a)
+ table.save(a,file="/var/www/html/rcomp/tmp/15gkiz1227528275.tab")
+ a<-table.start()
+ a<-table.row.start(a)
+ a<-table.element(a,'Meta Analysis of Goldfeld-Quandt test for Heteroskedasticity',4,TRUE)
+ a<-table.row.end(a)
+ a<-table.row.start(a)
+ a<-table.element(a,'Description',header=TRUE)
+ a<-table.element(a,'# significant tests',header=TRUE)
+ a<-table.element(a,'% significant tests',header=TRUE)
+ a<-table.element(a,'OK/NOK',header=TRUE)
+ a<-table.row.end(a)
+ a<-table.row.start(a)
+ a<-table.element(a,'1% type I error level',header=TRUE)
+ a<-table.element(a,numsignificant1)
+ a<-table.element(a,numsignificant1/numgqtests)
+ if (numsignificant1/numgqtests < 0.01) dum <- 'OK' else dum <- 'NOK'
+ a<-table.element(a,dum)
+ a<-table.row.end(a)
+ a<-table.row.start(a)
+ a<-table.element(a,'5% type I error level',header=TRUE)
+ a<-table.element(a,numsignificant5)
+ a<-table.element(a,numsignificant5/numgqtests)
+ if (numsignificant5/numgqtests < 0.05) dum <- 'OK' else dum <- 'NOK'
+ a<-table.element(a,dum)
+ a<-table.row.end(a)
+ a<-table.row.start(a)
+ a<-table.element(a,'10% type I error level',header=TRUE)
+ a<-table.element(a,numsignificant10)
+ a<-table.element(a,numsignificant10/numgqtests)
+ if (numsignificant10/numgqtests < 0.1) dum <- 'OK' else dum <- 'NOK'
+ a<-table.element(a,dum)
+ a<-table.row.end(a)
+ a<-table.end(a)
+ table.save(a,file="/var/www/html/rcomp/tmp/16xp891227528275.tab")
+ }
>
> system("convert tmp/14yjx1227528274.ps tmp/14yjx1227528274.png")
> system("convert tmp/2gbcp1227528274.ps tmp/2gbcp1227528274.png")
> system("convert tmp/32cwz1227528274.ps tmp/32cwz1227528274.png")
> system("convert tmp/4gn3v1227528274.ps tmp/4gn3v1227528274.png")
> system("convert tmp/5flqs1227528274.ps tmp/5flqs1227528274.png")
> system("convert tmp/6ztye1227528275.ps tmp/6ztye1227528275.png")
> system("convert tmp/7v3kx1227528275.ps tmp/7v3kx1227528275.png")
> system("convert tmp/8dzq31227528275.ps tmp/8dzq31227528275.png")
> system("convert tmp/9vtcw1227528275.ps tmp/9vtcw1227528275.png")
> system("convert tmp/10cddo1227528275.ps tmp/10cddo1227528275.png")
>
>
> proc.time()
user system elapsed
2.516 1.539 3.002