R version 2.9.0 (2009-04-17)
Copyright (C) 2009 The R Foundation for Statistical Computing
ISBN 3-900051-07-0
R is free software and comes with ABSOLUTELY NO WARRANTY.
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Type 'license()' or 'licence()' for distribution details.
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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
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Type 'q()' to quit R.
> x <- array(list(8.1,10.9,7.7,10.0,7.5,9.2,7.6,9.2,7.8,9.5,7.8,9.6,7.8,9.5,7.5,9.1,7.5,8.9,7.1,9.0,7.5,10.1,7.5,10.3,7.6,10.2,7.7,9.6,7.7,9.2,7.9,9.3,8.1,9.4,8.2,9.4,8.2,9.2,8.2,9.0,7.9,9.0,7.3,9.0,6.9,9.8,6.6,10.0,6.7,9.8,6.9,9.3,7.0,9.0,7.1,9.0,7.2,9.1,7.1,9.1,6.9,9.1,7.0,9.2,6.8,8.8,6.4,8.3,6.7,8.4,6.6,8.1,6.4,7.7,6.3,7.9,6.2,7.9,6.5,8.0,6.8,7.9,6.8,7.6,6.4,7.1,6.1,6.8,5.8,6.5,6.1,6.9,7.2,8.2,7.3,8.7,6.9,8.3,6.1,7.9,5.8,7.5,6.2,7.8,7.1,8.3,7.7,8.4,7.9,8.2,7.7,7.7,7.4,7.2,7.5,7.3,8.0,8.1,8.1,8.5),dim=c(2,60),dimnames=list(c('Y','X'),1:60))
> y <- array(NA,dim=c(2,60),dimnames=list(c('Y','X'),1:60))
> 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
Y X
1 8.1 10.9
2 7.7 10.0
3 7.5 9.2
4 7.6 9.2
5 7.8 9.5
6 7.8 9.6
7 7.8 9.5
8 7.5 9.1
9 7.5 8.9
10 7.1 9.0
11 7.5 10.1
12 7.5 10.3
13 7.6 10.2
14 7.7 9.6
15 7.7 9.2
16 7.9 9.3
17 8.1 9.4
18 8.2 9.4
19 8.2 9.2
20 8.2 9.0
21 7.9 9.0
22 7.3 9.0
23 6.9 9.8
24 6.6 10.0
25 6.7 9.8
26 6.9 9.3
27 7.0 9.0
28 7.1 9.0
29 7.2 9.1
30 7.1 9.1
31 6.9 9.1
32 7.0 9.2
33 6.8 8.8
34 6.4 8.3
35 6.7 8.4
36 6.6 8.1
37 6.4 7.7
38 6.3 7.9
39 6.2 7.9
40 6.5 8.0
41 6.8 7.9
42 6.8 7.6
43 6.4 7.1
44 6.1 6.8
45 5.8 6.5
46 6.1 6.9
47 7.2 8.2
48 7.3 8.7
49 6.9 8.3
50 6.1 7.9
51 5.8 7.5
52 6.2 7.8
53 7.1 8.3
54 7.7 8.4
55 7.9 8.2
56 7.7 7.7
57 7.4 7.2
58 7.5 7.3
59 8.0 8.1
60 8.1 8.5
> k <- length(x[1,])
> df <- as.data.frame(x)
> (mylm <- lm(df))
Call:
lm(formula = df)
Coefficients:
(Intercept) X
3.676 0.402
> (mysum <- summary(mylm))
Call:
lm(formula = df)
Residuals:
Min 1Q Median 3Q Max
-1.09596 -0.37207 -0.08212 0.30505 1.06788
Coefficients:
Estimate Std. Error t value Pr(>|t|)
(Intercept) 3.67573 0.64978 5.657 4.98e-07 ***
X 0.40202 0.07425 5.414 1.23e-06 ***
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
Residual standard error: 0.5425 on 58 degrees of freedom
Multiple R-squared: 0.3357, Adjusted R-squared: 0.3243
F-statistic: 29.31 on 1 and 58 DF, p-value: 1.230e-06
> 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,] 1.058222e-02 2.116445e-02 0.9894177772
[2,] 2.618280e-03 5.236560e-03 0.9973817200
[3,] 7.196508e-04 1.439302e-03 0.9992803492
[4,] 1.610311e-04 3.220622e-04 0.9998389689
[5,] 2.608331e-05 5.216662e-05 0.9999739167
[6,] 4.362051e-04 8.724102e-04 0.9995637949
[7,] 5.685435e-04 1.137087e-03 0.9994314565
[8,] 5.673224e-04 1.134645e-03 0.9994326776
[9,] 2.308053e-04 4.616106e-04 0.9997691947
[10,] 7.963105e-05 1.592621e-04 0.9999203690
[11,] 3.507202e-05 7.014405e-05 0.9999649280
[12,] 3.842459e-05 7.684919e-05 0.9999615754
[13,] 1.187595e-04 2.375190e-04 0.9998812405
[14,] 4.333052e-04 8.666104e-04 0.9995666948
[15,] 1.205834e-03 2.411669e-03 0.9987941657
[16,] 2.882502e-03 5.765004e-03 0.9971174982
[17,] 2.341904e-03 4.683808e-03 0.9976580958
[18,] 2.353990e-03 4.707981e-03 0.9976460096
[19,] 9.706993e-03 1.941399e-02 0.9902930073
[20,] 5.700896e-02 1.140179e-01 0.9429910369
[21,] 1.198123e-01 2.396247e-01 0.8801876570
[22,] 1.444359e-01 2.888718e-01 0.8555640841
[23,] 1.431015e-01 2.862030e-01 0.8568985073
[24,] 1.237402e-01 2.474804e-01 0.8762598091
[25,] 9.740238e-02 1.948048e-01 0.9025976240
[26,] 8.054786e-02 1.610957e-01 0.9194521398
[27,] 8.210272e-02 1.642054e-01 0.9178972819
[28,] 7.680161e-02 1.536032e-01 0.9231983900
[29,] 8.254177e-02 1.650835e-01 0.9174582262
[30,] 1.195245e-01 2.390490e-01 0.8804754953
[31,] 1.129928e-01 2.259855e-01 0.8870072417
[32,] 9.977385e-02 1.995477e-01 0.9002261525
[33,] 8.394938e-02 1.678988e-01 0.9160506182
[34,] 8.802243e-02 1.760449e-01 0.9119775690
[35,] 1.073298e-01 2.146596e-01 0.8926702154
[36,] 9.996216e-02 1.999243e-01 0.9000378442
[37,] 7.364873e-02 1.472975e-01 0.9263512705
[38,] 5.138125e-02 1.027625e-01 0.9486187548
[39,] 3.330194e-02 6.660387e-02 0.9666980633
[40,] 2.112170e-02 4.224341e-02 0.9788782975
[41,] 1.432179e-02 2.864357e-02 0.9856782144
[42,] 1.019778e-02 2.039555e-02 0.9898022229
[43,] 6.312895e-03 1.262579e-02 0.9936871052
[44,] 3.808068e-03 7.616136e-03 0.9961919321
[45,] 2.780080e-03 5.560160e-03 0.9972199200
[46,] 1.119474e-02 2.238948e-02 0.9888052578
[47,] 1.136874e-01 2.273749e-01 0.8863125559
[48,] 7.637403e-01 4.725194e-01 0.2362597060
[49,] 9.889471e-01 2.210584e-02 0.0110529217
[50,] 9.994103e-01 1.179374e-03 0.0005896872
[51,] 9.978915e-01 4.217026e-03 0.0021085128
> postscript(file="/var/www/html/rcomp/tmp/14q1h1258810777.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$resid)
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/2atpd1258810777.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> plot(mysum$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/3rjas1258810777.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> hist(mysum$resid, main='Residual Histogram', xlab='values of Residuals')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/4puph1258810777.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> densityplot(~mysum$resid,col='black',main='Residual Density Plot', xlab='values of Residuals')
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/5gueo1258810777.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 = 60
Frequency = 1
1 2 3 4 5 6
0.042215561 0.004036468 0.125655052 0.225655052 0.305048083 0.264845760
7 8 9 10 11 12
0.305048083 0.165857375 0.246262021 -0.193940302 -0.236165855 -0.316570501
13 14 15 16 17 18
-0.176368178 0.164845760 0.325655052 0.485452729 0.645250406 0.745250406
19 20 21 22 23 24
0.825655052 0.906059698 0.606059698 0.006059698 -0.715558886 -1.095963532
25 26 27 28 29 30
-0.915558886 -0.514547271 -0.293940302 -0.193940302 -0.134142625 -0.234142625
31 32 33 34 35 36
-0.434142625 -0.374344948 -0.413535656 -0.612524041 -0.352726364 -0.332119396
37 38 39 40 41 42
-0.371310104 -0.551714750 -0.651714750 -0.391917073 -0.051714750 0.068892219
43 44 45 46 47 48
-0.130096166 -0.309489197 -0.488882228 -0.349691520 0.227678282 0.126666667
49 50 51 52 53 54
-0.112524041 -0.751714750 -0.890905458 -0.611512427 0.087475959 0.647273636
55 56 57 58 59 60
0.927678282 0.928689896 0.829701511 0.889499188 1.067880604 1.007071313
> postscript(file="/var/www/html/rcomp/tmp/69rdw1258810777.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 = 60
Frequency = 1
lag(myerror, k = 1) myerror
0 0.042215561 NA
1 0.004036468 0.042215561
2 0.125655052 0.004036468
3 0.225655052 0.125655052
4 0.305048083 0.225655052
5 0.264845760 0.305048083
6 0.305048083 0.264845760
7 0.165857375 0.305048083
8 0.246262021 0.165857375
9 -0.193940302 0.246262021
10 -0.236165855 -0.193940302
11 -0.316570501 -0.236165855
12 -0.176368178 -0.316570501
13 0.164845760 -0.176368178
14 0.325655052 0.164845760
15 0.485452729 0.325655052
16 0.645250406 0.485452729
17 0.745250406 0.645250406
18 0.825655052 0.745250406
19 0.906059698 0.825655052
20 0.606059698 0.906059698
21 0.006059698 0.606059698
22 -0.715558886 0.006059698
23 -1.095963532 -0.715558886
24 -0.915558886 -1.095963532
25 -0.514547271 -0.915558886
26 -0.293940302 -0.514547271
27 -0.193940302 -0.293940302
28 -0.134142625 -0.193940302
29 -0.234142625 -0.134142625
30 -0.434142625 -0.234142625
31 -0.374344948 -0.434142625
32 -0.413535656 -0.374344948
33 -0.612524041 -0.413535656
34 -0.352726364 -0.612524041
35 -0.332119396 -0.352726364
36 -0.371310104 -0.332119396
37 -0.551714750 -0.371310104
38 -0.651714750 -0.551714750
39 -0.391917073 -0.651714750
40 -0.051714750 -0.391917073
41 0.068892219 -0.051714750
42 -0.130096166 0.068892219
43 -0.309489197 -0.130096166
44 -0.488882228 -0.309489197
45 -0.349691520 -0.488882228
46 0.227678282 -0.349691520
47 0.126666667 0.227678282
48 -0.112524041 0.126666667
49 -0.751714750 -0.112524041
50 -0.890905458 -0.751714750
51 -0.611512427 -0.890905458
52 0.087475959 -0.611512427
53 0.647273636 0.087475959
54 0.927678282 0.647273636
55 0.928689896 0.927678282
56 0.829701511 0.928689896
57 0.889499188 0.829701511
58 1.067880604 0.889499188
59 1.007071313 1.067880604
60 NA 1.007071313
> dum1 <- dum[2:length(myerror),]
> dum1
lag(myerror, k = 1) myerror
[1,] 0.004036468 0.042215561
[2,] 0.125655052 0.004036468
[3,] 0.225655052 0.125655052
[4,] 0.305048083 0.225655052
[5,] 0.264845760 0.305048083
[6,] 0.305048083 0.264845760
[7,] 0.165857375 0.305048083
[8,] 0.246262021 0.165857375
[9,] -0.193940302 0.246262021
[10,] -0.236165855 -0.193940302
[11,] -0.316570501 -0.236165855
[12,] -0.176368178 -0.316570501
[13,] 0.164845760 -0.176368178
[14,] 0.325655052 0.164845760
[15,] 0.485452729 0.325655052
[16,] 0.645250406 0.485452729
[17,] 0.745250406 0.645250406
[18,] 0.825655052 0.745250406
[19,] 0.906059698 0.825655052
[20,] 0.606059698 0.906059698
[21,] 0.006059698 0.606059698
[22,] -0.715558886 0.006059698
[23,] -1.095963532 -0.715558886
[24,] -0.915558886 -1.095963532
[25,] -0.514547271 -0.915558886
[26,] -0.293940302 -0.514547271
[27,] -0.193940302 -0.293940302
[28,] -0.134142625 -0.193940302
[29,] -0.234142625 -0.134142625
[30,] -0.434142625 -0.234142625
[31,] -0.374344948 -0.434142625
[32,] -0.413535656 -0.374344948
[33,] -0.612524041 -0.413535656
[34,] -0.352726364 -0.612524041
[35,] -0.332119396 -0.352726364
[36,] -0.371310104 -0.332119396
[37,] -0.551714750 -0.371310104
[38,] -0.651714750 -0.551714750
[39,] -0.391917073 -0.651714750
[40,] -0.051714750 -0.391917073
[41,] 0.068892219 -0.051714750
[42,] -0.130096166 0.068892219
[43,] -0.309489197 -0.130096166
[44,] -0.488882228 -0.309489197
[45,] -0.349691520 -0.488882228
[46,] 0.227678282 -0.349691520
[47,] 0.126666667 0.227678282
[48,] -0.112524041 0.126666667
[49,] -0.751714750 -0.112524041
[50,] -0.890905458 -0.751714750
[51,] -0.611512427 -0.890905458
[52,] 0.087475959 -0.611512427
[53,] 0.647273636 0.087475959
[54,] 0.927678282 0.647273636
[55,] 0.928689896 0.927678282
[56,] 0.829701511 0.928689896
[57,] 0.889499188 0.829701511
[58,] 1.067880604 0.889499188
[59,] 1.007071313 1.067880604
> z <- as.data.frame(dum1)
> z
lag(myerror, k = 1) myerror
1 0.004036468 0.042215561
2 0.125655052 0.004036468
3 0.225655052 0.125655052
4 0.305048083 0.225655052
5 0.264845760 0.305048083
6 0.305048083 0.264845760
7 0.165857375 0.305048083
8 0.246262021 0.165857375
9 -0.193940302 0.246262021
10 -0.236165855 -0.193940302
11 -0.316570501 -0.236165855
12 -0.176368178 -0.316570501
13 0.164845760 -0.176368178
14 0.325655052 0.164845760
15 0.485452729 0.325655052
16 0.645250406 0.485452729
17 0.745250406 0.645250406
18 0.825655052 0.745250406
19 0.906059698 0.825655052
20 0.606059698 0.906059698
21 0.006059698 0.606059698
22 -0.715558886 0.006059698
23 -1.095963532 -0.715558886
24 -0.915558886 -1.095963532
25 -0.514547271 -0.915558886
26 -0.293940302 -0.514547271
27 -0.193940302 -0.293940302
28 -0.134142625 -0.193940302
29 -0.234142625 -0.134142625
30 -0.434142625 -0.234142625
31 -0.374344948 -0.434142625
32 -0.413535656 -0.374344948
33 -0.612524041 -0.413535656
34 -0.352726364 -0.612524041
35 -0.332119396 -0.352726364
36 -0.371310104 -0.332119396
37 -0.551714750 -0.371310104
38 -0.651714750 -0.551714750
39 -0.391917073 -0.651714750
40 -0.051714750 -0.391917073
41 0.068892219 -0.051714750
42 -0.130096166 0.068892219
43 -0.309489197 -0.130096166
44 -0.488882228 -0.309489197
45 -0.349691520 -0.488882228
46 0.227678282 -0.349691520
47 0.126666667 0.227678282
48 -0.112524041 0.126666667
49 -0.751714750 -0.112524041
50 -0.890905458 -0.751714750
51 -0.611512427 -0.890905458
52 0.087475959 -0.611512427
53 0.647273636 0.087475959
54 0.927678282 0.647273636
55 0.928689896 0.927678282
56 0.829701511 0.928689896
57 0.889499188 0.829701511
58 1.067880604 0.889499188
59 1.007071313 1.067880604
> 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/7u7e91258810777.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> acf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/8js6u1258810777.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> pacf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Partial Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/9qsal1258810777.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> opar <- par(mfrow = c(2,2), oma = c(0, 0, 1.1, 0))
> plot(mylm, las = 1, sub='Residual Diagnostics')
> par(opar)
> dev.off()
null device
1
> if (n > n25) {
+ postscript(file="/var/www/html/rcomp/tmp/10j65s1258810777.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
+ plot(kp3:nmkm3,gqarr[,2], main='Goldfeld-Quandt test',ylab='2-sided p-value',xlab='breakpoint')
+ grid()
+ dev.off()
+ }
null device
1
>
> #Note: the /var/www/html/rcomp/createtable file can be downloaded at http://www.wessa.net/cretab
> load(file="/var/www/html/rcomp/createtable")
>
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a, 'Multiple Linear Regression - Estimated Regression Equation', 1, TRUE)
> a<-table.row.end(a)
> myeq <- colnames(x)[1]
> myeq <- paste(myeq, '[t] = ', sep='')
> for (i in 1:k){
+ if (mysum$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/1184ny1258810777.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/12b35w1258810777.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/13jexu1258810777.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/14pfsb1258810777.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/152r2n1258810777.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/16gw2b1258810777.tab")
+ }
>
> system("convert tmp/14q1h1258810777.ps tmp/14q1h1258810777.png")
> system("convert tmp/2atpd1258810777.ps tmp/2atpd1258810777.png")
> system("convert tmp/3rjas1258810777.ps tmp/3rjas1258810777.png")
> system("convert tmp/4puph1258810777.ps tmp/4puph1258810777.png")
> system("convert tmp/5gueo1258810777.ps tmp/5gueo1258810777.png")
> system("convert tmp/69rdw1258810777.ps tmp/69rdw1258810777.png")
> system("convert tmp/7u7e91258810777.ps tmp/7u7e91258810777.png")
> system("convert tmp/8js6u1258810777.ps tmp/8js6u1258810777.png")
> system("convert tmp/9qsal1258810777.ps tmp/9qsal1258810777.png")
> system("convert tmp/10j65s1258810777.ps tmp/10j65s1258810777.png")
>
>
> proc.time()
user system elapsed
2.453 1.559 3.436