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.
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(2756.76,0,2849.27,0,2921.44,0,2981.85,0,3080.58,0,3106.22,0,3119.31,0,3061.26,0,3097.31,0,3161.69,0,3257.16,0,3277.01,0,3295.32,0,3363.99,0,3494.17,0,3667.03,1,3813.06,1,3917.96,1,3895.51,1,3801.06,1,3570.12,0,3701.61,1,3862.27,1,3970.1,1,4138.52,1,4199.75,1,4290.89,1,4443.91,1,4502.64,1,4356.98,1,4591.27,1,4696.96,1,4621.4,1,4562.84,1,4202.52,1,4296.49,1,4435.23,1,4105.18,1,4116.68,1,3844.49,1,3720.98,1,3674.4,1,3857.62,1,3801.06,1,3504.37,1,3032.6,1,3047.03,0,2962.34,1,2197.82,1,2014.45,1,1862.83,0,1905.41,0,1810.99,0,1670.07,0,1864.44,0,2052.02,0,2029.6,0,2070.83,0,2293.41,0,2443.27,0),dim=c(2,60),dimnames=list(c('BEL20','X
'),1:60))
> y <- array(NA,dim=c(2,60),dimnames=list(c('BEL20','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
BEL20 X\r
1 2756.76 0
2 2849.27 0
3 2921.44 0
4 2981.85 0
5 3080.58 0
6 3106.22 0
7 3119.31 0
8 3061.26 0
9 3097.31 0
10 3161.69 0
11 3257.16 0
12 3277.01 0
13 3295.32 0
14 3363.99 0
15 3494.17 0
16 3667.03 1
17 3813.06 1
18 3917.96 1
19 3895.51 1
20 3801.06 1
21 3570.12 0
22 3701.61 1
23 3862.27 1
24 3970.10 1
25 4138.52 1
26 4199.75 1
27 4290.89 1
28 4443.91 1
29 4502.64 1
30 4356.98 1
31 4591.27 1
32 4696.96 1
33 4621.40 1
34 4562.84 1
35 4202.52 1
36 4296.49 1
37 4435.23 1
38 4105.18 1
39 4116.68 1
40 3844.49 1
41 3720.98 1
42 3674.40 1
43 3857.62 1
44 3801.06 1
45 3504.37 1
46 3032.60 1
47 3047.03 0
48 2962.34 1
49 2197.82 1
50 2014.45 1
51 1862.83 0
52 1905.41 0
53 1810.99 0
54 1670.07 0
55 1864.44 0
56 2052.02 0
57 2029.60 0
58 2070.83 0
59 2293.41 0
60 2443.27 0
> k <- length(x[1,])
> df <- as.data.frame(x)
> (mylm <- lm(df))
Call:
lm(formula = df)
Coefficients:
(Intercept) `X\r`
2720 1183
> (mysum <- summary(mylm))
Call:
lm(formula = df)
Residuals:
Min 1Q Median 3Q Max
-1888.6 -246.2 165.2 409.8 850.0
Coefficients:
Estimate Std. Error t value Pr(>|t|)
(Intercept) 2720.1 117.9 23.07 < 2e-16 ***
`X\r` 1182.9 159.0 7.44 5.35e-10 ***
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
Residual standard error: 612.7 on 58 degrees of freedom
Multiple R-squared: 0.4883, Adjusted R-squared: 0.4795
F-statistic: 55.35 on 1 and 58 DF, p-value: 5.349e-10
> 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,] 1.511238e-02 3.022477e-02 0.98488762
[2,] 5.901290e-03 1.180258e-02 0.99409871
[3,] 2.123534e-03 4.247067e-03 0.99787647
[4,] 5.211286e-04 1.042257e-03 0.99947887
[5,] 1.415153e-04 2.830307e-04 0.99985848
[6,] 5.457897e-05 1.091579e-04 0.99994542
[7,] 4.203199e-05 8.406398e-05 0.99995797
[8,] 3.043454e-05 6.086908e-05 0.99996957
[9,] 2.206299e-05 4.412598e-05 0.99997794
[10,] 2.488699e-05 4.977399e-05 0.99997511
[11,] 7.260981e-05 1.452196e-04 0.99992739
[12,] 2.313453e-05 4.626907e-05 0.99997687
[13,] 7.891364e-06 1.578273e-05 0.99999211
[14,] 2.974324e-06 5.948647e-06 0.99999703
[15,] 9.195314e-07 1.839063e-06 0.99999908
[16,] 2.538537e-07 5.077074e-07 0.99999975
[17,] 2.179077e-06 4.358154e-06 0.99999782
[18,] 7.911715e-07 1.582343e-06 0.99999921
[19,] 2.486747e-07 4.973494e-07 0.99999975
[20,] 9.540462e-08 1.908092e-07 0.99999990
[21,] 7.650082e-08 1.530016e-07 0.99999992
[22,] 7.176494e-08 1.435299e-07 0.99999993
[23,] 9.748505e-08 1.949701e-07 0.99999990
[24,] 3.028547e-07 6.057095e-07 0.99999970
[25,] 9.017096e-07 1.803419e-06 0.99999910
[26,] 8.203370e-07 1.640674e-06 0.99999918
[27,] 2.762844e-06 5.525688e-06 0.99999724
[28,] 1.472151e-05 2.944301e-05 0.99998528
[29,] 4.059918e-05 8.119837e-05 0.99995940
[30,] 8.605045e-05 1.721009e-04 0.99991395
[31,] 6.265420e-05 1.253084e-04 0.99993735
[32,] 6.389027e-05 1.277805e-04 0.99993611
[33,] 1.391629e-04 2.783258e-04 0.99986084
[34,] 1.485886e-04 2.971772e-04 0.99985141
[35,] 2.098764e-04 4.197529e-04 0.99979012
[36,] 2.787381e-04 5.574763e-04 0.99972126
[37,] 4.283969e-04 8.567937e-04 0.99957160
[38,] 7.316561e-04 1.463312e-03 0.99926834
[39,] 2.009981e-03 4.019963e-03 0.99799002
[40,] 1.016990e-02 2.033979e-02 0.98983010
[41,] 5.349621e-02 1.069924e-01 0.94650379
[42,] 1.795981e-01 3.591961e-01 0.82040194
[43,] 6.347588e-01 7.304823e-01 0.36524117
[44,] 9.527429e-01 9.451425e-02 0.04725713
[45,] 9.802138e-01 3.957239e-02 0.01978620
[46,] 9.853920e-01 2.921596e-02 0.01460798
[47,] 9.787242e-01 4.255156e-02 0.02127578
[48,] 9.632913e-01 7.341744e-02 0.03670872
[49,] 9.467703e-01 1.064594e-01 0.05322970
[50,] 9.629261e-01 7.414784e-02 0.03707392
[51,] 9.488467e-01 1.023066e-01 0.05115329
> postscript(file="/var/www/html/rcomp/tmp/1wyu91258815972.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$resid)
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/2jc5w1258815972.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> plot(mysum$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/35s2c1258815972.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> hist(mysum$resid, main='Residual Histogram', xlab='values of Residuals')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/4wsee1258815972.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> densityplot(~mysum$resid,col='black',main='Residual Density Plot', xlab='values of Residuals')
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/59ow11258815972.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
36.63556 129.14556 201.31556 261.72556 360.45556 386.09556
7 8 9 10 11 12
399.18556 341.13556 377.18556 441.56556 537.03556 556.88556
13 14 15 16 17 18
575.19556 643.86556 774.04556 -236.00000 -89.97000 14.93000
19 20 21 22 23 24
-7.52000 -101.97000 849.99556 -201.42000 -40.76000 67.07000
25 26 27 28 29 30
235.49000 296.72000 387.86000 540.88000 599.61000 453.95000
31 32 33 34 35 36
688.24000 793.93000 718.37000 659.81000 299.49000 393.46000
37 38 39 40 41 42
532.20000 202.15000 213.65000 -58.54000 -182.05000 -228.63000
43 44 45 46 47 48
-45.41000 -101.97000 -398.66000 -870.43000 326.90556 -940.69000
49 50 51 52 53 54
-1705.21000 -1888.58000 -857.29444 -814.71444 -909.13444 -1050.05444
55 56 57 58 59 60
-855.68444 -668.10444 -690.52444 -649.29444 -426.71444 -276.85444
> postscript(file="/var/www/html/rcomp/tmp/6npwq1258815972.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 36.63556 NA
1 129.14556 36.63556
2 201.31556 129.14556
3 261.72556 201.31556
4 360.45556 261.72556
5 386.09556 360.45556
6 399.18556 386.09556
7 341.13556 399.18556
8 377.18556 341.13556
9 441.56556 377.18556
10 537.03556 441.56556
11 556.88556 537.03556
12 575.19556 556.88556
13 643.86556 575.19556
14 774.04556 643.86556
15 -236.00000 774.04556
16 -89.97000 -236.00000
17 14.93000 -89.97000
18 -7.52000 14.93000
19 -101.97000 -7.52000
20 849.99556 -101.97000
21 -201.42000 849.99556
22 -40.76000 -201.42000
23 67.07000 -40.76000
24 235.49000 67.07000
25 296.72000 235.49000
26 387.86000 296.72000
27 540.88000 387.86000
28 599.61000 540.88000
29 453.95000 599.61000
30 688.24000 453.95000
31 793.93000 688.24000
32 718.37000 793.93000
33 659.81000 718.37000
34 299.49000 659.81000
35 393.46000 299.49000
36 532.20000 393.46000
37 202.15000 532.20000
38 213.65000 202.15000
39 -58.54000 213.65000
40 -182.05000 -58.54000
41 -228.63000 -182.05000
42 -45.41000 -228.63000
43 -101.97000 -45.41000
44 -398.66000 -101.97000
45 -870.43000 -398.66000
46 326.90556 -870.43000
47 -940.69000 326.90556
48 -1705.21000 -940.69000
49 -1888.58000 -1705.21000
50 -857.29444 -1888.58000
51 -814.71444 -857.29444
52 -909.13444 -814.71444
53 -1050.05444 -909.13444
54 -855.68444 -1050.05444
55 -668.10444 -855.68444
56 -690.52444 -668.10444
57 -649.29444 -690.52444
58 -426.71444 -649.29444
59 -276.85444 -426.71444
60 NA -276.85444
> dum1 <- dum[2:length(myerror),]
> dum1
lag(myerror, k = 1) myerror
[1,] 129.1456 36.63556
[2,] 201.3156 129.14556
[3,] 261.7256 201.31556
[4,] 360.4556 261.72556
[5,] 386.0956 360.45556
[6,] 399.1856 386.09556
[7,] 341.1356 399.18556
[8,] 377.1856 341.13556
[9,] 441.5656 377.18556
[10,] 537.0356 441.56556
[11,] 556.8856 537.03556
[12,] 575.1956 556.88556
[13,] 643.8656 575.19556
[14,] 774.0456 643.86556
[15,] -236.0000 774.04556
[16,] -89.9700 -236.00000
[17,] 14.9300 -89.97000
[18,] -7.5200 14.93000
[19,] -101.9700 -7.52000
[20,] 849.9956 -101.97000
[21,] -201.4200 849.99556
[22,] -40.7600 -201.42000
[23,] 67.0700 -40.76000
[24,] 235.4900 67.07000
[25,] 296.7200 235.49000
[26,] 387.8600 296.72000
[27,] 540.8800 387.86000
[28,] 599.6100 540.88000
[29,] 453.9500 599.61000
[30,] 688.2400 453.95000
[31,] 793.9300 688.24000
[32,] 718.3700 793.93000
[33,] 659.8100 718.37000
[34,] 299.4900 659.81000
[35,] 393.4600 299.49000
[36,] 532.2000 393.46000
[37,] 202.1500 532.20000
[38,] 213.6500 202.15000
[39,] -58.5400 213.65000
[40,] -182.0500 -58.54000
[41,] -228.6300 -182.05000
[42,] -45.4100 -228.63000
[43,] -101.9700 -45.41000
[44,] -398.6600 -101.97000
[45,] -870.4300 -398.66000
[46,] 326.9056 -870.43000
[47,] -940.6900 326.90556
[48,] -1705.2100 -940.69000
[49,] -1888.5800 -1705.21000
[50,] -857.2944 -1888.58000
[51,] -814.7144 -857.29444
[52,] -909.1344 -814.71444
[53,] -1050.0544 -909.13444
[54,] -855.6844 -1050.05444
[55,] -668.1044 -855.68444
[56,] -690.5244 -668.10444
[57,] -649.2944 -690.52444
[58,] -426.7144 -649.29444
[59,] -276.8544 -426.71444
> z <- as.data.frame(dum1)
> z
lag(myerror, k = 1) myerror
1 129.1456 36.63556
2 201.3156 129.14556
3 261.7256 201.31556
4 360.4556 261.72556
5 386.0956 360.45556
6 399.1856 386.09556
7 341.1356 399.18556
8 377.1856 341.13556
9 441.5656 377.18556
10 537.0356 441.56556
11 556.8856 537.03556
12 575.1956 556.88556
13 643.8656 575.19556
14 774.0456 643.86556
15 -236.0000 774.04556
16 -89.9700 -236.00000
17 14.9300 -89.97000
18 -7.5200 14.93000
19 -101.9700 -7.52000
20 849.9956 -101.97000
21 -201.4200 849.99556
22 -40.7600 -201.42000
23 67.0700 -40.76000
24 235.4900 67.07000
25 296.7200 235.49000
26 387.8600 296.72000
27 540.8800 387.86000
28 599.6100 540.88000
29 453.9500 599.61000
30 688.2400 453.95000
31 793.9300 688.24000
32 718.3700 793.93000
33 659.8100 718.37000
34 299.4900 659.81000
35 393.4600 299.49000
36 532.2000 393.46000
37 202.1500 532.20000
38 213.6500 202.15000
39 -58.5400 213.65000
40 -182.0500 -58.54000
41 -228.6300 -182.05000
42 -45.4100 -228.63000
43 -101.9700 -45.41000
44 -398.6600 -101.97000
45 -870.4300 -398.66000
46 326.9056 -870.43000
47 -940.6900 326.90556
48 -1705.2100 -940.69000
49 -1888.5800 -1705.21000
50 -857.2944 -1888.58000
51 -814.7144 -857.29444
52 -909.1344 -814.71444
53 -1050.0544 -909.13444
54 -855.6844 -1050.05444
55 -668.1044 -855.68444
56 -690.5244 -668.10444
57 -649.2944 -690.52444
58 -426.7144 -649.29444
59 -276.8544 -426.71444
> 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/7l38z1258815972.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> acf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/8ijy51258815972.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> pacf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Partial Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/9i19k1258815972.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> opar <- par(mfrow = c(2,2), oma = c(0, 0, 1.1, 0))
> plot(mylm, las = 1, sub='Residual Diagnostics')
> par(opar)
> dev.off()
null device
1
> if (n > n25) {
+ postscript(file="/var/www/html/rcomp/tmp/10k1261258815972.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
+ plot(kp3:nmkm3,gqarr[,2], main='Goldfeld-Quandt test',ylab='2-sided p-value',xlab='breakpoint')
+ grid()
+ dev.off()
+ }
null device
1
>
> #Note: the /var/www/html/rcomp/createtable file can be downloaded at http://www.wessa.net/cretab
> load(file="/var/www/html/rcomp/createtable")
>
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a, 'Multiple Linear Regression - Estimated Regression Equation', 1, TRUE)
> a<-table.row.end(a)
> myeq <- colnames(x)[1]
> myeq <- paste(myeq, '[t] = ', sep='')
> for (i in 1:k){
+ if (mysum$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/11ne1b1258815972.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/1252vh1258815972.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/13bc2k1258815972.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/14bfq91258815972.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/152mqr1258815972.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/16mwk21258815972.tab")
+ }
>
> system("convert tmp/1wyu91258815972.ps tmp/1wyu91258815972.png")
> system("convert tmp/2jc5w1258815972.ps tmp/2jc5w1258815972.png")
> system("convert tmp/35s2c1258815972.ps tmp/35s2c1258815972.png")
> system("convert tmp/4wsee1258815972.ps tmp/4wsee1258815972.png")
> system("convert tmp/59ow11258815972.ps tmp/59ow11258815972.png")
> system("convert tmp/6npwq1258815972.ps tmp/6npwq1258815972.png")
> system("convert tmp/7l38z1258815972.ps tmp/7l38z1258815972.png")
> system("convert tmp/8ijy51258815972.ps tmp/8ijy51258815972.png")
> system("convert tmp/9i19k1258815972.ps tmp/9i19k1258815972.png")
> system("convert tmp/10k1261258815972.ps tmp/10k1261258815972.png")
>
>
> proc.time()
user system elapsed
2.436 1.546 3.069