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(22,0,22,0,20,0,21,0,20,0,21,0,21,0,21,0,19,0,21,0,21,0,22,0,19,0,24,0,22,0,22,0,22,0,24,0,22,0,23,0,24,0,21,0,20,0,22,0,23,0,23,0,22,0,20,0,21,1,21,1,20,1,20,1,17,1,18,1,19,1,19,1,20,1,21,1,20,1,21,1,19,1,22,1,20,1,18,1,16,1,17,1,18,1,19,1,18,1,20,1,21,1,18,1,19,1,19,1,19,1,21,1,19,1,19,1,17,1,16,1,16,1,17,1,16,1,15,1,16,1,16,1,16,1,18,1,19,1,16,1,16,1,16,1),dim=c(2,72),dimnames=list(c('Y','X'),1:72))
> y <- array(NA,dim=c(2,72),dimnames=list(c('Y','X'),1:72))
> 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)
> 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 M1 M2 M3 M4 M5 M6 M7 M8 M9 M10 M11 t
1 22 0 1 0 0 0 0 0 0 0 0 0 0 1
2 22 0 0 1 0 0 0 0 0 0 0 0 0 2
3 20 0 0 0 1 0 0 0 0 0 0 0 0 3
4 21 0 0 0 0 1 0 0 0 0 0 0 0 4
5 20 0 0 0 0 0 1 0 0 0 0 0 0 5
6 21 0 0 0 0 0 0 1 0 0 0 0 0 6
7 21 0 0 0 0 0 0 0 1 0 0 0 0 7
8 21 0 0 0 0 0 0 0 0 1 0 0 0 8
9 19 0 0 0 0 0 0 0 0 0 1 0 0 9
10 21 0 0 0 0 0 0 0 0 0 0 1 0 10
11 21 0 0 0 0 0 0 0 0 0 0 0 1 11
12 22 0 0 0 0 0 0 0 0 0 0 0 0 12
13 19 0 1 0 0 0 0 0 0 0 0 0 0 13
14 24 0 0 1 0 0 0 0 0 0 0 0 0 14
15 22 0 0 0 1 0 0 0 0 0 0 0 0 15
16 22 0 0 0 0 1 0 0 0 0 0 0 0 16
17 22 0 0 0 0 0 1 0 0 0 0 0 0 17
18 24 0 0 0 0 0 0 1 0 0 0 0 0 18
19 22 0 0 0 0 0 0 0 1 0 0 0 0 19
20 23 0 0 0 0 0 0 0 0 1 0 0 0 20
21 24 0 0 0 0 0 0 0 0 0 1 0 0 21
22 21 0 0 0 0 0 0 0 0 0 0 1 0 22
23 20 0 0 0 0 0 0 0 0 0 0 0 1 23
24 22 0 0 0 0 0 0 0 0 0 0 0 0 24
25 23 0 1 0 0 0 0 0 0 0 0 0 0 25
26 23 0 0 1 0 0 0 0 0 0 0 0 0 26
27 22 0 0 0 1 0 0 0 0 0 0 0 0 27
28 20 0 0 0 0 1 0 0 0 0 0 0 0 28
29 21 1 0 0 0 0 1 0 0 0 0 0 0 29
30 21 1 0 0 0 0 0 1 0 0 0 0 0 30
31 20 1 0 0 0 0 0 0 1 0 0 0 0 31
32 20 1 0 0 0 0 0 0 0 1 0 0 0 32
33 17 1 0 0 0 0 0 0 0 0 1 0 0 33
34 18 1 0 0 0 0 0 0 0 0 0 1 0 34
35 19 1 0 0 0 0 0 0 0 0 0 0 1 35
36 19 1 0 0 0 0 0 0 0 0 0 0 0 36
37 20 1 1 0 0 0 0 0 0 0 0 0 0 37
38 21 1 0 1 0 0 0 0 0 0 0 0 0 38
39 20 1 0 0 1 0 0 0 0 0 0 0 0 39
40 21 1 0 0 0 1 0 0 0 0 0 0 0 40
41 19 1 0 0 0 0 1 0 0 0 0 0 0 41
42 22 1 0 0 0 0 0 1 0 0 0 0 0 42
43 20 1 0 0 0 0 0 0 1 0 0 0 0 43
44 18 1 0 0 0 0 0 0 0 1 0 0 0 44
45 16 1 0 0 0 0 0 0 0 0 1 0 0 45
46 17 1 0 0 0 0 0 0 0 0 0 1 0 46
47 18 1 0 0 0 0 0 0 0 0 0 0 1 47
48 19 1 0 0 0 0 0 0 0 0 0 0 0 48
49 18 1 1 0 0 0 0 0 0 0 0 0 0 49
50 20 1 0 1 0 0 0 0 0 0 0 0 0 50
51 21 1 0 0 1 0 0 0 0 0 0 0 0 51
52 18 1 0 0 0 1 0 0 0 0 0 0 0 52
53 19 1 0 0 0 0 1 0 0 0 0 0 0 53
54 19 1 0 0 0 0 0 1 0 0 0 0 0 54
55 19 1 0 0 0 0 0 0 1 0 0 0 0 55
56 21 1 0 0 0 0 0 0 0 1 0 0 0 56
57 19 1 0 0 0 0 0 0 0 0 1 0 0 57
58 19 1 0 0 0 0 0 0 0 0 0 1 0 58
59 17 1 0 0 0 0 0 0 0 0 0 0 1 59
60 16 1 0 0 0 0 0 0 0 0 0 0 0 60
61 16 1 1 0 0 0 0 0 0 0 0 0 0 61
62 17 1 0 1 0 0 0 0 0 0 0 0 0 62
63 16 1 0 0 1 0 0 0 0 0 0 0 0 63
64 15 1 0 0 0 1 0 0 0 0 0 0 0 64
65 16 1 0 0 0 0 1 0 0 0 0 0 0 65
66 16 1 0 0 0 0 0 1 0 0 0 0 0 66
67 16 1 0 0 0 0 0 0 1 0 0 0 0 67
68 18 1 0 0 0 0 0 0 0 1 0 0 0 68
69 19 1 0 0 0 0 0 0 0 0 1 0 0 69
70 16 1 0 0 0 0 0 0 0 0 0 1 0 70
71 16 1 0 0 0 0 0 0 0 0 0 0 1 71
72 16 1 0 0 0 0 0 0 0 0 0 0 0 72
> k <- length(x[1,])
> df <- as.data.frame(x)
> (mylm <- lm(df))
Call:
lm(formula = df)
Coefficients:
(Intercept) X M1 M2 M3 M4
22.15000 -1.05000 -0.15000 1.40833 0.46667 -0.14167
M5 M6 M7 M8 M9 M10
0.09167 1.15000 0.37500 0.93333 -0.17500 -0.45000
M11 t
-0.55833 -0.05833
> (mysum <- summary(mylm))
Call:
lm(formula = df)
Residuals:
Min 1Q Median 3Q Max
-2.45000 -1.18542 0.06667 0.93333 3.25000
Coefficients:
Estimate Std. Error t value Pr(>|t|)
(Intercept) 22.15000 0.74571 29.703 < 2e-16 ***
X -1.05000 0.71127 -1.476 0.14529
M1 -0.15000 0.90222 -0.166 0.86853
M2 1.40833 0.90083 1.563 0.12340
M3 0.46667 0.89975 0.519 0.60597
M4 -0.14167 0.89897 -0.158 0.87533
M5 0.09167 0.90370 0.101 0.91956
M6 1.15000 0.90170 1.275 0.20726
M7 0.37500 0.89999 0.417 0.67846
M8 0.93333 0.89860 1.039 0.30328
M9 -0.17500 0.89751 -0.195 0.84609
M10 -0.45000 0.89673 -0.502 0.61769
M11 -0.55833 0.89627 -0.623 0.53576
t -0.05833 0.01670 -3.493 0.00092 ***
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
Residual standard error: 1.552 on 58 degrees of freedom
Multiple R-squared: 0.6273, Adjusted R-squared: 0.5437
F-statistic: 7.509 on 13 and 58 DF, p-value: 2.188e-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,] 0.78796227 0.42407547 0.2120377
[2,] 0.74719252 0.50561496 0.2528075
[3,] 0.62185282 0.75629437 0.3781472
[4,] 0.50565577 0.98868847 0.4943442
[5,] 0.69208512 0.61582976 0.3079149
[6,] 0.63096996 0.73806008 0.3690300
[7,] 0.63898090 0.72203820 0.3610191
[8,] 0.56327581 0.87344839 0.4367242
[9,] 0.49778147 0.99556294 0.5022185
[10,] 0.47236785 0.94473569 0.5276322
[11,] 0.38694961 0.77389921 0.6130504
[12,] 0.44808537 0.89617075 0.5519146
[13,] 0.36472798 0.72945596 0.6352720
[14,] 0.30011435 0.60022869 0.6998857
[15,] 0.23247525 0.46495050 0.7675248
[16,] 0.18643501 0.37287002 0.8135650
[17,] 0.32052360 0.64104720 0.6794764
[18,] 0.29372371 0.58744743 0.7062763
[19,] 0.23105203 0.46210407 0.7689480
[20,] 0.18382270 0.36764540 0.8161773
[21,] 0.13777577 0.27555154 0.8622242
[22,] 0.09696070 0.19392141 0.9030393
[23,] 0.06648899 0.13297799 0.9335110
[24,] 0.07611474 0.15222947 0.9238853
[25,] 0.05940448 0.11880897 0.9405955
[26,] 0.06182113 0.12364226 0.9381789
[27,] 0.04192001 0.08384001 0.9580800
[28,] 0.09284948 0.18569895 0.9071505
[29,] 0.54513722 0.90972556 0.4548628
[30,] 0.80201954 0.39596092 0.1979805
[31,] 0.82450909 0.35098182 0.1754909
[32,] 0.76185777 0.47628446 0.2381422
[33,] 0.69688021 0.60623958 0.3031198
[34,] 0.60943129 0.78113742 0.3905687
[35,] 0.74660413 0.50679175 0.2533959
[36,] 0.67987860 0.64024280 0.3201214
[37,] 0.59434075 0.81131850 0.4056593
[38,] 0.53137802 0.93724396 0.4686220
[39,] 0.45715732 0.91431463 0.5428427
> postscript(file="/var/www/html/rcomp/tmp/1zjsn1258726607.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$resid)
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/213t31258726607.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> plot(mysum$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/3jzt01258726607.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> hist(mysum$resid, main='Residual Histogram', xlab='values of Residuals')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/43jry1258726607.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> densityplot(~mysum$resid,col='black',main='Residual Density Plot', xlab='values of Residuals')
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/5tggo1258726607.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 = 72
Frequency = 1
1 2 3 4 5
5.833333e-02 -1.441667e+00 -2.441667e+00 -7.750000e-01 -1.950000e+00
6 7 8 9 10
-1.950000e+00 -1.116667e+00 -1.616667e+00 -2.450000e+00 -1.166667e-01
11 12 13 14 15
5.000000e-02 5.500000e-01 -2.241667e+00 1.258333e+00 2.583333e-01
16 17 18 19 20
9.250000e-01 7.500000e-01 1.750000e+00 5.833333e-01 1.083333e+00
21 22 23 24 25
3.250000e+00 5.833333e-01 -2.500000e-01 1.250000e+00 2.458333e+00
26 27 28 29 30
9.583333e-01 9.583333e-01 -3.750000e-01 1.500000e+00 5.000000e-01
31 32 33 34 35
3.333333e-01 -1.666667e-01 -2.000000e+00 -6.666667e-01 5.000000e-01
36 37 38 39 40
-2.556115e-15 1.208333e+00 7.083333e-01 7.083333e-01 2.375000e+00
41 42 43 44 45
2.000000e-01 2.200000e+00 1.033333e+00 -1.466667e+00 -2.300000e+00
46 47 48 49 50
-9.666667e-01 2.000000e-01 7.000000e-01 -9.166667e-02 4.083333e-01
51 52 53 54 55
2.408333e+00 7.500000e-02 9.000000e-01 -1.000000e-01 7.333333e-01
56 57 58 59 60
2.233333e+00 1.400000e+00 1.733333e+00 -1.000000e-01 -1.600000e+00
61 62 63 64 65
-1.391667e+00 -1.891667e+00 -1.891667e+00 -2.225000e+00 -1.400000e+00
66 67 68 69 70
-2.400000e+00 -1.566667e+00 -6.666667e-02 2.100000e+00 -5.666667e-01
71 72
-4.000000e-01 -9.000000e-01
> postscript(file="/var/www/html/rcomp/tmp/6obl51258726607.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 = 72
Frequency = 1
lag(myerror, k = 1) myerror
0 5.833333e-02 NA
1 -1.441667e+00 5.833333e-02
2 -2.441667e+00 -1.441667e+00
3 -7.750000e-01 -2.441667e+00
4 -1.950000e+00 -7.750000e-01
5 -1.950000e+00 -1.950000e+00
6 -1.116667e+00 -1.950000e+00
7 -1.616667e+00 -1.116667e+00
8 -2.450000e+00 -1.616667e+00
9 -1.166667e-01 -2.450000e+00
10 5.000000e-02 -1.166667e-01
11 5.500000e-01 5.000000e-02
12 -2.241667e+00 5.500000e-01
13 1.258333e+00 -2.241667e+00
14 2.583333e-01 1.258333e+00
15 9.250000e-01 2.583333e-01
16 7.500000e-01 9.250000e-01
17 1.750000e+00 7.500000e-01
18 5.833333e-01 1.750000e+00
19 1.083333e+00 5.833333e-01
20 3.250000e+00 1.083333e+00
21 5.833333e-01 3.250000e+00
22 -2.500000e-01 5.833333e-01
23 1.250000e+00 -2.500000e-01
24 2.458333e+00 1.250000e+00
25 9.583333e-01 2.458333e+00
26 9.583333e-01 9.583333e-01
27 -3.750000e-01 9.583333e-01
28 1.500000e+00 -3.750000e-01
29 5.000000e-01 1.500000e+00
30 3.333333e-01 5.000000e-01
31 -1.666667e-01 3.333333e-01
32 -2.000000e+00 -1.666667e-01
33 -6.666667e-01 -2.000000e+00
34 5.000000e-01 -6.666667e-01
35 -2.556115e-15 5.000000e-01
36 1.208333e+00 -2.556115e-15
37 7.083333e-01 1.208333e+00
38 7.083333e-01 7.083333e-01
39 2.375000e+00 7.083333e-01
40 2.000000e-01 2.375000e+00
41 2.200000e+00 2.000000e-01
42 1.033333e+00 2.200000e+00
43 -1.466667e+00 1.033333e+00
44 -2.300000e+00 -1.466667e+00
45 -9.666667e-01 -2.300000e+00
46 2.000000e-01 -9.666667e-01
47 7.000000e-01 2.000000e-01
48 -9.166667e-02 7.000000e-01
49 4.083333e-01 -9.166667e-02
50 2.408333e+00 4.083333e-01
51 7.500000e-02 2.408333e+00
52 9.000000e-01 7.500000e-02
53 -1.000000e-01 9.000000e-01
54 7.333333e-01 -1.000000e-01
55 2.233333e+00 7.333333e-01
56 1.400000e+00 2.233333e+00
57 1.733333e+00 1.400000e+00
58 -1.000000e-01 1.733333e+00
59 -1.600000e+00 -1.000000e-01
60 -1.391667e+00 -1.600000e+00
61 -1.891667e+00 -1.391667e+00
62 -1.891667e+00 -1.891667e+00
63 -2.225000e+00 -1.891667e+00
64 -1.400000e+00 -2.225000e+00
65 -2.400000e+00 -1.400000e+00
66 -1.566667e+00 -2.400000e+00
67 -6.666667e-02 -1.566667e+00
68 2.100000e+00 -6.666667e-02
69 -5.666667e-01 2.100000e+00
70 -4.000000e-01 -5.666667e-01
71 -9.000000e-01 -4.000000e-01
72 NA -9.000000e-01
> dum1 <- dum[2:length(myerror),]
> dum1
lag(myerror, k = 1) myerror
[1,] -1.441667e+00 5.833333e-02
[2,] -2.441667e+00 -1.441667e+00
[3,] -7.750000e-01 -2.441667e+00
[4,] -1.950000e+00 -7.750000e-01
[5,] -1.950000e+00 -1.950000e+00
[6,] -1.116667e+00 -1.950000e+00
[7,] -1.616667e+00 -1.116667e+00
[8,] -2.450000e+00 -1.616667e+00
[9,] -1.166667e-01 -2.450000e+00
[10,] 5.000000e-02 -1.166667e-01
[11,] 5.500000e-01 5.000000e-02
[12,] -2.241667e+00 5.500000e-01
[13,] 1.258333e+00 -2.241667e+00
[14,] 2.583333e-01 1.258333e+00
[15,] 9.250000e-01 2.583333e-01
[16,] 7.500000e-01 9.250000e-01
[17,] 1.750000e+00 7.500000e-01
[18,] 5.833333e-01 1.750000e+00
[19,] 1.083333e+00 5.833333e-01
[20,] 3.250000e+00 1.083333e+00
[21,] 5.833333e-01 3.250000e+00
[22,] -2.500000e-01 5.833333e-01
[23,] 1.250000e+00 -2.500000e-01
[24,] 2.458333e+00 1.250000e+00
[25,] 9.583333e-01 2.458333e+00
[26,] 9.583333e-01 9.583333e-01
[27,] -3.750000e-01 9.583333e-01
[28,] 1.500000e+00 -3.750000e-01
[29,] 5.000000e-01 1.500000e+00
[30,] 3.333333e-01 5.000000e-01
[31,] -1.666667e-01 3.333333e-01
[32,] -2.000000e+00 -1.666667e-01
[33,] -6.666667e-01 -2.000000e+00
[34,] 5.000000e-01 -6.666667e-01
[35,] -2.556115e-15 5.000000e-01
[36,] 1.208333e+00 -2.556115e-15
[37,] 7.083333e-01 1.208333e+00
[38,] 7.083333e-01 7.083333e-01
[39,] 2.375000e+00 7.083333e-01
[40,] 2.000000e-01 2.375000e+00
[41,] 2.200000e+00 2.000000e-01
[42,] 1.033333e+00 2.200000e+00
[43,] -1.466667e+00 1.033333e+00
[44,] -2.300000e+00 -1.466667e+00
[45,] -9.666667e-01 -2.300000e+00
[46,] 2.000000e-01 -9.666667e-01
[47,] 7.000000e-01 2.000000e-01
[48,] -9.166667e-02 7.000000e-01
[49,] 4.083333e-01 -9.166667e-02
[50,] 2.408333e+00 4.083333e-01
[51,] 7.500000e-02 2.408333e+00
[52,] 9.000000e-01 7.500000e-02
[53,] -1.000000e-01 9.000000e-01
[54,] 7.333333e-01 -1.000000e-01
[55,] 2.233333e+00 7.333333e-01
[56,] 1.400000e+00 2.233333e+00
[57,] 1.733333e+00 1.400000e+00
[58,] -1.000000e-01 1.733333e+00
[59,] -1.600000e+00 -1.000000e-01
[60,] -1.391667e+00 -1.600000e+00
[61,] -1.891667e+00 -1.391667e+00
[62,] -1.891667e+00 -1.891667e+00
[63,] -2.225000e+00 -1.891667e+00
[64,] -1.400000e+00 -2.225000e+00
[65,] -2.400000e+00 -1.400000e+00
[66,] -1.566667e+00 -2.400000e+00
[67,] -6.666667e-02 -1.566667e+00
[68,] 2.100000e+00 -6.666667e-02
[69,] -5.666667e-01 2.100000e+00
[70,] -4.000000e-01 -5.666667e-01
[71,] -9.000000e-01 -4.000000e-01
> z <- as.data.frame(dum1)
> z
lag(myerror, k = 1) myerror
1 -1.441667e+00 5.833333e-02
2 -2.441667e+00 -1.441667e+00
3 -7.750000e-01 -2.441667e+00
4 -1.950000e+00 -7.750000e-01
5 -1.950000e+00 -1.950000e+00
6 -1.116667e+00 -1.950000e+00
7 -1.616667e+00 -1.116667e+00
8 -2.450000e+00 -1.616667e+00
9 -1.166667e-01 -2.450000e+00
10 5.000000e-02 -1.166667e-01
11 5.500000e-01 5.000000e-02
12 -2.241667e+00 5.500000e-01
13 1.258333e+00 -2.241667e+00
14 2.583333e-01 1.258333e+00
15 9.250000e-01 2.583333e-01
16 7.500000e-01 9.250000e-01
17 1.750000e+00 7.500000e-01
18 5.833333e-01 1.750000e+00
19 1.083333e+00 5.833333e-01
20 3.250000e+00 1.083333e+00
21 5.833333e-01 3.250000e+00
22 -2.500000e-01 5.833333e-01
23 1.250000e+00 -2.500000e-01
24 2.458333e+00 1.250000e+00
25 9.583333e-01 2.458333e+00
26 9.583333e-01 9.583333e-01
27 -3.750000e-01 9.583333e-01
28 1.500000e+00 -3.750000e-01
29 5.000000e-01 1.500000e+00
30 3.333333e-01 5.000000e-01
31 -1.666667e-01 3.333333e-01
32 -2.000000e+00 -1.666667e-01
33 -6.666667e-01 -2.000000e+00
34 5.000000e-01 -6.666667e-01
35 -2.556115e-15 5.000000e-01
36 1.208333e+00 -2.556115e-15
37 7.083333e-01 1.208333e+00
38 7.083333e-01 7.083333e-01
39 2.375000e+00 7.083333e-01
40 2.000000e-01 2.375000e+00
41 2.200000e+00 2.000000e-01
42 1.033333e+00 2.200000e+00
43 -1.466667e+00 1.033333e+00
44 -2.300000e+00 -1.466667e+00
45 -9.666667e-01 -2.300000e+00
46 2.000000e-01 -9.666667e-01
47 7.000000e-01 2.000000e-01
48 -9.166667e-02 7.000000e-01
49 4.083333e-01 -9.166667e-02
50 2.408333e+00 4.083333e-01
51 7.500000e-02 2.408333e+00
52 9.000000e-01 7.500000e-02
53 -1.000000e-01 9.000000e-01
54 7.333333e-01 -1.000000e-01
55 2.233333e+00 7.333333e-01
56 1.400000e+00 2.233333e+00
57 1.733333e+00 1.400000e+00
58 -1.000000e-01 1.733333e+00
59 -1.600000e+00 -1.000000e-01
60 -1.391667e+00 -1.600000e+00
61 -1.891667e+00 -1.391667e+00
62 -1.891667e+00 -1.891667e+00
63 -2.225000e+00 -1.891667e+00
64 -1.400000e+00 -2.225000e+00
65 -2.400000e+00 -1.400000e+00
66 -1.566667e+00 -2.400000e+00
67 -6.666667e-02 -1.566667e+00
68 2.100000e+00 -6.666667e-02
69 -5.666667e-01 2.100000e+00
70 -4.000000e-01 -5.666667e-01
71 -9.000000e-01 -4.000000e-01
> 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/7sga01258726607.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> acf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/8y7ql1258726607.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> pacf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Partial Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/9baok1258726607.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> opar <- par(mfrow = c(2,2), oma = c(0, 0, 1.1, 0))
> plot(mylm, las = 1, sub='Residual Diagnostics')
> par(opar)
> dev.off()
null device
1
> if (n > n25) {
+ postscript(file="/var/www/html/rcomp/tmp/10oxey1258726607.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
+ plot(kp3:nmkm3,gqarr[,2], main='Goldfeld-Quandt test',ylab='2-sided p-value',xlab='breakpoint')
+ grid()
+ dev.off()
+ }
null device
1
>
> #Note: the /var/www/html/rcomp/createtable file can be downloaded at http://www.wessa.net/cretab
> load(file="/var/www/html/rcomp/createtable")
>
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a, 'Multiple Linear Regression - Estimated Regression Equation', 1, TRUE)
> a<-table.row.end(a)
> myeq <- colnames(x)[1]
> myeq <- paste(myeq, '[t] = ', sep='')
> for (i in 1:k){
+ if (mysum$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/115eot1258726607.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/12m1ux1258726607.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/13xz2a1258726608.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/140obu1258726608.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/151gu61258726608.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/16e5q21258726608.tab")
+ }
> system("convert tmp/1zjsn1258726607.ps tmp/1zjsn1258726607.png")
> system("convert tmp/213t31258726607.ps tmp/213t31258726607.png")
> system("convert tmp/3jzt01258726607.ps tmp/3jzt01258726607.png")
> system("convert tmp/43jry1258726607.ps tmp/43jry1258726607.png")
> system("convert tmp/5tggo1258726607.ps tmp/5tggo1258726607.png")
> system("convert tmp/6obl51258726607.ps tmp/6obl51258726607.png")
> system("convert tmp/7sga01258726607.ps tmp/7sga01258726607.png")
> system("convert tmp/8y7ql1258726607.ps tmp/8y7ql1258726607.png")
> system("convert tmp/9baok1258726607.ps tmp/9baok1258726607.png")
> system("convert tmp/10oxey1258726607.ps tmp/10oxey1258726607.png")
>
>
> proc.time()
user system elapsed
2.502 1.615 3.478