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(2187
+ ,18.8
+ ,1855
+ ,2218
+ ,1852
+ ,18.2
+ ,2187
+ ,1855
+ ,1570
+ ,18
+ ,1852
+ ,2187
+ ,1851
+ ,19
+ ,1570
+ ,1852
+ ,1954
+ ,20.7
+ ,1851
+ ,1570
+ ,1828
+ ,21.2
+ ,1954
+ ,1851
+ ,2251
+ ,20.7
+ ,1828
+ ,1954
+ ,2277
+ ,19.6
+ ,2251
+ ,1828
+ ,2085
+ ,18.6
+ ,2277
+ ,2251
+ ,2282
+ ,18.7
+ ,2085
+ ,2277
+ ,2266
+ ,23.8
+ ,2282
+ ,2085
+ ,1878
+ ,24.9
+ ,2266
+ ,2282
+ ,2267
+ ,24.8
+ ,1878
+ ,2266
+ ,2069
+ ,23.8
+ ,2267
+ ,1878
+ ,1746
+ ,22.3
+ ,2069
+ ,2267
+ ,2299
+ ,21.7
+ ,1746
+ ,2069
+ ,2360
+ ,20.7
+ ,2299
+ ,1746
+ ,2214
+ ,19.7
+ ,2360
+ ,2299
+ ,2825
+ ,18.4
+ ,2214
+ ,2360
+ ,2355
+ ,17.4
+ ,2825
+ ,2214
+ ,2333
+ ,17
+ ,2355
+ ,2825
+ ,3016
+ ,18
+ ,2333
+ ,2355
+ ,2155
+ ,23.8
+ ,3016
+ ,2333
+ ,2172
+ ,25.5
+ ,2155
+ ,3016
+ ,2150
+ ,25.6
+ ,2172
+ ,2155
+ ,2533
+ ,23.7
+ ,2150
+ ,2172
+ ,2058
+ ,22
+ ,2533
+ ,2150
+ ,2160
+ ,21.3
+ ,2058
+ ,2533
+ ,2260
+ ,20.7
+ ,2160
+ ,2058
+ ,2498
+ ,20.4
+ ,2260
+ ,2160
+ ,2695
+ ,20.3
+ ,2498
+ ,2260
+ ,2799
+ ,20.4
+ ,2695
+ ,2498
+ ,2946
+ ,19.8
+ ,2799
+ ,2695
+ ,2930
+ ,19.5
+ ,2946
+ ,2799
+ ,2318
+ ,23.1
+ ,2930
+ ,2946
+ ,2540
+ ,23.5
+ ,2318
+ ,2930
+ ,2570
+ ,23.5
+ ,2540
+ ,2318
+ ,2669
+ ,22.9
+ ,2570
+ ,2540
+ ,2450
+ ,21.9
+ ,2669
+ ,2570
+ ,2842
+ ,21.5
+ ,2450
+ ,2669
+ ,3440
+ ,20.5
+ ,2842
+ ,2450
+ ,2678
+ ,20.2
+ ,3440
+ ,2842
+ ,2981
+ ,19.4
+ ,2678
+ ,3440
+ ,2260
+ ,19.2
+ ,2981
+ ,2678
+ ,2844
+ ,18.8
+ ,2260
+ ,2981
+ ,2546
+ ,18.8
+ ,2844
+ ,2260
+ ,2456
+ ,22.6
+ ,2546
+ ,2844
+ ,2295
+ ,23.3
+ ,2456
+ ,2546
+ ,2379
+ ,23
+ ,2295
+ ,2456
+ ,2479
+ ,21.4
+ ,2379
+ ,2295
+ ,2057
+ ,19.9
+ ,2479
+ ,2379
+ ,2280
+ ,18.8
+ ,2057
+ ,2479
+ ,2351
+ ,18.6
+ ,2280
+ ,2057
+ ,2276
+ ,18.4
+ ,2351
+ ,2280
+ ,2548
+ ,18.6
+ ,2276
+ ,2351
+ ,2311
+ ,19.9
+ ,2548
+ ,2276
+ ,2201
+ ,19.2
+ ,2311
+ ,2548
+ ,2725
+ ,18.4
+ ,2201
+ ,2311)
+ ,dim=c(4
+ ,58)
+ ,dimnames=list(c('Y'
+ ,'X'
+ ,'Y1'
+ ,'Y2')
+ ,1:58))
> y <- array(NA,dim=c(4,58),dimnames=list(c('Y','X','Y1','Y2'),1:58))
> 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 Y1 Y2 M1 M2 M3 M4 M5 M6 M7 M8 M9 M10 M11 t
1 2187 18.8 1855 2218 1 0 0 0 0 0 0 0 0 0 0 1
2 1852 18.2 2187 1855 0 1 0 0 0 0 0 0 0 0 0 2
3 1570 18.0 1852 2187 0 0 1 0 0 0 0 0 0 0 0 3
4 1851 19.0 1570 1852 0 0 0 1 0 0 0 0 0 0 0 4
5 1954 20.7 1851 1570 0 0 0 0 1 0 0 0 0 0 0 5
6 1828 21.2 1954 1851 0 0 0 0 0 1 0 0 0 0 0 6
7 2251 20.7 1828 1954 0 0 0 0 0 0 1 0 0 0 0 7
8 2277 19.6 2251 1828 0 0 0 0 0 0 0 1 0 0 0 8
9 2085 18.6 2277 2251 0 0 0 0 0 0 0 0 1 0 0 9
10 2282 18.7 2085 2277 0 0 0 0 0 0 0 0 0 1 0 10
11 2266 23.8 2282 2085 0 0 0 0 0 0 0 0 0 0 1 11
12 1878 24.9 2266 2282 0 0 0 0 0 0 0 0 0 0 0 12
13 2267 24.8 1878 2266 1 0 0 0 0 0 0 0 0 0 0 13
14 2069 23.8 2267 1878 0 1 0 0 0 0 0 0 0 0 0 14
15 1746 22.3 2069 2267 0 0 1 0 0 0 0 0 0 0 0 15
16 2299 21.7 1746 2069 0 0 0 1 0 0 0 0 0 0 0 16
17 2360 20.7 2299 1746 0 0 0 0 1 0 0 0 0 0 0 17
18 2214 19.7 2360 2299 0 0 0 0 0 1 0 0 0 0 0 18
19 2825 18.4 2214 2360 0 0 0 0 0 0 1 0 0 0 0 19
20 2355 17.4 2825 2214 0 0 0 0 0 0 0 1 0 0 0 20
21 2333 17.0 2355 2825 0 0 0 0 0 0 0 0 1 0 0 21
22 3016 18.0 2333 2355 0 0 0 0 0 0 0 0 0 1 0 22
23 2155 23.8 3016 2333 0 0 0 0 0 0 0 0 0 0 1 23
24 2172 25.5 2155 3016 0 0 0 0 0 0 0 0 0 0 0 24
25 2150 25.6 2172 2155 1 0 0 0 0 0 0 0 0 0 0 25
26 2533 23.7 2150 2172 0 1 0 0 0 0 0 0 0 0 0 26
27 2058 22.0 2533 2150 0 0 1 0 0 0 0 0 0 0 0 27
28 2160 21.3 2058 2533 0 0 0 1 0 0 0 0 0 0 0 28
29 2260 20.7 2160 2058 0 0 0 0 1 0 0 0 0 0 0 29
30 2498 20.4 2260 2160 0 0 0 0 0 1 0 0 0 0 0 30
31 2695 20.3 2498 2260 0 0 0 0 0 0 1 0 0 0 0 31
32 2799 20.4 2695 2498 0 0 0 0 0 0 0 1 0 0 0 32
33 2946 19.8 2799 2695 0 0 0 0 0 0 0 0 1 0 0 33
34 2930 19.5 2946 2799 0 0 0 0 0 0 0 0 0 1 0 34
35 2318 23.1 2930 2946 0 0 0 0 0 0 0 0 0 0 1 35
36 2540 23.5 2318 2930 0 0 0 0 0 0 0 0 0 0 0 36
37 2570 23.5 2540 2318 1 0 0 0 0 0 0 0 0 0 0 37
38 2669 22.9 2570 2540 0 1 0 0 0 0 0 0 0 0 0 38
39 2450 21.9 2669 2570 0 0 1 0 0 0 0 0 0 0 0 39
40 2842 21.5 2450 2669 0 0 0 1 0 0 0 0 0 0 0 40
41 3440 20.5 2842 2450 0 0 0 0 1 0 0 0 0 0 0 41
42 2678 20.2 3440 2842 0 0 0 0 0 1 0 0 0 0 0 42
43 2981 19.4 2678 3440 0 0 0 0 0 0 1 0 0 0 0 43
44 2260 19.2 2981 2678 0 0 0 0 0 0 0 1 0 0 0 44
45 2844 18.8 2260 2981 0 0 0 0 0 0 0 0 1 0 0 45
46 2546 18.8 2844 2260 0 0 0 0 0 0 0 0 0 1 0 46
47 2456 22.6 2546 2844 0 0 0 0 0 0 0 0 0 0 1 47
48 2295 23.3 2456 2546 0 0 0 0 0 0 0 0 0 0 0 48
49 2379 23.0 2295 2456 1 0 0 0 0 0 0 0 0 0 0 49
50 2479 21.4 2379 2295 0 1 0 0 0 0 0 0 0 0 0 50
51 2057 19.9 2479 2379 0 0 1 0 0 0 0 0 0 0 0 51
52 2280 18.8 2057 2479 0 0 0 1 0 0 0 0 0 0 0 52
53 2351 18.6 2280 2057 0 0 0 0 1 0 0 0 0 0 0 53
54 2276 18.4 2351 2280 0 0 0 0 0 1 0 0 0 0 0 54
55 2548 18.6 2276 2351 0 0 0 0 0 0 1 0 0 0 0 55
56 2311 19.9 2548 2276 0 0 0 0 0 0 0 1 0 0 0 56
57 2201 19.2 2311 2548 0 0 0 0 0 0 0 0 1 0 0 57
58 2725 18.4 2201 2311 0 0 0 0 0 0 0 0 0 1 0 58
> k <- length(x[1,])
> df <- as.data.frame(x)
> (mylm <- lm(df))
Call:
lm(formula = df)
Coefficients:
(Intercept) X Y1 Y2 M1 M2
-354.4058 29.7765 0.2907 0.4180 349.1248 399.9198
M3 M4 M5 M6 M7 M8
18.1139 433.0721 677.9641 325.6733 672.4825 384.1044
M9 M10 M11 t
406.5406 707.4416 52.8414 1.9341
> (mysum <- summary(mylm))
Call:
lm(formula = df)
Residuals:
Min 1Q Median 3Q Max
-412.44 -151.23 -28.66 149.70 576.50
Coefficients:
Estimate Std. Error t value Pr(>|t|)
(Intercept) -354.4058 656.4642 -0.540 0.59214
X 29.7765 23.7072 1.256 0.21605
Y1 0.2907 0.1409 2.063 0.04532 *
Y2 0.4180 0.1456 2.871 0.00638 **
M1 349.1248 165.3783 2.111 0.04076 *
M2 399.9198 184.3405 2.169 0.03576 *
M3 18.1139 187.0112 0.097 0.92330
M4 433.0721 185.2055 2.338 0.02421 *
M5 677.9641 213.7765 3.171 0.00283 **
M6 325.6733 205.2202 1.587 0.12003
M7 672.4825 197.4077 3.407 0.00146 **
M8 384.1044 224.1885 1.713 0.09403 .
M9 406.5406 207.3129 1.961 0.05653 .
M10 707.4416 218.7015 3.235 0.00238 **
M11 52.8414 180.6311 0.293 0.77132
t 1.9341 2.3274 0.831 0.41069
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
Residual standard error: 231.9 on 42 degrees of freedom
Multiple R-squared: 0.6798, Adjusted R-squared: 0.5654
F-statistic: 5.943 on 15 and 42 DF, p-value: 2.326e-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,] 0.028805423 0.05761085 0.9711946
[2,] 0.025939630 0.05187926 0.9740604
[3,] 0.049423175 0.09884635 0.9505768
[4,] 0.024667629 0.04933526 0.9753324
[5,] 0.012669780 0.02533956 0.9873302
[6,] 0.007539268 0.01507854 0.9924607
[7,] 0.176084656 0.35216931 0.8239153
[8,] 0.108074654 0.21614931 0.8919253
[9,] 0.067079689 0.13415938 0.9329203
[10,] 0.087255195 0.17451039 0.9127448
[11,] 0.429210506 0.85842101 0.5707895
[12,] 0.368034567 0.73606913 0.6319654
[13,] 0.349266745 0.69853349 0.6507333
[14,] 0.271655285 0.54331057 0.7283447
[15,] 0.380826457 0.76165291 0.6191735
[16,] 0.285140418 0.57028084 0.7148596
[17,] 0.276620582 0.55324116 0.7233794
[18,] 0.192462745 0.38492549 0.8075373
[19,] 0.123598086 0.24719617 0.8764019
[20,] 0.103621128 0.20724226 0.8963789
[21,] 0.091509061 0.18301812 0.9084909
> postscript(file="/var/www/html/rcomp/tmp/1as2j1258742931.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$resid)
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/20z4k1258742931.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> plot(mysum$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/3gbzh1258742931.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> hist(mysum$resid, main='Residual Histogram', xlab='values of Residuals')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/4syx01258742931.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> densityplot(~mysum$resid,col='black',main='Residual Density Plot', xlab='values of Residuals')
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/5xq3j1258742931.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 = 58
Frequency = 1
1 2 3 4 5 6 7
164.23036 -150.43807 -87.97699 -31.64646 -189.92467 -127.84572 -45.11804
8 9 10 11 12 13 14
229.76404 -141.18233 -205.04196 302.73743 -144.79431 15.61432 -156.26623
15 16 17 18 19 20 21
-159.74876 170.88459 -10.93915 -25.66783 292.24960 21.85615 -131.32986
22 23 24 25 26 27 28
421.89206 -148.51788 -166.37480 -187.49697 198.64008 51.97800 -264.05043
29 30 31 32 33 34 35
-224.13761 301.44813 41.69399 272.41433 300.33772 -95.76847 -219.08495
36 37 38 39 40 41 42
226.52469 96.71082 59.34039 208.66810 217.97866 576.49515 -163.90788
43 44 45 46 47 48 49
-214.23031 -412.44219 242.07382 -227.20315 64.86541 84.64442 -89.05853
50 51 52 53 54 55 56
48.72383 -12.92036 -93.16637 -151.49372 15.97330 -74.59524 -111.59232
57 58
-269.89934 106.12153
> postscript(file="/var/www/html/rcomp/tmp/6kui41258742931.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 = 58
Frequency = 1
lag(myerror, k = 1) myerror
0 164.23036 NA
1 -150.43807 164.23036
2 -87.97699 -150.43807
3 -31.64646 -87.97699
4 -189.92467 -31.64646
5 -127.84572 -189.92467
6 -45.11804 -127.84572
7 229.76404 -45.11804
8 -141.18233 229.76404
9 -205.04196 -141.18233
10 302.73743 -205.04196
11 -144.79431 302.73743
12 15.61432 -144.79431
13 -156.26623 15.61432
14 -159.74876 -156.26623
15 170.88459 -159.74876
16 -10.93915 170.88459
17 -25.66783 -10.93915
18 292.24960 -25.66783
19 21.85615 292.24960
20 -131.32986 21.85615
21 421.89206 -131.32986
22 -148.51788 421.89206
23 -166.37480 -148.51788
24 -187.49697 -166.37480
25 198.64008 -187.49697
26 51.97800 198.64008
27 -264.05043 51.97800
28 -224.13761 -264.05043
29 301.44813 -224.13761
30 41.69399 301.44813
31 272.41433 41.69399
32 300.33772 272.41433
33 -95.76847 300.33772
34 -219.08495 -95.76847
35 226.52469 -219.08495
36 96.71082 226.52469
37 59.34039 96.71082
38 208.66810 59.34039
39 217.97866 208.66810
40 576.49515 217.97866
41 -163.90788 576.49515
42 -214.23031 -163.90788
43 -412.44219 -214.23031
44 242.07382 -412.44219
45 -227.20315 242.07382
46 64.86541 -227.20315
47 84.64442 64.86541
48 -89.05853 84.64442
49 48.72383 -89.05853
50 -12.92036 48.72383
51 -93.16637 -12.92036
52 -151.49372 -93.16637
53 15.97330 -151.49372
54 -74.59524 15.97330
55 -111.59232 -74.59524
56 -269.89934 -111.59232
57 106.12153 -269.89934
58 NA 106.12153
> dum1 <- dum[2:length(myerror),]
> dum1
lag(myerror, k = 1) myerror
[1,] -150.43807 164.23036
[2,] -87.97699 -150.43807
[3,] -31.64646 -87.97699
[4,] -189.92467 -31.64646
[5,] -127.84572 -189.92467
[6,] -45.11804 -127.84572
[7,] 229.76404 -45.11804
[8,] -141.18233 229.76404
[9,] -205.04196 -141.18233
[10,] 302.73743 -205.04196
[11,] -144.79431 302.73743
[12,] 15.61432 -144.79431
[13,] -156.26623 15.61432
[14,] -159.74876 -156.26623
[15,] 170.88459 -159.74876
[16,] -10.93915 170.88459
[17,] -25.66783 -10.93915
[18,] 292.24960 -25.66783
[19,] 21.85615 292.24960
[20,] -131.32986 21.85615
[21,] 421.89206 -131.32986
[22,] -148.51788 421.89206
[23,] -166.37480 -148.51788
[24,] -187.49697 -166.37480
[25,] 198.64008 -187.49697
[26,] 51.97800 198.64008
[27,] -264.05043 51.97800
[28,] -224.13761 -264.05043
[29,] 301.44813 -224.13761
[30,] 41.69399 301.44813
[31,] 272.41433 41.69399
[32,] 300.33772 272.41433
[33,] -95.76847 300.33772
[34,] -219.08495 -95.76847
[35,] 226.52469 -219.08495
[36,] 96.71082 226.52469
[37,] 59.34039 96.71082
[38,] 208.66810 59.34039
[39,] 217.97866 208.66810
[40,] 576.49515 217.97866
[41,] -163.90788 576.49515
[42,] -214.23031 -163.90788
[43,] -412.44219 -214.23031
[44,] 242.07382 -412.44219
[45,] -227.20315 242.07382
[46,] 64.86541 -227.20315
[47,] 84.64442 64.86541
[48,] -89.05853 84.64442
[49,] 48.72383 -89.05853
[50,] -12.92036 48.72383
[51,] -93.16637 -12.92036
[52,] -151.49372 -93.16637
[53,] 15.97330 -151.49372
[54,] -74.59524 15.97330
[55,] -111.59232 -74.59524
[56,] -269.89934 -111.59232
[57,] 106.12153 -269.89934
> z <- as.data.frame(dum1)
> z
lag(myerror, k = 1) myerror
1 -150.43807 164.23036
2 -87.97699 -150.43807
3 -31.64646 -87.97699
4 -189.92467 -31.64646
5 -127.84572 -189.92467
6 -45.11804 -127.84572
7 229.76404 -45.11804
8 -141.18233 229.76404
9 -205.04196 -141.18233
10 302.73743 -205.04196
11 -144.79431 302.73743
12 15.61432 -144.79431
13 -156.26623 15.61432
14 -159.74876 -156.26623
15 170.88459 -159.74876
16 -10.93915 170.88459
17 -25.66783 -10.93915
18 292.24960 -25.66783
19 21.85615 292.24960
20 -131.32986 21.85615
21 421.89206 -131.32986
22 -148.51788 421.89206
23 -166.37480 -148.51788
24 -187.49697 -166.37480
25 198.64008 -187.49697
26 51.97800 198.64008
27 -264.05043 51.97800
28 -224.13761 -264.05043
29 301.44813 -224.13761
30 41.69399 301.44813
31 272.41433 41.69399
32 300.33772 272.41433
33 -95.76847 300.33772
34 -219.08495 -95.76847
35 226.52469 -219.08495
36 96.71082 226.52469
37 59.34039 96.71082
38 208.66810 59.34039
39 217.97866 208.66810
40 576.49515 217.97866
41 -163.90788 576.49515
42 -214.23031 -163.90788
43 -412.44219 -214.23031
44 242.07382 -412.44219
45 -227.20315 242.07382
46 64.86541 -227.20315
47 84.64442 64.86541
48 -89.05853 84.64442
49 48.72383 -89.05853
50 -12.92036 48.72383
51 -93.16637 -12.92036
52 -151.49372 -93.16637
53 15.97330 -151.49372
54 -74.59524 15.97330
55 -111.59232 -74.59524
56 -269.89934 -111.59232
57 106.12153 -269.89934
> 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/7rmq61258742931.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> acf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/8qg951258742931.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> pacf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Partial Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/94fhe1258742931.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> opar <- par(mfrow = c(2,2), oma = c(0, 0, 1.1, 0))
> plot(mylm, las = 1, sub='Residual Diagnostics')
> par(opar)
> dev.off()
null device
1
> if (n > n25) {
+ postscript(file="/var/www/html/rcomp/tmp/10lovj1258742931.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
+ plot(kp3:nmkm3,gqarr[,2], main='Goldfeld-Quandt test',ylab='2-sided p-value',xlab='breakpoint')
+ grid()
+ dev.off()
+ }
null device
1
>
> #Note: the /var/www/html/rcomp/createtable file can be downloaded at http://www.wessa.net/cretab
> load(file="/var/www/html/rcomp/createtable")
>
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a, 'Multiple Linear Regression - Estimated Regression Equation', 1, TRUE)
> a<-table.row.end(a)
> myeq <- colnames(x)[1]
> myeq <- paste(myeq, '[t] = ', sep='')
> for (i in 1:k){
+ if (mysum$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/110zdw1258742931.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/12temq1258742931.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/13gspc1258742931.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/14umq81258742931.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/151aok1258742931.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/16f0zz1258742931.tab")
+ }
> system("convert tmp/1as2j1258742931.ps tmp/1as2j1258742931.png")
> system("convert tmp/20z4k1258742931.ps tmp/20z4k1258742931.png")
> system("convert tmp/3gbzh1258742931.ps tmp/3gbzh1258742931.png")
> system("convert tmp/4syx01258742931.ps tmp/4syx01258742931.png")
> system("convert tmp/5xq3j1258742931.ps tmp/5xq3j1258742931.png")
> system("convert tmp/6kui41258742931.ps tmp/6kui41258742931.png")
> system("convert tmp/7rmq61258742931.ps tmp/7rmq61258742931.png")
> system("convert tmp/8qg951258742931.ps tmp/8qg951258742931.png")
> system("convert tmp/94fhe1258742931.ps tmp/94fhe1258742931.png")
> system("convert tmp/10lovj1258742931.ps tmp/10lovj1258742931.png")
>
>
> proc.time()
user system elapsed
2.450 1.609 3.841