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.
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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
'help.start()' for an HTML browser interface to help.
Type 'q()' to quit R.
> x <- array(list(2172
+ ,2155
+ ,3016
+ ,0
+ ,2150
+ ,2172
+ ,2155
+ ,0
+ ,2533
+ ,2150
+ ,2172
+ ,0
+ ,2058
+ ,2533
+ ,2150
+ ,0
+ ,2160
+ ,2058
+ ,2533
+ ,0
+ ,2260
+ ,2160
+ ,2058
+ ,0
+ ,2498
+ ,2260
+ ,2160
+ ,0
+ ,2695
+ ,2498
+ ,2260
+ ,0
+ ,2799
+ ,2695
+ ,2498
+ ,0
+ ,2946
+ ,2799
+ ,2695
+ ,0
+ ,2930
+ ,2946
+ ,2799
+ ,0
+ ,2318
+ ,2930
+ ,2946
+ ,0
+ ,2540
+ ,2318
+ ,2930
+ ,0
+ ,2570
+ ,2540
+ ,2318
+ ,0
+ ,2669
+ ,2570
+ ,2540
+ ,0
+ ,2450
+ ,2669
+ ,2570
+ ,0
+ ,2842
+ ,2450
+ ,2669
+ ,0
+ ,3440
+ ,2842
+ ,2450
+ ,0
+ ,2678
+ ,3440
+ ,2842
+ ,0
+ ,2981
+ ,2678
+ ,3440
+ ,0
+ ,2260
+ ,2981
+ ,2678
+ ,0
+ ,2844
+ ,2260
+ ,2981
+ ,0
+ ,2546
+ ,2844
+ ,2260
+ ,0
+ ,2456
+ ,2546
+ ,2844
+ ,0
+ ,2295
+ ,2456
+ ,2546
+ ,0
+ ,2379
+ ,2295
+ ,2456
+ ,0
+ ,2479
+ ,2379
+ ,2295
+ ,0
+ ,2057
+ ,2479
+ ,2379
+ ,0
+ ,2280
+ ,2057
+ ,2479
+ ,0
+ ,2351
+ ,2280
+ ,2057
+ ,0
+ ,2276
+ ,2351
+ ,2280
+ ,0
+ ,2548
+ ,2276
+ ,2351
+ ,0
+ ,2311
+ ,2548
+ ,2276
+ ,0
+ ,2201
+ ,2311
+ ,2548
+ ,1
+ ,2725
+ ,2201
+ ,2311
+ ,1
+ ,2408
+ ,2725
+ ,2201
+ ,1
+ ,2139
+ ,2408
+ ,2725
+ ,1
+ ,1898
+ ,2139
+ ,2408
+ ,1
+ ,2537
+ ,1898
+ ,2139
+ ,1
+ ,2068
+ ,2537
+ ,1898
+ ,1
+ ,2063
+ ,2068
+ ,2537
+ ,1
+ ,2520
+ ,2063
+ ,2068
+ ,1
+ ,2434
+ ,2520
+ ,2063
+ ,1
+ ,2190
+ ,2434
+ ,2520
+ ,1
+ ,2794
+ ,2190
+ ,2434
+ ,1
+ ,2070
+ ,2794
+ ,2190
+ ,1
+ ,2615
+ ,2070
+ ,2794
+ ,1
+ ,2265
+ ,2615
+ ,2070
+ ,1
+ ,2139
+ ,2265
+ ,2615
+ ,1
+ ,2428
+ ,2139
+ ,2265
+ ,1
+ ,2137
+ ,2428
+ ,2139
+ ,1
+ ,1823
+ ,2137
+ ,2428
+ ,1
+ ,2063
+ ,1823
+ ,2137
+ ,1
+ ,1806
+ ,2063
+ ,1823
+ ,1
+ ,1758
+ ,1806
+ ,2063
+ ,1
+ ,2243
+ ,1758
+ ,1806
+ ,1
+ ,1993
+ ,2243
+ ,1758
+ ,1
+ ,1932
+ ,1993
+ ,2243
+ ,1
+ ,2465
+ ,1932
+ ,1993
+ ,1)
+ ,dim=c(4
+ ,59)
+ ,dimnames=list(c('y'
+ ,'y(t-1)'
+ ,'y(t-2)'
+ ,'x')
+ ,1:59))
> y <- array(NA,dim=c(4,59),dimnames=list(c('y','y(t-1)','y(t-2)','x'),1:59))
> 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 y(t-1) y(t-2) x M1 M2 M3 M4 M5 M6 M7 M8 M9 M10 M11 t
1 2172 2155 3016 0 1 0 0 0 0 0 0 0 0 0 0 1
2 2150 2172 2155 0 0 1 0 0 0 0 0 0 0 0 0 2
3 2533 2150 2172 0 0 0 1 0 0 0 0 0 0 0 0 3
4 2058 2533 2150 0 0 0 0 1 0 0 0 0 0 0 0 4
5 2160 2058 2533 0 0 0 0 0 1 0 0 0 0 0 0 5
6 2260 2160 2058 0 0 0 0 0 0 1 0 0 0 0 0 6
7 2498 2260 2160 0 0 0 0 0 0 0 1 0 0 0 0 7
8 2695 2498 2260 0 0 0 0 0 0 0 0 1 0 0 0 8
9 2799 2695 2498 0 0 0 0 0 0 0 0 0 1 0 0 9
10 2946 2799 2695 0 0 0 0 0 0 0 0 0 0 1 0 10
11 2930 2946 2799 0 0 0 0 0 0 0 0 0 0 0 1 11
12 2318 2930 2946 0 0 0 0 0 0 0 0 0 0 0 0 12
13 2540 2318 2930 0 1 0 0 0 0 0 0 0 0 0 0 13
14 2570 2540 2318 0 0 1 0 0 0 0 0 0 0 0 0 14
15 2669 2570 2540 0 0 0 1 0 0 0 0 0 0 0 0 15
16 2450 2669 2570 0 0 0 0 1 0 0 0 0 0 0 0 16
17 2842 2450 2669 0 0 0 0 0 1 0 0 0 0 0 0 17
18 3440 2842 2450 0 0 0 0 0 0 1 0 0 0 0 0 18
19 2678 3440 2842 0 0 0 0 0 0 0 1 0 0 0 0 19
20 2981 2678 3440 0 0 0 0 0 0 0 0 1 0 0 0 20
21 2260 2981 2678 0 0 0 0 0 0 0 0 0 1 0 0 21
22 2844 2260 2981 0 0 0 0 0 0 0 0 0 0 1 0 22
23 2546 2844 2260 0 0 0 0 0 0 0 0 0 0 0 1 23
24 2456 2546 2844 0 0 0 0 0 0 0 0 0 0 0 0 24
25 2295 2456 2546 0 1 0 0 0 0 0 0 0 0 0 0 25
26 2379 2295 2456 0 0 1 0 0 0 0 0 0 0 0 0 26
27 2479 2379 2295 0 0 0 1 0 0 0 0 0 0 0 0 27
28 2057 2479 2379 0 0 0 0 1 0 0 0 0 0 0 0 28
29 2280 2057 2479 0 0 0 0 0 1 0 0 0 0 0 0 29
30 2351 2280 2057 0 0 0 0 0 0 1 0 0 0 0 0 30
31 2276 2351 2280 0 0 0 0 0 0 0 1 0 0 0 0 31
32 2548 2276 2351 0 0 0 0 0 0 0 0 1 0 0 0 32
33 2311 2548 2276 0 0 0 0 0 0 0 0 0 1 0 0 33
34 2201 2311 2548 1 0 0 0 0 0 0 0 0 0 1 0 34
35 2725 2201 2311 1 0 0 0 0 0 0 0 0 0 0 1 35
36 2408 2725 2201 1 0 0 0 0 0 0 0 0 0 0 0 36
37 2139 2408 2725 1 1 0 0 0 0 0 0 0 0 0 0 37
38 1898 2139 2408 1 0 1 0 0 0 0 0 0 0 0 0 38
39 2537 1898 2139 1 0 0 1 0 0 0 0 0 0 0 0 39
40 2068 2537 1898 1 0 0 0 1 0 0 0 0 0 0 0 40
41 2063 2068 2537 1 0 0 0 0 1 0 0 0 0 0 0 41
42 2520 2063 2068 1 0 0 0 0 0 1 0 0 0 0 0 42
43 2434 2520 2063 1 0 0 0 0 0 0 1 0 0 0 0 43
44 2190 2434 2520 1 0 0 0 0 0 0 0 1 0 0 0 44
45 2794 2190 2434 1 0 0 0 0 0 0 0 0 1 0 0 45
46 2070 2794 2190 1 0 0 0 0 0 0 0 0 0 1 0 46
47 2615 2070 2794 1 0 0 0 0 0 0 0 0 0 0 1 47
48 2265 2615 2070 1 0 0 0 0 0 0 0 0 0 0 0 48
49 2139 2265 2615 1 1 0 0 0 0 0 0 0 0 0 0 49
50 2428 2139 2265 1 0 1 0 0 0 0 0 0 0 0 0 50
51 2137 2428 2139 1 0 0 1 0 0 0 0 0 0 0 0 51
52 1823 2137 2428 1 0 0 0 1 0 0 0 0 0 0 0 52
53 2063 1823 2137 1 0 0 0 0 1 0 0 0 0 0 0 53
54 1806 2063 1823 1 0 0 0 0 0 1 0 0 0 0 0 54
55 1758 1806 2063 1 0 0 0 0 0 0 1 0 0 0 0 55
56 2243 1758 1806 1 0 0 0 0 0 0 0 1 0 0 0 56
57 1993 2243 1758 1 0 0 0 0 0 0 0 0 1 0 0 57
58 1932 1993 2243 1 0 0 0 0 0 0 0 0 0 1 0 58
59 2465 1932 1993 1 0 0 0 0 0 0 0 0 0 0 1 59
> k <- length(x[1,])
> df <- as.data.frame(x)
> (mylm <- lm(df))
Call:
lm(formula = df)
Coefficients:
(Intercept) `y(t-1)` `y(t-2)` x M1 M2
1134.9678 0.2183 0.3114 -16.8622 -123.9439 61.3838
M3 M4 M5 M6 M7 M8
265.6233 -158.8935 61.1246 336.2265 92.6392 271.5135
M9 M10 M11 t
177.5387 111.4711 411.9815 -4.6115
> (mysum <- summary(mylm))
Call:
lm(formula = df)
Residuals:
Min 1Q Median 3Q Max
-440.378 -166.145 -9.719 161.825 668.441
Coefficients:
Estimate Std. Error t value Pr(>|t|)
(Intercept) 1134.9678 498.0723 2.279 0.0277 *
`y(t-1)` 0.2183 0.1413 1.545 0.1297
`y(t-2)` 0.3114 0.1432 2.174 0.0352 *
x -16.8622 138.6594 -0.122 0.9038
M1 -123.9439 187.1136 -0.662 0.5113
M2 61.3838 183.6629 0.334 0.7398
M3 265.6233 183.0331 1.451 0.1540
M4 -158.8935 176.7008 -0.899 0.3735
M5 61.1246 192.3702 0.318 0.7522
M6 336.2265 186.9913 1.798 0.0792 .
M7 92.6392 176.8106 0.524 0.6030
M8 271.5135 180.1541 1.507 0.1391
M9 177.5387 175.6276 1.011 0.3177
M10 111.4711 175.0873 0.637 0.5277
M11 411.9815 175.1653 2.352 0.0233 *
t -4.6115 4.0345 -1.143 0.2593
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
Residual standard error: 255.1 on 43 degrees of freedom
Multiple R-squared: 0.5531, Adjusted R-squared: 0.3972
F-statistic: 3.548 on 15 and 43 DF, p-value: 0.0005644
> 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,] 0.9131395 0.17372108 0.08686054
[2,] 0.8548410 0.29031803 0.14515902
[3,] 0.9808386 0.03832288 0.01916144
[4,] 0.9780333 0.04393340 0.02196670
[5,] 0.9757813 0.04843736 0.02421868
[6,] 0.9573503 0.08529938 0.04264969
[7,] 0.9286754 0.14264929 0.07132464
[8,] 0.8844126 0.23117479 0.11558739
[9,] 0.8294567 0.34108661 0.17054331
[10,] 0.7632859 0.47342818 0.23671409
[11,] 0.6757831 0.64843375 0.32421687
[12,] 0.6174289 0.76514213 0.38257107
[13,] 0.5076567 0.98468651 0.49234326
[14,] 0.4418888 0.88377756 0.55811122
[15,] 0.3328151 0.66563021 0.66718489
[16,] 0.2414376 0.48287521 0.75856239
[17,] 0.2620872 0.52417438 0.73791281
[18,] 0.1932843 0.38656864 0.80671568
[19,] 0.1379808 0.27596151 0.86201925
[20,] 0.4135169 0.82703372 0.58648314
[21,] 0.3654741 0.73094828 0.63452586
[22,] 0.3504471 0.70089430 0.64955285
> postscript(file="/var/www/html/rcomp/tmp/1lr8e1261272031.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$resid)
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/2o0h01261272031.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> plot(mysum$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/3szi21261272031.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> hist(mysum$resid, main='Residual Histogram', xlab='values of Residuals')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/4qbdh1261272031.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> densityplot(~mysum$resid,col='black',main='Residual Density Plot', xlab='values of Residuals')
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/5kx3v1261272031.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 = 59
Frequency = 1
1 2 3 4 5 6
-244.0294021 -182.3621447 0.5198127 -122.1228277 -251.0787305 -295.9351329
7 8 9 10 11 12
136.6701000 76.3066094 161.7739386 295.4054143 -80.9714956 -318.6574126
13 14 15 16 17 18
170.4993673 161.8758076 -14.4276578 164.7444966 358.3264080 668.4413116
19 20 21 22 23 24
-97.9820554 10.9213131 -440.3782608 277.3714438 -219.5312043 -9.7188731
25 26 27 28 29 30
70.2765859 36.7358461 -31.1004322 -71.9609311 -3.3689463 -120.1464975
31 32 33 34 35 36
-31.8861634 60.1182582 -114.3285453 -169.7367430 156.1770633 175.6154368
37 38 39 40 41 42
-58.7790127 -323.0574439 252.6929062 148.3486194 -168.6296141 165.0072779
43 44 45 46 47 48
228.9851581 -312.8000238 469.8377609 -239.3799400 -20.2776057 152.7608489
49 50 51 52 53 54
62.0324615 306.8079349 -207.6846288 -119.0093572 64.7508830 -417.3669590
55 56 57 58 59
-235.7870393 165.4538431 -76.9048934 -163.6601752 164.6032422
> postscript(file="/var/www/html/rcomp/tmp/665ax1261272031.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 = 59
Frequency = 1
lag(myerror, k = 1) myerror
0 -244.0294021 NA
1 -182.3621447 -244.0294021
2 0.5198127 -182.3621447
3 -122.1228277 0.5198127
4 -251.0787305 -122.1228277
5 -295.9351329 -251.0787305
6 136.6701000 -295.9351329
7 76.3066094 136.6701000
8 161.7739386 76.3066094
9 295.4054143 161.7739386
10 -80.9714956 295.4054143
11 -318.6574126 -80.9714956
12 170.4993673 -318.6574126
13 161.8758076 170.4993673
14 -14.4276578 161.8758076
15 164.7444966 -14.4276578
16 358.3264080 164.7444966
17 668.4413116 358.3264080
18 -97.9820554 668.4413116
19 10.9213131 -97.9820554
20 -440.3782608 10.9213131
21 277.3714438 -440.3782608
22 -219.5312043 277.3714438
23 -9.7188731 -219.5312043
24 70.2765859 -9.7188731
25 36.7358461 70.2765859
26 -31.1004322 36.7358461
27 -71.9609311 -31.1004322
28 -3.3689463 -71.9609311
29 -120.1464975 -3.3689463
30 -31.8861634 -120.1464975
31 60.1182582 -31.8861634
32 -114.3285453 60.1182582
33 -169.7367430 -114.3285453
34 156.1770633 -169.7367430
35 175.6154368 156.1770633
36 -58.7790127 175.6154368
37 -323.0574439 -58.7790127
38 252.6929062 -323.0574439
39 148.3486194 252.6929062
40 -168.6296141 148.3486194
41 165.0072779 -168.6296141
42 228.9851581 165.0072779
43 -312.8000238 228.9851581
44 469.8377609 -312.8000238
45 -239.3799400 469.8377609
46 -20.2776057 -239.3799400
47 152.7608489 -20.2776057
48 62.0324615 152.7608489
49 306.8079349 62.0324615
50 -207.6846288 306.8079349
51 -119.0093572 -207.6846288
52 64.7508830 -119.0093572
53 -417.3669590 64.7508830
54 -235.7870393 -417.3669590
55 165.4538431 -235.7870393
56 -76.9048934 165.4538431
57 -163.6601752 -76.9048934
58 164.6032422 -163.6601752
59 NA 164.6032422
> dum1 <- dum[2:length(myerror),]
> dum1
lag(myerror, k = 1) myerror
[1,] -182.3621447 -244.0294021
[2,] 0.5198127 -182.3621447
[3,] -122.1228277 0.5198127
[4,] -251.0787305 -122.1228277
[5,] -295.9351329 -251.0787305
[6,] 136.6701000 -295.9351329
[7,] 76.3066094 136.6701000
[8,] 161.7739386 76.3066094
[9,] 295.4054143 161.7739386
[10,] -80.9714956 295.4054143
[11,] -318.6574126 -80.9714956
[12,] 170.4993673 -318.6574126
[13,] 161.8758076 170.4993673
[14,] -14.4276578 161.8758076
[15,] 164.7444966 -14.4276578
[16,] 358.3264080 164.7444966
[17,] 668.4413116 358.3264080
[18,] -97.9820554 668.4413116
[19,] 10.9213131 -97.9820554
[20,] -440.3782608 10.9213131
[21,] 277.3714438 -440.3782608
[22,] -219.5312043 277.3714438
[23,] -9.7188731 -219.5312043
[24,] 70.2765859 -9.7188731
[25,] 36.7358461 70.2765859
[26,] -31.1004322 36.7358461
[27,] -71.9609311 -31.1004322
[28,] -3.3689463 -71.9609311
[29,] -120.1464975 -3.3689463
[30,] -31.8861634 -120.1464975
[31,] 60.1182582 -31.8861634
[32,] -114.3285453 60.1182582
[33,] -169.7367430 -114.3285453
[34,] 156.1770633 -169.7367430
[35,] 175.6154368 156.1770633
[36,] -58.7790127 175.6154368
[37,] -323.0574439 -58.7790127
[38,] 252.6929062 -323.0574439
[39,] 148.3486194 252.6929062
[40,] -168.6296141 148.3486194
[41,] 165.0072779 -168.6296141
[42,] 228.9851581 165.0072779
[43,] -312.8000238 228.9851581
[44,] 469.8377609 -312.8000238
[45,] -239.3799400 469.8377609
[46,] -20.2776057 -239.3799400
[47,] 152.7608489 -20.2776057
[48,] 62.0324615 152.7608489
[49,] 306.8079349 62.0324615
[50,] -207.6846288 306.8079349
[51,] -119.0093572 -207.6846288
[52,] 64.7508830 -119.0093572
[53,] -417.3669590 64.7508830
[54,] -235.7870393 -417.3669590
[55,] 165.4538431 -235.7870393
[56,] -76.9048934 165.4538431
[57,] -163.6601752 -76.9048934
[58,] 164.6032422 -163.6601752
> z <- as.data.frame(dum1)
> z
lag(myerror, k = 1) myerror
1 -182.3621447 -244.0294021
2 0.5198127 -182.3621447
3 -122.1228277 0.5198127
4 -251.0787305 -122.1228277
5 -295.9351329 -251.0787305
6 136.6701000 -295.9351329
7 76.3066094 136.6701000
8 161.7739386 76.3066094
9 295.4054143 161.7739386
10 -80.9714956 295.4054143
11 -318.6574126 -80.9714956
12 170.4993673 -318.6574126
13 161.8758076 170.4993673
14 -14.4276578 161.8758076
15 164.7444966 -14.4276578
16 358.3264080 164.7444966
17 668.4413116 358.3264080
18 -97.9820554 668.4413116
19 10.9213131 -97.9820554
20 -440.3782608 10.9213131
21 277.3714438 -440.3782608
22 -219.5312043 277.3714438
23 -9.7188731 -219.5312043
24 70.2765859 -9.7188731
25 36.7358461 70.2765859
26 -31.1004322 36.7358461
27 -71.9609311 -31.1004322
28 -3.3689463 -71.9609311
29 -120.1464975 -3.3689463
30 -31.8861634 -120.1464975
31 60.1182582 -31.8861634
32 -114.3285453 60.1182582
33 -169.7367430 -114.3285453
34 156.1770633 -169.7367430
35 175.6154368 156.1770633
36 -58.7790127 175.6154368
37 -323.0574439 -58.7790127
38 252.6929062 -323.0574439
39 148.3486194 252.6929062
40 -168.6296141 148.3486194
41 165.0072779 -168.6296141
42 228.9851581 165.0072779
43 -312.8000238 228.9851581
44 469.8377609 -312.8000238
45 -239.3799400 469.8377609
46 -20.2776057 -239.3799400
47 152.7608489 -20.2776057
48 62.0324615 152.7608489
49 306.8079349 62.0324615
50 -207.6846288 306.8079349
51 -119.0093572 -207.6846288
52 64.7508830 -119.0093572
53 -417.3669590 64.7508830
54 -235.7870393 -417.3669590
55 165.4538431 -235.7870393
56 -76.9048934 165.4538431
57 -163.6601752 -76.9048934
58 164.6032422 -163.6601752
> 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/70nsq1261272031.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> acf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/8f3ym1261272031.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> pacf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Partial Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/9peaq1261272031.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> opar <- par(mfrow = c(2,2), oma = c(0, 0, 1.1, 0))
> plot(mylm, las = 1, sub='Residual Diagnostics')
> par(opar)
> dev.off()
null device
1
> if (n > n25) {
+ postscript(file="/var/www/html/rcomp/tmp/10s1v71261272031.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
+ plot(kp3:nmkm3,gqarr[,2], main='Goldfeld-Quandt test',ylab='2-sided p-value',xlab='breakpoint')
+ grid()
+ dev.off()
+ }
null device
1
>
> #Note: the /var/www/html/rcomp/createtable file can be downloaded at http://www.wessa.net/cretab
> load(file="/var/www/html/rcomp/createtable")
>
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a, 'Multiple Linear Regression - Estimated Regression Equation', 1, TRUE)
> a<-table.row.end(a)
> myeq <- colnames(x)[1]
> myeq <- paste(myeq, '[t] = ', sep='')
> for (i in 1:k){
+ if (mysum$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/11zwhc1261272031.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/12lev81261272031.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/130u7p1261272031.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/14didv1261272031.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/15jsqv1261272031.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/16xunq1261272032.tab")
+ }
>
> try(system("convert tmp/1lr8e1261272031.ps tmp/1lr8e1261272031.png",intern=TRUE))
character(0)
> try(system("convert tmp/2o0h01261272031.ps tmp/2o0h01261272031.png",intern=TRUE))
character(0)
> try(system("convert tmp/3szi21261272031.ps tmp/3szi21261272031.png",intern=TRUE))
character(0)
> try(system("convert tmp/4qbdh1261272031.ps tmp/4qbdh1261272031.png",intern=TRUE))
character(0)
> try(system("convert tmp/5kx3v1261272031.ps tmp/5kx3v1261272031.png",intern=TRUE))
character(0)
> try(system("convert tmp/665ax1261272031.ps tmp/665ax1261272031.png",intern=TRUE))
character(0)
> try(system("convert tmp/70nsq1261272031.ps tmp/70nsq1261272031.png",intern=TRUE))
character(0)
> try(system("convert tmp/8f3ym1261272031.ps tmp/8f3ym1261272031.png",intern=TRUE))
character(0)
> try(system("convert tmp/9peaq1261272031.ps tmp/9peaq1261272031.png",intern=TRUE))
character(0)
> try(system("convert tmp/10s1v71261272031.ps tmp/10s1v71261272031.png",intern=TRUE))
character(0)
>
>
> proc.time()
user system elapsed
2.400 1.563 4.008