R version 2.9.0 (2009-04-17)
Copyright (C) 2009 The R Foundation for Statistical Computing
ISBN 3-900051-07-0
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Type 'license()' or 'licence()' for distribution details.
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Type 'contributors()' for more information and
'citation()' on how to cite R or R packages in publications.
Type 'demo()' for some demos, 'help()' for on-line help, or
'help.start()' for an HTML browser interface to help.
Type 'q()' to quit R.
> x <- array(list(9283
+ ,4359
+ ,8947
+ ,9627
+ ,8700
+ ,9487
+ ,8829
+ ,5382
+ ,9283
+ ,8947
+ ,9627
+ ,8700
+ ,9947
+ ,4459
+ ,8829
+ ,9283
+ ,8947
+ ,9627
+ ,9628
+ ,6398
+ ,9947
+ ,8829
+ ,9283
+ ,8947
+ ,9318
+ ,4596
+ ,9628
+ ,9947
+ ,8829
+ ,9283
+ ,9605
+ ,3024
+ ,9318
+ ,9628
+ ,9947
+ ,8829
+ ,8640
+ ,1887
+ ,9605
+ ,9318
+ ,9628
+ ,9947
+ ,9214
+ ,2070
+ ,8640
+ ,9605
+ ,9318
+ ,9628
+ ,9567
+ ,1351
+ ,9214
+ ,8640
+ ,9605
+ ,9318
+ ,8547
+ ,2218
+ ,9567
+ ,9214
+ ,8640
+ ,9605
+ ,9185
+ ,2461
+ ,8547
+ ,9567
+ ,9214
+ ,8640
+ ,9470
+ ,3028
+ ,9185
+ ,8547
+ ,9567
+ ,9214
+ ,9123
+ ,4784
+ ,9470
+ ,9185
+ ,8547
+ ,9567
+ ,9278
+ ,4975
+ ,9123
+ ,9470
+ ,9185
+ ,8547
+ ,10170
+ ,4607
+ ,9278
+ ,9123
+ ,9470
+ ,9185
+ ,9434
+ ,6249
+ ,10170
+ ,9278
+ ,9123
+ ,9470
+ ,9655
+ ,4809
+ ,9434
+ ,10170
+ ,9278
+ ,9123
+ ,9429
+ ,3157
+ ,9655
+ ,9434
+ ,10170
+ ,9278
+ ,8739
+ ,1910
+ ,9429
+ ,9655
+ ,9434
+ ,10170
+ ,9552
+ ,2228
+ ,8739
+ ,9429
+ ,9655
+ ,9434
+ ,9784
+ ,1594
+ ,9552
+ ,8739
+ ,9429
+ ,9655
+ ,9089
+ ,2467
+ ,9784
+ ,9552
+ ,8739
+ ,9429
+ ,9763
+ ,2222
+ ,9089
+ ,9784
+ ,9552
+ ,8739
+ ,9330
+ ,3607
+ ,9763
+ ,9089
+ ,9784
+ ,9552
+ ,9144
+ ,4685
+ ,9330
+ ,9763
+ ,9089
+ ,9784
+ ,9895
+ ,4962
+ ,9144
+ ,9330
+ ,9763
+ ,9089
+ ,10404
+ ,5770
+ ,9895
+ ,9144
+ ,9330
+ ,9763
+ ,10195
+ ,5480
+ ,10404
+ ,9895
+ ,9144
+ ,9330
+ ,9987
+ ,5000
+ ,10195
+ ,10404
+ ,9895
+ ,9144
+ ,9789
+ ,3228
+ ,9987
+ ,10195
+ ,10404
+ ,9895
+ ,9437
+ ,1993
+ ,9789
+ ,9987
+ ,10195
+ ,10404
+ ,10096
+ ,2288
+ ,9437
+ ,9789
+ ,9987
+ ,10195
+ ,9776
+ ,1580
+ ,10096
+ ,9437
+ ,9789
+ ,9987
+ ,9106
+ ,2111
+ ,9776
+ ,10096
+ ,9437
+ ,9789
+ ,10258
+ ,2192
+ ,9106
+ ,9776
+ ,10096
+ ,9437
+ ,9766
+ ,3601
+ ,10258
+ ,9106
+ ,9776
+ ,10096
+ ,9826
+ ,4665
+ ,9766
+ ,10258
+ ,9106
+ ,9776
+ ,9957
+ ,4876
+ ,9826
+ ,9766
+ ,10258
+ ,9106
+ ,10036
+ ,5813
+ ,9957
+ ,9826
+ ,9766
+ ,10258
+ ,10508
+ ,5589
+ ,10036
+ ,9957
+ ,9826
+ ,9766
+ ,10146
+ ,5331
+ ,10508
+ ,10036
+ ,9957
+ ,9826
+ ,10166
+ ,3075
+ ,10146
+ ,10508
+ ,10036
+ ,9957
+ ,9365
+ ,2002
+ ,10166
+ ,10146
+ ,10508
+ ,10036
+ ,9968
+ ,2306
+ ,9365
+ ,10166
+ ,10146
+ ,10508
+ ,10123
+ ,1507
+ ,9968
+ ,9365
+ ,10166
+ ,10146
+ ,9144
+ ,1992
+ ,10123
+ ,9968
+ ,9365
+ ,10166
+ ,10447
+ ,2487
+ ,9144
+ ,10123
+ ,9968
+ ,9365
+ ,9699
+ ,3490
+ ,10447
+ ,9144
+ ,10123
+ ,9968
+ ,10451
+ ,4647
+ ,9699
+ ,10447
+ ,9144
+ ,10123
+ ,10192
+ ,5594
+ ,10451
+ ,9699
+ ,10447
+ ,9144
+ ,10404
+ ,5611
+ ,10192
+ ,10451
+ ,9699
+ ,10447
+ ,10597
+ ,5788
+ ,10404
+ ,10192
+ ,10451
+ ,9699
+ ,10633
+ ,6204
+ ,10597
+ ,10404
+ ,10192
+ ,10451
+ ,10727
+ ,3013
+ ,10633
+ ,10597
+ ,10404
+ ,10192
+ ,9784
+ ,1931
+ ,10727
+ ,10633
+ ,10597
+ ,10404
+ ,9667
+ ,2549
+ ,9784
+ ,10727
+ ,10633
+ ,10597
+ ,10297
+ ,1504
+ ,9667
+ ,9784
+ ,10727
+ ,10633
+ ,9426
+ ,2090
+ ,10297
+ ,9667
+ ,9784
+ ,10727
+ ,10274
+ ,2702
+ ,9426
+ ,10297
+ ,9667
+ ,9784
+ ,9598
+ ,2939
+ ,10274
+ ,9426
+ ,10297
+ ,9667
+ ,10400
+ ,4500
+ ,9598
+ ,10274
+ ,9426
+ ,10297
+ ,9985
+ ,6208
+ ,10400
+ ,9598
+ ,10274
+ ,9426
+ ,10761
+ ,6415
+ ,9985
+ ,10400
+ ,9598
+ ,10274
+ ,11081
+ ,5657
+ ,10761
+ ,9985
+ ,10400
+ ,9598
+ ,10297
+ ,5964
+ ,11081
+ ,10761
+ ,9985
+ ,10400
+ ,10751
+ ,3163
+ ,10297
+ ,11081
+ ,10761
+ ,9985
+ ,9760
+ ,1997
+ ,10751
+ ,10297
+ ,11081
+ ,10761
+ ,10133
+ ,2422
+ ,9760
+ ,10751
+ ,10297
+ ,11081
+ ,10806
+ ,1376
+ ,10133
+ ,9760
+ ,10751
+ ,10297
+ ,9734
+ ,2202
+ ,10806
+ ,10133
+ ,9760
+ ,10751
+ ,10083
+ ,2683
+ ,9734
+ ,10806
+ ,10133
+ ,9760
+ ,10691
+ ,3303
+ ,10083
+ ,9734
+ ,10806
+ ,10133
+ ,10446
+ ,5202
+ ,10691
+ ,10083
+ ,9734
+ ,10806
+ ,10517
+ ,5231
+ ,10446
+ ,10691
+ ,10083
+ ,9734
+ ,11353
+ ,4880
+ ,10517
+ ,10446
+ ,10691
+ ,10083
+ ,10436
+ ,7998
+ ,11353
+ ,10517
+ ,10446
+ ,10691
+ ,10721
+ ,4977
+ ,10436
+ ,11353
+ ,10517
+ ,10446
+ ,10701
+ ,3531
+ ,10721
+ ,10436
+ ,11353
+ ,10517
+ ,9793
+ ,2025
+ ,10701
+ ,10721
+ ,10436
+ ,11353
+ ,10142
+ ,2205
+ ,9793
+ ,10701
+ ,10721
+ ,10436)
+ ,dim=c(6
+ ,80)
+ ,dimnames=list(c('Y'
+ ,'X'
+ ,'Y1'
+ ,'Y2'
+ ,'Y3'
+ ,'Y4')
+ ,1:80))
> y <- array(NA,dim=c(6,80),dimnames=list(c('Y','X','Y1','Y2','Y3','Y4'),1:80))
> 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 Y3 Y4 M1 M2 M3 M4 M5 M6 M7 M8 M9 M10 M11 t
1 9283 4359 8947 9627 8700 9487 1 0 0 0 0 0 0 0 0 0 0 1
2 8829 5382 9283 8947 9627 8700 0 1 0 0 0 0 0 0 0 0 0 2
3 9947 4459 8829 9283 8947 9627 0 0 1 0 0 0 0 0 0 0 0 3
4 9628 6398 9947 8829 9283 8947 0 0 0 1 0 0 0 0 0 0 0 4
5 9318 4596 9628 9947 8829 9283 0 0 0 0 1 0 0 0 0 0 0 5
6 9605 3024 9318 9628 9947 8829 0 0 0 0 0 1 0 0 0 0 0 6
7 8640 1887 9605 9318 9628 9947 0 0 0 0 0 0 1 0 0 0 0 7
8 9214 2070 8640 9605 9318 9628 0 0 0 0 0 0 0 1 0 0 0 8
9 9567 1351 9214 8640 9605 9318 0 0 0 0 0 0 0 0 1 0 0 9
10 8547 2218 9567 9214 8640 9605 0 0 0 0 0 0 0 0 0 1 0 10
11 9185 2461 8547 9567 9214 8640 0 0 0 0 0 0 0 0 0 0 1 11
12 9470 3028 9185 8547 9567 9214 0 0 0 0 0 0 0 0 0 0 0 12
13 9123 4784 9470 9185 8547 9567 1 0 0 0 0 0 0 0 0 0 0 13
14 9278 4975 9123 9470 9185 8547 0 1 0 0 0 0 0 0 0 0 0 14
15 10170 4607 9278 9123 9470 9185 0 0 1 0 0 0 0 0 0 0 0 15
16 9434 6249 10170 9278 9123 9470 0 0 0 1 0 0 0 0 0 0 0 16
17 9655 4809 9434 10170 9278 9123 0 0 0 0 1 0 0 0 0 0 0 17
18 9429 3157 9655 9434 10170 9278 0 0 0 0 0 1 0 0 0 0 0 18
19 8739 1910 9429 9655 9434 10170 0 0 0 0 0 0 1 0 0 0 0 19
20 9552 2228 8739 9429 9655 9434 0 0 0 0 0 0 0 1 0 0 0 20
21 9784 1594 9552 8739 9429 9655 0 0 0 0 0 0 0 0 1 0 0 21
22 9089 2467 9784 9552 8739 9429 0 0 0 0 0 0 0 0 0 1 0 22
23 9763 2222 9089 9784 9552 8739 0 0 0 0 0 0 0 0 0 0 1 23
24 9330 3607 9763 9089 9784 9552 0 0 0 0 0 0 0 0 0 0 0 24
25 9144 4685 9330 9763 9089 9784 1 0 0 0 0 0 0 0 0 0 0 25
26 9895 4962 9144 9330 9763 9089 0 1 0 0 0 0 0 0 0 0 0 26
27 10404 5770 9895 9144 9330 9763 0 0 1 0 0 0 0 0 0 0 0 27
28 10195 5480 10404 9895 9144 9330 0 0 0 1 0 0 0 0 0 0 0 28
29 9987 5000 10195 10404 9895 9144 0 0 0 0 1 0 0 0 0 0 0 29
30 9789 3228 9987 10195 10404 9895 0 0 0 0 0 1 0 0 0 0 0 30
31 9437 1993 9789 9987 10195 10404 0 0 0 0 0 0 1 0 0 0 0 31
32 10096 2288 9437 9789 9987 10195 0 0 0 0 0 0 0 1 0 0 0 32
33 9776 1580 10096 9437 9789 9987 0 0 0 0 0 0 0 0 1 0 0 33
34 9106 2111 9776 10096 9437 9789 0 0 0 0 0 0 0 0 0 1 0 34
35 10258 2192 9106 9776 10096 9437 0 0 0 0 0 0 0 0 0 0 1 35
36 9766 3601 10258 9106 9776 10096 0 0 0 0 0 0 0 0 0 0 0 36
37 9826 4665 9766 10258 9106 9776 1 0 0 0 0 0 0 0 0 0 0 37
38 9957 4876 9826 9766 10258 9106 0 1 0 0 0 0 0 0 0 0 0 38
39 10036 5813 9957 9826 9766 10258 0 0 1 0 0 0 0 0 0 0 0 39
40 10508 5589 10036 9957 9826 9766 0 0 0 1 0 0 0 0 0 0 0 40
41 10146 5331 10508 10036 9957 9826 0 0 0 0 1 0 0 0 0 0 0 41
42 10166 3075 10146 10508 10036 9957 0 0 0 0 0 1 0 0 0 0 0 42
43 9365 2002 10166 10146 10508 10036 0 0 0 0 0 0 1 0 0 0 0 43
44 9968 2306 9365 10166 10146 10508 0 0 0 0 0 0 0 1 0 0 0 44
45 10123 1507 9968 9365 10166 10146 0 0 0 0 0 0 0 0 1 0 0 45
46 9144 1992 10123 9968 9365 10166 0 0 0 0 0 0 0 0 0 1 0 46
47 10447 2487 9144 10123 9968 9365 0 0 0 0 0 0 0 0 0 0 1 47
48 9699 3490 10447 9144 10123 9968 0 0 0 0 0 0 0 0 0 0 0 48
49 10451 4647 9699 10447 9144 10123 1 0 0 0 0 0 0 0 0 0 0 49
50 10192 5594 10451 9699 10447 9144 0 1 0 0 0 0 0 0 0 0 0 50
51 10404 5611 10192 10451 9699 10447 0 0 1 0 0 0 0 0 0 0 0 51
52 10597 5788 10404 10192 10451 9699 0 0 0 1 0 0 0 0 0 0 0 52
53 10633 6204 10597 10404 10192 10451 0 0 0 0 1 0 0 0 0 0 0 53
54 10727 3013 10633 10597 10404 10192 0 0 0 0 0 1 0 0 0 0 0 54
55 9784 1931 10727 10633 10597 10404 0 0 0 0 0 0 1 0 0 0 0 55
56 9667 2549 9784 10727 10633 10597 0 0 0 0 0 0 0 1 0 0 0 56
57 10297 1504 9667 9784 10727 10633 0 0 0 0 0 0 0 0 1 0 0 57
58 9426 2090 10297 9667 9784 10727 0 0 0 0 0 0 0 0 0 1 0 58
59 10274 2702 9426 10297 9667 9784 0 0 0 0 0 0 0 0 0 0 1 59
60 9598 2939 10274 9426 10297 9667 0 0 0 0 0 0 0 0 0 0 0 60
61 10400 4500 9598 10274 9426 10297 1 0 0 0 0 0 0 0 0 0 0 61
62 9985 6208 10400 9598 10274 9426 0 1 0 0 0 0 0 0 0 0 0 62
63 10761 6415 9985 10400 9598 10274 0 0 1 0 0 0 0 0 0 0 0 63
64 11081 5657 10761 9985 10400 9598 0 0 0 1 0 0 0 0 0 0 0 64
65 10297 5964 11081 10761 9985 10400 0 0 0 0 1 0 0 0 0 0 0 65
66 10751 3163 10297 11081 10761 9985 0 0 0 0 0 1 0 0 0 0 0 66
67 9760 1997 10751 10297 11081 10761 0 0 0 0 0 0 1 0 0 0 0 67
68 10133 2422 9760 10751 10297 11081 0 0 0 0 0 0 0 1 0 0 0 68
69 10806 1376 10133 9760 10751 10297 0 0 0 0 0 0 0 0 1 0 0 69
70 9734 2202 10806 10133 9760 10751 0 0 0 0 0 0 0 0 0 1 0 70
71 10083 2683 9734 10806 10133 9760 0 0 0 0 0 0 0 0 0 0 1 71
72 10691 3303 10083 9734 10806 10133 0 0 0 0 0 0 0 0 0 0 0 72
73 10446 5202 10691 10083 9734 10806 1 0 0 0 0 0 0 0 0 0 0 73
74 10517 5231 10446 10691 10083 9734 0 1 0 0 0 0 0 0 0 0 0 74
75 11353 4880 10517 10446 10691 10083 0 0 1 0 0 0 0 0 0 0 0 75
76 10436 7998 11353 10517 10446 10691 0 0 0 1 0 0 0 0 0 0 0 76
77 10721 4977 10436 11353 10517 10446 0 0 0 0 1 0 0 0 0 0 0 77
78 10701 3531 10721 10436 11353 10517 0 0 0 0 0 1 0 0 0 0 0 78
79 9793 2025 10701 10721 10436 11353 0 0 0 0 0 0 1 0 0 0 0 79
80 10142 2205 9793 10701 10721 10436 0 0 0 0 0 0 0 1 0 0 0 80
> k <- length(x[1,])
> df <- as.data.frame(x)
> (mylm <- lm(df))
Call:
lm(formula = df)
Coefficients:
(Intercept) X Y1 Y2 Y3 Y4
9650.17771 -0.20165 -0.03892 -0.06494 0.13012 -0.03483
M1 M2 M3 M4 M5 M6
588.59607 539.99454 1241.94351 1205.54424 886.02316 402.96891
M7 M8 M9 M10 M11 t
-630.32969 -130.21647 -10.75694 -626.18320 131.90526 18.96414
> (mysum <- summary(mylm))
Call:
lm(formula = df)
Residuals:
Min 1Q Median 3Q Max
-588.49 -133.21 13.58 124.31 489.18
Coefficients:
Estimate Std. Error t value Pr(>|t|)
(Intercept) 9650.17771 2414.05101 3.998 0.000173 ***
X -0.20165 0.08552 -2.358 0.021553 *
Y1 -0.03892 0.13250 -0.294 0.769917
Y2 -0.06494 0.12421 -0.523 0.602944
Y3 0.13012 0.12146 1.071 0.288182
Y4 -0.03483 0.12615 -0.276 0.783398
M1 588.59607 229.69113 2.563 0.012833 *
M2 539.99454 268.72669 2.009 0.048847 *
M3 1241.94351 245.01512 5.069 3.87e-06 ***
M4 1205.54424 293.60386 4.106 0.000120 ***
M5 886.02316 276.02008 3.210 0.002104 **
M6 402.96891 203.63390 1.979 0.052274 .
M7 -630.32969 235.27795 -2.679 0.009441 **
M8 -130.21647 205.54088 -0.634 0.528717
M9 -10.75694 213.22249 -0.050 0.959926
M10 -626.18320 208.91713 -2.997 0.003915 **
M11 131.90526 196.31134 0.672 0.504132
t 18.96414 4.91601 3.858 0.000275 ***
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
Residual standard error: 241.6 on 62 degrees of freedom
Multiple R-squared: 0.8653, Adjusted R-squared: 0.8284
F-statistic: 23.44 on 17 and 62 DF, p-value: < 2.2e-16
> 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,] 0.17731164 0.3546233 0.8226884
[2,] 0.09518844 0.1903769 0.9048116
[3,] 0.14730297 0.2946059 0.8526970
[4,] 0.12485347 0.2497069 0.8751465
[5,] 0.16055482 0.3211096 0.8394452
[6,] 0.46515065 0.9303013 0.5348494
[7,] 0.60791531 0.7841694 0.3920847
[8,] 0.51504779 0.9699044 0.4849522
[9,] 0.41928002 0.8385600 0.5807200
[10,] 0.37913157 0.7582631 0.6208684
[11,] 0.36470243 0.7294049 0.6352976
[12,] 0.46400324 0.9280065 0.5359968
[13,] 0.43200383 0.8640077 0.5679962
[14,] 0.39745971 0.7949194 0.6025403
[15,] 0.36043164 0.7208633 0.6395684
[16,] 0.31545205 0.6309041 0.6845480
[17,] 0.26686703 0.5337341 0.7331330
[18,] 0.21300899 0.4260180 0.7869910
[19,] 0.28305603 0.5661121 0.7169440
[20,] 0.21637474 0.4327495 0.7836253
[21,] 0.16807706 0.3361541 0.8319229
[22,] 0.13769892 0.2753978 0.8623011
[23,] 0.11769459 0.2353892 0.8823054
[24,] 0.09623404 0.1924681 0.9037660
[25,] 0.07102668 0.1420534 0.9289733
[26,] 0.09159339 0.1831868 0.9084066
[27,] 0.09839950 0.1967990 0.9016005
[28,] 0.08901819 0.1780364 0.9109818
[29,] 0.10781606 0.2156321 0.8921839
[30,] 0.07705981 0.1541196 0.9229402
[31,] 0.07899066 0.1579813 0.9210093
[32,] 0.06156936 0.1231387 0.9384306
[33,] 0.12976369 0.2595274 0.8702363
[34,] 0.11344313 0.2268863 0.8865569
[35,] 0.10563012 0.2112602 0.8943699
[36,] 0.09539821 0.1907964 0.9046018
[37,] 0.09855473 0.1971095 0.9014453
[38,] 0.09754666 0.1950933 0.9024533
[39,] 0.07068232 0.1413646 0.9293177
> postscript(file="/var/www/html/rcomp/tmp/1exdu1261231862.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$resid)
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/2mvfy1261231862.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> plot(mysum$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/3buyu1261231862.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> hist(mysum$resid, main='Residual Histogram', xlab='values of Residuals')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/40izk1261231862.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> densityplot(~mysum$resid,col='black',main='Residual Density Plot', xlab='values of Residuals')
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/585951261231862.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 = 80
Frequency = 1
1 2 3 4 5 6
76.074550 -321.117270 14.767276 50.824564 -191.021429 49.009427
7 8 9 10 11 12
-59.442341 42.685861 23.808681 -38.322499 -253.451336 191.476147
13 14 15 16 17 18
-211.447800 -101.836542 -36.320327 -323.916523 -95.705686 -340.600807
19 20 21 22 23 24
-135.328742 126.792752 116.463413 337.702840 43.441614 -18.106968
25 26 27 28 29 30
-468.860068 220.366584 268.353910 96.015326 12.503701 -140.468087
31 32 33 34 35 36
296.540479 489.175202 -90.705237 12.078967 258.490937 229.472883
37 38 39 40 41 42
28.163357 28.498254 -311.332564 119.572273 14.650305 54.669319
43 44 45 46 47 48
-29.759529 149.128664 -39.170262 -173.793490 317.568839 -127.265187
49 50 51 52 53 54
438.771740 177.418207 -146.598474 -32.942934 468.672414 360.633844
55 56 57 58 59 60
202.053173 -337.967887 -133.884899 -147.357124 36.389433 -588.487326
61 62 63 64 65 66
84.760400 -109.551249 140.703940 200.642382 -76.111185 152.002593
67 68 69 70 71 72
-107.637702 -63.944331 123.488303 9.691306 -402.439487 312.910451
73 74 75 76 77 78
52.537821 106.222015 70.426238 -110.195088 -132.988119 -135.246290
79 80
-166.425339 -405.870262
> postscript(file="/var/www/html/rcomp/tmp/6kppt1261231862.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 = 80
Frequency = 1
lag(myerror, k = 1) myerror
0 76.074550 NA
1 -321.117270 76.074550
2 14.767276 -321.117270
3 50.824564 14.767276
4 -191.021429 50.824564
5 49.009427 -191.021429
6 -59.442341 49.009427
7 42.685861 -59.442341
8 23.808681 42.685861
9 -38.322499 23.808681
10 -253.451336 -38.322499
11 191.476147 -253.451336
12 -211.447800 191.476147
13 -101.836542 -211.447800
14 -36.320327 -101.836542
15 -323.916523 -36.320327
16 -95.705686 -323.916523
17 -340.600807 -95.705686
18 -135.328742 -340.600807
19 126.792752 -135.328742
20 116.463413 126.792752
21 337.702840 116.463413
22 43.441614 337.702840
23 -18.106968 43.441614
24 -468.860068 -18.106968
25 220.366584 -468.860068
26 268.353910 220.366584
27 96.015326 268.353910
28 12.503701 96.015326
29 -140.468087 12.503701
30 296.540479 -140.468087
31 489.175202 296.540479
32 -90.705237 489.175202
33 12.078967 -90.705237
34 258.490937 12.078967
35 229.472883 258.490937
36 28.163357 229.472883
37 28.498254 28.163357
38 -311.332564 28.498254
39 119.572273 -311.332564
40 14.650305 119.572273
41 54.669319 14.650305
42 -29.759529 54.669319
43 149.128664 -29.759529
44 -39.170262 149.128664
45 -173.793490 -39.170262
46 317.568839 -173.793490
47 -127.265187 317.568839
48 438.771740 -127.265187
49 177.418207 438.771740
50 -146.598474 177.418207
51 -32.942934 -146.598474
52 468.672414 -32.942934
53 360.633844 468.672414
54 202.053173 360.633844
55 -337.967887 202.053173
56 -133.884899 -337.967887
57 -147.357124 -133.884899
58 36.389433 -147.357124
59 -588.487326 36.389433
60 84.760400 -588.487326
61 -109.551249 84.760400
62 140.703940 -109.551249
63 200.642382 140.703940
64 -76.111185 200.642382
65 152.002593 -76.111185
66 -107.637702 152.002593
67 -63.944331 -107.637702
68 123.488303 -63.944331
69 9.691306 123.488303
70 -402.439487 9.691306
71 312.910451 -402.439487
72 52.537821 312.910451
73 106.222015 52.537821
74 70.426238 106.222015
75 -110.195088 70.426238
76 -132.988119 -110.195088
77 -135.246290 -132.988119
78 -166.425339 -135.246290
79 -405.870262 -166.425339
80 NA -405.870262
> dum1 <- dum[2:length(myerror),]
> dum1
lag(myerror, k = 1) myerror
[1,] -321.117270 76.074550
[2,] 14.767276 -321.117270
[3,] 50.824564 14.767276
[4,] -191.021429 50.824564
[5,] 49.009427 -191.021429
[6,] -59.442341 49.009427
[7,] 42.685861 -59.442341
[8,] 23.808681 42.685861
[9,] -38.322499 23.808681
[10,] -253.451336 -38.322499
[11,] 191.476147 -253.451336
[12,] -211.447800 191.476147
[13,] -101.836542 -211.447800
[14,] -36.320327 -101.836542
[15,] -323.916523 -36.320327
[16,] -95.705686 -323.916523
[17,] -340.600807 -95.705686
[18,] -135.328742 -340.600807
[19,] 126.792752 -135.328742
[20,] 116.463413 126.792752
[21,] 337.702840 116.463413
[22,] 43.441614 337.702840
[23,] -18.106968 43.441614
[24,] -468.860068 -18.106968
[25,] 220.366584 -468.860068
[26,] 268.353910 220.366584
[27,] 96.015326 268.353910
[28,] 12.503701 96.015326
[29,] -140.468087 12.503701
[30,] 296.540479 -140.468087
[31,] 489.175202 296.540479
[32,] -90.705237 489.175202
[33,] 12.078967 -90.705237
[34,] 258.490937 12.078967
[35,] 229.472883 258.490937
[36,] 28.163357 229.472883
[37,] 28.498254 28.163357
[38,] -311.332564 28.498254
[39,] 119.572273 -311.332564
[40,] 14.650305 119.572273
[41,] 54.669319 14.650305
[42,] -29.759529 54.669319
[43,] 149.128664 -29.759529
[44,] -39.170262 149.128664
[45,] -173.793490 -39.170262
[46,] 317.568839 -173.793490
[47,] -127.265187 317.568839
[48,] 438.771740 -127.265187
[49,] 177.418207 438.771740
[50,] -146.598474 177.418207
[51,] -32.942934 -146.598474
[52,] 468.672414 -32.942934
[53,] 360.633844 468.672414
[54,] 202.053173 360.633844
[55,] -337.967887 202.053173
[56,] -133.884899 -337.967887
[57,] -147.357124 -133.884899
[58,] 36.389433 -147.357124
[59,] -588.487326 36.389433
[60,] 84.760400 -588.487326
[61,] -109.551249 84.760400
[62,] 140.703940 -109.551249
[63,] 200.642382 140.703940
[64,] -76.111185 200.642382
[65,] 152.002593 -76.111185
[66,] -107.637702 152.002593
[67,] -63.944331 -107.637702
[68,] 123.488303 -63.944331
[69,] 9.691306 123.488303
[70,] -402.439487 9.691306
[71,] 312.910451 -402.439487
[72,] 52.537821 312.910451
[73,] 106.222015 52.537821
[74,] 70.426238 106.222015
[75,] -110.195088 70.426238
[76,] -132.988119 -110.195088
[77,] -135.246290 -132.988119
[78,] -166.425339 -135.246290
[79,] -405.870262 -166.425339
> z <- as.data.frame(dum1)
> z
lag(myerror, k = 1) myerror
1 -321.117270 76.074550
2 14.767276 -321.117270
3 50.824564 14.767276
4 -191.021429 50.824564
5 49.009427 -191.021429
6 -59.442341 49.009427
7 42.685861 -59.442341
8 23.808681 42.685861
9 -38.322499 23.808681
10 -253.451336 -38.322499
11 191.476147 -253.451336
12 -211.447800 191.476147
13 -101.836542 -211.447800
14 -36.320327 -101.836542
15 -323.916523 -36.320327
16 -95.705686 -323.916523
17 -340.600807 -95.705686
18 -135.328742 -340.600807
19 126.792752 -135.328742
20 116.463413 126.792752
21 337.702840 116.463413
22 43.441614 337.702840
23 -18.106968 43.441614
24 -468.860068 -18.106968
25 220.366584 -468.860068
26 268.353910 220.366584
27 96.015326 268.353910
28 12.503701 96.015326
29 -140.468087 12.503701
30 296.540479 -140.468087
31 489.175202 296.540479
32 -90.705237 489.175202
33 12.078967 -90.705237
34 258.490937 12.078967
35 229.472883 258.490937
36 28.163357 229.472883
37 28.498254 28.163357
38 -311.332564 28.498254
39 119.572273 -311.332564
40 14.650305 119.572273
41 54.669319 14.650305
42 -29.759529 54.669319
43 149.128664 -29.759529
44 -39.170262 149.128664
45 -173.793490 -39.170262
46 317.568839 -173.793490
47 -127.265187 317.568839
48 438.771740 -127.265187
49 177.418207 438.771740
50 -146.598474 177.418207
51 -32.942934 -146.598474
52 468.672414 -32.942934
53 360.633844 468.672414
54 202.053173 360.633844
55 -337.967887 202.053173
56 -133.884899 -337.967887
57 -147.357124 -133.884899
58 36.389433 -147.357124
59 -588.487326 36.389433
60 84.760400 -588.487326
61 -109.551249 84.760400
62 140.703940 -109.551249
63 200.642382 140.703940
64 -76.111185 200.642382
65 152.002593 -76.111185
66 -107.637702 152.002593
67 -63.944331 -107.637702
68 123.488303 -63.944331
69 9.691306 123.488303
70 -402.439487 9.691306
71 312.910451 -402.439487
72 52.537821 312.910451
73 106.222015 52.537821
74 70.426238 106.222015
75 -110.195088 70.426238
76 -132.988119 -110.195088
77 -135.246290 -132.988119
78 -166.425339 -135.246290
79 -405.870262 -166.425339
> 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/7nzcc1261231862.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> acf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/8y6521261231862.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> pacf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Partial Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/9gmgz1261231862.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> opar <- par(mfrow = c(2,2), oma = c(0, 0, 1.1, 0))
> plot(mylm, las = 1, sub='Residual Diagnostics')
> par(opar)
> dev.off()
null device
1
> if (n > n25) {
+ postscript(file="/var/www/html/rcomp/tmp/10n30w1261231862.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
+ plot(kp3:nmkm3,gqarr[,2], main='Goldfeld-Quandt test',ylab='2-sided p-value',xlab='breakpoint')
+ grid()
+ dev.off()
+ }
null device
1
>
> #Note: the /var/www/html/rcomp/createtable file can be downloaded at http://www.wessa.net/cretab
> load(file="/var/www/html/rcomp/createtable")
>
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a, 'Multiple Linear Regression - Estimated Regression Equation', 1, TRUE)
> a<-table.row.end(a)
> myeq <- colnames(x)[1]
> myeq <- paste(myeq, '[t] = ', sep='')
> for (i in 1:k){
+ if (mysum$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/11tnpl1261231862.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/126in51261231862.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/138ih41261231862.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/147tnt1261231862.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/15upzf1261231862.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/16ioz01261231862.tab")
+ }
>
> try(system("convert tmp/1exdu1261231862.ps tmp/1exdu1261231862.png",intern=TRUE))
character(0)
> try(system("convert tmp/2mvfy1261231862.ps tmp/2mvfy1261231862.png",intern=TRUE))
character(0)
> try(system("convert tmp/3buyu1261231862.ps tmp/3buyu1261231862.png",intern=TRUE))
character(0)
> try(system("convert tmp/40izk1261231862.ps tmp/40izk1261231862.png",intern=TRUE))
character(0)
> try(system("convert tmp/585951261231862.ps tmp/585951261231862.png",intern=TRUE))
character(0)
> try(system("convert tmp/6kppt1261231862.ps tmp/6kppt1261231862.png",intern=TRUE))
character(0)
> try(system("convert tmp/7nzcc1261231862.ps tmp/7nzcc1261231862.png",intern=TRUE))
character(0)
> try(system("convert tmp/8y6521261231862.ps tmp/8y6521261231862.png",intern=TRUE))
character(0)
> try(system("convert tmp/9gmgz1261231862.ps tmp/9gmgz1261231862.png",intern=TRUE))
character(0)
> try(system("convert tmp/10n30w1261231862.ps tmp/10n30w1261231862.png",intern=TRUE))
character(0)
>
>
> proc.time()
user system elapsed
2.724 1.630 3.539