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 '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(9563
+ ,9731
+ ,8587
+ ,9743
+ ,9084
+ ,9081
+ ,9700
+ ,9998
+ ,9563
+ ,9731
+ ,8587
+ ,9743
+ ,9084
+ ,9081
+ ,9437
+ ,9998
+ ,9563
+ ,9731
+ ,8587
+ ,9743
+ ,9084
+ ,10038
+ ,9437
+ ,9998
+ ,9563
+ ,9731
+ ,8587
+ ,9743
+ ,9918
+ ,10038
+ ,9437
+ ,9998
+ ,9563
+ ,9731
+ ,8587
+ ,9252
+ ,9918
+ ,10038
+ ,9437
+ ,9998
+ ,9563
+ ,9731
+ ,9737
+ ,9252
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+ ,9437
+ ,9998
+ ,9563
+ ,9035
+ ,9737
+ ,9252
+ ,9918
+ ,10038
+ ,9437
+ ,9998
+ ,9133
+ ,9035
+ ,9737
+ ,9252
+ ,9918
+ ,10038
+ ,9437
+ ,9487
+ ,9133
+ ,9035
+ ,9737
+ ,9252
+ ,9918
+ ,10038
+ ,8700
+ ,9487
+ ,9133
+ ,9035
+ ,9737
+ ,9252
+ ,9918
+ ,9627
+ ,8700
+ ,9487
+ ,9133
+ ,9035
+ ,9737
+ ,9252
+ ,8947
+ ,9627
+ ,8700
+ ,9487
+ ,9133
+ ,9035
+ ,9737
+ ,9283
+ ,8947
+ ,9627
+ ,8700
+ ,9487
+ ,9133
+ ,9035
+ ,8829
+ ,9283
+ ,8947
+ ,9627
+ ,8700
+ ,9487
+ ,9133
+ ,9947
+ ,8829
+ ,9283
+ ,8947
+ ,9627
+ ,8700
+ ,9487
+ ,9628
+ ,9947
+ ,8829
+ ,9283
+ ,8947
+ ,9627
+ ,8700
+ ,9318
+ ,9628
+ ,9947
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+ ,9283
+ ,8947
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+ ,9947
+ ,8829
+ ,9283
+ ,9214
+ ,8640
+ ,9605
+ ,9318
+ ,9628
+ ,9947
+ ,8829
+ ,9567
+ ,9214
+ ,8640
+ ,9605
+ ,9318
+ ,9628
+ ,9947
+ ,8547
+ ,9567
+ ,9214
+ ,8640
+ ,9605
+ ,9318
+ ,9628
+ ,9185
+ ,8547
+ ,9567
+ ,9214
+ ,8640
+ ,9605
+ ,9318
+ ,9470
+ ,9185
+ ,8547
+ ,9567
+ ,9214
+ ,8640
+ ,9605
+ ,9123
+ ,9470
+ ,9185
+ ,8547
+ ,9567
+ ,9214
+ ,8640
+ ,9278
+ ,9123
+ ,9470
+ ,9185
+ ,8547
+ ,9567
+ ,9214
+ ,10170
+ ,9278
+ ,9123
+ ,9470
+ ,9185
+ ,8547
+ ,9567
+ ,9434
+ ,10170
+ ,9278
+ ,9123
+ ,9470
+ ,9185
+ ,8547
+ ,9655
+ ,9434
+ ,10170
+ ,9278
+ ,9123
+ ,9470
+ ,9185
+ ,9429
+ ,9655
+ ,9434
+ ,10170
+ ,9278
+ ,9123
+ ,9470
+ ,8739
+ ,9429
+ ,9655
+ ,9434
+ ,10170
+ ,9278
+ ,9123
+ ,9552
+ ,8739
+ ,9429
+ ,9655
+ ,9434
+ ,10170
+ ,9278
+ ,9687
+ ,9552
+ ,8739
+ ,9429
+ ,9655
+ ,9434
+ ,10170
+ ,9019
+ ,9687
+ ,9552
+ ,8739
+ ,9429
+ ,9655
+ ,9434
+ ,9672
+ ,9019
+ ,9687
+ ,9552
+ ,8739
+ ,9429
+ ,9655
+ ,9206
+ ,9672
+ ,9019
+ ,9687
+ ,9552
+ ,8739
+ ,9429
+ ,9069
+ ,9206
+ ,9672
+ ,9019
+ ,9687
+ ,9552
+ ,8739
+ ,9788
+ ,9069
+ ,9206
+ ,9672
+ ,9019
+ ,9687
+ ,9552
+ ,10312
+ ,9788
+ ,9069
+ ,9206
+ ,9672
+ ,9019
+ ,9687
+ ,10105
+ ,10312
+ ,9788
+ ,9069
+ ,9206
+ ,9672
+ ,9019
+ ,9863
+ ,10105
+ ,10312
+ ,9788
+ ,9069
+ ,9206
+ ,9672
+ ,9656
+ ,9863
+ ,10105
+ ,10312
+ ,9788
+ ,9069
+ ,9206
+ ,9295
+ ,9656
+ ,9863
+ ,10105
+ ,10312
+ ,9788
+ ,9069
+ ,9946
+ ,9295
+ ,9656
+ ,9863
+ ,10105
+ ,10312
+ ,9788
+ ,9701
+ ,9946
+ ,9295
+ ,9656
+ ,9863
+ ,10105
+ ,10312
+ ,9049
+ ,9701
+ ,9946
+ ,9295
+ ,9656
+ ,9863
+ ,10105
+ ,10190
+ ,9049
+ ,9701
+ ,9946
+ ,9295
+ ,9656
+ ,9863
+ ,9706
+ ,10190
+ ,9049
+ ,9701
+ ,9946
+ ,9295
+ ,9656
+ ,9765
+ ,9706
+ ,10190
+ ,9049
+ ,9701
+ ,9946
+ ,9295
+ ,9893
+ ,9765
+ ,9706
+ ,10190
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+ ,9994
+ ,9893
+ ,9765
+ ,9706
+ ,10190
+ ,9049
+ ,9701
+ ,10433
+ ,9994
+ ,9893
+ ,9765
+ ,9706
+ ,10190
+ ,9049
+ ,10073
+ ,10433
+ ,9994
+ ,9893
+ ,9765
+ ,9706
+ ,10190
+ ,10112
+ ,10073
+ ,10433
+ ,9994
+ ,9893
+ ,9765
+ ,9706
+ ,9266
+ ,10112
+ ,10073
+ ,10433
+ ,9994
+ ,9893
+ ,9765
+ ,9820
+ ,9266
+ ,10112
+ ,10073
+ ,10433
+ ,9994
+ ,9893
+ ,10097
+ ,9820
+ ,9266
+ ,10112
+ ,10073
+ ,10433
+ ,9994
+ ,9115
+ ,10097
+ ,9820
+ ,9266
+ ,10112
+ ,10073
+ ,10433
+ ,10411
+ ,9115
+ ,10097
+ ,9820
+ ,9266
+ ,10112
+ ,10073
+ ,9678
+ ,10411
+ ,9115
+ ,10097
+ ,9820
+ ,9266
+ ,10112
+ ,10408
+ ,9678
+ ,10411
+ ,9115
+ ,10097
+ ,9820
+ ,9266
+ ,10153
+ ,10408
+ ,9678
+ ,10411
+ ,9115
+ ,10097
+ ,9820
+ ,10368
+ ,10153
+ ,10408
+ ,9678
+ ,10411
+ ,9115
+ ,10097
+ ,10581
+ ,10368
+ ,10153
+ ,10408
+ ,9678
+ ,10411
+ ,9115
+ ,10597
+ ,10581
+ ,10368
+ ,10153
+ ,10408
+ ,9678
+ ,10411
+ ,10680
+ ,10597
+ ,10581
+ ,10368
+ ,10153
+ ,10408
+ ,9678
+ ,9738
+ ,10680
+ ,10597
+ ,10581
+ ,10368
+ ,10153
+ ,10408
+ ,9556
+ ,9738
+ ,10680
+ ,10597
+ ,10581
+ ,10368
+ ,10153)
+ ,dim=c(7
+ ,69)
+ ,dimnames=list(c('Yt'
+ ,'Yt-1'
+ ,'Yt-2'
+ ,'Yt-3'
+ ,'Yt-4'
+ ,'Yt-5'
+ ,'Yt-6')
+ ,1:69))
> y <- array(NA,dim=c(7,69),dimnames=list(c('Yt','Yt-1','Yt-2','Yt-3','Yt-4','Yt-5','Yt-6'),1:69))
> 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
Yt Yt-1 Yt-2 Yt-3 Yt-4 Yt-5 Yt-6 M1 M2 M3 M4 M5 M6 M7 M8 M9 M10 M11
1 9563 9731 8587 9743 9084 9081 9700 1 0 0 0 0 0 0 0 0 0 0
2 9998 9563 9731 8587 9743 9084 9081 0 1 0 0 0 0 0 0 0 0 0
3 9437 9998 9563 9731 8587 9743 9084 0 0 1 0 0 0 0 0 0 0 0
4 10038 9437 9998 9563 9731 8587 9743 0 0 0 1 0 0 0 0 0 0 0
5 9918 10038 9437 9998 9563 9731 8587 0 0 0 0 1 0 0 0 0 0 0
6 9252 9918 10038 9437 9998 9563 9731 0 0 0 0 0 1 0 0 0 0 0
7 9737 9252 9918 10038 9437 9998 9563 0 0 0 0 0 0 1 0 0 0 0
8 9035 9737 9252 9918 10038 9437 9998 0 0 0 0 0 0 0 1 0 0 0
9 9133 9035 9737 9252 9918 10038 9437 0 0 0 0 0 0 0 0 1 0 0
10 9487 9133 9035 9737 9252 9918 10038 0 0 0 0 0 0 0 0 0 1 0
11 8700 9487 9133 9035 9737 9252 9918 0 0 0 0 0 0 0 0 0 0 1
12 9627 8700 9487 9133 9035 9737 9252 0 0 0 0 0 0 0 0 0 0 0
13 8947 9627 8700 9487 9133 9035 9737 1 0 0 0 0 0 0 0 0 0 0
14 9283 8947 9627 8700 9487 9133 9035 0 1 0 0 0 0 0 0 0 0 0
15 8829 9283 8947 9627 8700 9487 9133 0 0 1 0 0 0 0 0 0 0 0
16 9947 8829 9283 8947 9627 8700 9487 0 0 0 1 0 0 0 0 0 0 0
17 9628 9947 8829 9283 8947 9627 8700 0 0 0 0 1 0 0 0 0 0 0
18 9318 9628 9947 8829 9283 8947 9627 0 0 0 0 0 1 0 0 0 0 0
19 9605 9318 9628 9947 8829 9283 8947 0 0 0 0 0 0 1 0 0 0 0
20 8640 9605 9318 9628 9947 8829 9283 0 0 0 0 0 0 0 1 0 0 0
21 9214 8640 9605 9318 9628 9947 8829 0 0 0 0 0 0 0 0 1 0 0
22 9567 9214 8640 9605 9318 9628 9947 0 0 0 0 0 0 0 0 0 1 0
23 8547 9567 9214 8640 9605 9318 9628 0 0 0 0 0 0 0 0 0 0 1
24 9185 8547 9567 9214 8640 9605 9318 0 0 0 0 0 0 0 0 0 0 0
25 9470 9185 8547 9567 9214 8640 9605 1 0 0 0 0 0 0 0 0 0 0
26 9123 9470 9185 8547 9567 9214 8640 0 1 0 0 0 0 0 0 0 0 0
27 9278 9123 9470 9185 8547 9567 9214 0 0 1 0 0 0 0 0 0 0 0
28 10170 9278 9123 9470 9185 8547 9567 0 0 0 1 0 0 0 0 0 0 0
29 9434 10170 9278 9123 9470 9185 8547 0 0 0 0 1 0 0 0 0 0 0
30 9655 9434 10170 9278 9123 9470 9185 0 0 0 0 0 1 0 0 0 0 0
31 9429 9655 9434 10170 9278 9123 9470 0 0 0 0 0 0 1 0 0 0 0
32 8739 9429 9655 9434 10170 9278 9123 0 0 0 0 0 0 0 1 0 0 0
33 9552 8739 9429 9655 9434 10170 9278 0 0 0 0 0 0 0 0 1 0 0
34 9687 9552 8739 9429 9655 9434 10170 0 0 0 0 0 0 0 0 0 1 0
35 9019 9687 9552 8739 9429 9655 9434 0 0 0 0 0 0 0 0 0 0 1
36 9672 9019 9687 9552 8739 9429 9655 0 0 0 0 0 0 0 0 0 0 0
37 9206 9672 9019 9687 9552 8739 9429 1 0 0 0 0 0 0 0 0 0 0
38 9069 9206 9672 9019 9687 9552 8739 0 1 0 0 0 0 0 0 0 0 0
39 9788 9069 9206 9672 9019 9687 9552 0 0 1 0 0 0 0 0 0 0 0
40 10312 9788 9069 9206 9672 9019 9687 0 0 0 1 0 0 0 0 0 0 0
41 10105 10312 9788 9069 9206 9672 9019 0 0 0 0 1 0 0 0 0 0 0
42 9863 10105 10312 9788 9069 9206 9672 0 0 0 0 0 1 0 0 0 0 0
43 9656 9863 10105 10312 9788 9069 9206 0 0 0 0 0 0 1 0 0 0 0
44 9295 9656 9863 10105 10312 9788 9069 0 0 0 0 0 0 0 1 0 0 0
45 9946 9295 9656 9863 10105 10312 9788 0 0 0 0 0 0 0 0 1 0 0
46 9701 9946 9295 9656 9863 10105 10312 0 0 0 0 0 0 0 0 0 1 0
47 9049 9701 9946 9295 9656 9863 10105 0 0 0 0 0 0 0 0 0 0 1
48 10190 9049 9701 9946 9295 9656 9863 0 0 0 0 0 0 0 0 0 0 0
49 9706 10190 9049 9701 9946 9295 9656 1 0 0 0 0 0 0 0 0 0 0
50 9765 9706 10190 9049 9701 9946 9295 0 1 0 0 0 0 0 0 0 0 0
51 9893 9765 9706 10190 9049 9701 9946 0 0 1 0 0 0 0 0 0 0 0
52 9994 9893 9765 9706 10190 9049 9701 0 0 0 1 0 0 0 0 0 0 0
53 10433 9994 9893 9765 9706 10190 9049 0 0 0 0 1 0 0 0 0 0 0
54 10073 10433 9994 9893 9765 9706 10190 0 0 0 0 0 1 0 0 0 0 0
55 10112 10073 10433 9994 9893 9765 9706 0 0 0 0 0 0 1 0 0 0 0
56 9266 10112 10073 10433 9994 9893 9765 0 0 0 0 0 0 0 1 0 0 0
57 9820 9266 10112 10073 10433 9994 9893 0 0 0 0 0 0 0 0 1 0 0
58 10097 9820 9266 10112 10073 10433 9994 0 0 0 0 0 0 0 0 0 1 0
59 9115 10097 9820 9266 10112 10073 10433 0 0 0 0 0 0 0 0 0 0 1
60 10411 9115 10097 9820 9266 10112 10073 0 0 0 0 0 0 0 0 0 0 0
61 9678 10411 9115 10097 9820 9266 10112 1 0 0 0 0 0 0 0 0 0 0
62 10408 9678 10411 9115 10097 9820 9266 0 1 0 0 0 0 0 0 0 0 0
63 10153 10408 9678 10411 9115 10097 9820 0 0 1 0 0 0 0 0 0 0 0
64 10368 10153 10408 9678 10411 9115 10097 0 0 0 1 0 0 0 0 0 0 0
65 10581 10368 10153 10408 9678 10411 9115 0 0 0 0 1 0 0 0 0 0 0
66 10597 10581 10368 10153 10408 9678 10411 0 0 0 0 0 1 0 0 0 0 0
67 10680 10597 10581 10368 10153 10408 9678 0 0 0 0 0 0 1 0 0 0 0
68 9738 10680 10597 10581 10368 10153 10408 0 0 0 0 0 0 0 1 0 0 0
69 9556 9738 10680 10597 10581 10368 10153 0 0 0 0 0 0 0 0 1 0 0
t
1 1
2 2
3 3
4 4
5 5
6 6
7 7
8 8
9 9
10 10
11 11
12 12
13 13
14 14
15 15
16 16
17 17
18 18
19 19
20 20
21 21
22 22
23 23
24 24
25 25
26 26
27 27
28 28
29 29
30 30
31 31
32 32
33 33
34 34
35 35
36 36
37 37
38 38
39 39
40 40
41 41
42 42
43 43
44 44
45 45
46 46
47 47
48 48
49 49
50 50
51 51
52 52
53 53
54 54
55 55
56 56
57 57
58 58
59 59
60 60
61 61
62 62
63 63
64 64
65 65
66 66
67 67
68 68
69 69
> k <- length(x[1,])
> df <- as.data.frame(x)
> (mylm <- lm(df))
Call:
lm(formula = df)
Coefficients:
(Intercept) `Yt-1` `Yt-2` `Yt-3` `Yt-4` `Yt-5`
2260.17635 0.03399 0.03501 0.11248 -0.01184 0.31608
`Yt-6` M1 M2 M3 M4 M5
0.28026 -179.02684 129.39808 -238.93757 585.73988 356.88104
M6 M7 M8 M9 M10 M11
-33.05508 33.60608 -732.85993 -442.64035 -299.09219 -930.99474
t
5.03344
> (mysum <- summary(mylm))
Call:
lm(formula = df)
Residuals:
Min 1Q Median 3Q Max
-531.51 -118.67 30.95 115.36 665.82
Coefficients:
Estimate Std. Error t value Pr(>|t|)
(Intercept) 2260.17635 1654.97621 1.366 0.178150
`Yt-1` 0.03399 0.14260 0.238 0.812569
`Yt-2` 0.03501 0.13827 0.253 0.801134
`Yt-3` 0.11248 0.14127 0.796 0.429709
`Yt-4` -0.01184 0.14192 -0.083 0.933838
`Yt-5` 0.31608 0.13890 2.276 0.027186 *
`Yt-6` 0.28026 0.14637 1.915 0.061267 .
M1 -179.02684 259.76784 -0.689 0.493896
M2 129.39808 243.25459 0.532 0.597120
M3 -238.93757 204.95797 -1.166 0.249231
M4 585.73988 240.23346 2.438 0.018356 *
M5 356.88104 288.87126 1.235 0.222443
M6 -33.05508 227.53212 -0.145 0.885077
M7 33.60608 226.52930 0.148 0.882662
M8 -732.85993 247.11497 -2.966 0.004620 **
M9 -442.64035 212.50857 -2.083 0.042392 *
M10 -299.09219 234.46333 -1.276 0.207976
M11 -930.99474 233.06605 -3.995 0.000213 ***
t 5.03344 2.59457 1.940 0.058032 .
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
Residual standard error: 257 on 50 degrees of freedom
Multiple R-squared: 0.8063, Adjusted R-squared: 0.7366
F-statistic: 11.56 on 18 and 50 DF, p-value: 4.022e-12
> 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,] 0.7568580 0.4862841 0.24314203
[2,] 0.6189425 0.7621150 0.38105751
[3,] 0.5080270 0.9839461 0.49197304
[4,] 0.8677056 0.2645889 0.13229443
[5,] 0.8070170 0.3859661 0.19298304
[6,] 0.8069416 0.3861168 0.19305842
[7,] 0.9110557 0.1778887 0.08894435
[8,] 0.8942545 0.2114909 0.10574546
[9,] 0.8889947 0.2220105 0.11100525
[10,] 0.8312890 0.3374221 0.16871103
[11,] 0.8172376 0.3655247 0.18276237
[12,] 0.7814450 0.4371100 0.21855502
[13,] 0.7853047 0.4293906 0.21469529
[14,] 0.7325406 0.5349188 0.26745939
[15,] 0.6484406 0.7031188 0.35155938
[16,] 0.5588275 0.8823450 0.44117252
[17,] 0.7980045 0.4039910 0.20199549
[18,] 0.8348351 0.3303298 0.16516490
[19,] 0.8096260 0.3807481 0.19037404
[20,] 0.7275894 0.5448211 0.27241055
[21,] 0.6626386 0.6747228 0.33736139
[22,] 0.5434588 0.9130823 0.45654117
[23,] 0.4798176 0.9596353 0.52018235
[24,] 0.6984466 0.6031068 0.30155339
[25,] 0.5640389 0.8719222 0.43596108
[26,] 0.7027705 0.5944590 0.29722951
> postscript(file="/var/www/html/rcomp/tmp/1z04d1290883230.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$resid)
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/2z04d1290883230.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> plot(mysum$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/3s93g1290883230.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> hist(mysum$resid, main='Residual Histogram', xlab='values of Residuals')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/4s93g1290883230.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> densityplot(~mysum$resid,col='black',main='Residual Density Plot', xlab='values of Residuals')
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/5s93g1290883230.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 = 69
Frequency = 1
1 2 3 4 5 6
268.269105 665.823343 107.721702 95.994445 110.494636 -386.828446
7 8 9 10 11 12
-111.336565 30.952163 -118.673445 -84.949050 68.298548 87.643611
13 14 15 16 17 18
-375.009203 -103.335099 -434.588102 94.375394 -141.196739 -84.413471
19 20 21 22 23 24
105.845771 1.829561 108.276118 78.521728 -47.380224 -402.919620
25 26 27 28 29 30
261.778435 -222.783983 -58.946974 209.195519 -212.121643 97.138154
31 32 33 34 35 36
-250.985013 -38.007605 152.148443 145.773896 282.936261 -72.226884
37 38 39 40 41 42
-87.164227 -531.511257 219.886979 127.987112 92.528062 105.915594
43 44 45 46 47 48
-33.825856 222.734471 255.635567 -208.443950 -75.381790 216.085845
49 50 51 52 53 54
97.506588 -214.612692 50.568035 -341.861779 122.758757 -51.284474
55 56 57 58 59 60
20.038851 -158.424528 105.605993 69.097376 -228.472795 171.417049
61 62 63 64 65 66
-165.380698 406.419688 115.358360 -185.690691 27.536926 319.472642
67 68 69
270.262811 -59.084062 -502.992676
> postscript(file="/var/www/html/rcomp/tmp/63j2j1290883230.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 = 69
Frequency = 1
lag(myerror, k = 1) myerror
0 268.269105 NA
1 665.823343 268.269105
2 107.721702 665.823343
3 95.994445 107.721702
4 110.494636 95.994445
5 -386.828446 110.494636
6 -111.336565 -386.828446
7 30.952163 -111.336565
8 -118.673445 30.952163
9 -84.949050 -118.673445
10 68.298548 -84.949050
11 87.643611 68.298548
12 -375.009203 87.643611
13 -103.335099 -375.009203
14 -434.588102 -103.335099
15 94.375394 -434.588102
16 -141.196739 94.375394
17 -84.413471 -141.196739
18 105.845771 -84.413471
19 1.829561 105.845771
20 108.276118 1.829561
21 78.521728 108.276118
22 -47.380224 78.521728
23 -402.919620 -47.380224
24 261.778435 -402.919620
25 -222.783983 261.778435
26 -58.946974 -222.783983
27 209.195519 -58.946974
28 -212.121643 209.195519
29 97.138154 -212.121643
30 -250.985013 97.138154
31 -38.007605 -250.985013
32 152.148443 -38.007605
33 145.773896 152.148443
34 282.936261 145.773896
35 -72.226884 282.936261
36 -87.164227 -72.226884
37 -531.511257 -87.164227
38 219.886979 -531.511257
39 127.987112 219.886979
40 92.528062 127.987112
41 105.915594 92.528062
42 -33.825856 105.915594
43 222.734471 -33.825856
44 255.635567 222.734471
45 -208.443950 255.635567
46 -75.381790 -208.443950
47 216.085845 -75.381790
48 97.506588 216.085845
49 -214.612692 97.506588
50 50.568035 -214.612692
51 -341.861779 50.568035
52 122.758757 -341.861779
53 -51.284474 122.758757
54 20.038851 -51.284474
55 -158.424528 20.038851
56 105.605993 -158.424528
57 69.097376 105.605993
58 -228.472795 69.097376
59 171.417049 -228.472795
60 -165.380698 171.417049
61 406.419688 -165.380698
62 115.358360 406.419688
63 -185.690691 115.358360
64 27.536926 -185.690691
65 319.472642 27.536926
66 270.262811 319.472642
67 -59.084062 270.262811
68 -502.992676 -59.084062
69 NA -502.992676
> dum1 <- dum[2:length(myerror),]
> dum1
lag(myerror, k = 1) myerror
[1,] 665.823343 268.269105
[2,] 107.721702 665.823343
[3,] 95.994445 107.721702
[4,] 110.494636 95.994445
[5,] -386.828446 110.494636
[6,] -111.336565 -386.828446
[7,] 30.952163 -111.336565
[8,] -118.673445 30.952163
[9,] -84.949050 -118.673445
[10,] 68.298548 -84.949050
[11,] 87.643611 68.298548
[12,] -375.009203 87.643611
[13,] -103.335099 -375.009203
[14,] -434.588102 -103.335099
[15,] 94.375394 -434.588102
[16,] -141.196739 94.375394
[17,] -84.413471 -141.196739
[18,] 105.845771 -84.413471
[19,] 1.829561 105.845771
[20,] 108.276118 1.829561
[21,] 78.521728 108.276118
[22,] -47.380224 78.521728
[23,] -402.919620 -47.380224
[24,] 261.778435 -402.919620
[25,] -222.783983 261.778435
[26,] -58.946974 -222.783983
[27,] 209.195519 -58.946974
[28,] -212.121643 209.195519
[29,] 97.138154 -212.121643
[30,] -250.985013 97.138154
[31,] -38.007605 -250.985013
[32,] 152.148443 -38.007605
[33,] 145.773896 152.148443
[34,] 282.936261 145.773896
[35,] -72.226884 282.936261
[36,] -87.164227 -72.226884
[37,] -531.511257 -87.164227
[38,] 219.886979 -531.511257
[39,] 127.987112 219.886979
[40,] 92.528062 127.987112
[41,] 105.915594 92.528062
[42,] -33.825856 105.915594
[43,] 222.734471 -33.825856
[44,] 255.635567 222.734471
[45,] -208.443950 255.635567
[46,] -75.381790 -208.443950
[47,] 216.085845 -75.381790
[48,] 97.506588 216.085845
[49,] -214.612692 97.506588
[50,] 50.568035 -214.612692
[51,] -341.861779 50.568035
[52,] 122.758757 -341.861779
[53,] -51.284474 122.758757
[54,] 20.038851 -51.284474
[55,] -158.424528 20.038851
[56,] 105.605993 -158.424528
[57,] 69.097376 105.605993
[58,] -228.472795 69.097376
[59,] 171.417049 -228.472795
[60,] -165.380698 171.417049
[61,] 406.419688 -165.380698
[62,] 115.358360 406.419688
[63,] -185.690691 115.358360
[64,] 27.536926 -185.690691
[65,] 319.472642 27.536926
[66,] 270.262811 319.472642
[67,] -59.084062 270.262811
[68,] -502.992676 -59.084062
> z <- as.data.frame(dum1)
> z
lag(myerror, k = 1) myerror
1 665.823343 268.269105
2 107.721702 665.823343
3 95.994445 107.721702
4 110.494636 95.994445
5 -386.828446 110.494636
6 -111.336565 -386.828446
7 30.952163 -111.336565
8 -118.673445 30.952163
9 -84.949050 -118.673445
10 68.298548 -84.949050
11 87.643611 68.298548
12 -375.009203 87.643611
13 -103.335099 -375.009203
14 -434.588102 -103.335099
15 94.375394 -434.588102
16 -141.196739 94.375394
17 -84.413471 -141.196739
18 105.845771 -84.413471
19 1.829561 105.845771
20 108.276118 1.829561
21 78.521728 108.276118
22 -47.380224 78.521728
23 -402.919620 -47.380224
24 261.778435 -402.919620
25 -222.783983 261.778435
26 -58.946974 -222.783983
27 209.195519 -58.946974
28 -212.121643 209.195519
29 97.138154 -212.121643
30 -250.985013 97.138154
31 -38.007605 -250.985013
32 152.148443 -38.007605
33 145.773896 152.148443
34 282.936261 145.773896
35 -72.226884 282.936261
36 -87.164227 -72.226884
37 -531.511257 -87.164227
38 219.886979 -531.511257
39 127.987112 219.886979
40 92.528062 127.987112
41 105.915594 92.528062
42 -33.825856 105.915594
43 222.734471 -33.825856
44 255.635567 222.734471
45 -208.443950 255.635567
46 -75.381790 -208.443950
47 216.085845 -75.381790
48 97.506588 216.085845
49 -214.612692 97.506588
50 50.568035 -214.612692
51 -341.861779 50.568035
52 122.758757 -341.861779
53 -51.284474 122.758757
54 20.038851 -51.284474
55 -158.424528 20.038851
56 105.605993 -158.424528
57 69.097376 105.605993
58 -228.472795 69.097376
59 171.417049 -228.472795
60 -165.380698 171.417049
61 406.419688 -165.380698
62 115.358360 406.419688
63 -185.690691 115.358360
64 27.536926 -185.690691
65 319.472642 27.536926
66 270.262811 319.472642
67 -59.084062 270.262811
68 -502.992676 -59.084062
> 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/7wsk41290883230.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> acf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/8wsk41290883230.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> pacf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Partial Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/9wsk41290883230.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> opar <- par(mfrow = c(2,2), oma = c(0, 0, 1.1, 0))
> plot(mylm, las = 1, sub='Residual Diagnostics')
> par(opar)
> dev.off()
null device
1
> if (n > n25) {
+ postscript(file="/var/www/html/rcomp/tmp/10o1171290883230.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
+ plot(kp3:nmkm3,gqarr[,2], main='Goldfeld-Quandt test',ylab='2-sided p-value',xlab='breakpoint')
+ grid()
+ dev.off()
+ }
null device
1
>
> #Note: the /var/www/html/rcomp/createtable file can be downloaded at http://www.wessa.net/cretab
> load(file="/var/www/html/rcomp/createtable")
>
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a, 'Multiple Linear Regression - Estimated Regression Equation', 1, TRUE)
> a<-table.row.end(a)
> myeq <- colnames(x)[1]
> myeq <- paste(myeq, '[t] = ', sep='')
> for (i in 1:k){
+ if (mysum$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/11s2zv1290883230.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/12d2g01290883230.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/132lvc1290883230.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/14ducx1290883230.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/15gvs31290883230.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/16u58t1290883230.tab")
+ }
>
> try(system("convert tmp/1z04d1290883230.ps tmp/1z04d1290883230.png",intern=TRUE))
character(0)
> try(system("convert tmp/2z04d1290883230.ps tmp/2z04d1290883230.png",intern=TRUE))
character(0)
> try(system("convert tmp/3s93g1290883230.ps tmp/3s93g1290883230.png",intern=TRUE))
character(0)
> try(system("convert tmp/4s93g1290883230.ps tmp/4s93g1290883230.png",intern=TRUE))
character(0)
> try(system("convert tmp/5s93g1290883230.ps tmp/5s93g1290883230.png",intern=TRUE))
character(0)
> try(system("convert tmp/63j2j1290883230.ps tmp/63j2j1290883230.png",intern=TRUE))
character(0)
> try(system("convert tmp/7wsk41290883230.ps tmp/7wsk41290883230.png",intern=TRUE))
character(0)
> try(system("convert tmp/8wsk41290883230.ps tmp/8wsk41290883230.png",intern=TRUE))
character(0)
> try(system("convert tmp/9wsk41290883230.ps tmp/9wsk41290883230.png",intern=TRUE))
character(0)
> try(system("convert tmp/10o1171290883230.ps tmp/10o1171290883230.png",intern=TRUE))
character(0)
>
>
> proc.time()
user system elapsed
3.034 1.978 6.901