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(103.91
+ ,100.30
+ ,103.88
+ ,103.77
+ ,103.66
+ ,103.64
+ ,103.63
+ ,103.91
+ ,98.50
+ ,103.91
+ ,103.88
+ ,103.77
+ ,103.66
+ ,103.64
+ ,103.92
+ ,95.10
+ ,103.91
+ ,103.91
+ ,103.88
+ ,103.77
+ ,103.66
+ ,104.05
+ ,93.10
+ ,103.92
+ ,103.91
+ ,103.91
+ ,103.88
+ ,103.77
+ ,104.23
+ ,92.20
+ ,104.05
+ ,103.92
+ ,103.91
+ ,103.91
+ ,103.88
+ ,104.30
+ ,89.00
+ ,104.23
+ ,104.05
+ ,103.92
+ ,103.91
+ ,103.91
+ ,104.31
+ ,86.40
+ ,104.30
+ ,104.23
+ ,104.05
+ ,103.92
+ ,103.91
+ ,104.31
+ ,84.50
+ ,104.31
+ ,104.30
+ ,104.23
+ ,104.05
+ ,103.92
+ ,104.34
+ ,82.70
+ ,104.31
+ ,104.31
+ ,104.30
+ ,104.23
+ ,104.05
+ ,104.55
+ ,80.80
+ ,104.34
+ ,104.31
+ ,104.31
+ ,104.30
+ ,104.23
+ ,104.65
+ ,81.80
+ ,104.55
+ ,104.34
+ ,104.31
+ ,104.31
+ ,104.30
+ ,104.73
+ ,81.80
+ ,104.65
+ ,104.55
+ ,104.34
+ ,104.31
+ ,104.31
+ ,104.75
+ ,82.90
+ ,104.73
+ ,104.65
+ ,104.55
+ ,104.34
+ ,104.31
+ ,104.75
+ ,83.80
+ ,104.75
+ ,104.73
+ ,104.65
+ ,104.55
+ ,104.34
+ ,104.76
+ ,86.20
+ ,104.75
+ ,104.75
+ ,104.73
+ ,104.65
+ ,104.55
+ ,104.94
+ ,86.10
+ ,104.76
+ ,104.75
+ ,104.75
+ ,104.73
+ ,104.65
+ ,105.29
+ ,86.20
+ ,104.94
+ ,104.76
+ ,104.75
+ ,104.75
+ ,104.73
+ ,105.38
+ ,88.80
+ ,105.29
+ ,104.94
+ ,104.76
+ ,104.75
+ ,104.75
+ ,105.43
+ ,89.60
+ ,105.38
+ ,105.29
+ ,104.94
+ ,104.76
+ ,104.75
+ ,105.43
+ ,87.80
+ ,105.43
+ ,105.38
+ ,105.29
+ ,104.94
+ ,104.76
+ ,105.42
+ ,88.30
+ ,105.43
+ ,105.43
+ ,105.38
+ ,105.29
+ ,104.94
+ ,105.52
+ ,88.60
+ ,105.42
+ ,105.43
+ ,105.43
+ ,105.38
+ ,105.29
+ ,105.69
+ ,91.00
+ ,105.52
+ ,105.42
+ ,105.43
+ ,105.43
+ ,105.38
+ ,105.72
+ ,91.50
+ ,105.69
+ ,105.52
+ ,105.42
+ ,105.43
+ ,105.43
+ ,105.74
+ ,95.40
+ ,105.72
+ ,105.69
+ ,105.52
+ ,105.42
+ ,105.43
+ ,105.74
+ ,98.70
+ ,105.74
+ ,105.72
+ ,105.69
+ ,105.52
+ ,105.42
+ ,105.74
+ ,99.90
+ ,105.74
+ ,105.74
+ ,105.72
+ ,105.69
+ ,105.52
+ ,105.95
+ ,98.60
+ ,105.74
+ ,105.74
+ ,105.74
+ ,105.72
+ ,105.69
+ ,106.17
+ ,100.30
+ ,105.95
+ ,105.74
+ ,105.74
+ ,105.74
+ ,105.72
+ ,106.34
+ ,100.20
+ ,106.17
+ ,105.95
+ ,105.74
+ ,105.74
+ ,105.74
+ ,106.37
+ ,100.40
+ ,106.34
+ ,106.17
+ ,105.95
+ ,105.74
+ ,105.74
+ ,106.37
+ ,101.40
+ ,106.37
+ ,106.34
+ ,106.17
+ ,105.95
+ ,105.74
+ ,106.36
+ ,103.00
+ ,106.37
+ ,106.37
+ ,106.34
+ ,106.17
+ ,105.95
+ ,106.44
+ ,109.10
+ ,106.36
+ ,106.37
+ ,106.37
+ ,106.34
+ ,106.17
+ ,106.29
+ ,111.40
+ ,106.44
+ ,106.36
+ ,106.37
+ ,106.37
+ ,106.34
+ ,106.23
+ ,114.10
+ ,106.29
+ ,106.44
+ ,106.36
+ ,106.37
+ ,106.37
+ ,106.23
+ ,121.80
+ ,106.23
+ ,106.29
+ ,106.44
+ ,106.36
+ ,106.37
+ ,106.23
+ ,127.60
+ ,106.23
+ ,106.23
+ ,106.29
+ ,106.44
+ ,106.36
+ ,106.23
+ ,129.90
+ ,106.23
+ ,106.23
+ ,106.23
+ ,106.29
+ ,106.44
+ ,106.34
+ ,128.00
+ ,106.23
+ ,106.23
+ ,106.23
+ ,106.23
+ ,106.29
+ ,106.44
+ ,123.50
+ ,106.34
+ ,106.23
+ ,106.23
+ ,106.23
+ ,106.23
+ ,106.44
+ ,124.00
+ ,106.44
+ ,106.34
+ ,106.23
+ ,106.23
+ ,106.23
+ ,106.48
+ ,127.40
+ ,106.44
+ ,106.44
+ ,106.34
+ ,106.23
+ ,106.23
+ ,106.50
+ ,127.60
+ ,106.48
+ ,106.44
+ ,106.44
+ ,106.34
+ ,106.23
+ ,106.57
+ ,128.40
+ ,106.50
+ ,106.48
+ ,106.44
+ ,106.44
+ ,106.34
+ ,106.40
+ ,131.40
+ ,106.57
+ ,106.50
+ ,106.48
+ ,106.44
+ ,106.44
+ ,106.37
+ ,135.10
+ ,106.40
+ ,106.57
+ ,106.50
+ ,106.48
+ ,106.44
+ ,106.25
+ ,134.00
+ ,106.37
+ ,106.40
+ ,106.57
+ ,106.50
+ ,106.48
+ ,106.21
+ ,144.50
+ ,106.25
+ ,106.37
+ ,106.40
+ ,106.57
+ ,106.50
+ ,106.21
+ ,147.30
+ ,106.21
+ ,106.25
+ ,106.37
+ ,106.40
+ ,106.57
+ ,106.24
+ ,150.90
+ ,106.21
+ ,106.21
+ ,106.25
+ ,106.37
+ ,106.40
+ ,106.19
+ ,148.70
+ ,106.24
+ ,106.21
+ ,106.21
+ ,106.25
+ ,106.37
+ ,106.08
+ ,141.40
+ ,106.19
+ ,106.24
+ ,106.21
+ ,106.21
+ ,106.25
+ ,106.13
+ ,138.90
+ ,106.08
+ ,106.19
+ ,106.24
+ ,106.21
+ ,106.21
+ ,106.09
+ ,139.80
+ ,106.13
+ ,106.08
+ ,106.19
+ ,106.24
+ ,106.21)
+ ,dim=c(7
+ ,55)
+ ,dimnames=list(c('Y'
+ ,'X'
+ ,'Y1'
+ ,'Y2'
+ ,'Y3'
+ ,'Y4'
+ ,'Y5
')
+ ,1:55))
> y <- array(NA,dim=c(7,55),dimnames=list(c('Y','X','Y1','Y2','Y3','Y4','Y5
'),1:55))
> 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 Y5\r M1 M2 M3 M4 M5 M6 M7 M8 M9
1 103.91 100.3 103.88 103.77 103.66 103.64 103.63 1 0 0 0 0 0 0 0 0
2 103.91 98.5 103.91 103.88 103.77 103.66 103.64 0 1 0 0 0 0 0 0 0
3 103.92 95.1 103.91 103.91 103.88 103.77 103.66 0 0 1 0 0 0 0 0 0
4 104.05 93.1 103.92 103.91 103.91 103.88 103.77 0 0 0 1 0 0 0 0 0
5 104.23 92.2 104.05 103.92 103.91 103.91 103.88 0 0 0 0 1 0 0 0 0
6 104.30 89.0 104.23 104.05 103.92 103.91 103.91 0 0 0 0 0 1 0 0 0
7 104.31 86.4 104.30 104.23 104.05 103.92 103.91 0 0 0 0 0 0 1 0 0
8 104.31 84.5 104.31 104.30 104.23 104.05 103.92 0 0 0 0 0 0 0 1 0
9 104.34 82.7 104.31 104.31 104.30 104.23 104.05 0 0 0 0 0 0 0 0 1
10 104.55 80.8 104.34 104.31 104.31 104.30 104.23 0 0 0 0 0 0 0 0 0
11 104.65 81.8 104.55 104.34 104.31 104.31 104.30 0 0 0 0 0 0 0 0 0
12 104.73 81.8 104.65 104.55 104.34 104.31 104.31 0 0 0 0 0 0 0 0 0
13 104.75 82.9 104.73 104.65 104.55 104.34 104.31 1 0 0 0 0 0 0 0 0
14 104.75 83.8 104.75 104.73 104.65 104.55 104.34 0 1 0 0 0 0 0 0 0
15 104.76 86.2 104.75 104.75 104.73 104.65 104.55 0 0 1 0 0 0 0 0 0
16 104.94 86.1 104.76 104.75 104.75 104.73 104.65 0 0 0 1 0 0 0 0 0
17 105.29 86.2 104.94 104.76 104.75 104.75 104.73 0 0 0 0 1 0 0 0 0
18 105.38 88.8 105.29 104.94 104.76 104.75 104.75 0 0 0 0 0 1 0 0 0
19 105.43 89.6 105.38 105.29 104.94 104.76 104.75 0 0 0 0 0 0 1 0 0
20 105.43 87.8 105.43 105.38 105.29 104.94 104.76 0 0 0 0 0 0 0 1 0
21 105.42 88.3 105.43 105.43 105.38 105.29 104.94 0 0 0 0 0 0 0 0 1
22 105.52 88.6 105.42 105.43 105.43 105.38 105.29 0 0 0 0 0 0 0 0 0
23 105.69 91.0 105.52 105.42 105.43 105.43 105.38 0 0 0 0 0 0 0 0 0
24 105.72 91.5 105.69 105.52 105.42 105.43 105.43 0 0 0 0 0 0 0 0 0
25 105.74 95.4 105.72 105.69 105.52 105.42 105.43 1 0 0 0 0 0 0 0 0
26 105.74 98.7 105.74 105.72 105.69 105.52 105.42 0 1 0 0 0 0 0 0 0
27 105.74 99.9 105.74 105.74 105.72 105.69 105.52 0 0 1 0 0 0 0 0 0
28 105.95 98.6 105.74 105.74 105.74 105.72 105.69 0 0 0 1 0 0 0 0 0
29 106.17 100.3 105.95 105.74 105.74 105.74 105.72 0 0 0 0 1 0 0 0 0
30 106.34 100.2 106.17 105.95 105.74 105.74 105.74 0 0 0 0 0 1 0 0 0
31 106.37 100.4 106.34 106.17 105.95 105.74 105.74 0 0 0 0 0 0 1 0 0
32 106.37 101.4 106.37 106.34 106.17 105.95 105.74 0 0 0 0 0 0 0 1 0
33 106.36 103.0 106.37 106.37 106.34 106.17 105.95 0 0 0 0 0 0 0 0 1
34 106.44 109.1 106.36 106.37 106.37 106.34 106.17 0 0 0 0 0 0 0 0 0
35 106.29 111.4 106.44 106.36 106.37 106.37 106.34 0 0 0 0 0 0 0 0 0
36 106.23 114.1 106.29 106.44 106.36 106.37 106.37 0 0 0 0 0 0 0 0 0
37 106.23 121.8 106.23 106.29 106.44 106.36 106.37 1 0 0 0 0 0 0 0 0
38 106.23 127.6 106.23 106.23 106.29 106.44 106.36 0 1 0 0 0 0 0 0 0
39 106.23 129.9 106.23 106.23 106.23 106.29 106.44 0 0 1 0 0 0 0 0 0
40 106.34 128.0 106.23 106.23 106.23 106.23 106.29 0 0 0 1 0 0 0 0 0
41 106.44 123.5 106.34 106.23 106.23 106.23 106.23 0 0 0 0 1 0 0 0 0
42 106.44 124.0 106.44 106.34 106.23 106.23 106.23 0 0 0 0 0 1 0 0 0
43 106.48 127.4 106.44 106.44 106.34 106.23 106.23 0 0 0 0 0 0 1 0 0
44 106.50 127.6 106.48 106.44 106.44 106.34 106.23 0 0 0 0 0 0 0 1 0
45 106.57 128.4 106.50 106.48 106.44 106.44 106.34 0 0 0 0 0 0 0 0 1
46 106.40 131.4 106.57 106.50 106.48 106.44 106.44 0 0 0 0 0 0 0 0 0
47 106.37 135.1 106.40 106.57 106.50 106.48 106.44 0 0 0 0 0 0 0 0 0
48 106.25 134.0 106.37 106.40 106.57 106.50 106.48 0 0 0 0 0 0 0 0 0
49 106.21 144.5 106.25 106.37 106.40 106.57 106.50 1 0 0 0 0 0 0 0 0
50 106.21 147.3 106.21 106.25 106.37 106.40 106.57 0 1 0 0 0 0 0 0 0
51 106.24 150.9 106.21 106.21 106.25 106.37 106.40 0 0 1 0 0 0 0 0 0
52 106.19 148.7 106.24 106.21 106.21 106.25 106.37 0 0 0 1 0 0 0 0 0
53 106.08 141.4 106.19 106.24 106.21 106.21 106.25 0 0 0 0 1 0 0 0 0
54 106.13 138.9 106.08 106.19 106.24 106.21 106.21 0 0 0 0 0 1 0 0 0
55 106.09 139.8 106.13 106.08 106.19 106.24 106.21 0 0 0 0 0 0 1 0 0
M10 M11 t
1 0 0 1
2 0 0 2
3 0 0 3
4 0 0 4
5 0 0 5
6 0 0 6
7 0 0 7
8 0 0 8
9 0 0 9
10 1 0 10
11 0 1 11
12 0 0 12
13 0 0 13
14 0 0 14
15 0 0 15
16 0 0 16
17 0 0 17
18 0 0 18
19 0 0 19
20 0 0 20
21 0 0 21
22 1 0 22
23 0 1 23
24 0 0 24
25 0 0 25
26 0 0 26
27 0 0 27
28 0 0 28
29 0 0 29
30 0 0 30
31 0 0 31
32 0 0 32
33 0 0 33
34 1 0 34
35 0 1 35
36 0 0 36
37 0 0 37
38 0 0 38
39 0 0 39
40 0 0 40
41 0 0 41
42 0 0 42
43 0 0 43
44 0 0 44
45 0 0 45
46 1 0 46
47 0 1 47
48 0 0 48
49 0 0 49
50 0 0 50
51 0 0 51
52 0 0 52
53 0 0 53
54 0 0 54
55 0 0 55
> k <- length(x[1,])
> df <- as.data.frame(x)
> (mylm <- lm(df))
Call:
lm(formula = df)
Coefficients:
(Intercept) X Y1 Y2 Y3 Y4
-2.8310397 -0.0049797 0.9327138 -0.0849262 -0.2950205 0.1793902
`Y5\r` M1 M2 M3 M4 M5
0.2996729 0.0662920 0.0702756 0.0678099 0.1555106 0.1819848
M6 M7 M8 M9 M10 M11
0.1284070 0.1233565 0.1441148 0.1027503 0.0801148 0.0357875
t
-0.0001492
> (mysum <- summary(mylm))
Call:
lm(formula = df)
Residuals:
Min 1Q Median 3Q Max
-0.167730 -0.036947 0.003218 0.031243 0.116239
Coefficients:
Estimate Std. Error t value Pr(>|t|)
(Intercept) -2.8310397 4.3422505 -0.652 0.51856
X -0.0049797 0.0016434 -3.030 0.00451 **
Y1 0.9327138 0.1577453 5.913 9.09e-07 ***
Y2 -0.0849262 0.2246089 -0.378 0.70757
Y3 -0.2950205 0.2437821 -1.210 0.23410
Y4 0.1793902 0.2394235 0.749 0.45857
`Y5\r` 0.2996729 0.1858830 1.612 0.11566
M1 0.0662920 0.0497117 1.334 0.19073
M2 0.0702756 0.0512925 1.370 0.17914
M3 0.0678099 0.0502295 1.350 0.18544
M4 0.1555106 0.0486286 3.198 0.00288 **
M5 0.1819848 0.0511739 3.556 0.00108 **
M6 0.1284070 0.0537281 2.390 0.02221 *
M7 0.1233565 0.0550833 2.239 0.03140 *
M8 0.1441148 0.0657718 2.191 0.03500 *
M9 0.1027503 0.0617912 1.663 0.10502
M10 0.0801148 0.0517506 1.548 0.13035
M11 0.0357875 0.0505545 0.708 0.48357
t -0.0001492 0.0036034 -0.041 0.96719
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
Residual standard error: 0.07019 on 36 degrees of freedom
Multiple R-squared: 0.9955, Adjusted R-squared: 0.9932
F-statistic: 437.9 on 18 and 36 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,] 0.17104780 0.3420956 0.8289522
[2,] 0.07907249 0.1581450 0.9209275
[3,] 0.05536821 0.1107364 0.9446318
[4,] 0.09036578 0.1807316 0.9096342
[5,] 0.20446263 0.4089253 0.7955374
[6,] 0.23377112 0.4675422 0.7662289
[7,] 0.14608847 0.2921769 0.8539115
[8,] 0.15843515 0.3168703 0.8415648
[9,] 0.15935509 0.3187102 0.8406449
[10,] 0.08838058 0.1767612 0.9116194
[11,] 0.30631536 0.6126307 0.6936846
[12,] 0.33906040 0.6781208 0.6609396
> postscript(file="/var/www/html/rcomp/tmp/1orbs1258207131.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$resid)
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/2zjom1258207131.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> plot(mysum$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/33v301258207131.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> hist(mysum$resid, main='Residual Histogram', xlab='values of Residuals')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/49pa81258207131.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> densityplot(~mysum$resid,col='black',main='Residual Density Plot', xlab='values of Residuals')
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/536j11258207131.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 = 55
Frequency = 1
1 2 3 4 5
0.0315487618 0.0259790536 0.0309366911 0.0102524229 0.0006964371
6 7 8 9 10
-0.0543995861 -0.0655916295 -0.0722581594 -0.0594548699 0.0723387888
11 12 13 14 15
0.0057019024 0.0520555955 0.0018386408 -0.0265343410 -0.0575382868
16 17 18 19 20
-0.0133328970 0.1162392134 -0.0412928765 0.0149802533 0.0143856315
21 22 23 24 25
-0.0375403053 -0.0102141421 0.0861529551 -0.0134230901 -0.0223930067
26 27 28 29 30
0.0093102544 -0.0320136472 0.0335356506 0.0272282470 0.0571013539
31 32 33 34 35
0.0153736683 0.0134329337 0.0032183227 0.0581325859 -0.1677300395
36 37 38 39 40
-0.0435873839 -0.0027669950 -0.0384223166 -0.0391205791 0.0295809517
41 42 43 44 45
-0.0037708253 -0.0314833992 0.0715921112 0.0444395942 0.0937768525
46 47 48 49 50
-0.1202572326 0.0758751821 0.0049548785 -0.0082274010 0.0296673497
51 52 53 54 55
0.0977358220 -0.0600361282 -0.1403930721 0.0700745079 -0.0363544034
> postscript(file="/var/www/html/rcomp/tmp/6cvsi1258207131.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 = 55
Frequency = 1
lag(myerror, k = 1) myerror
0 0.0315487618 NA
1 0.0259790536 0.0315487618
2 0.0309366911 0.0259790536
3 0.0102524229 0.0309366911
4 0.0006964371 0.0102524229
5 -0.0543995861 0.0006964371
6 -0.0655916295 -0.0543995861
7 -0.0722581594 -0.0655916295
8 -0.0594548699 -0.0722581594
9 0.0723387888 -0.0594548699
10 0.0057019024 0.0723387888
11 0.0520555955 0.0057019024
12 0.0018386408 0.0520555955
13 -0.0265343410 0.0018386408
14 -0.0575382868 -0.0265343410
15 -0.0133328970 -0.0575382868
16 0.1162392134 -0.0133328970
17 -0.0412928765 0.1162392134
18 0.0149802533 -0.0412928765
19 0.0143856315 0.0149802533
20 -0.0375403053 0.0143856315
21 -0.0102141421 -0.0375403053
22 0.0861529551 -0.0102141421
23 -0.0134230901 0.0861529551
24 -0.0223930067 -0.0134230901
25 0.0093102544 -0.0223930067
26 -0.0320136472 0.0093102544
27 0.0335356506 -0.0320136472
28 0.0272282470 0.0335356506
29 0.0571013539 0.0272282470
30 0.0153736683 0.0571013539
31 0.0134329337 0.0153736683
32 0.0032183227 0.0134329337
33 0.0581325859 0.0032183227
34 -0.1677300395 0.0581325859
35 -0.0435873839 -0.1677300395
36 -0.0027669950 -0.0435873839
37 -0.0384223166 -0.0027669950
38 -0.0391205791 -0.0384223166
39 0.0295809517 -0.0391205791
40 -0.0037708253 0.0295809517
41 -0.0314833992 -0.0037708253
42 0.0715921112 -0.0314833992
43 0.0444395942 0.0715921112
44 0.0937768525 0.0444395942
45 -0.1202572326 0.0937768525
46 0.0758751821 -0.1202572326
47 0.0049548785 0.0758751821
48 -0.0082274010 0.0049548785
49 0.0296673497 -0.0082274010
50 0.0977358220 0.0296673497
51 -0.0600361282 0.0977358220
52 -0.1403930721 -0.0600361282
53 0.0700745079 -0.1403930721
54 -0.0363544034 0.0700745079
55 NA -0.0363544034
> dum1 <- dum[2:length(myerror),]
> dum1
lag(myerror, k = 1) myerror
[1,] 0.0259790536 0.0315487618
[2,] 0.0309366911 0.0259790536
[3,] 0.0102524229 0.0309366911
[4,] 0.0006964371 0.0102524229
[5,] -0.0543995861 0.0006964371
[6,] -0.0655916295 -0.0543995861
[7,] -0.0722581594 -0.0655916295
[8,] -0.0594548699 -0.0722581594
[9,] 0.0723387888 -0.0594548699
[10,] 0.0057019024 0.0723387888
[11,] 0.0520555955 0.0057019024
[12,] 0.0018386408 0.0520555955
[13,] -0.0265343410 0.0018386408
[14,] -0.0575382868 -0.0265343410
[15,] -0.0133328970 -0.0575382868
[16,] 0.1162392134 -0.0133328970
[17,] -0.0412928765 0.1162392134
[18,] 0.0149802533 -0.0412928765
[19,] 0.0143856315 0.0149802533
[20,] -0.0375403053 0.0143856315
[21,] -0.0102141421 -0.0375403053
[22,] 0.0861529551 -0.0102141421
[23,] -0.0134230901 0.0861529551
[24,] -0.0223930067 -0.0134230901
[25,] 0.0093102544 -0.0223930067
[26,] -0.0320136472 0.0093102544
[27,] 0.0335356506 -0.0320136472
[28,] 0.0272282470 0.0335356506
[29,] 0.0571013539 0.0272282470
[30,] 0.0153736683 0.0571013539
[31,] 0.0134329337 0.0153736683
[32,] 0.0032183227 0.0134329337
[33,] 0.0581325859 0.0032183227
[34,] -0.1677300395 0.0581325859
[35,] -0.0435873839 -0.1677300395
[36,] -0.0027669950 -0.0435873839
[37,] -0.0384223166 -0.0027669950
[38,] -0.0391205791 -0.0384223166
[39,] 0.0295809517 -0.0391205791
[40,] -0.0037708253 0.0295809517
[41,] -0.0314833992 -0.0037708253
[42,] 0.0715921112 -0.0314833992
[43,] 0.0444395942 0.0715921112
[44,] 0.0937768525 0.0444395942
[45,] -0.1202572326 0.0937768525
[46,] 0.0758751821 -0.1202572326
[47,] 0.0049548785 0.0758751821
[48,] -0.0082274010 0.0049548785
[49,] 0.0296673497 -0.0082274010
[50,] 0.0977358220 0.0296673497
[51,] -0.0600361282 0.0977358220
[52,] -0.1403930721 -0.0600361282
[53,] 0.0700745079 -0.1403930721
[54,] -0.0363544034 0.0700745079
> z <- as.data.frame(dum1)
> z
lag(myerror, k = 1) myerror
1 0.0259790536 0.0315487618
2 0.0309366911 0.0259790536
3 0.0102524229 0.0309366911
4 0.0006964371 0.0102524229
5 -0.0543995861 0.0006964371
6 -0.0655916295 -0.0543995861
7 -0.0722581594 -0.0655916295
8 -0.0594548699 -0.0722581594
9 0.0723387888 -0.0594548699
10 0.0057019024 0.0723387888
11 0.0520555955 0.0057019024
12 0.0018386408 0.0520555955
13 -0.0265343410 0.0018386408
14 -0.0575382868 -0.0265343410
15 -0.0133328970 -0.0575382868
16 0.1162392134 -0.0133328970
17 -0.0412928765 0.1162392134
18 0.0149802533 -0.0412928765
19 0.0143856315 0.0149802533
20 -0.0375403053 0.0143856315
21 -0.0102141421 -0.0375403053
22 0.0861529551 -0.0102141421
23 -0.0134230901 0.0861529551
24 -0.0223930067 -0.0134230901
25 0.0093102544 -0.0223930067
26 -0.0320136472 0.0093102544
27 0.0335356506 -0.0320136472
28 0.0272282470 0.0335356506
29 0.0571013539 0.0272282470
30 0.0153736683 0.0571013539
31 0.0134329337 0.0153736683
32 0.0032183227 0.0134329337
33 0.0581325859 0.0032183227
34 -0.1677300395 0.0581325859
35 -0.0435873839 -0.1677300395
36 -0.0027669950 -0.0435873839
37 -0.0384223166 -0.0027669950
38 -0.0391205791 -0.0384223166
39 0.0295809517 -0.0391205791
40 -0.0037708253 0.0295809517
41 -0.0314833992 -0.0037708253
42 0.0715921112 -0.0314833992
43 0.0444395942 0.0715921112
44 0.0937768525 0.0444395942
45 -0.1202572326 0.0937768525
46 0.0758751821 -0.1202572326
47 0.0049548785 0.0758751821
48 -0.0082274010 0.0049548785
49 0.0296673497 -0.0082274010
50 0.0977358220 0.0296673497
51 -0.0600361282 0.0977358220
52 -0.1403930721 -0.0600361282
53 0.0700745079 -0.1403930721
54 -0.0363544034 0.0700745079
> 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/7z7k21258207131.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> acf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/89qqy1258207131.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> pacf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Partial Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/9krzm1258207131.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> opar <- par(mfrow = c(2,2), oma = c(0, 0, 1.1, 0))
> plot(mylm, las = 1, sub='Residual Diagnostics')
> par(opar)
> dev.off()
null device
1
> if (n > n25) {
+ postscript(file="/var/www/html/rcomp/tmp/106c3j1258207131.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
+ plot(kp3:nmkm3,gqarr[,2], main='Goldfeld-Quandt test',ylab='2-sided p-value',xlab='breakpoint')
+ grid()
+ dev.off()
+ }
null device
1
>
> #Note: the /var/www/html/rcomp/createtable file can be downloaded at http://www.wessa.net/cretab
> load(file="/var/www/html/rcomp/createtable")
>
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a, 'Multiple Linear Regression - Estimated Regression Equation', 1, TRUE)
> a<-table.row.end(a)
> myeq <- colnames(x)[1]
> myeq <- paste(myeq, '[t] = ', sep='')
> for (i in 1:k){
+ if (mysum$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/11iico1258207131.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/12cx1x1258207131.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/13yrp11258207131.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/14rxo21258207131.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/1515z11258207131.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/16yztw1258207131.tab")
+ }
>
> system("convert tmp/1orbs1258207131.ps tmp/1orbs1258207131.png")
> system("convert tmp/2zjom1258207131.ps tmp/2zjom1258207131.png")
> system("convert tmp/33v301258207131.ps tmp/33v301258207131.png")
> system("convert tmp/49pa81258207131.ps tmp/49pa81258207131.png")
> system("convert tmp/536j11258207131.ps tmp/536j11258207131.png")
> system("convert tmp/6cvsi1258207131.ps tmp/6cvsi1258207131.png")
> system("convert tmp/7z7k21258207131.ps tmp/7z7k21258207131.png")
> system("convert tmp/89qqy1258207131.ps tmp/89qqy1258207131.png")
> system("convert tmp/9krzm1258207131.ps tmp/9krzm1258207131.png")
> system("convert tmp/106c3j1258207131.ps tmp/106c3j1258207131.png")
>
>
> proc.time()
user system elapsed
2.399 1.620 3.466