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(900.1
+ ,33
+ ,880.4
+ ,849.4
+ ,819.3
+ ,785.8
+ ,937.2
+ ,31.3
+ ,900.1
+ ,880.4
+ ,849.4
+ ,819.3
+ ,948.9
+ ,29
+ ,937.2
+ ,900.1
+ ,880.4
+ ,849.4
+ ,952.6
+ ,28.7
+ ,948.9
+ ,937.2
+ ,900.1
+ ,880.4
+ ,947.3
+ ,28
+ ,952.6
+ ,948.9
+ ,937.2
+ ,900.1
+ ,974.2
+ ,29.7
+ ,947.3
+ ,952.6
+ ,948.9
+ ,937.2
+ ,1000.8
+ ,30.7
+ ,974.2
+ ,947.3
+ ,952.6
+ ,948.9
+ ,1032.8
+ ,24
+ ,1000.8
+ ,974.2
+ ,947.3
+ ,952.6
+ ,1050.7
+ ,29
+ ,1032.8
+ ,1000.8
+ ,974.2
+ ,947.3
+ ,1057.3
+ ,33
+ ,1050.7
+ ,1032.8
+ ,1000.8
+ ,974.2
+ ,1075.4
+ ,28
+ ,1057.3
+ ,1050.7
+ ,1032.8
+ ,1000.8
+ ,1118.4
+ ,28.7
+ ,1075.4
+ ,1057.3
+ ,1050.7
+ ,1032.8
+ ,1179.8
+ ,31.7
+ ,1118.4
+ ,1075.4
+ ,1057.3
+ ,1050.7
+ ,1227
+ ,34
+ ,1179.8
+ ,1118.4
+ ,1075.4
+ ,1057.3
+ ,1257.8
+ ,35.3
+ ,1227
+ ,1179.8
+ ,1118.4
+ ,1075.4
+ ,1251.5
+ ,27
+ ,1257.8
+ ,1227
+ ,1179.8
+ ,1118.4
+ ,1236.3
+ ,31.3
+ ,1251.5
+ ,1257.8
+ ,1227
+ ,1179.8
+ ,1170.6
+ ,38.7
+ ,1236.3
+ ,1251.5
+ ,1257.8
+ ,1227
+ ,1213.1
+ ,37.3
+ ,1170.6
+ ,1236.3
+ ,1251.5
+ ,1257.8
+ ,1265.5
+ ,37.3
+ ,1213.1
+ ,1170.6
+ ,1236.3
+ ,1251.5
+ ,1300.8
+ ,37.7
+ ,1265.5
+ ,1213.1
+ ,1170.6
+ ,1236.3
+ ,1348.4
+ ,34.7
+ ,1300.8
+ ,1265.5
+ ,1213.1
+ ,1170.6
+ ,1371.9
+ ,34.7
+ ,1348.4
+ ,1300.8
+ ,1265.5
+ ,1213.1
+ ,1403.3
+ ,33.7
+ ,1371.9
+ ,1348.4
+ ,1300.8
+ ,1265.5
+ ,1451.8
+ ,38.3
+ ,1403.3
+ ,1371.9
+ ,1348.4
+ ,1300.8
+ ,1474.2
+ ,38
+ ,1451.8
+ ,1403.3
+ ,1371.9
+ ,1348.4
+ ,1438.2
+ ,38.3
+ ,1474.2
+ ,1451.8
+ ,1403.3
+ ,1371.9
+ ,1513.6
+ ,42.7
+ ,1438.2
+ ,1474.2
+ ,1451.8
+ ,1403.3
+ ,1562.2
+ ,41.7
+ ,1513.6
+ ,1438.2
+ ,1474.2
+ ,1451.8
+ ,1546.2
+ ,39.7
+ ,1562.2
+ ,1513.6
+ ,1438.2
+ ,1474.2
+ ,1527.5
+ ,39.3
+ ,1546.2
+ ,1562.2
+ ,1513.6
+ ,1438.2
+ ,1418.7
+ ,39.3
+ ,1527.5
+ ,1546.2
+ ,1562.2
+ ,1513.6
+ ,1448.5
+ ,37.7
+ ,1418.7
+ ,1527.5
+ ,1546.2
+ ,1562.2
+ ,1492.1
+ ,38.3
+ ,1448.5
+ ,1418.7
+ ,1527.5
+ ,1546.2
+ ,1395.4
+ ,37.7
+ ,1492.1
+ ,1448.5
+ ,1418.7
+ ,1527.5
+ ,1403.7
+ ,37
+ ,1395.4
+ ,1492.1
+ ,1448.5
+ ,1418.7
+ ,1316.6
+ ,34.3
+ ,1403.7
+ ,1395.4
+ ,1492.1
+ ,1448.5
+ ,1274.5
+ ,29.7
+ ,1316.6
+ ,1403.7
+ ,1395.4
+ ,1492.1
+ ,1264.4
+ ,34.7
+ ,1274.5
+ ,1316.6
+ ,1403.7
+ ,1395.4
+ ,1323.9
+ ,32
+ ,1264.4
+ ,1274.5
+ ,1316.6
+ ,1403.7
+ ,1332.1
+ ,30.3
+ ,1323.9
+ ,1264.4
+ ,1274.5
+ ,1316.6
+ ,1250.2
+ ,28.3
+ ,1332.1
+ ,1323.9
+ ,1264.4
+ ,1274.5
+ ,1096.7
+ ,31.3
+ ,1250.2
+ ,1332.1
+ ,1323.9
+ ,1264.4
+ ,1080.8
+ ,17.7
+ ,1096.7
+ ,1250.2
+ ,1332.1
+ ,1323.9
+ ,1039.2
+ ,15.7
+ ,1080.8
+ ,1096.7
+ ,1250.2
+ ,1332.1
+ ,792
+ ,14.3
+ ,1039.2
+ ,1080.8
+ ,1096.7
+ ,1250.2
+ ,746.6
+ ,13.3
+ ,792
+ ,1039.2
+ ,1080.8
+ ,1096.7
+ ,688.8
+ ,11
+ ,746.6
+ ,792
+ ,1039.2
+ ,1080.8
+ ,715.8
+ ,2.7
+ ,688.8
+ ,746.6
+ ,792
+ ,1039.2
+ ,672.9
+ ,3.3
+ ,715.8
+ ,688.8
+ ,746.6
+ ,792
+ ,629.5
+ ,3.7
+ ,672.9
+ ,715.8
+ ,688.8
+ ,746.6
+ ,681.2
+ ,1.4
+ ,629.5
+ ,672.9
+ ,715.8
+ ,688.8
+ ,755.4
+ ,7.1
+ ,681.2
+ ,629.5
+ ,672.9
+ ,715.8
+ ,760.6
+ ,8.1
+ ,755.4
+ ,681.2
+ ,629.5
+ ,672.9
+ ,765.9
+ ,12.4
+ ,760.6
+ ,755.4
+ ,681.2
+ ,629.5
+ ,836.8
+ ,12.4
+ ,765.9
+ ,760.6
+ ,755.4
+ ,681.2
+ ,904.9
+ ,9.2
+ ,836.8
+ ,765.9
+ ,760.6
+ ,755.4)
+ ,dim=c(6
+ ,57)
+ ,dimnames=list(c('Y'
+ ,'X'
+ ,'Y1'
+ ,'Y2'
+ ,'Y3'
+ ,'Y4')
+ ,1:57))
> y <- array(NA,dim=c(6,57),dimnames=list(c('Y','X','Y1','Y2','Y3','Y4'),1:57))
> 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
1 900.1 33.0 880.4 849.4 819.3 785.8 1 0 0 0 0 0 0 0 0 0 0
2 937.2 31.3 900.1 880.4 849.4 819.3 0 1 0 0 0 0 0 0 0 0 0
3 948.9 29.0 937.2 900.1 880.4 849.4 0 0 1 0 0 0 0 0 0 0 0
4 952.6 28.7 948.9 937.2 900.1 880.4 0 0 0 1 0 0 0 0 0 0 0
5 947.3 28.0 952.6 948.9 937.2 900.1 0 0 0 0 1 0 0 0 0 0 0
6 974.2 29.7 947.3 952.6 948.9 937.2 0 0 0 0 0 1 0 0 0 0 0
7 1000.8 30.7 974.2 947.3 952.6 948.9 0 0 0 0 0 0 1 0 0 0 0
8 1032.8 24.0 1000.8 974.2 947.3 952.6 0 0 0 0 0 0 0 1 0 0 0
9 1050.7 29.0 1032.8 1000.8 974.2 947.3 0 0 0 0 0 0 0 0 1 0 0
10 1057.3 33.0 1050.7 1032.8 1000.8 974.2 0 0 0 0 0 0 0 0 0 1 0
11 1075.4 28.0 1057.3 1050.7 1032.8 1000.8 0 0 0 0 0 0 0 0 0 0 1
12 1118.4 28.7 1075.4 1057.3 1050.7 1032.8 0 0 0 0 0 0 0 0 0 0 0
13 1179.8 31.7 1118.4 1075.4 1057.3 1050.7 1 0 0 0 0 0 0 0 0 0 0
14 1227.0 34.0 1179.8 1118.4 1075.4 1057.3 0 1 0 0 0 0 0 0 0 0 0
15 1257.8 35.3 1227.0 1179.8 1118.4 1075.4 0 0 1 0 0 0 0 0 0 0 0
16 1251.5 27.0 1257.8 1227.0 1179.8 1118.4 0 0 0 1 0 0 0 0 0 0 0
17 1236.3 31.3 1251.5 1257.8 1227.0 1179.8 0 0 0 0 1 0 0 0 0 0 0
18 1170.6 38.7 1236.3 1251.5 1257.8 1227.0 0 0 0 0 0 1 0 0 0 0 0
19 1213.1 37.3 1170.6 1236.3 1251.5 1257.8 0 0 0 0 0 0 1 0 0 0 0
20 1265.5 37.3 1213.1 1170.6 1236.3 1251.5 0 0 0 0 0 0 0 1 0 0 0
21 1300.8 37.7 1265.5 1213.1 1170.6 1236.3 0 0 0 0 0 0 0 0 1 0 0
22 1348.4 34.7 1300.8 1265.5 1213.1 1170.6 0 0 0 0 0 0 0 0 0 1 0
23 1371.9 34.7 1348.4 1300.8 1265.5 1213.1 0 0 0 0 0 0 0 0 0 0 1
24 1403.3 33.7 1371.9 1348.4 1300.8 1265.5 0 0 0 0 0 0 0 0 0 0 0
25 1451.8 38.3 1403.3 1371.9 1348.4 1300.8 1 0 0 0 0 0 0 0 0 0 0
26 1474.2 38.0 1451.8 1403.3 1371.9 1348.4 0 1 0 0 0 0 0 0 0 0 0
27 1438.2 38.3 1474.2 1451.8 1403.3 1371.9 0 0 1 0 0 0 0 0 0 0 0
28 1513.6 42.7 1438.2 1474.2 1451.8 1403.3 0 0 0 1 0 0 0 0 0 0 0
29 1562.2 41.7 1513.6 1438.2 1474.2 1451.8 0 0 0 0 1 0 0 0 0 0 0
30 1546.2 39.7 1562.2 1513.6 1438.2 1474.2 0 0 0 0 0 1 0 0 0 0 0
31 1527.5 39.3 1546.2 1562.2 1513.6 1438.2 0 0 0 0 0 0 1 0 0 0 0
32 1418.7 39.3 1527.5 1546.2 1562.2 1513.6 0 0 0 0 0 0 0 1 0 0 0
33 1448.5 37.7 1418.7 1527.5 1546.2 1562.2 0 0 0 0 0 0 0 0 1 0 0
34 1492.1 38.3 1448.5 1418.7 1527.5 1546.2 0 0 0 0 0 0 0 0 0 1 0
35 1395.4 37.7 1492.1 1448.5 1418.7 1527.5 0 0 0 0 0 0 0 0 0 0 1
36 1403.7 37.0 1395.4 1492.1 1448.5 1418.7 0 0 0 0 0 0 0 0 0 0 0
37 1316.6 34.3 1403.7 1395.4 1492.1 1448.5 1 0 0 0 0 0 0 0 0 0 0
38 1274.5 29.7 1316.6 1403.7 1395.4 1492.1 0 1 0 0 0 0 0 0 0 0 0
39 1264.4 34.7 1274.5 1316.6 1403.7 1395.4 0 0 1 0 0 0 0 0 0 0 0
40 1323.9 32.0 1264.4 1274.5 1316.6 1403.7 0 0 0 1 0 0 0 0 0 0 0
41 1332.1 30.3 1323.9 1264.4 1274.5 1316.6 0 0 0 0 1 0 0 0 0 0 0
42 1250.2 28.3 1332.1 1323.9 1264.4 1274.5 0 0 0 0 0 1 0 0 0 0 0
43 1096.7 31.3 1250.2 1332.1 1323.9 1264.4 0 0 0 0 0 0 1 0 0 0 0
44 1080.8 17.7 1096.7 1250.2 1332.1 1323.9 0 0 0 0 0 0 0 1 0 0 0
45 1039.2 15.7 1080.8 1096.7 1250.2 1332.1 0 0 0 0 0 0 0 0 1 0 0
46 792.0 14.3 1039.2 1080.8 1096.7 1250.2 0 0 0 0 0 0 0 0 0 1 0
47 746.6 13.3 792.0 1039.2 1080.8 1096.7 0 0 0 0 0 0 0 0 0 0 1
48 688.8 11.0 746.6 792.0 1039.2 1080.8 0 0 0 0 0 0 0 0 0 0 0
49 715.8 2.7 688.8 746.6 792.0 1039.2 1 0 0 0 0 0 0 0 0 0 0
50 672.9 3.3 715.8 688.8 746.6 792.0 0 1 0 0 0 0 0 0 0 0 0
51 629.5 3.7 672.9 715.8 688.8 746.6 0 0 1 0 0 0 0 0 0 0 0
52 681.2 1.4 629.5 672.9 715.8 688.8 0 0 0 1 0 0 0 0 0 0 0
53 755.4 7.1 681.2 629.5 672.9 715.8 0 0 0 0 1 0 0 0 0 0 0
54 760.6 8.1 755.4 681.2 629.5 672.9 0 0 0 0 0 1 0 0 0 0 0
55 765.9 12.4 760.6 755.4 681.2 629.5 0 0 0 0 0 0 1 0 0 0 0
56 836.8 12.4 765.9 760.6 755.4 681.2 0 0 0 0 0 0 0 1 0 0 0
57 904.9 9.2 836.8 765.9 760.6 755.4 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
> k <- length(x[1,])
> df <- as.data.frame(x)
> (mylm <- lm(df))
Call:
lm(formula = df)
Coefficients:
(Intercept) X Y1 Y2 Y3 Y4
89.73117 6.02273 1.03931 -0.14931 -0.03970 -0.09415
M1 M2 M3 M4 M5 M6
-9.91199 -18.00632 -37.75743 20.77361 -4.61820 -57.07722
M7 M8 M9 M10 M11 t
-54.63009 -4.68642 9.28293 -50.79586 -29.81918 1.37270
> (mysum <- summary(mylm))
Call:
lm(formula = df)
Residuals:
Min 1Q Median 3Q Max
-153.635 -18.954 9.997 27.295 88.424
Coefficients:
Estimate Std. Error t value Pr(>|t|)
(Intercept) 89.73117 47.45805 1.891 0.0661 .
X 6.02273 2.51439 2.395 0.0215 *
Y1 1.03931 0.16611 6.257 2.28e-07 ***
Y2 -0.14931 0.23482 -0.636 0.5286
Y3 -0.03970 0.24233 -0.164 0.8707
Y4 -0.09415 0.15661 -0.601 0.5512
M1 -9.91199 38.07506 -0.260 0.7960
M2 -18.00632 38.21460 -0.471 0.6401
M3 -37.75743 37.88625 -0.997 0.3251
M4 20.77361 37.45093 0.555 0.5823
M5 -4.61820 38.04822 -0.121 0.9040
M6 -57.07722 39.34799 -1.451 0.1549
M7 -54.63009 39.05607 -1.399 0.1698
M8 -4.68642 37.05144 -0.126 0.9000
M9 9.28293 37.80429 0.246 0.8073
M10 -50.79586 39.98677 -1.270 0.2115
M11 -29.81918 39.95095 -0.746 0.4599
t 1.37270 0.92382 1.486 0.1453
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
Residual standard error: 55.05 on 39 degrees of freedom
Multiple R-squared: 0.9704, Adjusted R-squared: 0.9576
F-statistic: 75.31 on 17 and 39 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,] 6.257037e-02 0.1251407491 0.9374296
[2,] 2.622969e-02 0.0524593893 0.9737703
[3,] 7.304448e-03 0.0146088954 0.9926956
[4,] 1.832219e-03 0.0036644389 0.9981678
[5,] 4.496160e-04 0.0008992320 0.9995504
[6,] 9.672486e-05 0.0001934497 0.9999033
[7,] 2.371350e-04 0.0004742700 0.9997629
[8,] 2.695871e-04 0.0005391743 0.9997304
[9,] 4.428661e-04 0.0008857322 0.9995571
[10,] 2.204523e-04 0.0004409045 0.9997795
[11,] 1.913298e-04 0.0003826597 0.9998087
[12,] 1.576488e-03 0.0031529751 0.9984235
[13,] 1.956045e-02 0.0391208959 0.9804396
[14,] 1.867441e-01 0.3734881668 0.8132559
[15,] 4.682211e-01 0.9364422491 0.5317789
[16,] 4.130901e-01 0.8261801075 0.5869099
> postscript(file="/var/www/html/rcomp/tmp/1ufkd1258556748.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$resid)
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/2azff1258556748.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> plot(mysum$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/3wmx31258556748.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> hist(mysum$resid, main='Residual Histogram', xlab='values of Residuals')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/4cr5l1258556748.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> densityplot(~mysum$resid,col='black',main='Residual Density Plot', xlab='values of Residuals')
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/5lk2c1258556748.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 = 57
Frequency = 1
1 2 3 4 5 6
-61.5172770 -18.9537888 -6.5754830 -63.8921362 -39.7281042 38.0378587
7 8 9 10 11 12
27.2949917 24.8397545 -31.4333597 -0.4552664 24.9969649 18.4865613
13 14 15 16 17 18
30.3172168 14.3332721 19.2055225 -15.4869111 -13.7645127 -52.4229504
19 20 21 22 23 24
63.3519526 9.2586464 -25.3456628 65.6661585 28.6978818 23.9470323
25 26 27 28 29 30
29.3693514 19.9941938 -12.0141150 22.6234554 22.9817460 31.5411650
31 32 33 34 35 36
34.9194621 -99.1225115 39.1972276 88.4244320 -73.9552128 5.3191376
37 38 39 40 41 42
-75.5084150 8.8474197 8.9869923 26.3796402 -4.3814064 -27.1526711
43 44 45 46 47 48
-114.7859698 53.1397530 -0.6301179 -153.6353241 20.2603661 -47.7527312
49 50 51 52 53 54
77.3391238 -24.2210969 -9.6029167 30.3759517 34.8922772 9.9965978
55 56 57
-10.7804366 11.8843577 18.2119128
> postscript(file="/var/www/html/rcomp/tmp/68i991258556748.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 = 57
Frequency = 1
lag(myerror, k = 1) myerror
0 -61.5172770 NA
1 -18.9537888 -61.5172770
2 -6.5754830 -18.9537888
3 -63.8921362 -6.5754830
4 -39.7281042 -63.8921362
5 38.0378587 -39.7281042
6 27.2949917 38.0378587
7 24.8397545 27.2949917
8 -31.4333597 24.8397545
9 -0.4552664 -31.4333597
10 24.9969649 -0.4552664
11 18.4865613 24.9969649
12 30.3172168 18.4865613
13 14.3332721 30.3172168
14 19.2055225 14.3332721
15 -15.4869111 19.2055225
16 -13.7645127 -15.4869111
17 -52.4229504 -13.7645127
18 63.3519526 -52.4229504
19 9.2586464 63.3519526
20 -25.3456628 9.2586464
21 65.6661585 -25.3456628
22 28.6978818 65.6661585
23 23.9470323 28.6978818
24 29.3693514 23.9470323
25 19.9941938 29.3693514
26 -12.0141150 19.9941938
27 22.6234554 -12.0141150
28 22.9817460 22.6234554
29 31.5411650 22.9817460
30 34.9194621 31.5411650
31 -99.1225115 34.9194621
32 39.1972276 -99.1225115
33 88.4244320 39.1972276
34 -73.9552128 88.4244320
35 5.3191376 -73.9552128
36 -75.5084150 5.3191376
37 8.8474197 -75.5084150
38 8.9869923 8.8474197
39 26.3796402 8.9869923
40 -4.3814064 26.3796402
41 -27.1526711 -4.3814064
42 -114.7859698 -27.1526711
43 53.1397530 -114.7859698
44 -0.6301179 53.1397530
45 -153.6353241 -0.6301179
46 20.2603661 -153.6353241
47 -47.7527312 20.2603661
48 77.3391238 -47.7527312
49 -24.2210969 77.3391238
50 -9.6029167 -24.2210969
51 30.3759517 -9.6029167
52 34.8922772 30.3759517
53 9.9965978 34.8922772
54 -10.7804366 9.9965978
55 11.8843577 -10.7804366
56 18.2119128 11.8843577
57 NA 18.2119128
> dum1 <- dum[2:length(myerror),]
> dum1
lag(myerror, k = 1) myerror
[1,] -18.9537888 -61.5172770
[2,] -6.5754830 -18.9537888
[3,] -63.8921362 -6.5754830
[4,] -39.7281042 -63.8921362
[5,] 38.0378587 -39.7281042
[6,] 27.2949917 38.0378587
[7,] 24.8397545 27.2949917
[8,] -31.4333597 24.8397545
[9,] -0.4552664 -31.4333597
[10,] 24.9969649 -0.4552664
[11,] 18.4865613 24.9969649
[12,] 30.3172168 18.4865613
[13,] 14.3332721 30.3172168
[14,] 19.2055225 14.3332721
[15,] -15.4869111 19.2055225
[16,] -13.7645127 -15.4869111
[17,] -52.4229504 -13.7645127
[18,] 63.3519526 -52.4229504
[19,] 9.2586464 63.3519526
[20,] -25.3456628 9.2586464
[21,] 65.6661585 -25.3456628
[22,] 28.6978818 65.6661585
[23,] 23.9470323 28.6978818
[24,] 29.3693514 23.9470323
[25,] 19.9941938 29.3693514
[26,] -12.0141150 19.9941938
[27,] 22.6234554 -12.0141150
[28,] 22.9817460 22.6234554
[29,] 31.5411650 22.9817460
[30,] 34.9194621 31.5411650
[31,] -99.1225115 34.9194621
[32,] 39.1972276 -99.1225115
[33,] 88.4244320 39.1972276
[34,] -73.9552128 88.4244320
[35,] 5.3191376 -73.9552128
[36,] -75.5084150 5.3191376
[37,] 8.8474197 -75.5084150
[38,] 8.9869923 8.8474197
[39,] 26.3796402 8.9869923
[40,] -4.3814064 26.3796402
[41,] -27.1526711 -4.3814064
[42,] -114.7859698 -27.1526711
[43,] 53.1397530 -114.7859698
[44,] -0.6301179 53.1397530
[45,] -153.6353241 -0.6301179
[46,] 20.2603661 -153.6353241
[47,] -47.7527312 20.2603661
[48,] 77.3391238 -47.7527312
[49,] -24.2210969 77.3391238
[50,] -9.6029167 -24.2210969
[51,] 30.3759517 -9.6029167
[52,] 34.8922772 30.3759517
[53,] 9.9965978 34.8922772
[54,] -10.7804366 9.9965978
[55,] 11.8843577 -10.7804366
[56,] 18.2119128 11.8843577
> z <- as.data.frame(dum1)
> z
lag(myerror, k = 1) myerror
1 -18.9537888 -61.5172770
2 -6.5754830 -18.9537888
3 -63.8921362 -6.5754830
4 -39.7281042 -63.8921362
5 38.0378587 -39.7281042
6 27.2949917 38.0378587
7 24.8397545 27.2949917
8 -31.4333597 24.8397545
9 -0.4552664 -31.4333597
10 24.9969649 -0.4552664
11 18.4865613 24.9969649
12 30.3172168 18.4865613
13 14.3332721 30.3172168
14 19.2055225 14.3332721
15 -15.4869111 19.2055225
16 -13.7645127 -15.4869111
17 -52.4229504 -13.7645127
18 63.3519526 -52.4229504
19 9.2586464 63.3519526
20 -25.3456628 9.2586464
21 65.6661585 -25.3456628
22 28.6978818 65.6661585
23 23.9470323 28.6978818
24 29.3693514 23.9470323
25 19.9941938 29.3693514
26 -12.0141150 19.9941938
27 22.6234554 -12.0141150
28 22.9817460 22.6234554
29 31.5411650 22.9817460
30 34.9194621 31.5411650
31 -99.1225115 34.9194621
32 39.1972276 -99.1225115
33 88.4244320 39.1972276
34 -73.9552128 88.4244320
35 5.3191376 -73.9552128
36 -75.5084150 5.3191376
37 8.8474197 -75.5084150
38 8.9869923 8.8474197
39 26.3796402 8.9869923
40 -4.3814064 26.3796402
41 -27.1526711 -4.3814064
42 -114.7859698 -27.1526711
43 53.1397530 -114.7859698
44 -0.6301179 53.1397530
45 -153.6353241 -0.6301179
46 20.2603661 -153.6353241
47 -47.7527312 20.2603661
48 77.3391238 -47.7527312
49 -24.2210969 77.3391238
50 -9.6029167 -24.2210969
51 30.3759517 -9.6029167
52 34.8922772 30.3759517
53 9.9965978 34.8922772
54 -10.7804366 9.9965978
55 11.8843577 -10.7804366
56 18.2119128 11.8843577
> 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/7g69m1258556748.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> acf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/8qe7g1258556748.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> pacf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Partial Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/9nvdx1258556748.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> opar <- par(mfrow = c(2,2), oma = c(0, 0, 1.1, 0))
> plot(mylm, las = 1, sub='Residual Diagnostics')
> par(opar)
> dev.off()
null device
1
> if (n > n25) {
+ postscript(file="/var/www/html/rcomp/tmp/105i1v1258556748.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
+ plot(kp3:nmkm3,gqarr[,2], main='Goldfeld-Quandt test',ylab='2-sided p-value',xlab='breakpoint')
+ grid()
+ dev.off()
+ }
null device
1
>
> #Note: the /var/www/html/rcomp/createtable file can be downloaded at http://www.wessa.net/cretab
> load(file="/var/www/html/rcomp/createtable")
>
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a, 'Multiple Linear Regression - Estimated Regression Equation', 1, TRUE)
> a<-table.row.end(a)
> myeq <- colnames(x)[1]
> myeq <- paste(myeq, '[t] = ', sep='')
> for (i in 1:k){
+ if (mysum$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/11skgx1258556748.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/12uxyy1258556748.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/134ngb1258556748.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/144qcj1258556749.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/15y0t41258556749.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/16ta211258556749.tab")
+ }
>
> system("convert tmp/1ufkd1258556748.ps tmp/1ufkd1258556748.png")
> system("convert tmp/2azff1258556748.ps tmp/2azff1258556748.png")
> system("convert tmp/3wmx31258556748.ps tmp/3wmx31258556748.png")
> system("convert tmp/4cr5l1258556748.ps tmp/4cr5l1258556748.png")
> system("convert tmp/5lk2c1258556748.ps tmp/5lk2c1258556748.png")
> system("convert tmp/68i991258556748.ps tmp/68i991258556748.png")
> system("convert tmp/7g69m1258556748.ps tmp/7g69m1258556748.png")
> system("convert tmp/8qe7g1258556748.ps tmp/8qe7g1258556748.png")
> system("convert tmp/9nvdx1258556748.ps tmp/9nvdx1258556748.png")
> system("convert tmp/105i1v1258556748.ps tmp/105i1v1258556748.png")
>
>
> proc.time()
user system elapsed
2.366 1.589 2.826