R version 2.8.0 (2008-10-20)
Copyright (C) 2008 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(6340.5
+ ,0
+ ,7901.5
+ ,0
+ ,8191.1
+ ,0
+ ,7181.7
+ ,0
+ ,7594.4
+ ,0
+ ,7384.7
+ ,0
+ ,7876.7
+ ,0
+ ,8463.4
+ ,0
+ ,8317.2
+ ,0
+ ,7778.7
+ ,0
+ ,8532.8
+ ,0
+ ,7272.2
+ ,0
+ ,6680.1
+ ,0
+ ,8427.6
+ ,0
+ ,8752.8
+ ,0
+ ,7952.7
+ ,0
+ ,8694.3
+ ,0
+ ,7787
+ ,0
+ ,8474.2
+ ,0
+ ,9154.7
+ ,0
+ ,8557.2
+ ,0
+ ,7951.1
+ ,0
+ ,9156.7
+ ,0
+ ,7865.7
+ ,0
+ ,7337.4
+ ,0
+ ,9131.7
+ ,0
+ ,8814.6
+ ,0
+ ,8598.8
+ ,0
+ ,8439.6
+ ,0
+ ,7451.8
+ ,0
+ ,8016.2
+ ,0
+ ,9544.1
+ ,0
+ ,8270.7
+ ,0
+ ,8102.2
+ ,0
+ ,9369
+ ,0
+ ,7657.7
+ ,0
+ ,7816.6
+ ,0
+ ,9391.3
+ ,0
+ ,9445.4
+ ,0
+ ,9533.1
+ ,0
+ ,10068.7
+ ,0
+ ,8955.5
+ ,0
+ ,10423.9
+ ,0
+ ,11617.2
+ ,0
+ ,9391.1
+ ,0
+ ,10872
+ ,0
+ ,10230.4
+ ,0
+ ,9221
+ ,0
+ ,9428.6
+ ,0
+ ,10934.5
+ ,0
+ ,10986
+ ,0
+ ,11724.6
+ ,0
+ ,11180.9
+ ,0
+ ,11163.2
+ ,0
+ ,11240.9
+ ,0
+ ,12107.1
+ ,0
+ ,10762.3
+ ,0
+ ,11340.4
+ ,0
+ ,11266.8
+ ,0
+ ,9542.7
+ ,0
+ ,9227.7
+ ,0
+ ,10571.9
+ ,1
+ ,10774.4
+ ,1
+ ,10392.8
+ ,1
+ ,9920.2
+ ,1
+ ,9884.9
+ ,1
+ ,10174.5
+ ,1
+ ,11395.4
+ ,1
+ ,10760.2
+ ,1
+ ,10570.1
+ ,1
+ ,10536
+ ,1
+ ,9902.6
+ ,1
+ ,8889
+ ,1
+ ,10837.3
+ ,1
+ ,11624.1
+ ,1
+ ,10509
+ ,1
+ ,10984.9
+ ,1
+ ,10649.1
+ ,1
+ ,10855.7
+ ,1
+ ,11677.4
+ ,1
+ ,10760.2
+ ,1
+ ,10046.2
+ ,1
+ ,10772.8
+ ,1
+ ,9987.7
+ ,1
+ ,8638.7
+ ,1
+ ,11063.7
+ ,1
+ ,11855.7
+ ,1
+ ,10684.5
+ ,1
+ ,11337.4
+ ,1
+ ,10478
+ ,1
+ ,11123.9
+ ,1
+ ,12909.3
+ ,1
+ ,11339.9
+ ,1
+ ,10462.2
+ ,1
+ ,12733.5
+ ,1
+ ,10519.2
+ ,1
+ ,10414.9
+ ,1
+ ,12476.8
+ ,1
+ ,12384.6
+ ,1
+ ,12266.7
+ ,1
+ ,12919.9
+ ,1
+ ,11497.3
+ ,1
+ ,12142
+ ,1
+ ,13919.4
+ ,1
+ ,12656.8
+ ,1
+ ,12034.1
+ ,1
+ ,13199.7
+ ,1
+ ,10881.3
+ ,1
+ ,11301.2
+ ,1
+ ,13643.9
+ ,1
+ ,12517
+ ,1
+ ,13981.1
+ ,1
+ ,14275.7
+ ,1
+ ,13435
+ ,1
+ ,13565.7
+ ,1
+ ,16216.3
+ ,1
+ ,12970
+ ,1
+ ,14079.9
+ ,1
+ ,14235
+ ,1
+ ,12213.4
+ ,1
+ ,12581
+ ,1)
+ ,dim=c(2
+ ,121)
+ ,dimnames=list(c('y'
+ ,'x')
+ ,1:121))
> y <- array(NA,dim=c(2,121),dimnames=list(c('y','x'),1:121))
> 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 M1 M2 M3 M4 M5 M6 M7 M8 M9 M10 M11 t
1 6340.5 0 1 0 0 0 0 0 0 0 0 0 0 1
2 7901.5 0 0 1 0 0 0 0 0 0 0 0 0 2
3 8191.1 0 0 0 1 0 0 0 0 0 0 0 0 3
4 7181.7 0 0 0 0 1 0 0 0 0 0 0 0 4
5 7594.4 0 0 0 0 0 1 0 0 0 0 0 0 5
6 7384.7 0 0 0 0 0 0 1 0 0 0 0 0 6
7 7876.7 0 0 0 0 0 0 0 1 0 0 0 0 7
8 8463.4 0 0 0 0 0 0 0 0 1 0 0 0 8
9 8317.2 0 0 0 0 0 0 0 0 0 1 0 0 9
10 7778.7 0 0 0 0 0 0 0 0 0 0 1 0 10
11 8532.8 0 0 0 0 0 0 0 0 0 0 0 1 11
12 7272.2 0 0 0 0 0 0 0 0 0 0 0 0 12
13 6680.1 0 1 0 0 0 0 0 0 0 0 0 0 13
14 8427.6 0 0 1 0 0 0 0 0 0 0 0 0 14
15 8752.8 0 0 0 1 0 0 0 0 0 0 0 0 15
16 7952.7 0 0 0 0 1 0 0 0 0 0 0 0 16
17 8694.3 0 0 0 0 0 1 0 0 0 0 0 0 17
18 7787.0 0 0 0 0 0 0 1 0 0 0 0 0 18
19 8474.2 0 0 0 0 0 0 0 1 0 0 0 0 19
20 9154.7 0 0 0 0 0 0 0 0 1 0 0 0 20
21 8557.2 0 0 0 0 0 0 0 0 0 1 0 0 21
22 7951.1 0 0 0 0 0 0 0 0 0 0 1 0 22
23 9156.7 0 0 0 0 0 0 0 0 0 0 0 1 23
24 7865.7 0 0 0 0 0 0 0 0 0 0 0 0 24
25 7337.4 0 1 0 0 0 0 0 0 0 0 0 0 25
26 9131.7 0 0 1 0 0 0 0 0 0 0 0 0 26
27 8814.6 0 0 0 1 0 0 0 0 0 0 0 0 27
28 8598.8 0 0 0 0 1 0 0 0 0 0 0 0 28
29 8439.6 0 0 0 0 0 1 0 0 0 0 0 0 29
30 7451.8 0 0 0 0 0 0 1 0 0 0 0 0 30
31 8016.2 0 0 0 0 0 0 0 1 0 0 0 0 31
32 9544.1 0 0 0 0 0 0 0 0 1 0 0 0 32
33 8270.7 0 0 0 0 0 0 0 0 0 1 0 0 33
34 8102.2 0 0 0 0 0 0 0 0 0 0 1 0 34
35 9369.0 0 0 0 0 0 0 0 0 0 0 0 1 35
36 7657.7 0 0 0 0 0 0 0 0 0 0 0 0 36
37 7816.6 0 1 0 0 0 0 0 0 0 0 0 0 37
38 9391.3 0 0 1 0 0 0 0 0 0 0 0 0 38
39 9445.4 0 0 0 1 0 0 0 0 0 0 0 0 39
40 9533.1 0 0 0 0 1 0 0 0 0 0 0 0 40
41 10068.7 0 0 0 0 0 1 0 0 0 0 0 0 41
42 8955.5 0 0 0 0 0 0 1 0 0 0 0 0 42
43 10423.9 0 0 0 0 0 0 0 1 0 0 0 0 43
44 11617.2 0 0 0 0 0 0 0 0 1 0 0 0 44
45 9391.1 0 0 0 0 0 0 0 0 0 1 0 0 45
46 10872.0 0 0 0 0 0 0 0 0 0 0 1 0 46
47 10230.4 0 0 0 0 0 0 0 0 0 0 0 1 47
48 9221.0 0 0 0 0 0 0 0 0 0 0 0 0 48
49 9428.6 0 1 0 0 0 0 0 0 0 0 0 0 49
50 10934.5 0 0 1 0 0 0 0 0 0 0 0 0 50
51 10986.0 0 0 0 1 0 0 0 0 0 0 0 0 51
52 11724.6 0 0 0 0 1 0 0 0 0 0 0 0 52
53 11180.9 0 0 0 0 0 1 0 0 0 0 0 0 53
54 11163.2 0 0 0 0 0 0 1 0 0 0 0 0 54
55 11240.9 0 0 0 0 0 0 0 1 0 0 0 0 55
56 12107.1 0 0 0 0 0 0 0 0 1 0 0 0 56
57 10762.3 0 0 0 0 0 0 0 0 0 1 0 0 57
58 11340.4 0 0 0 0 0 0 0 0 0 0 1 0 58
59 11266.8 0 0 0 0 0 0 0 0 0 0 0 1 59
60 9542.7 0 0 0 0 0 0 0 0 0 0 0 0 60
61 9227.7 0 1 0 0 0 0 0 0 0 0 0 0 61
62 10571.9 1 0 1 0 0 0 0 0 0 0 0 0 62
63 10774.4 1 0 0 1 0 0 0 0 0 0 0 0 63
64 10392.8 1 0 0 0 1 0 0 0 0 0 0 0 64
65 9920.2 1 0 0 0 0 1 0 0 0 0 0 0 65
66 9884.9 1 0 0 0 0 0 1 0 0 0 0 0 66
67 10174.5 1 0 0 0 0 0 0 1 0 0 0 0 67
68 11395.4 1 0 0 0 0 0 0 0 1 0 0 0 68
69 10760.2 1 0 0 0 0 0 0 0 0 1 0 0 69
70 10570.1 1 0 0 0 0 0 0 0 0 0 1 0 70
71 10536.0 1 0 0 0 0 0 0 0 0 0 0 1 71
72 9902.6 1 0 0 0 0 0 0 0 0 0 0 0 72
73 8889.0 1 1 0 0 0 0 0 0 0 0 0 0 73
74 10837.3 1 0 1 0 0 0 0 0 0 0 0 0 74
75 11624.1 1 0 0 1 0 0 0 0 0 0 0 0 75
76 10509.0 1 0 0 0 1 0 0 0 0 0 0 0 76
77 10984.9 1 0 0 0 0 1 0 0 0 0 0 0 77
78 10649.1 1 0 0 0 0 0 1 0 0 0 0 0 78
79 10855.7 1 0 0 0 0 0 0 1 0 0 0 0 79
80 11677.4 1 0 0 0 0 0 0 0 1 0 0 0 80
81 10760.2 1 0 0 0 0 0 0 0 0 1 0 0 81
82 10046.2 1 0 0 0 0 0 0 0 0 0 1 0 82
83 10772.8 1 0 0 0 0 0 0 0 0 0 0 1 83
84 9987.7 1 0 0 0 0 0 0 0 0 0 0 0 84
85 8638.7 1 1 0 0 0 0 0 0 0 0 0 0 85
86 11063.7 1 0 1 0 0 0 0 0 0 0 0 0 86
87 11855.7 1 0 0 1 0 0 0 0 0 0 0 0 87
88 10684.5 1 0 0 0 1 0 0 0 0 0 0 0 88
89 11337.4 1 0 0 0 0 1 0 0 0 0 0 0 89
90 10478.0 1 0 0 0 0 0 1 0 0 0 0 0 90
91 11123.9 1 0 0 0 0 0 0 1 0 0 0 0 91
92 12909.3 1 0 0 0 0 0 0 0 1 0 0 0 92
93 11339.9 1 0 0 0 0 0 0 0 0 1 0 0 93
94 10462.2 1 0 0 0 0 0 0 0 0 0 1 0 94
95 12733.5 1 0 0 0 0 0 0 0 0 0 0 1 95
96 10519.2 1 0 0 0 0 0 0 0 0 0 0 0 96
97 10414.9 1 1 0 0 0 0 0 0 0 0 0 0 97
98 12476.8 1 0 1 0 0 0 0 0 0 0 0 0 98
99 12384.6 1 0 0 1 0 0 0 0 0 0 0 0 99
100 12266.7 1 0 0 0 1 0 0 0 0 0 0 0 100
101 12919.9 1 0 0 0 0 1 0 0 0 0 0 0 101
102 11497.3 1 0 0 0 0 0 1 0 0 0 0 0 102
103 12142.0 1 0 0 0 0 0 0 1 0 0 0 0 103
104 13919.4 1 0 0 0 0 0 0 0 1 0 0 0 104
105 12656.8 1 0 0 0 0 0 0 0 0 1 0 0 105
106 12034.1 1 0 0 0 0 0 0 0 0 0 1 0 106
107 13199.7 1 0 0 0 0 0 0 0 0 0 0 1 107
108 10881.3 1 0 0 0 0 0 0 0 0 0 0 0 108
109 11301.2 1 1 0 0 0 0 0 0 0 0 0 0 109
110 13643.9 1 0 1 0 0 0 0 0 0 0 0 0 110
111 12517.0 1 0 0 1 0 0 0 0 0 0 0 0 111
112 13981.1 1 0 0 0 1 0 0 0 0 0 0 0 112
113 14275.7 1 0 0 0 0 1 0 0 0 0 0 0 113
114 13435.0 1 0 0 0 0 0 1 0 0 0 0 0 114
115 13565.7 1 0 0 0 0 0 0 1 0 0 0 0 115
116 16216.3 1 0 0 0 0 0 0 0 1 0 0 0 116
117 12970.0 1 0 0 0 0 0 0 0 0 1 0 0 117
118 14079.9 1 0 0 0 0 0 0 0 0 0 1 0 118
119 14235.0 1 0 0 0 0 0 0 0 0 0 0 1 119
120 12213.4 1 0 0 0 0 0 0 0 0 0 0 0 120
121 12581.0 1 1 0 0 0 0 0 0 0 0 0 0 121
> k <- length(x[1,])
> df <- as.data.frame(x)
> (mylm <- lm(df))
Call:
lm(formula = df)
Coefficients:
(Intercept) x M1 M2 M3 M4
5824.18 -1487.69 -269.97 1602.28 1631.77 1312.64
M5 M6 M7 M8 M9 M10
1504.68 764.66 1218.32 2462.32 1073.39 951.46
M11 t
1563.98 67.06
> (mysum <- summary(mylm))
Call:
lm(formula = df)
Residuals:
Min 1Q Median 3Q Max
-1148.87 -359.59 -8.94 357.73 1638.43
Coefficients:
Estimate Std. Error t value Pr(>|t|)
(Intercept) 5824.182 213.351 27.299 < 2e-16 ***
x -1487.685 207.085 -7.184 9.48e-11 ***
M1 -269.968 245.790 -1.098 0.274509
M2 1602.278 253.189 6.328 5.91e-09 ***
M3 1631.767 252.857 6.453 3.27e-09 ***
M4 1312.636 252.560 5.197 9.76e-07 ***
M5 1504.675 252.297 5.964 3.22e-08 ***
M6 764.665 252.069 3.034 0.003034 **
M7 1218.324 251.876 4.837 4.45e-06 ***
M8 2462.323 251.717 9.782 < 2e-16 ***
M9 1073.392 251.594 4.266 4.30e-05 ***
M10 951.462 251.507 3.783 0.000256 ***
M11 1563.981 251.454 6.220 9.84e-09 ***
t 67.061 2.974 22.546 < 2e-16 ***
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
Residual standard error: 562.2 on 107 degrees of freedom
Multiple R-squared: 0.9245, Adjusted R-squared: 0.9154
F-statistic: 100.8 on 13 and 107 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,] 8.520930e-02 1.704186e-01 0.9147907
[2,] 3.705839e-02 7.411679e-02 0.9629416
[3,] 1.206765e-02 2.413531e-02 0.9879323
[4,] 3.745821e-03 7.491642e-03 0.9962542
[5,] 2.687171e-03 5.374342e-03 0.9973128
[6,] 1.995951e-03 3.991902e-03 0.9980040
[7,] 6.859275e-04 1.371855e-03 0.9993141
[8,] 2.333583e-04 4.667166e-04 0.9997666
[9,] 7.157002e-05 1.431400e-04 0.9999284
[10,] 2.413496e-05 4.826993e-05 0.9999759
[11,] 5.178181e-05 1.035636e-04 0.9999482
[12,] 2.594253e-05 5.188506e-05 0.9999741
[13,] 4.904592e-05 9.809185e-05 0.9999510
[14,] 6.814089e-04 1.362818e-03 0.9993186
[15,] 2.638904e-03 5.277807e-03 0.9973611
[16,] 1.780589e-03 3.561179e-03 0.9982194
[17,] 3.938399e-03 7.876798e-03 0.9960616
[18,] 3.390381e-03 6.780761e-03 0.9966096
[19,] 1.867348e-03 3.734695e-03 0.9981327
[20,] 1.604988e-03 3.209975e-03 0.9983950
[21,] 1.174633e-03 2.349265e-03 0.9988254
[22,] 7.966435e-04 1.593287e-03 0.9992034
[23,] 5.334023e-04 1.066805e-03 0.9994666
[24,] 1.934775e-03 3.869551e-03 0.9980652
[25,] 6.784958e-03 1.356992e-02 0.9932150
[26,] 7.811695e-03 1.562339e-02 0.9921883
[27,] 4.231841e-02 8.463681e-02 0.9576816
[28,] 1.495209e-01 2.990419e-01 0.8504791
[29,] 1.328297e-01 2.656594e-01 0.8671703
[30,] 4.025126e-01 8.050251e-01 0.5974874
[31,] 3.586960e-01 7.173921e-01 0.6413040
[32,] 3.178917e-01 6.357834e-01 0.6821083
[33,] 3.491553e-01 6.983106e-01 0.6508447
[34,] 3.284100e-01 6.568201e-01 0.6715900
[35,] 3.012826e-01 6.025651e-01 0.6987174
[36,] 5.354883e-01 9.290235e-01 0.4645117
[37,] 5.136880e-01 9.726240e-01 0.4863120
[38,] 6.410893e-01 7.178213e-01 0.3589107
[39,] 6.294719e-01 7.410563e-01 0.3705281
[40,] 5.903094e-01 8.193812e-01 0.4096906
[41,] 5.339804e-01 9.320392e-01 0.4660196
[42,] 5.590502e-01 8.818996e-01 0.4409498
[43,] 5.010908e-01 9.978183e-01 0.4989092
[44,] 4.566784e-01 9.133568e-01 0.5433216
[45,] 4.286954e-01 8.573908e-01 0.5713046
[46,] 4.003355e-01 8.006710e-01 0.5996645
[47,] 3.879196e-01 7.758391e-01 0.6120804
[48,] 3.652199e-01 7.304399e-01 0.6347801
[49,] 3.412072e-01 6.824144e-01 0.6587928
[50,] 3.082795e-01 6.165591e-01 0.6917205
[51,] 2.758168e-01 5.516335e-01 0.7241832
[52,] 2.285333e-01 4.570666e-01 0.7714667
[53,] 2.627830e-01 5.255659e-01 0.7372170
[54,] 3.208453e-01 6.416905e-01 0.6791547
[55,] 2.823156e-01 5.646312e-01 0.7176844
[56,] 4.071365e-01 8.142731e-01 0.5928635
[57,] 4.114574e-01 8.229148e-01 0.5885426
[58,] 3.817095e-01 7.634190e-01 0.6182905
[59,] 5.487320e-01 9.025360e-01 0.4512680
[60,] 5.159129e-01 9.681741e-01 0.4840871
[61,] 4.641105e-01 9.282210e-01 0.5358895
[62,] 5.322628e-01 9.354744e-01 0.4677372
[63,] 5.641626e-01 8.716749e-01 0.4358374
[64,] 5.311101e-01 9.377798e-01 0.4688899
[65,] 5.450522e-01 9.098955e-01 0.4549478
[66,] 5.506118e-01 8.987763e-01 0.4493882
[67,] 5.234447e-01 9.531105e-01 0.4765553
[68,] 6.527255e-01 6.945490e-01 0.3472745
[69,] 6.825529e-01 6.348941e-01 0.3174471
[70,] 6.396407e-01 7.207185e-01 0.3603593
[71,] 7.730448e-01 4.539105e-01 0.2269552
[72,] 7.804941e-01 4.390117e-01 0.2195059
[73,] 7.503760e-01 4.992481e-01 0.2496240
[74,] 7.032773e-01 5.934454e-01 0.2967227
[75,] 6.395570e-01 7.208859e-01 0.3604430
[76,] 5.917832e-01 8.164335e-01 0.4082168
[77,] 5.245977e-01 9.508045e-01 0.4754023
[78,] 6.168873e-01 7.662253e-01 0.3831127
[79,] 6.451515e-01 7.096969e-01 0.3548485
[80,] 6.866701e-01 6.266598e-01 0.3133299
[81,] 6.348237e-01 7.303526e-01 0.3651763
[82,] 5.421662e-01 9.156675e-01 0.4578338
[83,] 7.395132e-01 5.209736e-01 0.2604868
[84,] 6.505881e-01 6.988239e-01 0.3494119
[85,] 5.419325e-01 9.161351e-01 0.4580675
[86,] 4.697705e-01 9.395411e-01 0.5302295
[87,] 3.312278e-01 6.624557e-01 0.6687722
[88,] 4.221286e-01 8.442573e-01 0.5778714
> postscript(file="/var/www/html/freestat/rcomp/tmp/1hczr1229348214.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$resid)
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/freestat/rcomp/tmp/2utjy1229348214.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> plot(mysum$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/freestat/rcomp/tmp/3f4qg1229348214.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> hist(mysum$resid, main='Residual Histogram', xlab='values of Residuals')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/freestat/rcomp/tmp/4g08y1229348214.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> densityplot(~mysum$resid,col='black',main='Residual Density Plot', xlab='values of Residuals')
> dev.off()
null device
1
> postscript(file="/var/www/html/freestat/rcomp/tmp/57g0y1229348214.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 = 121
Frequency = 1
1 2 3 4 5 6
719.225818 340.919139 533.969139 -223.360861 -69.760861 393.489139
7 8 9 10 11 12
364.769139 -359.590861 816.079139 332.449139 406.969139 643.289139
13 14 15 16 17 18
254.096558 62.289879 290.939879 -257.090121 225.409879 -8.940121
19 20 21 22 23 24
157.539879 -473.020121 251.349879 -299.880121 226.139879 432.059879
25 26 27 28 29 30
106.667297 -38.339382 -451.989382 -415.719382 -834.019382 -1148.869382
31 32 33 34 35 36
-1105.189382 -888.349382 -839.879382 -953.509382 -366.289382 -580.669382
37 38 39 40 41 42
-218.861964 -583.468642 -625.918642 -286.148642 -9.648642 -449.898642
43 44 45 46 47 48
497.781358 380.021358 -524.208642 1011.561358 -309.618642 177.901358
49 50 51 52 53 54
588.408776 155.002097 109.952097 1100.622097 297.822097 953.072097
55 56 57 58 59 60
510.052097 65.192097 42.262097 675.232097 -77.947903 -305.127903
61 62 63 64 65 66
-417.220485 475.357903 581.307903 451.777903 -279.922097 357.727903
67 68 69 70 71 72
126.607903 36.447903 723.117903 587.887903 -125.792097 737.727903
73 74 75 76 77 78
-72.964679 -63.971358 626.278642 -236.751358 -19.951358 317.198642
79 80 81 82 83 84
3.078642 -486.281358 -81.611358 -740.741358 -693.721358 18.098642
85 86 87 88 89 90
-1127.993939 -642.300618 53.149382 -865.980618 -472.180618 -658.630618
91 92 93 94 95 96
-533.450618 -59.110618 -306.640618 -1129.470618 462.249382 -255.130618
97 98 99 100 101 102
-156.523200 -33.929879 -222.679879 -88.509879 305.590121 -444.059879
103 104 105 106 107 108
-320.079879 146.260121 205.530121 -362.299879 123.720121 -697.759879
109 110 111 112 113 114
-74.952461 328.440861 -895.009139 821.160861 856.660861 688.910861
115 116 117 118 119 120
298.890861 1638.430861 -285.999139 878.770861 354.290861 -170.389139
121
400.118279
> postscript(file="/var/www/html/freestat/rcomp/tmp/64mo01229348214.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 = 121
Frequency = 1
lag(myerror, k = 1) myerror
0 719.225818 NA
1 340.919139 719.225818
2 533.969139 340.919139
3 -223.360861 533.969139
4 -69.760861 -223.360861
5 393.489139 -69.760861
6 364.769139 393.489139
7 -359.590861 364.769139
8 816.079139 -359.590861
9 332.449139 816.079139
10 406.969139 332.449139
11 643.289139 406.969139
12 254.096558 643.289139
13 62.289879 254.096558
14 290.939879 62.289879
15 -257.090121 290.939879
16 225.409879 -257.090121
17 -8.940121 225.409879
18 157.539879 -8.940121
19 -473.020121 157.539879
20 251.349879 -473.020121
21 -299.880121 251.349879
22 226.139879 -299.880121
23 432.059879 226.139879
24 106.667297 432.059879
25 -38.339382 106.667297
26 -451.989382 -38.339382
27 -415.719382 -451.989382
28 -834.019382 -415.719382
29 -1148.869382 -834.019382
30 -1105.189382 -1148.869382
31 -888.349382 -1105.189382
32 -839.879382 -888.349382
33 -953.509382 -839.879382
34 -366.289382 -953.509382
35 -580.669382 -366.289382
36 -218.861964 -580.669382
37 -583.468642 -218.861964
38 -625.918642 -583.468642
39 -286.148642 -625.918642
40 -9.648642 -286.148642
41 -449.898642 -9.648642
42 497.781358 -449.898642
43 380.021358 497.781358
44 -524.208642 380.021358
45 1011.561358 -524.208642
46 -309.618642 1011.561358
47 177.901358 -309.618642
48 588.408776 177.901358
49 155.002097 588.408776
50 109.952097 155.002097
51 1100.622097 109.952097
52 297.822097 1100.622097
53 953.072097 297.822097
54 510.052097 953.072097
55 65.192097 510.052097
56 42.262097 65.192097
57 675.232097 42.262097
58 -77.947903 675.232097
59 -305.127903 -77.947903
60 -417.220485 -305.127903
61 475.357903 -417.220485
62 581.307903 475.357903
63 451.777903 581.307903
64 -279.922097 451.777903
65 357.727903 -279.922097
66 126.607903 357.727903
67 36.447903 126.607903
68 723.117903 36.447903
69 587.887903 723.117903
70 -125.792097 587.887903
71 737.727903 -125.792097
72 -72.964679 737.727903
73 -63.971358 -72.964679
74 626.278642 -63.971358
75 -236.751358 626.278642
76 -19.951358 -236.751358
77 317.198642 -19.951358
78 3.078642 317.198642
79 -486.281358 3.078642
80 -81.611358 -486.281358
81 -740.741358 -81.611358
82 -693.721358 -740.741358
83 18.098642 -693.721358
84 -1127.993939 18.098642
85 -642.300618 -1127.993939
86 53.149382 -642.300618
87 -865.980618 53.149382
88 -472.180618 -865.980618
89 -658.630618 -472.180618
90 -533.450618 -658.630618
91 -59.110618 -533.450618
92 -306.640618 -59.110618
93 -1129.470618 -306.640618
94 462.249382 -1129.470618
95 -255.130618 462.249382
96 -156.523200 -255.130618
97 -33.929879 -156.523200
98 -222.679879 -33.929879
99 -88.509879 -222.679879
100 305.590121 -88.509879
101 -444.059879 305.590121
102 -320.079879 -444.059879
103 146.260121 -320.079879
104 205.530121 146.260121
105 -362.299879 205.530121
106 123.720121 -362.299879
107 -697.759879 123.720121
108 -74.952461 -697.759879
109 328.440861 -74.952461
110 -895.009139 328.440861
111 821.160861 -895.009139
112 856.660861 821.160861
113 688.910861 856.660861
114 298.890861 688.910861
115 1638.430861 298.890861
116 -285.999139 1638.430861
117 878.770861 -285.999139
118 354.290861 878.770861
119 -170.389139 354.290861
120 400.118279 -170.389139
121 NA 400.118279
> dum1 <- dum[2:length(myerror),]
> dum1
lag(myerror, k = 1) myerror
[1,] 340.919139 719.225818
[2,] 533.969139 340.919139
[3,] -223.360861 533.969139
[4,] -69.760861 -223.360861
[5,] 393.489139 -69.760861
[6,] 364.769139 393.489139
[7,] -359.590861 364.769139
[8,] 816.079139 -359.590861
[9,] 332.449139 816.079139
[10,] 406.969139 332.449139
[11,] 643.289139 406.969139
[12,] 254.096558 643.289139
[13,] 62.289879 254.096558
[14,] 290.939879 62.289879
[15,] -257.090121 290.939879
[16,] 225.409879 -257.090121
[17,] -8.940121 225.409879
[18,] 157.539879 -8.940121
[19,] -473.020121 157.539879
[20,] 251.349879 -473.020121
[21,] -299.880121 251.349879
[22,] 226.139879 -299.880121
[23,] 432.059879 226.139879
[24,] 106.667297 432.059879
[25,] -38.339382 106.667297
[26,] -451.989382 -38.339382
[27,] -415.719382 -451.989382
[28,] -834.019382 -415.719382
[29,] -1148.869382 -834.019382
[30,] -1105.189382 -1148.869382
[31,] -888.349382 -1105.189382
[32,] -839.879382 -888.349382
[33,] -953.509382 -839.879382
[34,] -366.289382 -953.509382
[35,] -580.669382 -366.289382
[36,] -218.861964 -580.669382
[37,] -583.468642 -218.861964
[38,] -625.918642 -583.468642
[39,] -286.148642 -625.918642
[40,] -9.648642 -286.148642
[41,] -449.898642 -9.648642
[42,] 497.781358 -449.898642
[43,] 380.021358 497.781358
[44,] -524.208642 380.021358
[45,] 1011.561358 -524.208642
[46,] -309.618642 1011.561358
[47,] 177.901358 -309.618642
[48,] 588.408776 177.901358
[49,] 155.002097 588.408776
[50,] 109.952097 155.002097
[51,] 1100.622097 109.952097
[52,] 297.822097 1100.622097
[53,] 953.072097 297.822097
[54,] 510.052097 953.072097
[55,] 65.192097 510.052097
[56,] 42.262097 65.192097
[57,] 675.232097 42.262097
[58,] -77.947903 675.232097
[59,] -305.127903 -77.947903
[60,] -417.220485 -305.127903
[61,] 475.357903 -417.220485
[62,] 581.307903 475.357903
[63,] 451.777903 581.307903
[64,] -279.922097 451.777903
[65,] 357.727903 -279.922097
[66,] 126.607903 357.727903
[67,] 36.447903 126.607903
[68,] 723.117903 36.447903
[69,] 587.887903 723.117903
[70,] -125.792097 587.887903
[71,] 737.727903 -125.792097
[72,] -72.964679 737.727903
[73,] -63.971358 -72.964679
[74,] 626.278642 -63.971358
[75,] -236.751358 626.278642
[76,] -19.951358 -236.751358
[77,] 317.198642 -19.951358
[78,] 3.078642 317.198642
[79,] -486.281358 3.078642
[80,] -81.611358 -486.281358
[81,] -740.741358 -81.611358
[82,] -693.721358 -740.741358
[83,] 18.098642 -693.721358
[84,] -1127.993939 18.098642
[85,] -642.300618 -1127.993939
[86,] 53.149382 -642.300618
[87,] -865.980618 53.149382
[88,] -472.180618 -865.980618
[89,] -658.630618 -472.180618
[90,] -533.450618 -658.630618
[91,] -59.110618 -533.450618
[92,] -306.640618 -59.110618
[93,] -1129.470618 -306.640618
[94,] 462.249382 -1129.470618
[95,] -255.130618 462.249382
[96,] -156.523200 -255.130618
[97,] -33.929879 -156.523200
[98,] -222.679879 -33.929879
[99,] -88.509879 -222.679879
[100,] 305.590121 -88.509879
[101,] -444.059879 305.590121
[102,] -320.079879 -444.059879
[103,] 146.260121 -320.079879
[104,] 205.530121 146.260121
[105,] -362.299879 205.530121
[106,] 123.720121 -362.299879
[107,] -697.759879 123.720121
[108,] -74.952461 -697.759879
[109,] 328.440861 -74.952461
[110,] -895.009139 328.440861
[111,] 821.160861 -895.009139
[112,] 856.660861 821.160861
[113,] 688.910861 856.660861
[114,] 298.890861 688.910861
[115,] 1638.430861 298.890861
[116,] -285.999139 1638.430861
[117,] 878.770861 -285.999139
[118,] 354.290861 878.770861
[119,] -170.389139 354.290861
[120,] 400.118279 -170.389139
> z <- as.data.frame(dum1)
> z
lag(myerror, k = 1) myerror
1 340.919139 719.225818
2 533.969139 340.919139
3 -223.360861 533.969139
4 -69.760861 -223.360861
5 393.489139 -69.760861
6 364.769139 393.489139
7 -359.590861 364.769139
8 816.079139 -359.590861
9 332.449139 816.079139
10 406.969139 332.449139
11 643.289139 406.969139
12 254.096558 643.289139
13 62.289879 254.096558
14 290.939879 62.289879
15 -257.090121 290.939879
16 225.409879 -257.090121
17 -8.940121 225.409879
18 157.539879 -8.940121
19 -473.020121 157.539879
20 251.349879 -473.020121
21 -299.880121 251.349879
22 226.139879 -299.880121
23 432.059879 226.139879
24 106.667297 432.059879
25 -38.339382 106.667297
26 -451.989382 -38.339382
27 -415.719382 -451.989382
28 -834.019382 -415.719382
29 -1148.869382 -834.019382
30 -1105.189382 -1148.869382
31 -888.349382 -1105.189382
32 -839.879382 -888.349382
33 -953.509382 -839.879382
34 -366.289382 -953.509382
35 -580.669382 -366.289382
36 -218.861964 -580.669382
37 -583.468642 -218.861964
38 -625.918642 -583.468642
39 -286.148642 -625.918642
40 -9.648642 -286.148642
41 -449.898642 -9.648642
42 497.781358 -449.898642
43 380.021358 497.781358
44 -524.208642 380.021358
45 1011.561358 -524.208642
46 -309.618642 1011.561358
47 177.901358 -309.618642
48 588.408776 177.901358
49 155.002097 588.408776
50 109.952097 155.002097
51 1100.622097 109.952097
52 297.822097 1100.622097
53 953.072097 297.822097
54 510.052097 953.072097
55 65.192097 510.052097
56 42.262097 65.192097
57 675.232097 42.262097
58 -77.947903 675.232097
59 -305.127903 -77.947903
60 -417.220485 -305.127903
61 475.357903 -417.220485
62 581.307903 475.357903
63 451.777903 581.307903
64 -279.922097 451.777903
65 357.727903 -279.922097
66 126.607903 357.727903
67 36.447903 126.607903
68 723.117903 36.447903
69 587.887903 723.117903
70 -125.792097 587.887903
71 737.727903 -125.792097
72 -72.964679 737.727903
73 -63.971358 -72.964679
74 626.278642 -63.971358
75 -236.751358 626.278642
76 -19.951358 -236.751358
77 317.198642 -19.951358
78 3.078642 317.198642
79 -486.281358 3.078642
80 -81.611358 -486.281358
81 -740.741358 -81.611358
82 -693.721358 -740.741358
83 18.098642 -693.721358
84 -1127.993939 18.098642
85 -642.300618 -1127.993939
86 53.149382 -642.300618
87 -865.980618 53.149382
88 -472.180618 -865.980618
89 -658.630618 -472.180618
90 -533.450618 -658.630618
91 -59.110618 -533.450618
92 -306.640618 -59.110618
93 -1129.470618 -306.640618
94 462.249382 -1129.470618
95 -255.130618 462.249382
96 -156.523200 -255.130618
97 -33.929879 -156.523200
98 -222.679879 -33.929879
99 -88.509879 -222.679879
100 305.590121 -88.509879
101 -444.059879 305.590121
102 -320.079879 -444.059879
103 146.260121 -320.079879
104 205.530121 146.260121
105 -362.299879 205.530121
106 123.720121 -362.299879
107 -697.759879 123.720121
108 -74.952461 -697.759879
109 328.440861 -74.952461
110 -895.009139 328.440861
111 821.160861 -895.009139
112 856.660861 821.160861
113 688.910861 856.660861
114 298.890861 688.910861
115 1638.430861 298.890861
116 -285.999139 1638.430861
117 878.770861 -285.999139
118 354.290861 878.770861
119 -170.389139 354.290861
120 400.118279 -170.389139
> 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/freestat/rcomp/tmp/7get61229348214.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> acf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/freestat/rcomp/tmp/8fs321229348214.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> pacf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Partial Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/freestat/rcomp/tmp/92ury1229348214.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> opar <- par(mfrow = c(2,2), oma = c(0, 0, 1.1, 0))
> plot(mylm, las = 1, sub='Residual Diagnostics')
> par(opar)
> dev.off()
null device
1
> if (n > n25) {
+ postscript(file="/var/www/html/freestat/rcomp/tmp/10mgp91229348214.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
+ plot(kp3:nmkm3,gqarr[,2], main='Goldfeld-Quandt test',ylab='2-sided p-value',xlab='breakpoint')
+ grid()
+ dev.off()
+ }
null device
1
>
> #Note: the /var/www/html/freestat/rcomp/createtable file can be downloaded at http://www.wessa.net/cretab
> load(file="/var/www/html/freestat/rcomp/createtable")
>
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a, 'Multiple Linear Regression - Estimated Regression Equation', 1, TRUE)
> a<-table.row.end(a)
> myeq <- colnames(x)[1]
> myeq <- paste(myeq, '[t] = ', sep='')
> for (i in 1:k){
+ if (mysum$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/freestat/rcomp/tmp/11u8k71229348214.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/freestat/rcomp/tmp/12y12b1229348214.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/freestat/rcomp/tmp/130zzg1229348214.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/freestat/rcomp/tmp/145jnf1229348215.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/freestat/rcomp/tmp/150ic81229348215.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/freestat/rcomp/tmp/162bmf1229348215.tab")
+ }
>
> system("convert tmp/1hczr1229348214.ps tmp/1hczr1229348214.png")
> system("convert tmp/2utjy1229348214.ps tmp/2utjy1229348214.png")
> system("convert tmp/3f4qg1229348214.ps tmp/3f4qg1229348214.png")
> system("convert tmp/4g08y1229348214.ps tmp/4g08y1229348214.png")
> system("convert tmp/57g0y1229348214.ps tmp/57g0y1229348214.png")
> system("convert tmp/64mo01229348214.ps tmp/64mo01229348214.png")
> system("convert tmp/7get61229348214.ps tmp/7get61229348214.png")
> system("convert tmp/8fs321229348214.ps tmp/8fs321229348214.png")
> system("convert tmp/92ury1229348214.ps tmp/92ury1229348214.png")
> system("convert tmp/10mgp91229348214.ps tmp/10mgp91229348214.png")
>
>
> proc.time()
user system elapsed
4.705 2.627 5.091