R version 2.15.2 (2012-10-26) -- "Trick or Treat"
Copyright (C) 2012 The R Foundation for Statistical Computing
ISBN 3-900051-07-0
Platform: i686-pc-linux-gnu (32-bit)
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(4
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+ ,2
+ ,1)
+ ,dim=c(3
+ ,154)
+ ,dimnames=list(c('Weeks'
+ ,'Limit'
+ ,'Usefull')
+ ,1:154))
> y <- array(NA,dim=c(3,154),dimnames=list(c('Weeks','Limit','Usefull'),1:154))
> for (i in 1:dim(x)[1])
+ {
+ for (j in 1:dim(x)[2])
+ {
+ y[i,j] <- as.numeric(x[i,j])
+ }
+ }
> par3 = 'No Linear Trend'
> par2 = 'Do not include Seasonal Dummies'
> par1 = '1'
> par3 <- 'No Linear Trend'
> par2 <- 'Do not include Seasonal 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, 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
Weeks Limit Usefull
1 4 2 1
2 4 1 1
3 4 1 1
4 4 1 1
5 4 1 1
6 4 2 2
7 4 1 1
8 4 1 1
9 4 1 1
10 4 2 1
11 4 2 1
12 4 1 1
13 4 1 2
14 4 2 1
15 4 1 2
16 4 1 2
17 4 2 2
18 4 2 1
19 4 1 1
20 4 1 2
21 4 2 2
22 4 2 2
23 4 1 2
24 4 2 2
25 4 1 1
26 4 1 2
27 4 2 1
28 4 1 1
29 4 1 1
30 4 1 2
31 4 1 1
32 4 2 1
33 4 2 2
34 4 1 1
35 4 1 1
36 4 1 1
37 4 2 2
38 4 1 1
39 4 1 2
40 4 1 2
41 4 1 2
42 4 1 1
43 4 2 2
44 4 2 1
45 4 1 2
46 4 1 2
47 4 1 1
48 4 1 1
49 4 1 2
50 4 1 1
51 4 1 1
52 4 2 2
53 4 1 1
54 4 1 1
55 4 1 1
56 4 1 1
57 4 1 2
58 4 1 1
59 4 1 1
60 4 2 2
61 4 2 1
62 4 1 2
63 4 1 1
64 4 2 1
65 4 1 1
66 4 1 1
67 4 1 2
68 4 2 1
69 4 1 1
70 4 1 1
71 4 1 1
72 4 1 1
73 4 1 1
74 4 2 1
75 4 1 1
76 4 1 2
77 4 1 1
78 4 1 2
79 4 1 1
80 4 1 2
81 4 1 1
82 4 2 1
83 4 1 1
84 4 1 1
85 4 1 2
86 4 2 1
87 2 2 1
88 2 2 1
89 2 1 1
90 2 1 1
91 2 1 2
92 2 2 1
93 2 2 2
94 2 1 1
95 2 1 1
96 2 1 1
97 2 2 1
98 2 1 1
99 2 2 1
100 2 1 1
101 2 2 1
102 2 1 1
103 2 1 1
104 2 1 1
105 2 1 1
106 2 1 1
107 2 1 1
108 2 2 1
109 2 1 1
110 2 2 1
111 2 2 2
112 2 1 1
113 2 1 1
114 2 2 1
115 2 2 1
116 2 1 1
117 2 2 1
118 2 2 1
119 2 1 1
120 2 1 1
121 2 2 1
122 2 1 1
123 2 2 1
124 2 1 2
125 2 1 1
126 2 1 1
127 2 1 2
128 2 1 1
129 2 1 1
130 2 1 1
131 2 2 1
132 2 2 1
133 2 2 1
134 2 1 1
135 2 1 1
136 2 1 1
137 2 2 2
138 2 2 2
139 2 1 1
140 2 1 1
141 2 1 1
142 2 1 1
143 2 2 1
144 2 1 2
145 2 1 2
146 2 1 1
147 2 1 1
148 2 1 1
149 2 2 1
150 2 1 2
151 2 1 1
152 2 2 1
153 2 2 2
154 2 2 1
> k <- length(x[1,])
> df <- as.data.frame(x)
> (mylm <- lm(df))
Call:
lm(formula = df)
Coefficients:
(Intercept) Limit Usefull
2.8406 -0.2566 0.4867
> (mysum <- summary(mylm))
Call:
lm(formula = df)
Residuals:
Min 1Q Median 3Q Max
-1.5573 -1.0706 0.4427 0.9294 1.1860
Coefficients:
Estimate Std. Error t value Pr(>|t|)
(Intercept) 2.8406 0.3175 8.947 1.23e-15 ***
Limit -0.2566 0.1677 -1.530 0.1280
Usefull 0.4867 0.1777 2.739 0.0069 **
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
Residual standard error: 0.973 on 151 degrees of freedom
Multiple R-squared: 0.05877, Adjusted R-squared: 0.04631
F-statistic: 4.715 on 2 and 151 DF, p-value: 0.01032
> 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,] 3.422243e-95 6.844486e-95 1.000000e+00
[2,] 6.507383e-125 1.301477e-124 1.000000e+00
[3,] 3.601170e-154 7.202341e-154 1.000000e+00
[4,] 5.268825e-192 1.053765e-191 1.000000e+00
[5,] 6.815000e-110 1.363000e-109 1.000000e+00
[6,] 6.252539e-131 1.250508e-130 1.000000e+00
[7,] 1.454496e-137 2.908991e-137 1.000000e+00
[8,] 2.259184e-173 4.518368e-173 1.000000e+00
[9,] 2.080828e-166 4.161657e-166 1.000000e+00
[10,] 1.152937e-181 2.305875e-181 1.000000e+00
[11,] 0.000000e+00 0.000000e+00 1.000000e+00
[12,] 3.688828e-228 7.377656e-228 1.000000e+00
[13,] 5.240837e-229 1.048167e-228 1.000000e+00
[14,] 1.339414e-242 2.678829e-242 1.000000e+00
[15,] 2.830617e-270 5.661235e-270 1.000000e+00
[16,] 4.222919e-309 8.445837e-309 1.000000e+00
[17,] 5.403635e-292 1.080727e-291 1.000000e+00
[18,] 2.713969e-302 5.427939e-302 1.000000e+00
[19,] 2.485150e-321 4.970300e-321 1.000000e+00
[20,] 0.000000e+00 0.000000e+00 1.000000e+00
[21,] 0.000000e+00 0.000000e+00 1.000000e+00
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[80,] 0.000000e+00 0.000000e+00 1.000000e+00
[81,] 1.000000e+00 5.927687e-20 2.963843e-20
[82,] 1.000000e+00 0.000000e+00 0.000000e+00
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[125,] 1.000000e+00 0.000000e+00 0.000000e+00
[126,] 1.000000e+00 1.827648e-307 9.138238e-308
[127,] 1.000000e+00 5.235328e-297 2.617664e-297
[128,] 1.000000e+00 1.739584e-313 8.697920e-314
[129,] 1.000000e+00 1.994676e-274 9.973378e-275
[130,] 1.000000e+00 1.501113e-246 7.505564e-247
[131,] 1.000000e+00 3.367367e-233 1.683683e-233
[132,] 1.000000e+00 3.211868e-232 1.605934e-232
[133,] 1.000000e+00 0.000000e+00 0.000000e+00
[134,] 1.000000e+00 1.454064e-184 7.270319e-185
[135,] 1.000000e+00 4.256583e-169 2.128291e-169
[136,] 1.000000e+00 1.149971e-175 5.749854e-176
[137,] 1.000000e+00 1.400438e-139 7.002191e-140
[138,] 1.000000e+00 8.007022e-133 4.003511e-133
[139,] 1.000000e+00 2.511797e-111 1.255898e-111
[140,] 1.000000e+00 3.455327e-95 1.727663e-95
[141,] 1.000000e+00 1.532580e-77 7.662899e-78
[142,] 1.000000e+00 1.435939e-62 7.179695e-63
[143,] 1.000000e+00 2.635337e-47 1.317669e-47
> postscript(file="/var/fisher/rcomp/tmp/1oui81356102862.ps",horizontal=F,onefile=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$resid)
> grid()
> dev.off()
null device
1
> postscript(file="/var/fisher/rcomp/tmp/2hbwe1356102862.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> plot(mysum$resid, type='b', pch=19, main='Residuals', ylab='value of Residuals', xlab='time or index')
> grid()
> dev.off()
null device
1
> postscript(file="/var/fisher/rcomp/tmp/3lldo1356102862.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> hist(mysum$resid, main='Residual Histogram', xlab='values of Residuals')
> grid()
> dev.off()
null device
1
> postscript(file="/var/fisher/rcomp/tmp/4i6ac1356102862.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> densityplot(~mysum$resid,col='black',main='Residual Density Plot', xlab='values of Residuals')
> dev.off()
null device
1
> postscript(file="/var/fisher/rcomp/tmp/5v6lf1356102862.ps",horizontal=F,onefile=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 = 154
Frequency = 1
1 2 3 4 5 6 7
1.1860000 0.9293590 0.9293590 0.9293590 0.9293590 0.6993333 0.9293590
8 9 10 11 12 13 14
0.9293590 0.9293590 1.1860000 1.1860000 0.9293590 0.4426923 1.1860000
15 16 17 18 19 20 21
0.4426923 0.4426923 0.6993333 1.1860000 0.9293590 0.4426923 0.6993333
22 23 24 25 26 27 28
0.6993333 0.4426923 0.6993333 0.9293590 0.4426923 1.1860000 0.9293590
29 30 31 32 33 34 35
0.9293590 0.4426923 0.9293590 1.1860000 0.6993333 0.9293590 0.9293590
36 37 38 39 40 41 42
0.9293590 0.6993333 0.9293590 0.4426923 0.4426923 0.4426923 0.9293590
43 44 45 46 47 48 49
0.6993333 1.1860000 0.4426923 0.4426923 0.9293590 0.9293590 0.4426923
50 51 52 53 54 55 56
0.9293590 0.9293590 0.6993333 0.9293590 0.9293590 0.9293590 0.9293590
57 58 59 60 61 62 63
0.4426923 0.9293590 0.9293590 0.6993333 1.1860000 0.4426923 0.9293590
64 65 66 67 68 69 70
1.1860000 0.9293590 0.9293590 0.4426923 1.1860000 0.9293590 0.9293590
71 72 73 74 75 76 77
0.9293590 0.9293590 0.9293590 1.1860000 0.9293590 0.4426923 0.9293590
78 79 80 81 82 83 84
0.4426923 0.9293590 0.4426923 0.9293590 1.1860000 0.9293590 0.9293590
85 86 87 88 89 90 91
0.4426923 1.1860000 -0.8140000 -0.8140000 -1.0706410 -1.0706410 -1.5573077
92 93 94 95 96 97 98
-0.8140000 -1.3006667 -1.0706410 -1.0706410 -1.0706410 -0.8140000 -1.0706410
99 100 101 102 103 104 105
-0.8140000 -1.0706410 -0.8140000 -1.0706410 -1.0706410 -1.0706410 -1.0706410
106 107 108 109 110 111 112
-1.0706410 -1.0706410 -0.8140000 -1.0706410 -0.8140000 -1.3006667 -1.0706410
113 114 115 116 117 118 119
-1.0706410 -0.8140000 -0.8140000 -1.0706410 -0.8140000 -0.8140000 -1.0706410
120 121 122 123 124 125 126
-1.0706410 -0.8140000 -1.0706410 -0.8140000 -1.5573077 -1.0706410 -1.0706410
127 128 129 130 131 132 133
-1.5573077 -1.0706410 -1.0706410 -1.0706410 -0.8140000 -0.8140000 -0.8140000
134 135 136 137 138 139 140
-1.0706410 -1.0706410 -1.0706410 -1.3006667 -1.3006667 -1.0706410 -1.0706410
141 142 143 144 145 146 147
-1.0706410 -1.0706410 -0.8140000 -1.5573077 -1.5573077 -1.0706410 -1.0706410
148 149 150 151 152 153 154
-1.0706410 -0.8140000 -1.5573077 -1.0706410 -0.8140000 -1.3006667 -0.8140000
> postscript(file="/var/fisher/rcomp/tmp/67zd11356102863.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> dum <- cbind(lag(myerror,k=1),myerror)
> dum
Time Series:
Start = 0
End = 154
Frequency = 1
lag(myerror, k = 1) myerror
0 1.1860000 NA
1 0.9293590 1.1860000
2 0.9293590 0.9293590
3 0.9293590 0.9293590
4 0.9293590 0.9293590
5 0.6993333 0.9293590
6 0.9293590 0.6993333
7 0.9293590 0.9293590
8 0.9293590 0.9293590
9 1.1860000 0.9293590
10 1.1860000 1.1860000
11 0.9293590 1.1860000
12 0.4426923 0.9293590
13 1.1860000 0.4426923
14 0.4426923 1.1860000
15 0.4426923 0.4426923
16 0.6993333 0.4426923
17 1.1860000 0.6993333
18 0.9293590 1.1860000
19 0.4426923 0.9293590
20 0.6993333 0.4426923
21 0.6993333 0.6993333
22 0.4426923 0.6993333
23 0.6993333 0.4426923
24 0.9293590 0.6993333
25 0.4426923 0.9293590
26 1.1860000 0.4426923
27 0.9293590 1.1860000
28 0.9293590 0.9293590
29 0.4426923 0.9293590
30 0.9293590 0.4426923
31 1.1860000 0.9293590
32 0.6993333 1.1860000
33 0.9293590 0.6993333
34 0.9293590 0.9293590
35 0.9293590 0.9293590
36 0.6993333 0.9293590
37 0.9293590 0.6993333
38 0.4426923 0.9293590
39 0.4426923 0.4426923
40 0.4426923 0.4426923
41 0.9293590 0.4426923
42 0.6993333 0.9293590
43 1.1860000 0.6993333
44 0.4426923 1.1860000
45 0.4426923 0.4426923
46 0.9293590 0.4426923
47 0.9293590 0.9293590
48 0.4426923 0.9293590
49 0.9293590 0.4426923
50 0.9293590 0.9293590
51 0.6993333 0.9293590
52 0.9293590 0.6993333
53 0.9293590 0.9293590
54 0.9293590 0.9293590
55 0.9293590 0.9293590
56 0.4426923 0.9293590
57 0.9293590 0.4426923
58 0.9293590 0.9293590
59 0.6993333 0.9293590
60 1.1860000 0.6993333
61 0.4426923 1.1860000
62 0.9293590 0.4426923
63 1.1860000 0.9293590
64 0.9293590 1.1860000
65 0.9293590 0.9293590
66 0.4426923 0.9293590
67 1.1860000 0.4426923
68 0.9293590 1.1860000
69 0.9293590 0.9293590
70 0.9293590 0.9293590
71 0.9293590 0.9293590
72 0.9293590 0.9293590
73 1.1860000 0.9293590
74 0.9293590 1.1860000
75 0.4426923 0.9293590
76 0.9293590 0.4426923
77 0.4426923 0.9293590
78 0.9293590 0.4426923
79 0.4426923 0.9293590
80 0.9293590 0.4426923
81 1.1860000 0.9293590
82 0.9293590 1.1860000
83 0.9293590 0.9293590
84 0.4426923 0.9293590
85 1.1860000 0.4426923
86 -0.8140000 1.1860000
87 -0.8140000 -0.8140000
88 -1.0706410 -0.8140000
89 -1.0706410 -1.0706410
90 -1.5573077 -1.0706410
91 -0.8140000 -1.5573077
92 -1.3006667 -0.8140000
93 -1.0706410 -1.3006667
94 -1.0706410 -1.0706410
95 -1.0706410 -1.0706410
96 -0.8140000 -1.0706410
97 -1.0706410 -0.8140000
98 -0.8140000 -1.0706410
99 -1.0706410 -0.8140000
100 -0.8140000 -1.0706410
101 -1.0706410 -0.8140000
102 -1.0706410 -1.0706410
103 -1.0706410 -1.0706410
104 -1.0706410 -1.0706410
105 -1.0706410 -1.0706410
106 -1.0706410 -1.0706410
107 -0.8140000 -1.0706410
108 -1.0706410 -0.8140000
109 -0.8140000 -1.0706410
110 -1.3006667 -0.8140000
111 -1.0706410 -1.3006667
112 -1.0706410 -1.0706410
113 -0.8140000 -1.0706410
114 -0.8140000 -0.8140000
115 -1.0706410 -0.8140000
116 -0.8140000 -1.0706410
117 -0.8140000 -0.8140000
118 -1.0706410 -0.8140000
119 -1.0706410 -1.0706410
120 -0.8140000 -1.0706410
121 -1.0706410 -0.8140000
122 -0.8140000 -1.0706410
123 -1.5573077 -0.8140000
124 -1.0706410 -1.5573077
125 -1.0706410 -1.0706410
126 -1.5573077 -1.0706410
127 -1.0706410 -1.5573077
128 -1.0706410 -1.0706410
129 -1.0706410 -1.0706410
130 -0.8140000 -1.0706410
131 -0.8140000 -0.8140000
132 -0.8140000 -0.8140000
133 -1.0706410 -0.8140000
134 -1.0706410 -1.0706410
135 -1.0706410 -1.0706410
136 -1.3006667 -1.0706410
137 -1.3006667 -1.3006667
138 -1.0706410 -1.3006667
139 -1.0706410 -1.0706410
140 -1.0706410 -1.0706410
141 -1.0706410 -1.0706410
142 -0.8140000 -1.0706410
143 -1.5573077 -0.8140000
144 -1.5573077 -1.5573077
145 -1.0706410 -1.5573077
146 -1.0706410 -1.0706410
147 -1.0706410 -1.0706410
148 -0.8140000 -1.0706410
149 -1.5573077 -0.8140000
150 -1.0706410 -1.5573077
151 -0.8140000 -1.0706410
152 -1.3006667 -0.8140000
153 -0.8140000 -1.3006667
154 NA -0.8140000
> dum1 <- dum[2:length(myerror),]
> dum1
lag(myerror, k = 1) myerror
[1,] 0.9293590 1.1860000
[2,] 0.9293590 0.9293590
[3,] 0.9293590 0.9293590
[4,] 0.9293590 0.9293590
[5,] 0.6993333 0.9293590
[6,] 0.9293590 0.6993333
[7,] 0.9293590 0.9293590
[8,] 0.9293590 0.9293590
[9,] 1.1860000 0.9293590
[10,] 1.1860000 1.1860000
[11,] 0.9293590 1.1860000
[12,] 0.4426923 0.9293590
[13,] 1.1860000 0.4426923
[14,] 0.4426923 1.1860000
[15,] 0.4426923 0.4426923
[16,] 0.6993333 0.4426923
[17,] 1.1860000 0.6993333
[18,] 0.9293590 1.1860000
[19,] 0.4426923 0.9293590
[20,] 0.6993333 0.4426923
[21,] 0.6993333 0.6993333
[22,] 0.4426923 0.6993333
[23,] 0.6993333 0.4426923
[24,] 0.9293590 0.6993333
[25,] 0.4426923 0.9293590
[26,] 1.1860000 0.4426923
[27,] 0.9293590 1.1860000
[28,] 0.9293590 0.9293590
[29,] 0.4426923 0.9293590
[30,] 0.9293590 0.4426923
[31,] 1.1860000 0.9293590
[32,] 0.6993333 1.1860000
[33,] 0.9293590 0.6993333
[34,] 0.9293590 0.9293590
[35,] 0.9293590 0.9293590
[36,] 0.6993333 0.9293590
[37,] 0.9293590 0.6993333
[38,] 0.4426923 0.9293590
[39,] 0.4426923 0.4426923
[40,] 0.4426923 0.4426923
[41,] 0.9293590 0.4426923
[42,] 0.6993333 0.9293590
[43,] 1.1860000 0.6993333
[44,] 0.4426923 1.1860000
[45,] 0.4426923 0.4426923
[46,] 0.9293590 0.4426923
[47,] 0.9293590 0.9293590
[48,] 0.4426923 0.9293590
[49,] 0.9293590 0.4426923
[50,] 0.9293590 0.9293590
[51,] 0.6993333 0.9293590
[52,] 0.9293590 0.6993333
[53,] 0.9293590 0.9293590
[54,] 0.9293590 0.9293590
[55,] 0.9293590 0.9293590
[56,] 0.4426923 0.9293590
[57,] 0.9293590 0.4426923
[58,] 0.9293590 0.9293590
[59,] 0.6993333 0.9293590
[60,] 1.1860000 0.6993333
[61,] 0.4426923 1.1860000
[62,] 0.9293590 0.4426923
[63,] 1.1860000 0.9293590
[64,] 0.9293590 1.1860000
[65,] 0.9293590 0.9293590
[66,] 0.4426923 0.9293590
[67,] 1.1860000 0.4426923
[68,] 0.9293590 1.1860000
[69,] 0.9293590 0.9293590
[70,] 0.9293590 0.9293590
[71,] 0.9293590 0.9293590
[72,] 0.9293590 0.9293590
[73,] 1.1860000 0.9293590
[74,] 0.9293590 1.1860000
[75,] 0.4426923 0.9293590
[76,] 0.9293590 0.4426923
[77,] 0.4426923 0.9293590
[78,] 0.9293590 0.4426923
[79,] 0.4426923 0.9293590
[80,] 0.9293590 0.4426923
[81,] 1.1860000 0.9293590
[82,] 0.9293590 1.1860000
[83,] 0.9293590 0.9293590
[84,] 0.4426923 0.9293590
[85,] 1.1860000 0.4426923
[86,] -0.8140000 1.1860000
[87,] -0.8140000 -0.8140000
[88,] -1.0706410 -0.8140000
[89,] -1.0706410 -1.0706410
[90,] -1.5573077 -1.0706410
[91,] -0.8140000 -1.5573077
[92,] -1.3006667 -0.8140000
[93,] -1.0706410 -1.3006667
[94,] -1.0706410 -1.0706410
[95,] -1.0706410 -1.0706410
[96,] -0.8140000 -1.0706410
[97,] -1.0706410 -0.8140000
[98,] -0.8140000 -1.0706410
[99,] -1.0706410 -0.8140000
[100,] -0.8140000 -1.0706410
[101,] -1.0706410 -0.8140000
[102,] -1.0706410 -1.0706410
[103,] -1.0706410 -1.0706410
[104,] -1.0706410 -1.0706410
[105,] -1.0706410 -1.0706410
[106,] -1.0706410 -1.0706410
[107,] -0.8140000 -1.0706410
[108,] -1.0706410 -0.8140000
[109,] -0.8140000 -1.0706410
[110,] -1.3006667 -0.8140000
[111,] -1.0706410 -1.3006667
[112,] -1.0706410 -1.0706410
[113,] -0.8140000 -1.0706410
[114,] -0.8140000 -0.8140000
[115,] -1.0706410 -0.8140000
[116,] -0.8140000 -1.0706410
[117,] -0.8140000 -0.8140000
[118,] -1.0706410 -0.8140000
[119,] -1.0706410 -1.0706410
[120,] -0.8140000 -1.0706410
[121,] -1.0706410 -0.8140000
[122,] -0.8140000 -1.0706410
[123,] -1.5573077 -0.8140000
[124,] -1.0706410 -1.5573077
[125,] -1.0706410 -1.0706410
[126,] -1.5573077 -1.0706410
[127,] -1.0706410 -1.5573077
[128,] -1.0706410 -1.0706410
[129,] -1.0706410 -1.0706410
[130,] -0.8140000 -1.0706410
[131,] -0.8140000 -0.8140000
[132,] -0.8140000 -0.8140000
[133,] -1.0706410 -0.8140000
[134,] -1.0706410 -1.0706410
[135,] -1.0706410 -1.0706410
[136,] -1.3006667 -1.0706410
[137,] -1.3006667 -1.3006667
[138,] -1.0706410 -1.3006667
[139,] -1.0706410 -1.0706410
[140,] -1.0706410 -1.0706410
[141,] -1.0706410 -1.0706410
[142,] -0.8140000 -1.0706410
[143,] -1.5573077 -0.8140000
[144,] -1.5573077 -1.5573077
[145,] -1.0706410 -1.5573077
[146,] -1.0706410 -1.0706410
[147,] -1.0706410 -1.0706410
[148,] -0.8140000 -1.0706410
[149,] -1.5573077 -0.8140000
[150,] -1.0706410 -1.5573077
[151,] -0.8140000 -1.0706410
[152,] -1.3006667 -0.8140000
[153,] -0.8140000 -1.3006667
> z <- as.data.frame(dum1)
> z
lag(myerror, k = 1) myerror
1 0.9293590 1.1860000
2 0.9293590 0.9293590
3 0.9293590 0.9293590
4 0.9293590 0.9293590
5 0.6993333 0.9293590
6 0.9293590 0.6993333
7 0.9293590 0.9293590
8 0.9293590 0.9293590
9 1.1860000 0.9293590
10 1.1860000 1.1860000
11 0.9293590 1.1860000
12 0.4426923 0.9293590
13 1.1860000 0.4426923
14 0.4426923 1.1860000
15 0.4426923 0.4426923
16 0.6993333 0.4426923
17 1.1860000 0.6993333
18 0.9293590 1.1860000
19 0.4426923 0.9293590
20 0.6993333 0.4426923
21 0.6993333 0.6993333
22 0.4426923 0.6993333
23 0.6993333 0.4426923
24 0.9293590 0.6993333
25 0.4426923 0.9293590
26 1.1860000 0.4426923
27 0.9293590 1.1860000
28 0.9293590 0.9293590
29 0.4426923 0.9293590
30 0.9293590 0.4426923
31 1.1860000 0.9293590
32 0.6993333 1.1860000
33 0.9293590 0.6993333
34 0.9293590 0.9293590
35 0.9293590 0.9293590
36 0.6993333 0.9293590
37 0.9293590 0.6993333
38 0.4426923 0.9293590
39 0.4426923 0.4426923
40 0.4426923 0.4426923
41 0.9293590 0.4426923
42 0.6993333 0.9293590
43 1.1860000 0.6993333
44 0.4426923 1.1860000
45 0.4426923 0.4426923
46 0.9293590 0.4426923
47 0.9293590 0.9293590
48 0.4426923 0.9293590
49 0.9293590 0.4426923
50 0.9293590 0.9293590
51 0.6993333 0.9293590
52 0.9293590 0.6993333
53 0.9293590 0.9293590
54 0.9293590 0.9293590
55 0.9293590 0.9293590
56 0.4426923 0.9293590
57 0.9293590 0.4426923
58 0.9293590 0.9293590
59 0.6993333 0.9293590
60 1.1860000 0.6993333
61 0.4426923 1.1860000
62 0.9293590 0.4426923
63 1.1860000 0.9293590
64 0.9293590 1.1860000
65 0.9293590 0.9293590
66 0.4426923 0.9293590
67 1.1860000 0.4426923
68 0.9293590 1.1860000
69 0.9293590 0.9293590
70 0.9293590 0.9293590
71 0.9293590 0.9293590
72 0.9293590 0.9293590
73 1.1860000 0.9293590
74 0.9293590 1.1860000
75 0.4426923 0.9293590
76 0.9293590 0.4426923
77 0.4426923 0.9293590
78 0.9293590 0.4426923
79 0.4426923 0.9293590
80 0.9293590 0.4426923
81 1.1860000 0.9293590
82 0.9293590 1.1860000
83 0.9293590 0.9293590
84 0.4426923 0.9293590
85 1.1860000 0.4426923
86 -0.8140000 1.1860000
87 -0.8140000 -0.8140000
88 -1.0706410 -0.8140000
89 -1.0706410 -1.0706410
90 -1.5573077 -1.0706410
91 -0.8140000 -1.5573077
92 -1.3006667 -0.8140000
93 -1.0706410 -1.3006667
94 -1.0706410 -1.0706410
95 -1.0706410 -1.0706410
96 -0.8140000 -1.0706410
97 -1.0706410 -0.8140000
98 -0.8140000 -1.0706410
99 -1.0706410 -0.8140000
100 -0.8140000 -1.0706410
101 -1.0706410 -0.8140000
102 -1.0706410 -1.0706410
103 -1.0706410 -1.0706410
104 -1.0706410 -1.0706410
105 -1.0706410 -1.0706410
106 -1.0706410 -1.0706410
107 -0.8140000 -1.0706410
108 -1.0706410 -0.8140000
109 -0.8140000 -1.0706410
110 -1.3006667 -0.8140000
111 -1.0706410 -1.3006667
112 -1.0706410 -1.0706410
113 -0.8140000 -1.0706410
114 -0.8140000 -0.8140000
115 -1.0706410 -0.8140000
116 -0.8140000 -1.0706410
117 -0.8140000 -0.8140000
118 -1.0706410 -0.8140000
119 -1.0706410 -1.0706410
120 -0.8140000 -1.0706410
121 -1.0706410 -0.8140000
122 -0.8140000 -1.0706410
123 -1.5573077 -0.8140000
124 -1.0706410 -1.5573077
125 -1.0706410 -1.0706410
126 -1.5573077 -1.0706410
127 -1.0706410 -1.5573077
128 -1.0706410 -1.0706410
129 -1.0706410 -1.0706410
130 -0.8140000 -1.0706410
131 -0.8140000 -0.8140000
132 -0.8140000 -0.8140000
133 -1.0706410 -0.8140000
134 -1.0706410 -1.0706410
135 -1.0706410 -1.0706410
136 -1.3006667 -1.0706410
137 -1.3006667 -1.3006667
138 -1.0706410 -1.3006667
139 -1.0706410 -1.0706410
140 -1.0706410 -1.0706410
141 -1.0706410 -1.0706410
142 -0.8140000 -1.0706410
143 -1.5573077 -0.8140000
144 -1.5573077 -1.5573077
145 -1.0706410 -1.5573077
146 -1.0706410 -1.0706410
147 -1.0706410 -1.0706410
148 -0.8140000 -1.0706410
149 -1.5573077 -0.8140000
150 -1.0706410 -1.5573077
151 -0.8140000 -1.0706410
152 -1.3006667 -0.8140000
153 -0.8140000 -1.3006667
> 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/fisher/rcomp/tmp/77x761356102863.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> acf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/fisher/rcomp/tmp/8wm1n1356102863.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> pacf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Partial Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/fisher/rcomp/tmp/9h1qs1356102863.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> opar <- par(mfrow = c(2,2), oma = c(0, 0, 1.1, 0))
> plot(mylm, las = 1, sub='Residual Diagnostics')
> par(opar)
> dev.off()
null device
1
> if (n > n25) {
+ postscript(file="/var/fisher/rcomp/tmp/10q2jw1356102863.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
+ plot(kp3:nmkm3,gqarr[,2], main='Goldfeld-Quandt test',ylab='2-sided p-value',xlab='breakpoint')
+ grid()
+ dev.off()
+ }
null device
1
>
> #Note: the /var/fisher/rcomp/createtable file can be downloaded at http://www.wessa.net/cretab
> load(file="/var/fisher/rcomp/createtable")
>
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a, 'Multiple Linear Regression - Estimated Regression Equation', 1, TRUE)
> a<-table.row.end(a)
> myeq <- colnames(x)[1]
> myeq <- paste(myeq, '[t] = ', sep='')
> for (i in 1:k){
+ if (mysum$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/fisher/rcomp/tmp/11i4vv1356102863.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/fisher/rcomp/tmp/12wj2k1356102863.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/fisher/rcomp/tmp/13cq6a1356102863.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/fisher/rcomp/tmp/14k8871356102863.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/fisher/rcomp/tmp/15ohqq1356102863.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/fisher/rcomp/tmp/16dhtz1356102863.tab")
+ }
>
> try(system("convert tmp/1oui81356102862.ps tmp/1oui81356102862.png",intern=TRUE))
character(0)
> try(system("convert tmp/2hbwe1356102862.ps tmp/2hbwe1356102862.png",intern=TRUE))
character(0)
> try(system("convert tmp/3lldo1356102862.ps tmp/3lldo1356102862.png",intern=TRUE))
character(0)
> try(system("convert tmp/4i6ac1356102862.ps tmp/4i6ac1356102862.png",intern=TRUE))
character(0)
> try(system("convert tmp/5v6lf1356102862.ps tmp/5v6lf1356102862.png",intern=TRUE))
character(0)
> try(system("convert tmp/67zd11356102863.ps tmp/67zd11356102863.png",intern=TRUE))
character(0)
> try(system("convert tmp/77x761356102863.ps tmp/77x761356102863.png",intern=TRUE))
character(0)
> try(system("convert tmp/8wm1n1356102863.ps tmp/8wm1n1356102863.png",intern=TRUE))
character(0)
> try(system("convert tmp/9h1qs1356102863.ps tmp/9h1qs1356102863.png",intern=TRUE))
character(0)
> try(system("convert tmp/10q2jw1356102863.ps tmp/10q2jw1356102863.png",intern=TRUE))
character(0)
>
>
> proc.time()
user system elapsed
7.293 1.740 9.037