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(100.00
+ ,100.00
+ ,103.53
+ ,102.62
+ ,108.36
+ ,107.62
+ ,115.20
+ ,103.46
+ ,123.51
+ ,103.61
+ ,132.87
+ ,106.10
+ ,130.55
+ ,107.13
+ ,136.68
+ ,108.82
+ ,140.63
+ ,112.93
+ ,143.47
+ ,109.35
+ ,124.10
+ ,108.75
+ ,111.49
+ ,110.83
+ ,119.93
+ ,110.95
+ ,131.79
+ ,114.96
+ ,136.61
+ ,120.45
+ ,141.79
+ ,122.89
+ ,142.23
+ ,120.43
+ ,146.74
+ ,121.76
+ ,154.85
+ ,122.78
+ ,148.44
+ ,125.32
+ ,154.18
+ ,128.68
+ ,149.10
+ ,127.91
+ ,152.22
+ ,125.52
+ ,149.34
+ ,127.56
+ ,160.94
+ ,127.90
+ ,176.16
+ ,130.75
+ ,195.12
+ ,133.57
+ ,186.07
+ ,135.83
+ ,200.78
+ ,135.26
+ ,208.15
+ ,135.99
+ ,209.56
+ ,139.12
+ ,203.33
+ ,137.64
+ ,198.84
+ ,138.59
+ ,200.63
+ ,138.32
+ ,206.47
+ ,135.99
+ ,196.68
+ ,136.96
+ ,203.81
+ ,137.13
+ ,190.18
+ ,138.67
+ ,187.50
+ ,143.04
+ ,187.62
+ ,143.98
+ ,168.92
+ ,144.09
+ ,164.78
+ ,144.97
+ ,175.98
+ ,147.77
+ ,174.70
+ ,149.73
+ ,166.95
+ ,153.11
+ ,161.76
+ ,151.58
+ ,149.65
+ ,149.04
+ ,137.42
+ ,154.70
+ ,142.60
+ ,154.91
+ ,146.94
+ ,159.08
+ ,152.52
+ ,168.01
+ ,147.47
+ ,164.17
+ ,146.15
+ ,163.77
+ ,152.04
+ ,163.49
+ ,144.42
+ ,166.13
+ ,138.15
+ ,166.15
+ ,125.94
+ ,170.05
+ ,112.61
+ ,167.37
+ ,111.48
+ ,164.80
+ ,95.25
+ ,169.53
+ ,105.38
+ ,168.17
+ ,109.59
+ ,172.45
+ ,99.07
+ ,177.81
+ ,92.07
+ ,175.38
+ ,89.10
+ ,175.64
+ ,86.36
+ ,178.80
+ ,95.39
+ ,180.49
+ ,95.27
+ ,182.71
+ ,98.56
+ ,185.73
+ ,101.79
+ ,183.17
+ ,102.02
+ ,182.11
+ ,98.21
+ ,185.43
+ ,104.42
+ ,185.29
+ ,105.62
+ ,188.55
+ ,109.46
+ ,191.89
+ ,110.94
+ ,190.62
+ ,113.09
+ ,190.29
+ ,109.58
+ ,193.27
+ ,111.41
+ ,194.54
+ ,109.83
+ ,195.42
+ ,110.58
+ ,198.58
+ ,109.04
+ ,197.60
+ ,107.80
+ ,194.62
+ ,109.79
+ ,199.30
+ ,110.76
+ ,199.51
+ ,112.64
+ ,203.08
+ ,114.17
+ ,204.36
+ ,115.99
+ ,206.47
+ ,119.01
+ ,206.51
+ ,117.92
+ ,208.09
+ ,115.92
+ ,210.08
+ ,120.75
+ ,212.42
+ ,124.94
+ ,231.32
+ ,129.17
+ ,231.94
+ ,128.14
+ ,228.02
+ ,134.18
+ ,231.95
+ ,131.74
+ ,233.88
+ ,134.32
+ ,235.95
+ ,137.80
+ ,242.92
+ ,141.79
+ ,240.80
+ ,142.75
+ ,240.34
+ ,144.30
+ ,241.95
+ ,145.49
+ ,246.61
+ ,138.21
+ ,247.80
+ ,139.02
+ ,250.97
+ ,141.91
+ ,248.11
+ ,144.95
+ ,243.75
+ ,146.11
+ ,248.79
+ ,150.96
+ ,247.03
+ ,148.20
+ ,250.49
+ ,152.12
+ ,260.83
+ ,154.74
+ ,256.22
+ ,150.80
+ ,255.33
+ ,152.60
+ ,259.54
+ ,158.74
+ ,260.64
+ ,161.83
+ ,262.20
+ ,162.40
+ ,267.29
+ ,156.11
+ ,265.55
+ ,154.93
+ ,258.99
+ ,157.18
+ ,265.04
+ ,159.85
+ ,262.18
+ ,154.40
+ ,265.05
+ ,151.57
+ ,268.78
+ ,133.34
+ ,265.93
+ ,131.20
+ ,261.30
+ ,124.17
+ ,265.20
+ ,133.19
+ ,263.26
+ ,130.94
+ ,265.41
+ ,119.58
+ ,268.75
+ ,118.55
+ ,261.95
+ ,119.96
+ ,258.16
+ ,108.42
+ ,265.22
+ ,95.93
+ ,267.34
+ ,88.83
+ ,269.01
+ ,84.98
+ ,272.90
+ ,81.61
+ ,278.76
+ ,72.84
+ ,278.98
+ ,74.72
+ ,281.03
+ ,83.40
+ ,285.65
+ ,87.42
+ ,287.34
+ ,86.33
+ ,294.57
+ ,94.28
+ ,294.24
+ ,98.81
+ ,295.13
+ ,100.96
+ ,299.65
+ ,99.14
+ ,303.59)
+ ,dim=c(2
+ ,145)
+ ,dimnames=list(c('Y'
+ ,'X')
+ ,1:145))
> y <- array(NA,dim=c(2,145),dimnames=list(c('Y','X'),1:145))
> 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 = '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
1 100.00 100.00 1 0 0 0 0 0 0 0 0 0 0
2 103.53 102.62 0 1 0 0 0 0 0 0 0 0 0
3 108.36 107.62 0 0 1 0 0 0 0 0 0 0 0
4 115.20 103.46 0 0 0 1 0 0 0 0 0 0 0
5 123.51 103.61 0 0 0 0 1 0 0 0 0 0 0
6 132.87 106.10 0 0 0 0 0 1 0 0 0 0 0
7 130.55 107.13 0 0 0 0 0 0 1 0 0 0 0
8 136.68 108.82 0 0 0 0 0 0 0 1 0 0 0
9 140.63 112.93 0 0 0 0 0 0 0 0 1 0 0
10 143.47 109.35 0 0 0 0 0 0 0 0 0 1 0
11 124.10 108.75 0 0 0 0 0 0 0 0 0 0 1
12 111.49 110.83 0 0 0 0 0 0 0 0 0 0 0
13 119.93 110.95 1 0 0 0 0 0 0 0 0 0 0
14 131.79 114.96 0 1 0 0 0 0 0 0 0 0 0
15 136.61 120.45 0 0 1 0 0 0 0 0 0 0 0
16 141.79 122.89 0 0 0 1 0 0 0 0 0 0 0
17 142.23 120.43 0 0 0 0 1 0 0 0 0 0 0
18 146.74 121.76 0 0 0 0 0 1 0 0 0 0 0
19 154.85 122.78 0 0 0 0 0 0 1 0 0 0 0
20 148.44 125.32 0 0 0 0 0 0 0 1 0 0 0
21 154.18 128.68 0 0 0 0 0 0 0 0 1 0 0
22 149.10 127.91 0 0 0 0 0 0 0 0 0 1 0
23 152.22 125.52 0 0 0 0 0 0 0 0 0 0 1
24 149.34 127.56 0 0 0 0 0 0 0 0 0 0 0
25 160.94 127.90 1 0 0 0 0 0 0 0 0 0 0
26 176.16 130.75 0 1 0 0 0 0 0 0 0 0 0
27 195.12 133.57 0 0 1 0 0 0 0 0 0 0 0
28 186.07 135.83 0 0 0 1 0 0 0 0 0 0 0
29 200.78 135.26 0 0 0 0 1 0 0 0 0 0 0
30 208.15 135.99 0 0 0 0 0 1 0 0 0 0 0
31 209.56 139.12 0 0 0 0 0 0 1 0 0 0 0
32 203.33 137.64 0 0 0 0 0 0 0 1 0 0 0
33 198.84 138.59 0 0 0 0 0 0 0 0 1 0 0
34 200.63 138.32 0 0 0 0 0 0 0 0 0 1 0
35 206.47 135.99 0 0 0 0 0 0 0 0 0 0 1
36 196.68 136.96 0 0 0 0 0 0 0 0 0 0 0
37 203.81 137.13 1 0 0 0 0 0 0 0 0 0 0
38 190.18 138.67 0 1 0 0 0 0 0 0 0 0 0
39 187.50 143.04 0 0 1 0 0 0 0 0 0 0 0
40 187.62 143.98 0 0 0 1 0 0 0 0 0 0 0
41 168.92 144.09 0 0 0 0 1 0 0 0 0 0 0
42 164.78 144.97 0 0 0 0 0 1 0 0 0 0 0
43 175.98 147.77 0 0 0 0 0 0 1 0 0 0 0
44 174.70 149.73 0 0 0 0 0 0 0 1 0 0 0
45 166.95 153.11 0 0 0 0 0 0 0 0 1 0 0
46 161.76 151.58 0 0 0 0 0 0 0 0 0 1 0
47 149.65 149.04 0 0 0 0 0 0 0 0 0 0 1
48 137.42 154.70 0 0 0 0 0 0 0 0 0 0 0
49 142.60 154.91 1 0 0 0 0 0 0 0 0 0 0
50 146.94 159.08 0 1 0 0 0 0 0 0 0 0 0
51 152.52 168.01 0 0 1 0 0 0 0 0 0 0 0
52 147.47 164.17 0 0 0 1 0 0 0 0 0 0 0
53 146.15 163.77 0 0 0 0 1 0 0 0 0 0 0
54 152.04 163.49 0 0 0 0 0 1 0 0 0 0 0
55 144.42 166.13 0 0 0 0 0 0 1 0 0 0 0
56 138.15 166.15 0 0 0 0 0 0 0 1 0 0 0
57 125.94 170.05 0 0 0 0 0 0 0 0 1 0 0
58 112.61 167.37 0 0 0 0 0 0 0 0 0 1 0
59 111.48 164.80 0 0 0 0 0 0 0 0 0 0 1
60 95.25 169.53 0 0 0 0 0 0 0 0 0 0 0
61 105.38 168.17 1 0 0 0 0 0 0 0 0 0 0
62 109.59 172.45 0 1 0 0 0 0 0 0 0 0 0
63 99.07 177.81 0 0 1 0 0 0 0 0 0 0 0
64 92.07 175.38 0 0 0 1 0 0 0 0 0 0 0
65 89.10 175.64 0 0 0 0 1 0 0 0 0 0 0
66 86.36 178.80 0 0 0 0 0 1 0 0 0 0 0
67 95.39 180.49 0 0 0 0 0 0 1 0 0 0 0
68 95.27 182.71 0 0 0 0 0 0 0 1 0 0 0
69 98.56 185.73 0 0 0 0 0 0 0 0 1 0 0
70 101.79 183.17 0 0 0 0 0 0 0 0 0 1 0
71 102.02 182.11 0 0 0 0 0 0 0 0 0 0 1
72 98.21 185.43 0 0 0 0 0 0 0 0 0 0 0
73 104.42 185.29 1 0 0 0 0 0 0 0 0 0 0
74 105.62 188.55 0 1 0 0 0 0 0 0 0 0 0
75 109.46 191.89 0 0 1 0 0 0 0 0 0 0 0
76 110.94 190.62 0 0 0 1 0 0 0 0 0 0 0
77 113.09 190.29 0 0 0 0 1 0 0 0 0 0 0
78 109.58 193.27 0 0 0 0 0 1 0 0 0 0 0
79 111.41 194.54 0 0 0 0 0 0 1 0 0 0 0
80 109.83 195.42 0 0 0 0 0 0 0 1 0 0 0
81 110.58 198.58 0 0 0 0 0 0 0 0 1 0 0
82 109.04 197.60 0 0 0 0 0 0 0 0 0 1 0
83 107.80 194.62 0 0 0 0 0 0 0 0 0 0 1
84 109.79 199.30 0 0 0 0 0 0 0 0 0 0 0
85 110.76 199.51 1 0 0 0 0 0 0 0 0 0 0
86 112.64 203.08 0 1 0 0 0 0 0 0 0 0 0
87 114.17 204.36 0 0 1 0 0 0 0 0 0 0 0
88 115.99 206.47 0 0 0 1 0 0 0 0 0 0 0
89 119.01 206.51 0 0 0 0 1 0 0 0 0 0 0
90 117.92 208.09 0 0 0 0 0 1 0 0 0 0 0
91 115.92 210.08 0 0 0 0 0 0 1 0 0 0 0
92 120.75 212.42 0 0 0 0 0 0 0 1 0 0 0
93 124.94 231.32 0 0 0 0 0 0 0 0 1 0 0
94 129.17 231.94 0 0 0 0 0 0 0 0 0 1 0
95 128.14 228.02 0 0 0 0 0 0 0 0 0 0 1
96 134.18 231.95 0 0 0 0 0 0 0 0 0 0 0
97 131.74 233.88 1 0 0 0 0 0 0 0 0 0 0
98 134.32 235.95 0 1 0 0 0 0 0 0 0 0 0
99 137.80 242.92 0 0 1 0 0 0 0 0 0 0 0
100 141.79 240.80 0 0 0 1 0 0 0 0 0 0 0
101 142.75 240.34 0 0 0 0 1 0 0 0 0 0 0
102 144.30 241.95 0 0 0 0 0 1 0 0 0 0 0
103 145.49 246.61 0 0 0 0 0 0 1 0 0 0 0
104 138.21 247.80 0 0 0 0 0 0 0 1 0 0 0
105 139.02 250.97 0 0 0 0 0 0 0 0 1 0 0
106 141.91 248.11 0 0 0 0 0 0 0 0 0 1 0
107 144.95 243.75 0 0 0 0 0 0 0 0 0 0 1
108 146.11 248.79 0 0 0 0 0 0 0 0 0 0 0
109 150.96 247.03 1 0 0 0 0 0 0 0 0 0 0
110 148.20 250.49 0 1 0 0 0 0 0 0 0 0 0
111 152.12 260.83 0 0 1 0 0 0 0 0 0 0 0
112 154.74 256.22 0 0 0 1 0 0 0 0 0 0 0
113 150.80 255.33 0 0 0 0 1 0 0 0 0 0 0
114 152.60 259.54 0 0 0 0 0 1 0 0 0 0 0
115 158.74 260.64 0 0 0 0 0 0 1 0 0 0 0
116 161.83 262.20 0 0 0 0 0 0 0 1 0 0 0
117 162.40 267.29 0 0 0 0 0 0 0 0 1 0 0
118 156.11 265.55 0 0 0 0 0 0 0 0 0 1 0
119 154.93 258.99 0 0 0 0 0 0 0 0 0 0 1
120 157.18 265.04 0 0 0 0 0 0 0 0 0 0 0
121 159.85 262.18 1 0 0 0 0 0 0 0 0 0 0
122 154.40 265.05 0 1 0 0 0 0 0 0 0 0 0
123 151.57 268.78 0 0 1 0 0 0 0 0 0 0 0
124 133.34 265.93 0 0 0 1 0 0 0 0 0 0 0
125 131.20 261.30 0 0 0 0 1 0 0 0 0 0 0
126 124.17 265.20 0 0 0 0 0 1 0 0 0 0 0
127 133.19 263.26 0 0 0 0 0 0 1 0 0 0 0
128 130.94 265.41 0 0 0 0 0 0 0 1 0 0 0
129 119.58 268.75 0 0 0 0 0 0 0 0 1 0 0
130 118.55 261.95 0 0 0 0 0 0 0 0 0 1 0
131 119.96 258.16 0 0 0 0 0 0 0 0 0 0 1
132 108.42 265.22 0 0 0 0 0 0 0 0 0 0 0
133 95.93 267.34 1 0 0 0 0 0 0 0 0 0 0
134 88.83 269.01 0 1 0 0 0 0 0 0 0 0 0
135 84.98 272.90 0 0 1 0 0 0 0 0 0 0 0
136 81.61 278.76 0 0 0 1 0 0 0 0 0 0 0
137 72.84 278.98 0 0 0 0 1 0 0 0 0 0 0
138 74.72 281.03 0 0 0 0 0 1 0 0 0 0 0
139 83.40 285.65 0 0 0 0 0 0 1 0 0 0 0
140 87.42 287.34 0 0 0 0 0 0 0 1 0 0 0
141 86.33 294.57 0 0 0 0 0 0 0 0 1 0 0
142 94.28 294.24 0 0 0 0 0 0 0 0 0 1 0
143 98.81 295.13 0 0 0 0 0 0 0 0 0 0 1
144 100.96 299.65 0 0 0 0 0 0 0 0 0 0 0
145 99.14 303.59 1 0 0 0 0 0 0 0 0 0 0
> k <- length(x[1,])
> df <- as.data.frame(x)
> (mylm <- lm(df))
Call:
lm(formula = df)
Coefficients:
(Intercept) X M1 M2 M3 M4
166.0033 -0.1866 -0.4895 2.2087 5.4222 3.5821
M5 M6 M7 M8 M9 M10
2.7552 4.2926 8.3886 7.5368 6.9973 5.8379
M11
3.8461
> (mysum <- summary(mylm))
Call:
lm(formula = df)
Residuals:
Min 1Q Median 3Q Max
-50.564 -25.452 -1.705 20.596 63.891
Coefficients:
Estimate Std. Error t value Pr(>|t|)
(Intercept) 166.00335 12.45867 13.324 < 2e-16 ***
X -0.18665 0.04387 -4.255 3.93e-05 ***
M1 -0.48952 12.29673 -0.040 0.968
M2 2.20867 12.55022 0.176 0.861
M3 5.42221 12.54147 0.432 0.666
M4 3.58208 12.54234 0.286 0.776
M5 2.75521 12.54343 0.220 0.826
M6 4.29263 12.54062 0.342 0.733
M7 8.38858 12.53851 0.669 0.505
M8 7.53676 12.53739 0.601 0.549
M9 6.99726 12.53585 0.558 0.578
M10 5.83789 12.53601 0.466 0.642
M11 3.84606 12.53717 0.307 0.759
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
Residual standard error: 30.71 on 132 degrees of freedom
Multiple R-squared: 0.1268, Adjusted R-squared: 0.04743
F-statistic: 1.598 on 12 and 132 DF, p-value: 0.0996
> 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,] 5.092333e-03 1.018467e-02 0.994907667
[2,] 1.806201e-03 3.612402e-03 0.998193799
[3,] 6.723427e-04 1.344685e-03 0.999327657
[4,] 1.109628e-04 2.219256e-04 0.999889037
[5,] 5.599204e-05 1.119841e-04 0.999944008
[6,] 1.483364e-05 2.966727e-05 0.999985166
[7,] 1.795997e-05 3.591994e-05 0.999982040
[8,] 5.164635e-06 1.032927e-05 0.999994835
[9,] 4.190301e-06 8.380602e-06 0.999995810
[10,] 6.802884e-06 1.360577e-05 0.999993197
[11,] 1.605652e-05 3.211304e-05 0.999983943
[12,] 1.860508e-04 3.721017e-04 0.999813949
[13,] 1.063581e-04 2.127163e-04 0.999893642
[14,] 1.044976e-04 2.089952e-04 0.999895502
[15,] 1.135480e-04 2.270960e-04 0.999886452
[16,] 7.991788e-05 1.598358e-04 0.999920082
[17,] 5.738905e-05 1.147781e-04 0.999942611
[18,] 3.571078e-05 7.142155e-05 0.999964289
[19,] 2.226832e-05 4.453663e-05 0.999977732
[20,] 3.577843e-05 7.155687e-05 0.999964222
[21,] 5.181814e-05 1.036363e-04 0.999948182
[22,] 6.205289e-05 1.241058e-04 0.999937947
[23,] 4.137131e-05 8.274262e-05 0.999958629
[24,] 3.969691e-05 7.939383e-05 0.999960303
[25,] 4.630536e-05 9.261072e-05 0.999953695
[26,] 4.092431e-04 8.184862e-04 0.999590757
[27,] 3.290680e-03 6.581361e-03 0.996709320
[28,] 9.242802e-03 1.848560e-02 0.990757198
[29,] 2.074024e-02 4.148047e-02 0.979259764
[30,] 5.236685e-02 1.047337e-01 0.947633150
[31,] 1.110671e-01 2.221343e-01 0.888932868
[32,] 2.032064e-01 4.064129e-01 0.796793552
[33,] 3.435642e-01 6.871283e-01 0.656435847
[34,] 4.653114e-01 9.306229e-01 0.534688554
[35,] 5.644626e-01 8.710747e-01 0.435537357
[36,] 6.674449e-01 6.651101e-01 0.332555050
[37,] 7.389784e-01 5.220431e-01 0.261021560
[38,] 7.974063e-01 4.051874e-01 0.202593684
[39,] 8.437170e-01 3.125660e-01 0.156282982
[40,] 8.863842e-01 2.272317e-01 0.113615834
[41,] 9.152381e-01 1.695237e-01 0.084761865
[42,] 9.423248e-01 1.153505e-01 0.057675231
[43,] 9.646424e-01 7.071526e-02 0.035357629
[44,] 9.738744e-01 5.225112e-02 0.026125560
[45,] 9.827552e-01 3.448965e-02 0.017244826
[46,] 9.844331e-01 3.113383e-02 0.015566913
[47,] 9.851206e-01 2.975879e-02 0.014879393
[48,] 9.890229e-01 2.195418e-02 0.010977088
[49,] 9.925063e-01 1.498745e-02 0.007493725
[50,] 9.949502e-01 1.009958e-02 0.005049791
[51,] 9.968731e-01 6.253859e-03 0.003126929
[52,] 9.975166e-01 4.966727e-03 0.002483363
[53,] 9.978430e-01 4.313948e-03 0.002156974
[54,] 9.977898e-01 4.420406e-03 0.002210203
[55,] 9.974717e-01 5.056668e-03 0.002528334
[56,] 9.969912e-01 6.017564e-03 0.003008782
[57,] 9.964629e-01 7.074201e-03 0.003537101
[58,] 9.953820e-01 9.236068e-03 0.004618034
[59,] 9.941988e-01 1.160246e-02 0.005801229
[60,] 9.925739e-01 1.485226e-02 0.007426130
[61,] 9.902053e-01 1.958938e-02 0.009794688
[62,] 9.868116e-01 2.637675e-02 0.013188375
[63,] 9.830747e-01 3.385068e-02 0.016925339
[64,] 9.791492e-01 4.170161e-02 0.020850803
[65,] 9.751444e-01 4.971122e-02 0.024855609
[66,] 9.702892e-01 5.942151e-02 0.029710756
[67,] 9.662582e-01 6.748369e-02 0.033741845
[68,] 9.639137e-01 7.217260e-02 0.036086299
[69,] 9.619853e-01 7.602944e-02 0.038014719
[70,] 9.605380e-01 7.892399e-02 0.039461995
[71,] 9.595170e-01 8.096596e-02 0.040482981
[72,] 9.609022e-01 7.819569e-02 0.039097844
[73,] 9.604627e-01 7.907469e-02 0.039537345
[74,] 9.578202e-01 8.435967e-02 0.042179836
[75,] 9.582076e-01 8.358487e-02 0.041792437
[76,] 9.687758e-01 6.244834e-02 0.031224171
[77,] 9.780937e-01 4.381264e-02 0.021906319
[78,] 9.795032e-01 4.099355e-02 0.020496777
[79,] 9.798005e-01 4.039903e-02 0.020199514
[80,] 9.826443e-01 3.471132e-02 0.017355662
[81,] 9.853301e-01 2.933976e-02 0.014669878
[82,] 9.881724e-01 2.365529e-02 0.011827646
[83,] 9.877378e-01 2.452433e-02 0.012262164
[84,] 9.861402e-01 2.771966e-02 0.013859828
[85,] 9.828723e-01 3.425534e-02 0.017127669
[86,] 9.774464e-01 4.510729e-02 0.022553647
[87,] 9.703007e-01 5.939865e-02 0.029699326
[88,] 9.615639e-01 7.687216e-02 0.038436078
[89,] 9.545088e-01 9.098241e-02 0.045491204
[90,] 9.459243e-01 1.081515e-01 0.054075727
[91,] 9.353299e-01 1.293402e-01 0.064670117
[92,] 9.255792e-01 1.488416e-01 0.074420780
[93,] 9.158371e-01 1.683257e-01 0.084162854
[94,] 9.037148e-01 1.925704e-01 0.096285200
[95,] 8.758091e-01 2.483819e-01 0.124190928
[96,] 8.500090e-01 2.999821e-01 0.149991034
[97,] 8.241249e-01 3.517502e-01 0.175875112
[98,] 7.991442e-01 4.017116e-01 0.200855803
[99,] 7.863954e-01 4.272093e-01 0.213604637
[100,] 7.680161e-01 4.639678e-01 0.231983904
[101,] 7.562589e-01 4.874822e-01 0.243741113
[102,] 7.677319e-01 4.645362e-01 0.232268102
[103,] 7.568797e-01 4.862405e-01 0.243120268
[104,] 7.164684e-01 5.670631e-01 0.283531564
[105,] 6.997227e-01 6.005545e-01 0.300277263
[106,] 7.021751e-01 5.956498e-01 0.297824897
[107,] 7.954349e-01 4.091301e-01 0.204565053
[108,] 8.935433e-01 2.129134e-01 0.106456684
[109,] 9.017591e-01 1.964818e-01 0.098240923
[110,] 9.269464e-01 1.461073e-01 0.073053634
[111,] 9.399400e-01 1.201201e-01 0.060060043
[112,] 9.535421e-01 9.291589e-02 0.046457946
[113,] 9.677653e-01 6.446939e-02 0.032234696
[114,] 9.643609e-01 7.127811e-02 0.035639056
> postscript(file="/var/www/html/rcomp/tmp/1eu4d1260702576.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$resid)
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/2kk271260702576.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> plot(mysum$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/39lof1260702576.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> hist(mysum$resid, main='Residual Histogram', xlab='values of Residuals')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/4idme1260702576.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> densityplot(~mysum$resid,col='black',main='Residual Density Plot', xlab='values of Residuals')
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/5touf1260702576.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 = 145
Frequency = 1
1 2 3 4 5 6
-46.8492118 -45.5283849 -42.9786934 -35.0750103 -25.9101509 -17.6228153
7 8 9 10 11 12
-23.8465177 -16.5492681 -11.2926506 -7.9614729 -25.4516378 -33.8273505
13 14 15 16 17 18
-24.8754359 -14.9651708 -12.3340227 -4.8584746 -4.0507617 -0.8299358
19 20 21 22 23 24
3.3744954 -1.7096058 5.1970271 1.1326806 5.7984190 7.1452405
25 26 27 28 29 30
19.2982172 32.3519728 48.6247755 41.8367273 57.2672015 63.2360397
31 32 33 34 35 36
61.1342943 55.4798754 51.7066910 54.6056676 62.0026048 56.2397148
37 38 39 40 41 42
63.8909617 47.8502107 42.7723151 44.9078939 27.0552874 21.5421226
43 44 45 46 47 48
29.1687840 29.1064280 22.5267938 18.2105962 7.6183377 0.2908184
49 50 51 52 53 54
5.9995312 8.4196597 12.4528708 8.5262807 7.9584847 12.2588103
55 56 57 58 59 60
1.0356083 -4.3788413 -15.3214195 -27.9922602 -27.6101181 -39.1112184
61 62 63 64 65 66
-28.7455402 -26.4348806 -39.1679964 -44.7814154 -46.8760248 -50.5636364
67 68 69 70 71 72
-45.3141522 -44.1679802 -39.7748070 -35.8632502 -33.8392723 -33.1835438
73 74 75 76 77 78
-26.5101572 -27.3998767 -26.1500179 -23.0669272 -20.1516580 -24.6428658
79 80 81 82 83 84
-26.6717731 -27.2357070 -25.3564033 -25.9199455 -25.7243283 -19.0147609
85 86 87 88 89 90
-17.5160482 -17.6679074 -19.1125398 -15.0585849 -11.2042566 -13.5367691
91 92 93 94 95 96
-19.2612911 -13.1427215 -4.8856066 0.6194851 0.8496548 11.4692376
97 98 99 100 101 102
9.8789818 10.1471533 11.7145378 17.1489793 18.8499845 19.1630713
103 104 105 106 107 108
17.1268947 10.9208212 12.8619913 16.3775542 20.5955996 26.5423597
109 110 111 112 113 114
31.5533794 26.7409891 29.3773713 32.9770637 29.6978111 30.7461781
115 116 117 118 119 120
32.9955409 37.2285265 39.2880573 33.8326640 33.4200877 40.6453605
121 122 123 124 125 126
43.2710694 35.6585578 30.3112087 13.3893983 11.2120889 3.3725956
127 128 129 130 131 132
7.9345540 6.9376608 -3.2594392 -4.3992623 -1.7048286 -8.0810432
133 134 135 136 137 138
-19.6858362 -29.1723232 -35.5098090 -35.9459309 -43.8480062 -43.1227950
139 140 141 142 143 144
-37.6764375 -32.4891880 -31.6902343 -22.6424564 -15.9545185 -9.1148145
145
-9.7099113
> postscript(file="/var/www/html/rcomp/tmp/63x271260702576.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 = 145
Frequency = 1
lag(myerror, k = 1) myerror
0 -46.8492118 NA
1 -45.5283849 -46.8492118
2 -42.9786934 -45.5283849
3 -35.0750103 -42.9786934
4 -25.9101509 -35.0750103
5 -17.6228153 -25.9101509
6 -23.8465177 -17.6228153
7 -16.5492681 -23.8465177
8 -11.2926506 -16.5492681
9 -7.9614729 -11.2926506
10 -25.4516378 -7.9614729
11 -33.8273505 -25.4516378
12 -24.8754359 -33.8273505
13 -14.9651708 -24.8754359
14 -12.3340227 -14.9651708
15 -4.8584746 -12.3340227
16 -4.0507617 -4.8584746
17 -0.8299358 -4.0507617
18 3.3744954 -0.8299358
19 -1.7096058 3.3744954
20 5.1970271 -1.7096058
21 1.1326806 5.1970271
22 5.7984190 1.1326806
23 7.1452405 5.7984190
24 19.2982172 7.1452405
25 32.3519728 19.2982172
26 48.6247755 32.3519728
27 41.8367273 48.6247755
28 57.2672015 41.8367273
29 63.2360397 57.2672015
30 61.1342943 63.2360397
31 55.4798754 61.1342943
32 51.7066910 55.4798754
33 54.6056676 51.7066910
34 62.0026048 54.6056676
35 56.2397148 62.0026048
36 63.8909617 56.2397148
37 47.8502107 63.8909617
38 42.7723151 47.8502107
39 44.9078939 42.7723151
40 27.0552874 44.9078939
41 21.5421226 27.0552874
42 29.1687840 21.5421226
43 29.1064280 29.1687840
44 22.5267938 29.1064280
45 18.2105962 22.5267938
46 7.6183377 18.2105962
47 0.2908184 7.6183377
48 5.9995312 0.2908184
49 8.4196597 5.9995312
50 12.4528708 8.4196597
51 8.5262807 12.4528708
52 7.9584847 8.5262807
53 12.2588103 7.9584847
54 1.0356083 12.2588103
55 -4.3788413 1.0356083
56 -15.3214195 -4.3788413
57 -27.9922602 -15.3214195
58 -27.6101181 -27.9922602
59 -39.1112184 -27.6101181
60 -28.7455402 -39.1112184
61 -26.4348806 -28.7455402
62 -39.1679964 -26.4348806
63 -44.7814154 -39.1679964
64 -46.8760248 -44.7814154
65 -50.5636364 -46.8760248
66 -45.3141522 -50.5636364
67 -44.1679802 -45.3141522
68 -39.7748070 -44.1679802
69 -35.8632502 -39.7748070
70 -33.8392723 -35.8632502
71 -33.1835438 -33.8392723
72 -26.5101572 -33.1835438
73 -27.3998767 -26.5101572
74 -26.1500179 -27.3998767
75 -23.0669272 -26.1500179
76 -20.1516580 -23.0669272
77 -24.6428658 -20.1516580
78 -26.6717731 -24.6428658
79 -27.2357070 -26.6717731
80 -25.3564033 -27.2357070
81 -25.9199455 -25.3564033
82 -25.7243283 -25.9199455
83 -19.0147609 -25.7243283
84 -17.5160482 -19.0147609
85 -17.6679074 -17.5160482
86 -19.1125398 -17.6679074
87 -15.0585849 -19.1125398
88 -11.2042566 -15.0585849
89 -13.5367691 -11.2042566
90 -19.2612911 -13.5367691
91 -13.1427215 -19.2612911
92 -4.8856066 -13.1427215
93 0.6194851 -4.8856066
94 0.8496548 0.6194851
95 11.4692376 0.8496548
96 9.8789818 11.4692376
97 10.1471533 9.8789818
98 11.7145378 10.1471533
99 17.1489793 11.7145378
100 18.8499845 17.1489793
101 19.1630713 18.8499845
102 17.1268947 19.1630713
103 10.9208212 17.1268947
104 12.8619913 10.9208212
105 16.3775542 12.8619913
106 20.5955996 16.3775542
107 26.5423597 20.5955996
108 31.5533794 26.5423597
109 26.7409891 31.5533794
110 29.3773713 26.7409891
111 32.9770637 29.3773713
112 29.6978111 32.9770637
113 30.7461781 29.6978111
114 32.9955409 30.7461781
115 37.2285265 32.9955409
116 39.2880573 37.2285265
117 33.8326640 39.2880573
118 33.4200877 33.8326640
119 40.6453605 33.4200877
120 43.2710694 40.6453605
121 35.6585578 43.2710694
122 30.3112087 35.6585578
123 13.3893983 30.3112087
124 11.2120889 13.3893983
125 3.3725956 11.2120889
126 7.9345540 3.3725956
127 6.9376608 7.9345540
128 -3.2594392 6.9376608
129 -4.3992623 -3.2594392
130 -1.7048286 -4.3992623
131 -8.0810432 -1.7048286
132 -19.6858362 -8.0810432
133 -29.1723232 -19.6858362
134 -35.5098090 -29.1723232
135 -35.9459309 -35.5098090
136 -43.8480062 -35.9459309
137 -43.1227950 -43.8480062
138 -37.6764375 -43.1227950
139 -32.4891880 -37.6764375
140 -31.6902343 -32.4891880
141 -22.6424564 -31.6902343
142 -15.9545185 -22.6424564
143 -9.1148145 -15.9545185
144 -9.7099113 -9.1148145
145 NA -9.7099113
> dum1 <- dum[2:length(myerror),]
> dum1
lag(myerror, k = 1) myerror
[1,] -45.5283849 -46.8492118
[2,] -42.9786934 -45.5283849
[3,] -35.0750103 -42.9786934
[4,] -25.9101509 -35.0750103
[5,] -17.6228153 -25.9101509
[6,] -23.8465177 -17.6228153
[7,] -16.5492681 -23.8465177
[8,] -11.2926506 -16.5492681
[9,] -7.9614729 -11.2926506
[10,] -25.4516378 -7.9614729
[11,] -33.8273505 -25.4516378
[12,] -24.8754359 -33.8273505
[13,] -14.9651708 -24.8754359
[14,] -12.3340227 -14.9651708
[15,] -4.8584746 -12.3340227
[16,] -4.0507617 -4.8584746
[17,] -0.8299358 -4.0507617
[18,] 3.3744954 -0.8299358
[19,] -1.7096058 3.3744954
[20,] 5.1970271 -1.7096058
[21,] 1.1326806 5.1970271
[22,] 5.7984190 1.1326806
[23,] 7.1452405 5.7984190
[24,] 19.2982172 7.1452405
[25,] 32.3519728 19.2982172
[26,] 48.6247755 32.3519728
[27,] 41.8367273 48.6247755
[28,] 57.2672015 41.8367273
[29,] 63.2360397 57.2672015
[30,] 61.1342943 63.2360397
[31,] 55.4798754 61.1342943
[32,] 51.7066910 55.4798754
[33,] 54.6056676 51.7066910
[34,] 62.0026048 54.6056676
[35,] 56.2397148 62.0026048
[36,] 63.8909617 56.2397148
[37,] 47.8502107 63.8909617
[38,] 42.7723151 47.8502107
[39,] 44.9078939 42.7723151
[40,] 27.0552874 44.9078939
[41,] 21.5421226 27.0552874
[42,] 29.1687840 21.5421226
[43,] 29.1064280 29.1687840
[44,] 22.5267938 29.1064280
[45,] 18.2105962 22.5267938
[46,] 7.6183377 18.2105962
[47,] 0.2908184 7.6183377
[48,] 5.9995312 0.2908184
[49,] 8.4196597 5.9995312
[50,] 12.4528708 8.4196597
[51,] 8.5262807 12.4528708
[52,] 7.9584847 8.5262807
[53,] 12.2588103 7.9584847
[54,] 1.0356083 12.2588103
[55,] -4.3788413 1.0356083
[56,] -15.3214195 -4.3788413
[57,] -27.9922602 -15.3214195
[58,] -27.6101181 -27.9922602
[59,] -39.1112184 -27.6101181
[60,] -28.7455402 -39.1112184
[61,] -26.4348806 -28.7455402
[62,] -39.1679964 -26.4348806
[63,] -44.7814154 -39.1679964
[64,] -46.8760248 -44.7814154
[65,] -50.5636364 -46.8760248
[66,] -45.3141522 -50.5636364
[67,] -44.1679802 -45.3141522
[68,] -39.7748070 -44.1679802
[69,] -35.8632502 -39.7748070
[70,] -33.8392723 -35.8632502
[71,] -33.1835438 -33.8392723
[72,] -26.5101572 -33.1835438
[73,] -27.3998767 -26.5101572
[74,] -26.1500179 -27.3998767
[75,] -23.0669272 -26.1500179
[76,] -20.1516580 -23.0669272
[77,] -24.6428658 -20.1516580
[78,] -26.6717731 -24.6428658
[79,] -27.2357070 -26.6717731
[80,] -25.3564033 -27.2357070
[81,] -25.9199455 -25.3564033
[82,] -25.7243283 -25.9199455
[83,] -19.0147609 -25.7243283
[84,] -17.5160482 -19.0147609
[85,] -17.6679074 -17.5160482
[86,] -19.1125398 -17.6679074
[87,] -15.0585849 -19.1125398
[88,] -11.2042566 -15.0585849
[89,] -13.5367691 -11.2042566
[90,] -19.2612911 -13.5367691
[91,] -13.1427215 -19.2612911
[92,] -4.8856066 -13.1427215
[93,] 0.6194851 -4.8856066
[94,] 0.8496548 0.6194851
[95,] 11.4692376 0.8496548
[96,] 9.8789818 11.4692376
[97,] 10.1471533 9.8789818
[98,] 11.7145378 10.1471533
[99,] 17.1489793 11.7145378
[100,] 18.8499845 17.1489793
[101,] 19.1630713 18.8499845
[102,] 17.1268947 19.1630713
[103,] 10.9208212 17.1268947
[104,] 12.8619913 10.9208212
[105,] 16.3775542 12.8619913
[106,] 20.5955996 16.3775542
[107,] 26.5423597 20.5955996
[108,] 31.5533794 26.5423597
[109,] 26.7409891 31.5533794
[110,] 29.3773713 26.7409891
[111,] 32.9770637 29.3773713
[112,] 29.6978111 32.9770637
[113,] 30.7461781 29.6978111
[114,] 32.9955409 30.7461781
[115,] 37.2285265 32.9955409
[116,] 39.2880573 37.2285265
[117,] 33.8326640 39.2880573
[118,] 33.4200877 33.8326640
[119,] 40.6453605 33.4200877
[120,] 43.2710694 40.6453605
[121,] 35.6585578 43.2710694
[122,] 30.3112087 35.6585578
[123,] 13.3893983 30.3112087
[124,] 11.2120889 13.3893983
[125,] 3.3725956 11.2120889
[126,] 7.9345540 3.3725956
[127,] 6.9376608 7.9345540
[128,] -3.2594392 6.9376608
[129,] -4.3992623 -3.2594392
[130,] -1.7048286 -4.3992623
[131,] -8.0810432 -1.7048286
[132,] -19.6858362 -8.0810432
[133,] -29.1723232 -19.6858362
[134,] -35.5098090 -29.1723232
[135,] -35.9459309 -35.5098090
[136,] -43.8480062 -35.9459309
[137,] -43.1227950 -43.8480062
[138,] -37.6764375 -43.1227950
[139,] -32.4891880 -37.6764375
[140,] -31.6902343 -32.4891880
[141,] -22.6424564 -31.6902343
[142,] -15.9545185 -22.6424564
[143,] -9.1148145 -15.9545185
[144,] -9.7099113 -9.1148145
> z <- as.data.frame(dum1)
> z
lag(myerror, k = 1) myerror
1 -45.5283849 -46.8492118
2 -42.9786934 -45.5283849
3 -35.0750103 -42.9786934
4 -25.9101509 -35.0750103
5 -17.6228153 -25.9101509
6 -23.8465177 -17.6228153
7 -16.5492681 -23.8465177
8 -11.2926506 -16.5492681
9 -7.9614729 -11.2926506
10 -25.4516378 -7.9614729
11 -33.8273505 -25.4516378
12 -24.8754359 -33.8273505
13 -14.9651708 -24.8754359
14 -12.3340227 -14.9651708
15 -4.8584746 -12.3340227
16 -4.0507617 -4.8584746
17 -0.8299358 -4.0507617
18 3.3744954 -0.8299358
19 -1.7096058 3.3744954
20 5.1970271 -1.7096058
21 1.1326806 5.1970271
22 5.7984190 1.1326806
23 7.1452405 5.7984190
24 19.2982172 7.1452405
25 32.3519728 19.2982172
26 48.6247755 32.3519728
27 41.8367273 48.6247755
28 57.2672015 41.8367273
29 63.2360397 57.2672015
30 61.1342943 63.2360397
31 55.4798754 61.1342943
32 51.7066910 55.4798754
33 54.6056676 51.7066910
34 62.0026048 54.6056676
35 56.2397148 62.0026048
36 63.8909617 56.2397148
37 47.8502107 63.8909617
38 42.7723151 47.8502107
39 44.9078939 42.7723151
40 27.0552874 44.9078939
41 21.5421226 27.0552874
42 29.1687840 21.5421226
43 29.1064280 29.1687840
44 22.5267938 29.1064280
45 18.2105962 22.5267938
46 7.6183377 18.2105962
47 0.2908184 7.6183377
48 5.9995312 0.2908184
49 8.4196597 5.9995312
50 12.4528708 8.4196597
51 8.5262807 12.4528708
52 7.9584847 8.5262807
53 12.2588103 7.9584847
54 1.0356083 12.2588103
55 -4.3788413 1.0356083
56 -15.3214195 -4.3788413
57 -27.9922602 -15.3214195
58 -27.6101181 -27.9922602
59 -39.1112184 -27.6101181
60 -28.7455402 -39.1112184
61 -26.4348806 -28.7455402
62 -39.1679964 -26.4348806
63 -44.7814154 -39.1679964
64 -46.8760248 -44.7814154
65 -50.5636364 -46.8760248
66 -45.3141522 -50.5636364
67 -44.1679802 -45.3141522
68 -39.7748070 -44.1679802
69 -35.8632502 -39.7748070
70 -33.8392723 -35.8632502
71 -33.1835438 -33.8392723
72 -26.5101572 -33.1835438
73 -27.3998767 -26.5101572
74 -26.1500179 -27.3998767
75 -23.0669272 -26.1500179
76 -20.1516580 -23.0669272
77 -24.6428658 -20.1516580
78 -26.6717731 -24.6428658
79 -27.2357070 -26.6717731
80 -25.3564033 -27.2357070
81 -25.9199455 -25.3564033
82 -25.7243283 -25.9199455
83 -19.0147609 -25.7243283
84 -17.5160482 -19.0147609
85 -17.6679074 -17.5160482
86 -19.1125398 -17.6679074
87 -15.0585849 -19.1125398
88 -11.2042566 -15.0585849
89 -13.5367691 -11.2042566
90 -19.2612911 -13.5367691
91 -13.1427215 -19.2612911
92 -4.8856066 -13.1427215
93 0.6194851 -4.8856066
94 0.8496548 0.6194851
95 11.4692376 0.8496548
96 9.8789818 11.4692376
97 10.1471533 9.8789818
98 11.7145378 10.1471533
99 17.1489793 11.7145378
100 18.8499845 17.1489793
101 19.1630713 18.8499845
102 17.1268947 19.1630713
103 10.9208212 17.1268947
104 12.8619913 10.9208212
105 16.3775542 12.8619913
106 20.5955996 16.3775542
107 26.5423597 20.5955996
108 31.5533794 26.5423597
109 26.7409891 31.5533794
110 29.3773713 26.7409891
111 32.9770637 29.3773713
112 29.6978111 32.9770637
113 30.7461781 29.6978111
114 32.9955409 30.7461781
115 37.2285265 32.9955409
116 39.2880573 37.2285265
117 33.8326640 39.2880573
118 33.4200877 33.8326640
119 40.6453605 33.4200877
120 43.2710694 40.6453605
121 35.6585578 43.2710694
122 30.3112087 35.6585578
123 13.3893983 30.3112087
124 11.2120889 13.3893983
125 3.3725956 11.2120889
126 7.9345540 3.3725956
127 6.9376608 7.9345540
128 -3.2594392 6.9376608
129 -4.3992623 -3.2594392
130 -1.7048286 -4.3992623
131 -8.0810432 -1.7048286
132 -19.6858362 -8.0810432
133 -29.1723232 -19.6858362
134 -35.5098090 -29.1723232
135 -35.9459309 -35.5098090
136 -43.8480062 -35.9459309
137 -43.1227950 -43.8480062
138 -37.6764375 -43.1227950
139 -32.4891880 -37.6764375
140 -31.6902343 -32.4891880
141 -22.6424564 -31.6902343
142 -15.9545185 -22.6424564
143 -9.1148145 -15.9545185
144 -9.7099113 -9.1148145
> 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/7xj931260702576.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> acf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/8nuo21260702576.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> pacf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Partial Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/9gaol1260702576.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> opar <- par(mfrow = c(2,2), oma = c(0, 0, 1.1, 0))
> plot(mylm, las = 1, sub='Residual Diagnostics')
> par(opar)
> dev.off()
null device
1
> if (n > n25) {
+ postscript(file="/var/www/html/rcomp/tmp/104hwl1260702576.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
+ plot(kp3:nmkm3,gqarr[,2], main='Goldfeld-Quandt test',ylab='2-sided p-value',xlab='breakpoint')
+ grid()
+ dev.off()
+ }
null device
1
>
> #Note: the /var/www/html/rcomp/createtable file can be downloaded at http://www.wessa.net/cretab
> load(file="/var/www/html/rcomp/createtable")
>
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a, 'Multiple Linear Regression - Estimated Regression Equation', 1, TRUE)
> a<-table.row.end(a)
> myeq <- colnames(x)[1]
> myeq <- paste(myeq, '[t] = ', sep='')
> for (i in 1:k){
+ if (mysum$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/117cg01260702576.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/12t9x11260702576.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/13dt4h1260702576.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/14plmv1260702576.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/15uuom1260702576.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/16lszt1260702576.tab")
+ }
>
> try(system("convert tmp/1eu4d1260702576.ps tmp/1eu4d1260702576.png",intern=TRUE))
character(0)
> try(system("convert tmp/2kk271260702576.ps tmp/2kk271260702576.png",intern=TRUE))
character(0)
> try(system("convert tmp/39lof1260702576.ps tmp/39lof1260702576.png",intern=TRUE))
character(0)
> try(system("convert tmp/4idme1260702576.ps tmp/4idme1260702576.png",intern=TRUE))
character(0)
> try(system("convert tmp/5touf1260702576.ps tmp/5touf1260702576.png",intern=TRUE))
character(0)
> try(system("convert tmp/63x271260702576.ps tmp/63x271260702576.png",intern=TRUE))
character(0)
> try(system("convert tmp/7xj931260702576.ps tmp/7xj931260702576.png",intern=TRUE))
character(0)
> try(system("convert tmp/8nuo21260702576.ps tmp/8nuo21260702576.png",intern=TRUE))
character(0)
> try(system("convert tmp/9gaol1260702576.ps tmp/9gaol1260702576.png",intern=TRUE))
character(0)
> try(system("convert tmp/104hwl1260702576.ps tmp/104hwl1260702576.png",intern=TRUE))
character(0)
>
>
> proc.time()
user system elapsed
3.660 1.675 4.498