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.
Natural language support but running in an English locale
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(2938,2909,3141,2427,3059,2918,2901,2823,2798,2892,2967,2397,3458,3024,3100,2904,3056,2771,2897,2772,2857,3020,2648,2364,3194,3013,2560,3074,2746,2846,3184,2354,3080,2963,2430,2296,2416,2647,2789,2685,2666,2882,2953,2127,2563,3061,2809,2861,2781,2555,3206,2570,2410,3195,2736,2743,2934,2668,2907,2866,2983,2878,3225,2515,3193,2663,2908,2896,2853,3028,3053,2455,3401,2969,3243,2849,3296,3121,3194,3023,2984,3525,3116,2383,3294,2882,2820,2583,2803,2767,2945,2716,2644,2956,2598,2171,2994,2645,2724,2550,2707,2679,2878,2307,2496,2637,2436,2426,2607,2533,2888,2520,2229,2804,2661,2547,2509,2465,2629,2706,2666,2432,2836,2888,2566,2802,2611,2683,2675,2434,2693,2619,2903,2550,2900,2456,2912,2883,2464,2655,2447,2592,2698,2274,2901,2397,3004,2614,2882,2671,2761,2806,2414,2673,2748,2112,2903,2633,2684,2861,2504,2708,2961,2535,2688,2699,2469,2585,2582,2480,2709,2441,2182,2585,2881,2422,2690,2659,2535,2613),dim=c(1,180),dimnames=list(c('Echtscheidingen'),1:180))
> y <- array(NA,dim=c(1,180),dimnames=list(c('Echtscheidingen'),1:180))
> 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
Echtscheidingen M1 M2 M3 M4 M5 M6 M7 M8 M9 M10 M11 t
1 2938 1 0 0 0 0 0 0 0 0 0 0 1
2 2909 0 1 0 0 0 0 0 0 0 0 0 2
3 3141 0 0 1 0 0 0 0 0 0 0 0 3
4 2427 0 0 0 1 0 0 0 0 0 0 0 4
5 3059 0 0 0 0 1 0 0 0 0 0 0 5
6 2918 0 0 0 0 0 1 0 0 0 0 0 6
7 2901 0 0 0 0 0 0 1 0 0 0 0 7
8 2823 0 0 0 0 0 0 0 1 0 0 0 8
9 2798 0 0 0 0 0 0 0 0 1 0 0 9
10 2892 0 0 0 0 0 0 0 0 0 1 0 10
11 2967 0 0 0 0 0 0 0 0 0 0 1 11
12 2397 0 0 0 0 0 0 0 0 0 0 0 12
13 3458 1 0 0 0 0 0 0 0 0 0 0 13
14 3024 0 1 0 0 0 0 0 0 0 0 0 14
15 3100 0 0 1 0 0 0 0 0 0 0 0 15
16 2904 0 0 0 1 0 0 0 0 0 0 0 16
17 3056 0 0 0 0 1 0 0 0 0 0 0 17
18 2771 0 0 0 0 0 1 0 0 0 0 0 18
19 2897 0 0 0 0 0 0 1 0 0 0 0 19
20 2772 0 0 0 0 0 0 0 1 0 0 0 20
21 2857 0 0 0 0 0 0 0 0 1 0 0 21
22 3020 0 0 0 0 0 0 0 0 0 1 0 22
23 2648 0 0 0 0 0 0 0 0 0 0 1 23
24 2364 0 0 0 0 0 0 0 0 0 0 0 24
25 3194 1 0 0 0 0 0 0 0 0 0 0 25
26 3013 0 1 0 0 0 0 0 0 0 0 0 26
27 2560 0 0 1 0 0 0 0 0 0 0 0 27
28 3074 0 0 0 1 0 0 0 0 0 0 0 28
29 2746 0 0 0 0 1 0 0 0 0 0 0 29
30 2846 0 0 0 0 0 1 0 0 0 0 0 30
31 3184 0 0 0 0 0 0 1 0 0 0 0 31
32 2354 0 0 0 0 0 0 0 1 0 0 0 32
33 3080 0 0 0 0 0 0 0 0 1 0 0 33
34 2963 0 0 0 0 0 0 0 0 0 1 0 34
35 2430 0 0 0 0 0 0 0 0 0 0 1 35
36 2296 0 0 0 0 0 0 0 0 0 0 0 36
37 2416 1 0 0 0 0 0 0 0 0 0 0 37
38 2647 0 1 0 0 0 0 0 0 0 0 0 38
39 2789 0 0 1 0 0 0 0 0 0 0 0 39
40 2685 0 0 0 1 0 0 0 0 0 0 0 40
41 2666 0 0 0 0 1 0 0 0 0 0 0 41
42 2882 0 0 0 0 0 1 0 0 0 0 0 42
43 2953 0 0 0 0 0 0 1 0 0 0 0 43
44 2127 0 0 0 0 0 0 0 1 0 0 0 44
45 2563 0 0 0 0 0 0 0 0 1 0 0 45
46 3061 0 0 0 0 0 0 0 0 0 1 0 46
47 2809 0 0 0 0 0 0 0 0 0 0 1 47
48 2861 0 0 0 0 0 0 0 0 0 0 0 48
49 2781 1 0 0 0 0 0 0 0 0 0 0 49
50 2555 0 1 0 0 0 0 0 0 0 0 0 50
51 3206 0 0 1 0 0 0 0 0 0 0 0 51
52 2570 0 0 0 1 0 0 0 0 0 0 0 52
53 2410 0 0 0 0 1 0 0 0 0 0 0 53
54 3195 0 0 0 0 0 1 0 0 0 0 0 54
55 2736 0 0 0 0 0 0 1 0 0 0 0 55
56 2743 0 0 0 0 0 0 0 1 0 0 0 56
57 2934 0 0 0 0 0 0 0 0 1 0 0 57
58 2668 0 0 0 0 0 0 0 0 0 1 0 58
59 2907 0 0 0 0 0 0 0 0 0 0 1 59
60 2866 0 0 0 0 0 0 0 0 0 0 0 60
61 2983 1 0 0 0 0 0 0 0 0 0 0 61
62 2878 0 1 0 0 0 0 0 0 0 0 0 62
63 3225 0 0 1 0 0 0 0 0 0 0 0 63
64 2515 0 0 0 1 0 0 0 0 0 0 0 64
65 3193 0 0 0 0 1 0 0 0 0 0 0 65
66 2663 0 0 0 0 0 1 0 0 0 0 0 66
67 2908 0 0 0 0 0 0 1 0 0 0 0 67
68 2896 0 0 0 0 0 0 0 1 0 0 0 68
69 2853 0 0 0 0 0 0 0 0 1 0 0 69
70 3028 0 0 0 0 0 0 0 0 0 1 0 70
71 3053 0 0 0 0 0 0 0 0 0 0 1 71
72 2455 0 0 0 0 0 0 0 0 0 0 0 72
73 3401 1 0 0 0 0 0 0 0 0 0 0 73
74 2969 0 1 0 0 0 0 0 0 0 0 0 74
75 3243 0 0 1 0 0 0 0 0 0 0 0 75
76 2849 0 0 0 1 0 0 0 0 0 0 0 76
77 3296 0 0 0 0 1 0 0 0 0 0 0 77
78 3121 0 0 0 0 0 1 0 0 0 0 0 78
79 3194 0 0 0 0 0 0 1 0 0 0 0 79
80 3023 0 0 0 0 0 0 0 1 0 0 0 80
81 2984 0 0 0 0 0 0 0 0 1 0 0 81
82 3525 0 0 0 0 0 0 0 0 0 1 0 82
83 3116 0 0 0 0 0 0 0 0 0 0 1 83
84 2383 0 0 0 0 0 0 0 0 0 0 0 84
85 3294 1 0 0 0 0 0 0 0 0 0 0 85
86 2882 0 1 0 0 0 0 0 0 0 0 0 86
87 2820 0 0 1 0 0 0 0 0 0 0 0 87
88 2583 0 0 0 1 0 0 0 0 0 0 0 88
89 2803 0 0 0 0 1 0 0 0 0 0 0 89
90 2767 0 0 0 0 0 1 0 0 0 0 0 90
91 2945 0 0 0 0 0 0 1 0 0 0 0 91
92 2716 0 0 0 0 0 0 0 1 0 0 0 92
93 2644 0 0 0 0 0 0 0 0 1 0 0 93
94 2956 0 0 0 0 0 0 0 0 0 1 0 94
95 2598 0 0 0 0 0 0 0 0 0 0 1 95
96 2171 0 0 0 0 0 0 0 0 0 0 0 96
97 2994 1 0 0 0 0 0 0 0 0 0 0 97
98 2645 0 1 0 0 0 0 0 0 0 0 0 98
99 2724 0 0 1 0 0 0 0 0 0 0 0 99
100 2550 0 0 0 1 0 0 0 0 0 0 0 100
101 2707 0 0 0 0 1 0 0 0 0 0 0 101
102 2679 0 0 0 0 0 1 0 0 0 0 0 102
103 2878 0 0 0 0 0 0 1 0 0 0 0 103
104 2307 0 0 0 0 0 0 0 1 0 0 0 104
105 2496 0 0 0 0 0 0 0 0 1 0 0 105
106 2637 0 0 0 0 0 0 0 0 0 1 0 106
107 2436 0 0 0 0 0 0 0 0 0 0 1 107
108 2426 0 0 0 0 0 0 0 0 0 0 0 108
109 2607 1 0 0 0 0 0 0 0 0 0 0 109
110 2533 0 1 0 0 0 0 0 0 0 0 0 110
111 2888 0 0 1 0 0 0 0 0 0 0 0 111
112 2520 0 0 0 1 0 0 0 0 0 0 0 112
113 2229 0 0 0 0 1 0 0 0 0 0 0 113
114 2804 0 0 0 0 0 1 0 0 0 0 0 114
115 2661 0 0 0 0 0 0 1 0 0 0 0 115
116 2547 0 0 0 0 0 0 0 1 0 0 0 116
117 2509 0 0 0 0 0 0 0 0 1 0 0 117
118 2465 0 0 0 0 0 0 0 0 0 1 0 118
119 2629 0 0 0 0 0 0 0 0 0 0 1 119
120 2706 0 0 0 0 0 0 0 0 0 0 0 120
121 2666 1 0 0 0 0 0 0 0 0 0 0 121
122 2432 0 1 0 0 0 0 0 0 0 0 0 122
123 2836 0 0 1 0 0 0 0 0 0 0 0 123
124 2888 0 0 0 1 0 0 0 0 0 0 0 124
125 2566 0 0 0 0 1 0 0 0 0 0 0 125
126 2802 0 0 0 0 0 1 0 0 0 0 0 126
127 2611 0 0 0 0 0 0 1 0 0 0 0 127
128 2683 0 0 0 0 0 0 0 1 0 0 0 128
129 2675 0 0 0 0 0 0 0 0 1 0 0 129
130 2434 0 0 0 0 0 0 0 0 0 1 0 130
131 2693 0 0 0 0 0 0 0 0 0 0 1 131
132 2619 0 0 0 0 0 0 0 0 0 0 0 132
133 2903 1 0 0 0 0 0 0 0 0 0 0 133
134 2550 0 1 0 0 0 0 0 0 0 0 0 134
135 2900 0 0 1 0 0 0 0 0 0 0 0 135
136 2456 0 0 0 1 0 0 0 0 0 0 0 136
137 2912 0 0 0 0 1 0 0 0 0 0 0 137
138 2883 0 0 0 0 0 1 0 0 0 0 0 138
139 2464 0 0 0 0 0 0 1 0 0 0 0 139
140 2655 0 0 0 0 0 0 0 1 0 0 0 140
141 2447 0 0 0 0 0 0 0 0 1 0 0 141
142 2592 0 0 0 0 0 0 0 0 0 1 0 142
143 2698 0 0 0 0 0 0 0 0 0 0 1 143
144 2274 0 0 0 0 0 0 0 0 0 0 0 144
145 2901 1 0 0 0 0 0 0 0 0 0 0 145
146 2397 0 1 0 0 0 0 0 0 0 0 0 146
147 3004 0 0 1 0 0 0 0 0 0 0 0 147
148 2614 0 0 0 1 0 0 0 0 0 0 0 148
149 2882 0 0 0 0 1 0 0 0 0 0 0 149
150 2671 0 0 0 0 0 1 0 0 0 0 0 150
151 2761 0 0 0 0 0 0 1 0 0 0 0 151
152 2806 0 0 0 0 0 0 0 1 0 0 0 152
153 2414 0 0 0 0 0 0 0 0 1 0 0 153
154 2673 0 0 0 0 0 0 0 0 0 1 0 154
155 2748 0 0 0 0 0 0 0 0 0 0 1 155
156 2112 0 0 0 0 0 0 0 0 0 0 0 156
157 2903 1 0 0 0 0 0 0 0 0 0 0 157
158 2633 0 1 0 0 0 0 0 0 0 0 0 158
159 2684 0 0 1 0 0 0 0 0 0 0 0 159
160 2861 0 0 0 1 0 0 0 0 0 0 0 160
161 2504 0 0 0 0 1 0 0 0 0 0 0 161
162 2708 0 0 0 0 0 1 0 0 0 0 0 162
163 2961 0 0 0 0 0 0 1 0 0 0 0 163
164 2535 0 0 0 0 0 0 0 1 0 0 0 164
165 2688 0 0 0 0 0 0 0 0 1 0 0 165
166 2699 0 0 0 0 0 0 0 0 0 1 0 166
167 2469 0 0 0 0 0 0 0 0 0 0 1 167
168 2585 0 0 0 0 0 0 0 0 0 0 0 168
169 2582 1 0 0 0 0 0 0 0 0 0 0 169
170 2480 0 1 0 0 0 0 0 0 0 0 0 170
171 2709 0 0 1 0 0 0 0 0 0 0 0 171
172 2441 0 0 0 1 0 0 0 0 0 0 0 172
173 2182 0 0 0 0 1 0 0 0 0 0 0 173
174 2585 0 0 0 0 0 1 0 0 0 0 0 174
175 2881 0 0 0 0 0 0 1 0 0 0 0 175
176 2422 0 0 0 0 0 0 0 1 0 0 0 176
177 2690 0 0 0 0 0 0 0 0 1 0 0 177
178 2659 0 0 0 0 0 0 0 0 0 1 0 178
179 2535 0 0 0 0 0 0 0 0 0 0 1 179
180 2613 0 0 0 0 0 0 0 0 0 0 0 180
> k <- length(x[1,])
> df <- as.data.frame(x)
> (mylm <- lm(df))
Call:
lm(formula = df)
Coefficients:
(Intercept) M1 M2 M3 M4 M5
2639.474 440.710 210.821 431.333 173.577 260.222
M6 M7 M8 M9 M10 M11
334.200 378.577 145.222 228.466 339.511 238.822
t
-1.711
> (mysum <- summary(mylm))
Call:
lm(formula = df)
Residuals:
Min 1Q Median 3Q Max
-600.870 -141.354 2.705 148.252 686.332
Coefficients:
Estimate Std. Error t value Pr(>|t|)
(Intercept) 2639.4738 64.8756 40.685 < 2e-16 ***
M1 440.7103 80.9899 5.442 1.85e-07 ***
M2 210.8215 80.9767 2.603 0.01006 *
M3 431.3327 80.9648 5.327 3.18e-07 ***
M4 173.5772 80.9542 2.144 0.03347 *
M5 260.2217 80.9448 3.215 0.00157 **
M6 334.1996 80.9366 4.129 5.74e-05 ***
M7 378.5774 80.9297 4.678 5.96e-06 ***
M8 145.2219 80.9241 1.795 0.07453 .
M9 228.4664 80.9197 2.823 0.00533 **
M10 339.5110 80.9165 4.196 4.41e-05 ***
M11 238.8221 80.9147 2.952 0.00362 **
t -1.7112 0.3186 -5.371 2.59e-07 ***
---
Signif. codes: 0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1
Residual standard error: 221.6 on 167 degrees of freedom
Multiple R-squared: 0.3415, Adjusted R-squared: 0.2942
F-statistic: 7.219 on 12 and 167 DF, p-value: 1.482e-10
> if (n > n25) {
+ kp3 <- k + 3
+ nmkm3 <- n - k - 3
+ gqarr <- array(NA, dim=c(nmkm3-kp3+1,3))
+ numgqtests <- 0
+ numsignificant1 <- 0
+ numsignificant5 <- 0
+ numsignificant10 <- 0
+ for (mypoint in kp3:nmkm3) {
+ j <- 0
+ numgqtests <- numgqtests + 1
+ for (myalt in c('greater', 'two.sided', 'less')) {
+ j <- j + 1
+ gqarr[mypoint-kp3+1,j] <- gqtest(mylm, point=mypoint, alternative=myalt)$p.value
+ }
+ if (gqarr[mypoint-kp3+1,2] < 0.01) numsignificant1 <- numsignificant1 + 1
+ if (gqarr[mypoint-kp3+1,2] < 0.05) numsignificant5 <- numsignificant5 + 1
+ if (gqarr[mypoint-kp3+1,2] < 0.10) numsignificant10 <- numsignificant10 + 1
+ }
+ gqarr
+ }
[,1] [,2] [,3]
[1,] 0.47111311 0.9422262297 0.5288868851
[2,] 0.40672225 0.8134445095 0.5932777452
[3,] 0.42782313 0.8556462567 0.5721768717
[4,] 0.32872423 0.6574484508 0.6712757746
[5,] 0.25587120 0.5117423956 0.7441288022
[6,] 0.17194044 0.3438808753 0.8280595623
[7,] 0.10978801 0.2195760145 0.8902119927
[8,] 0.17315803 0.3463160509 0.8268419745
[9,] 0.12526109 0.2505221744 0.8747389128
[10,] 0.08744442 0.1748888326 0.9125555837
[11,] 0.05751435 0.1150286961 0.9424856520
[12,] 0.28055403 0.5611080552 0.7194459724
[13,] 0.37669160 0.7533832005 0.6233083997
[14,] 0.40030168 0.8006033554 0.5996983223
[15,] 0.32984639 0.6596927878 0.6701536061
[16,] 0.33448721 0.6689744122 0.6655127939
[17,] 0.45381690 0.9076338049 0.5461830975
[18,] 0.45220833 0.9044166574 0.5477916713
[19,] 0.38537536 0.7707507141 0.6146246429
[20,] 0.45429291 0.9085858177 0.5457070912
[21,] 0.41362411 0.8272482154 0.5863758923
[22,] 0.78377349 0.4324530230 0.2162265115
[23,] 0.76273942 0.4745211510 0.2372605755
[24,] 0.72883197 0.5423360532 0.2711680266
[25,] 0.67907237 0.6418552520 0.3209276260
[26,] 0.64557222 0.7088555582 0.3544277791
[27,] 0.61348643 0.7730271384 0.3865135692
[28,] 0.56300930 0.8739813936 0.4369906968
[29,] 0.71136404 0.5772719122 0.2886359561
[30,] 0.70158942 0.5968211569 0.2984105784
[31,] 0.69540325 0.6091934952 0.3045967476
[32,] 0.69132092 0.6173581688 0.3086790844
[33,] 0.83802228 0.3239554405 0.1619777202
[34,] 0.82401082 0.3519783635 0.1759891817
[35,] 0.81744665 0.3651066943 0.1825533471
[36,] 0.85845316 0.2830936734 0.1415468367
[37,] 0.83969981 0.3206003869 0.1603001935
[38,] 0.88695368 0.2260926448 0.1130463224
[39,] 0.92281921 0.1543615745 0.0771807873
[40,] 0.91654570 0.1669085986 0.0834542993
[41,] 0.92182058 0.1563588441 0.0781794221
[42,] 0.91251172 0.1749765504 0.0874882752
[43,] 0.91351352 0.1729729519 0.0864864760
[44,] 0.91091795 0.1781641008 0.0890820504
[45,] 0.93673631 0.1265273879 0.0632636940
[46,] 0.92410472 0.1517905523 0.0758952761
[47,] 0.90931186 0.1813762788 0.0906881394
[48,] 0.91480683 0.1703863346 0.0851931673
[49,] 0.91309156 0.1738168840 0.0869084420
[50,] 0.94234400 0.1153119980 0.0576559990
[51,] 0.94357495 0.1128501018 0.0564250509
[52,] 0.93012265 0.1397546983 0.0698773491
[53,] 0.93519442 0.1296111698 0.0648055849
[54,] 0.91950504 0.1609899284 0.0804949642
[55,] 0.90562575 0.1887484906 0.0943742453
[56,] 0.91111543 0.1777691450 0.0888845725
[57,] 0.89637101 0.2072579701 0.1036289850
[58,] 0.93223953 0.1355209324 0.0677604662
[59,] 0.92669894 0.1466021287 0.0733010644
[60,] 0.92821323 0.1435735326 0.0717867663
[61,] 0.91523902 0.1695219549 0.0847609775
[62,] 0.95996644 0.0800671265 0.0400335633
[63,] 0.95973644 0.0805271289 0.0402635645
[64,] 0.96266598 0.0746680475 0.0373340238
[65,] 0.97162830 0.0567433979 0.0283716989
[66,] 0.97221681 0.0555663872 0.0277831936
[67,] 0.99798443 0.0040311318 0.0020155659
[68,] 0.99908461 0.0018307745 0.0009153873
[69,] 0.99892195 0.0021560973 0.0010780487
[70,] 0.99953215 0.0009356936 0.0004678468
[71,] 0.99963734 0.0007253170 0.0003626585
[72,] 0.99959153 0.0008169381 0.0004084690
[73,] 0.99947458 0.0010508318 0.0005254159
[74,] 0.99946035 0.0010792912 0.0005396456
[75,] 0.99929364 0.0014127183 0.0007063592
[76,] 0.99916260 0.0016748097 0.0008374049
[77,] 0.99890526 0.0021894857 0.0010947428
[78,] 0.99874357 0.0025128541 0.0012564271
[79,] 0.99919860 0.0016027941 0.0008013971
[80,] 0.99905261 0.0018947896 0.0009473948
[81,] 0.99944127 0.0011174615 0.0005587307
[82,] 0.99943124 0.0011375157 0.0005687578
[83,] 0.99936670 0.0012665950 0.0006332975
[84,] 0.99929194 0.0014161206 0.0007080603
[85,] 0.99903469 0.0019306245 0.0009653122
[86,] 0.99892041 0.0021591853 0.0010795926
[87,] 0.99858377 0.0028324547 0.0014162273
[88,] 0.99828555 0.0034288932 0.0017144466
[89,] 0.99887249 0.0022550239 0.0011275120
[90,] 0.99870109 0.0025978106 0.0012989053
[91,] 0.99853729 0.0029254111 0.0014627056
[92,] 0.99863682 0.0027263517 0.0013631759
[93,] 0.99802521 0.0039495805 0.0019747903
[94,] 0.99826875 0.0034624951 0.0017312476
[95,] 0.99771749 0.0045650245 0.0022825123
[96,] 0.99672123 0.0065575357 0.0032787678
[97,] 0.99583438 0.0083312324 0.0041656162
[98,] 0.99875180 0.0024964050 0.0012482025
[99,] 0.99814659 0.0037068122 0.0018534061
[100,] 0.99760627 0.0047874664 0.0023937332
[101,] 0.99671206 0.0065758883 0.0032879441
[102,] 0.99582845 0.0083431092 0.0041715546
[103,] 0.99627072 0.0074585605 0.0037292802
[104,] 0.99466103 0.0106779473 0.0053389737
[105,] 0.99504613 0.0099077328 0.0049538664
[106,] 0.99466761 0.0106647789 0.0053323894
[107,] 0.99359371 0.0128125815 0.0064062907
[108,] 0.99083897 0.0183220563 0.0091610281
[109,] 0.99200685 0.0159862908 0.0079931454
[110,] 0.98934466 0.0213106724 0.0106553362
[111,] 0.98507234 0.0298553102 0.0149276551
[112,] 0.98389472 0.0322105520 0.0161052760
[113,] 0.97821745 0.0435651069 0.0217825534
[114,] 0.97047530 0.0590493930 0.0295246965
[115,] 0.97605514 0.0478897104 0.0239448552
[116,] 0.96696242 0.0660751551 0.0330375776
[117,] 0.96236406 0.0752718731 0.0376359366
[118,] 0.94994139 0.1001172100 0.0500586050
[119,] 0.93348282 0.1330343663 0.0665171832
[120,] 0.91392827 0.1721434560 0.0860717280
[121,] 0.90767746 0.1846450817 0.0923225409
[122,] 0.92854641 0.1429071787 0.0714535894
[123,] 0.92177519 0.1564496237 0.0782248118
[124,] 0.95927239 0.0814552210 0.0407276105
[125,] 0.94431507 0.1113698554 0.0556849277
[126,] 0.93900439 0.1219912155 0.0609956077
[127,] 0.92656761 0.1468647888 0.0734323944
[128,] 0.90155941 0.1968811781 0.0984405891
[129,] 0.90043974 0.1991205241 0.0995602620
[130,] 0.87100745 0.2579851053 0.1289925526
[131,] 0.86545438 0.2690912401 0.1345456201
[132,] 0.85719510 0.2856098019 0.1428049010
[133,] 0.82064762 0.3587047602 0.1793523801
[134,] 0.91411942 0.1717611596 0.0858805798
[135,] 0.87953075 0.2409385086 0.1204692543
[136,] 0.86442311 0.2711537743 0.1355768872
[137,] 0.87915204 0.2416959118 0.1208479559
[138,] 0.90520832 0.1895833650 0.0947916825
[139,] 0.86704286 0.2659142748 0.1329571374
[140,] 0.84230290 0.3153942046 0.1576971023
[141,] 0.99447473 0.0110505353 0.0055252677
[142,] 0.99409072 0.0118185516 0.0059092758
[143,] 0.98738701 0.0252259862 0.0126129931
[144,] 0.97896426 0.0420714855 0.0210357428
[145,] 0.99480540 0.0103891975 0.0051945987
[146,] 0.99945886 0.0010822802 0.0005411401
[147,] 0.99883092 0.0023381536 0.0011690768
[148,] 0.99598193 0.0080361416 0.0040180708
[149,] 0.99629014 0.0074197226 0.0037098613
> postscript(file="/var/www/html/freestat/rcomp/tmp/1m2dv1291114246.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$resid)
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/freestat/rcomp/tmp/2m2dv1291114246.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> plot(mysum$resid, type='b', pch=19, main='Residuals', ylab='value of Residuals', xlab='time or index')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/freestat/rcomp/tmp/3fbcg1291114246.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> hist(mysum$resid, main='Residual Histogram', xlab='values of Residuals')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/freestat/rcomp/tmp/4fbcg1291114246.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> densityplot(~mysum$resid,col='black',main='Residual Density Plot', xlab='values of Residuals')
> dev.off()
null device
1
> postscript(file="/var/www/html/freestat/rcomp/tmp/5fbcg1291114246.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 = 180
Frequency = 1
1 2 3 4 5 6
-140.472917 62.127083 75.327083 -379.206250 167.860417 -45.406250
7 8 9 10 11 12
-105.072917 51.993750 -54.539583 -69.872917 107.527083 -221.939583
13 14 15 16 17 18
400.061310 197.661310 54.861310 118.327976 185.394643 -171.872024
19 20 21 22 23 24
-88.538690 21.527976 24.994643 78.661310 -190.938690 -234.405357
25 26 27 28 29 30
156.595536 207.195536 -464.604464 308.862202 -104.071131 -76.337798
31 32 33 34 35 36
218.995536 -375.937798 268.528869 42.195536 -388.404464 -281.871131
37 38 39 40 41 42
-600.870238 -138.270238 -215.070238 -59.603571 -163.536905 -19.803571
43 44 45 46 47 48
8.529762 -582.403571 -227.936905 160.729762 11.129762 303.663095
49 50 51 52 53 54
-215.336012 -209.736012 222.463988 -154.069345 -399.002679 313.730655
55 56 57 58 59 60
-187.936012 54.130655 163.597321 -211.736012 129.663988 329.197321
61 62 63 64 65 66
7.198214 133.798214 261.998214 -188.535119 404.531548 -197.735119
67 68 69 70 71 72
4.598214 227.664881 103.131548 168.798214 296.198214 -61.268452
73 74 75 76 77 78
445.732440 245.332440 300.532440 165.999107 528.065774 280.799107
79 80 81 82 83 84
311.132440 375.199107 254.665774 686.332440 379.732440 -112.734226
85 86 87 88 89 90
359.266667 178.866667 -101.933333 -79.466667 55.600000 -52.666667
91 92 93 94 95 96
82.666667 88.733333 -64.800000 137.866667 -117.733333 -304.200000
97 98 99 100 101 102
79.800893 -37.599107 -177.399107 -91.932440 -19.865774 -120.132440
103 104 105 106 107 108
36.200893 -299.732440 -192.265774 -160.599107 -259.199107 -28.665774
109 110 111 112 113 114
-286.664881 -129.064881 7.135119 -101.398214 -477.331548 25.401786
115 116 117 118 119 120
-160.264881 -39.198214 -158.731548 -312.064881 -45.664881 271.868452
121 122 123 124 125 126
-207.130655 -209.530655 -24.330655 287.136012 -119.797321 43.936012
127 128 129 130 131 132
-189.730655 117.336012 27.802679 -322.530655 38.869345 205.402679
133 134 135 136 137 138
50.403571 -70.996429 60.203571 -124.329762 246.736905 145.470238
139 140 141 142 143 144
-316.196429 109.870238 -179.663095 -143.996429 64.403571 -119.063095
145 146 147 148 149 150
68.937798 -203.462202 184.737798 54.204464 237.271131 -45.995536
151 152 153 154 155 156
1.337798 281.404464 -192.128869 -42.462202 134.937798 -260.528869
157 158 159 160 161 162
91.472024 53.072024 -114.727976 321.738690 -120.194643 11.538690
163 164 165 166 167 168
221.872024 30.938690 102.405357 4.072024 -123.527976 233.005357
169 170 171 172 173 174
-208.993750 -79.393750 -69.193750 -77.727083 -421.660417 -90.927083
175 176 177 178 179 180
162.406250 -61.527083 124.939583 -15.393750 -36.993750 281.539583
> postscript(file="/var/www/html/freestat/rcomp/tmp/68kuj1291114246.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 = 180
Frequency = 1
lag(myerror, k = 1) myerror
0 -140.472917 NA
1 62.127083 -140.472917
2 75.327083 62.127083
3 -379.206250 75.327083
4 167.860417 -379.206250
5 -45.406250 167.860417
6 -105.072917 -45.406250
7 51.993750 -105.072917
8 -54.539583 51.993750
9 -69.872917 -54.539583
10 107.527083 -69.872917
11 -221.939583 107.527083
12 400.061310 -221.939583
13 197.661310 400.061310
14 54.861310 197.661310
15 118.327976 54.861310
16 185.394643 118.327976
17 -171.872024 185.394643
18 -88.538690 -171.872024
19 21.527976 -88.538690
20 24.994643 21.527976
21 78.661310 24.994643
22 -190.938690 78.661310
23 -234.405357 -190.938690
24 156.595536 -234.405357
25 207.195536 156.595536
26 -464.604464 207.195536
27 308.862202 -464.604464
28 -104.071131 308.862202
29 -76.337798 -104.071131
30 218.995536 -76.337798
31 -375.937798 218.995536
32 268.528869 -375.937798
33 42.195536 268.528869
34 -388.404464 42.195536
35 -281.871131 -388.404464
36 -600.870238 -281.871131
37 -138.270238 -600.870238
38 -215.070238 -138.270238
39 -59.603571 -215.070238
40 -163.536905 -59.603571
41 -19.803571 -163.536905
42 8.529762 -19.803571
43 -582.403571 8.529762
44 -227.936905 -582.403571
45 160.729762 -227.936905
46 11.129762 160.729762
47 303.663095 11.129762
48 -215.336012 303.663095
49 -209.736012 -215.336012
50 222.463988 -209.736012
51 -154.069345 222.463988
52 -399.002679 -154.069345
53 313.730655 -399.002679
54 -187.936012 313.730655
55 54.130655 -187.936012
56 163.597321 54.130655
57 -211.736012 163.597321
58 129.663988 -211.736012
59 329.197321 129.663988
60 7.198214 329.197321
61 133.798214 7.198214
62 261.998214 133.798214
63 -188.535119 261.998214
64 404.531548 -188.535119
65 -197.735119 404.531548
66 4.598214 -197.735119
67 227.664881 4.598214
68 103.131548 227.664881
69 168.798214 103.131548
70 296.198214 168.798214
71 -61.268452 296.198214
72 445.732440 -61.268452
73 245.332440 445.732440
74 300.532440 245.332440
75 165.999107 300.532440
76 528.065774 165.999107
77 280.799107 528.065774
78 311.132440 280.799107
79 375.199107 311.132440
80 254.665774 375.199107
81 686.332440 254.665774
82 379.732440 686.332440
83 -112.734226 379.732440
84 359.266667 -112.734226
85 178.866667 359.266667
86 -101.933333 178.866667
87 -79.466667 -101.933333
88 55.600000 -79.466667
89 -52.666667 55.600000
90 82.666667 -52.666667
91 88.733333 82.666667
92 -64.800000 88.733333
93 137.866667 -64.800000
94 -117.733333 137.866667
95 -304.200000 -117.733333
96 79.800893 -304.200000
97 -37.599107 79.800893
98 -177.399107 -37.599107
99 -91.932440 -177.399107
100 -19.865774 -91.932440
101 -120.132440 -19.865774
102 36.200893 -120.132440
103 -299.732440 36.200893
104 -192.265774 -299.732440
105 -160.599107 -192.265774
106 -259.199107 -160.599107
107 -28.665774 -259.199107
108 -286.664881 -28.665774
109 -129.064881 -286.664881
110 7.135119 -129.064881
111 -101.398214 7.135119
112 -477.331548 -101.398214
113 25.401786 -477.331548
114 -160.264881 25.401786
115 -39.198214 -160.264881
116 -158.731548 -39.198214
117 -312.064881 -158.731548
118 -45.664881 -312.064881
119 271.868452 -45.664881
120 -207.130655 271.868452
121 -209.530655 -207.130655
122 -24.330655 -209.530655
123 287.136012 -24.330655
124 -119.797321 287.136012
125 43.936012 -119.797321
126 -189.730655 43.936012
127 117.336012 -189.730655
128 27.802679 117.336012
129 -322.530655 27.802679
130 38.869345 -322.530655
131 205.402679 38.869345
132 50.403571 205.402679
133 -70.996429 50.403571
134 60.203571 -70.996429
135 -124.329762 60.203571
136 246.736905 -124.329762
137 145.470238 246.736905
138 -316.196429 145.470238
139 109.870238 -316.196429
140 -179.663095 109.870238
141 -143.996429 -179.663095
142 64.403571 -143.996429
143 -119.063095 64.403571
144 68.937798 -119.063095
145 -203.462202 68.937798
146 184.737798 -203.462202
147 54.204464 184.737798
148 237.271131 54.204464
149 -45.995536 237.271131
150 1.337798 -45.995536
151 281.404464 1.337798
152 -192.128869 281.404464
153 -42.462202 -192.128869
154 134.937798 -42.462202
155 -260.528869 134.937798
156 91.472024 -260.528869
157 53.072024 91.472024
158 -114.727976 53.072024
159 321.738690 -114.727976
160 -120.194643 321.738690
161 11.538690 -120.194643
162 221.872024 11.538690
163 30.938690 221.872024
164 102.405357 30.938690
165 4.072024 102.405357
166 -123.527976 4.072024
167 233.005357 -123.527976
168 -208.993750 233.005357
169 -79.393750 -208.993750
170 -69.193750 -79.393750
171 -77.727083 -69.193750
172 -421.660417 -77.727083
173 -90.927083 -421.660417
174 162.406250 -90.927083
175 -61.527083 162.406250
176 124.939583 -61.527083
177 -15.393750 124.939583
178 -36.993750 -15.393750
179 281.539583 -36.993750
180 NA 281.539583
> dum1 <- dum[2:length(myerror),]
> dum1
lag(myerror, k = 1) myerror
[1,] 62.127083 -140.472917
[2,] 75.327083 62.127083
[3,] -379.206250 75.327083
[4,] 167.860417 -379.206250
[5,] -45.406250 167.860417
[6,] -105.072917 -45.406250
[7,] 51.993750 -105.072917
[8,] -54.539583 51.993750
[9,] -69.872917 -54.539583
[10,] 107.527083 -69.872917
[11,] -221.939583 107.527083
[12,] 400.061310 -221.939583
[13,] 197.661310 400.061310
[14,] 54.861310 197.661310
[15,] 118.327976 54.861310
[16,] 185.394643 118.327976
[17,] -171.872024 185.394643
[18,] -88.538690 -171.872024
[19,] 21.527976 -88.538690
[20,] 24.994643 21.527976
[21,] 78.661310 24.994643
[22,] -190.938690 78.661310
[23,] -234.405357 -190.938690
[24,] 156.595536 -234.405357
[25,] 207.195536 156.595536
[26,] -464.604464 207.195536
[27,] 308.862202 -464.604464
[28,] -104.071131 308.862202
[29,] -76.337798 -104.071131
[30,] 218.995536 -76.337798
[31,] -375.937798 218.995536
[32,] 268.528869 -375.937798
[33,] 42.195536 268.528869
[34,] -388.404464 42.195536
[35,] -281.871131 -388.404464
[36,] -600.870238 -281.871131
[37,] -138.270238 -600.870238
[38,] -215.070238 -138.270238
[39,] -59.603571 -215.070238
[40,] -163.536905 -59.603571
[41,] -19.803571 -163.536905
[42,] 8.529762 -19.803571
[43,] -582.403571 8.529762
[44,] -227.936905 -582.403571
[45,] 160.729762 -227.936905
[46,] 11.129762 160.729762
[47,] 303.663095 11.129762
[48,] -215.336012 303.663095
[49,] -209.736012 -215.336012
[50,] 222.463988 -209.736012
[51,] -154.069345 222.463988
[52,] -399.002679 -154.069345
[53,] 313.730655 -399.002679
[54,] -187.936012 313.730655
[55,] 54.130655 -187.936012
[56,] 163.597321 54.130655
[57,] -211.736012 163.597321
[58,] 129.663988 -211.736012
[59,] 329.197321 129.663988
[60,] 7.198214 329.197321
[61,] 133.798214 7.198214
[62,] 261.998214 133.798214
[63,] -188.535119 261.998214
[64,] 404.531548 -188.535119
[65,] -197.735119 404.531548
[66,] 4.598214 -197.735119
[67,] 227.664881 4.598214
[68,] 103.131548 227.664881
[69,] 168.798214 103.131548
[70,] 296.198214 168.798214
[71,] -61.268452 296.198214
[72,] 445.732440 -61.268452
[73,] 245.332440 445.732440
[74,] 300.532440 245.332440
[75,] 165.999107 300.532440
[76,] 528.065774 165.999107
[77,] 280.799107 528.065774
[78,] 311.132440 280.799107
[79,] 375.199107 311.132440
[80,] 254.665774 375.199107
[81,] 686.332440 254.665774
[82,] 379.732440 686.332440
[83,] -112.734226 379.732440
[84,] 359.266667 -112.734226
[85,] 178.866667 359.266667
[86,] -101.933333 178.866667
[87,] -79.466667 -101.933333
[88,] 55.600000 -79.466667
[89,] -52.666667 55.600000
[90,] 82.666667 -52.666667
[91,] 88.733333 82.666667
[92,] -64.800000 88.733333
[93,] 137.866667 -64.800000
[94,] -117.733333 137.866667
[95,] -304.200000 -117.733333
[96,] 79.800893 -304.200000
[97,] -37.599107 79.800893
[98,] -177.399107 -37.599107
[99,] -91.932440 -177.399107
[100,] -19.865774 -91.932440
[101,] -120.132440 -19.865774
[102,] 36.200893 -120.132440
[103,] -299.732440 36.200893
[104,] -192.265774 -299.732440
[105,] -160.599107 -192.265774
[106,] -259.199107 -160.599107
[107,] -28.665774 -259.199107
[108,] -286.664881 -28.665774
[109,] -129.064881 -286.664881
[110,] 7.135119 -129.064881
[111,] -101.398214 7.135119
[112,] -477.331548 -101.398214
[113,] 25.401786 -477.331548
[114,] -160.264881 25.401786
[115,] -39.198214 -160.264881
[116,] -158.731548 -39.198214
[117,] -312.064881 -158.731548
[118,] -45.664881 -312.064881
[119,] 271.868452 -45.664881
[120,] -207.130655 271.868452
[121,] -209.530655 -207.130655
[122,] -24.330655 -209.530655
[123,] 287.136012 -24.330655
[124,] -119.797321 287.136012
[125,] 43.936012 -119.797321
[126,] -189.730655 43.936012
[127,] 117.336012 -189.730655
[128,] 27.802679 117.336012
[129,] -322.530655 27.802679
[130,] 38.869345 -322.530655
[131,] 205.402679 38.869345
[132,] 50.403571 205.402679
[133,] -70.996429 50.403571
[134,] 60.203571 -70.996429
[135,] -124.329762 60.203571
[136,] 246.736905 -124.329762
[137,] 145.470238 246.736905
[138,] -316.196429 145.470238
[139,] 109.870238 -316.196429
[140,] -179.663095 109.870238
[141,] -143.996429 -179.663095
[142,] 64.403571 -143.996429
[143,] -119.063095 64.403571
[144,] 68.937798 -119.063095
[145,] -203.462202 68.937798
[146,] 184.737798 -203.462202
[147,] 54.204464 184.737798
[148,] 237.271131 54.204464
[149,] -45.995536 237.271131
[150,] 1.337798 -45.995536
[151,] 281.404464 1.337798
[152,] -192.128869 281.404464
[153,] -42.462202 -192.128869
[154,] 134.937798 -42.462202
[155,] -260.528869 134.937798
[156,] 91.472024 -260.528869
[157,] 53.072024 91.472024
[158,] -114.727976 53.072024
[159,] 321.738690 -114.727976
[160,] -120.194643 321.738690
[161,] 11.538690 -120.194643
[162,] 221.872024 11.538690
[163,] 30.938690 221.872024
[164,] 102.405357 30.938690
[165,] 4.072024 102.405357
[166,] -123.527976 4.072024
[167,] 233.005357 -123.527976
[168,] -208.993750 233.005357
[169,] -79.393750 -208.993750
[170,] -69.193750 -79.393750
[171,] -77.727083 -69.193750
[172,] -421.660417 -77.727083
[173,] -90.927083 -421.660417
[174,] 162.406250 -90.927083
[175,] -61.527083 162.406250
[176,] 124.939583 -61.527083
[177,] -15.393750 124.939583
[178,] -36.993750 -15.393750
[179,] 281.539583 -36.993750
> z <- as.data.frame(dum1)
> z
lag(myerror, k = 1) myerror
1 62.127083 -140.472917
2 75.327083 62.127083
3 -379.206250 75.327083
4 167.860417 -379.206250
5 -45.406250 167.860417
6 -105.072917 -45.406250
7 51.993750 -105.072917
8 -54.539583 51.993750
9 -69.872917 -54.539583
10 107.527083 -69.872917
11 -221.939583 107.527083
12 400.061310 -221.939583
13 197.661310 400.061310
14 54.861310 197.661310
15 118.327976 54.861310
16 185.394643 118.327976
17 -171.872024 185.394643
18 -88.538690 -171.872024
19 21.527976 -88.538690
20 24.994643 21.527976
21 78.661310 24.994643
22 -190.938690 78.661310
23 -234.405357 -190.938690
24 156.595536 -234.405357
25 207.195536 156.595536
26 -464.604464 207.195536
27 308.862202 -464.604464
28 -104.071131 308.862202
29 -76.337798 -104.071131
30 218.995536 -76.337798
31 -375.937798 218.995536
32 268.528869 -375.937798
33 42.195536 268.528869
34 -388.404464 42.195536
35 -281.871131 -388.404464
36 -600.870238 -281.871131
37 -138.270238 -600.870238
38 -215.070238 -138.270238
39 -59.603571 -215.070238
40 -163.536905 -59.603571
41 -19.803571 -163.536905
42 8.529762 -19.803571
43 -582.403571 8.529762
44 -227.936905 -582.403571
45 160.729762 -227.936905
46 11.129762 160.729762
47 303.663095 11.129762
48 -215.336012 303.663095
49 -209.736012 -215.336012
50 222.463988 -209.736012
51 -154.069345 222.463988
52 -399.002679 -154.069345
53 313.730655 -399.002679
54 -187.936012 313.730655
55 54.130655 -187.936012
56 163.597321 54.130655
57 -211.736012 163.597321
58 129.663988 -211.736012
59 329.197321 129.663988
60 7.198214 329.197321
61 133.798214 7.198214
62 261.998214 133.798214
63 -188.535119 261.998214
64 404.531548 -188.535119
65 -197.735119 404.531548
66 4.598214 -197.735119
67 227.664881 4.598214
68 103.131548 227.664881
69 168.798214 103.131548
70 296.198214 168.798214
71 -61.268452 296.198214
72 445.732440 -61.268452
73 245.332440 445.732440
74 300.532440 245.332440
75 165.999107 300.532440
76 528.065774 165.999107
77 280.799107 528.065774
78 311.132440 280.799107
79 375.199107 311.132440
80 254.665774 375.199107
81 686.332440 254.665774
82 379.732440 686.332440
83 -112.734226 379.732440
84 359.266667 -112.734226
85 178.866667 359.266667
86 -101.933333 178.866667
87 -79.466667 -101.933333
88 55.600000 -79.466667
89 -52.666667 55.600000
90 82.666667 -52.666667
91 88.733333 82.666667
92 -64.800000 88.733333
93 137.866667 -64.800000
94 -117.733333 137.866667
95 -304.200000 -117.733333
96 79.800893 -304.200000
97 -37.599107 79.800893
98 -177.399107 -37.599107
99 -91.932440 -177.399107
100 -19.865774 -91.932440
101 -120.132440 -19.865774
102 36.200893 -120.132440
103 -299.732440 36.200893
104 -192.265774 -299.732440
105 -160.599107 -192.265774
106 -259.199107 -160.599107
107 -28.665774 -259.199107
108 -286.664881 -28.665774
109 -129.064881 -286.664881
110 7.135119 -129.064881
111 -101.398214 7.135119
112 -477.331548 -101.398214
113 25.401786 -477.331548
114 -160.264881 25.401786
115 -39.198214 -160.264881
116 -158.731548 -39.198214
117 -312.064881 -158.731548
118 -45.664881 -312.064881
119 271.868452 -45.664881
120 -207.130655 271.868452
121 -209.530655 -207.130655
122 -24.330655 -209.530655
123 287.136012 -24.330655
124 -119.797321 287.136012
125 43.936012 -119.797321
126 -189.730655 43.936012
127 117.336012 -189.730655
128 27.802679 117.336012
129 -322.530655 27.802679
130 38.869345 -322.530655
131 205.402679 38.869345
132 50.403571 205.402679
133 -70.996429 50.403571
134 60.203571 -70.996429
135 -124.329762 60.203571
136 246.736905 -124.329762
137 145.470238 246.736905
138 -316.196429 145.470238
139 109.870238 -316.196429
140 -179.663095 109.870238
141 -143.996429 -179.663095
142 64.403571 -143.996429
143 -119.063095 64.403571
144 68.937798 -119.063095
145 -203.462202 68.937798
146 184.737798 -203.462202
147 54.204464 184.737798
148 237.271131 54.204464
149 -45.995536 237.271131
150 1.337798 -45.995536
151 281.404464 1.337798
152 -192.128869 281.404464
153 -42.462202 -192.128869
154 134.937798 -42.462202
155 -260.528869 134.937798
156 91.472024 -260.528869
157 53.072024 91.472024
158 -114.727976 53.072024
159 321.738690 -114.727976
160 -120.194643 321.738690
161 11.538690 -120.194643
162 221.872024 11.538690
163 30.938690 221.872024
164 102.405357 30.938690
165 4.072024 102.405357
166 -123.527976 4.072024
167 233.005357 -123.527976
168 -208.993750 233.005357
169 -79.393750 -208.993750
170 -69.193750 -79.393750
171 -77.727083 -69.193750
172 -421.660417 -77.727083
173 -90.927083 -421.660417
174 162.406250 -90.927083
175 -61.527083 162.406250
176 124.939583 -61.527083
177 -15.393750 124.939583
178 -36.993750 -15.393750
179 281.539583 -36.993750
> 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/78kuj1291114246.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> acf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/freestat/rcomp/tmp/8iub41291114246.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> pacf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Partial Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/freestat/rcomp/tmp/9iub41291114246.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> opar <- par(mfrow = c(2,2), oma = c(0, 0, 1.1, 0))
> plot(mylm, las = 1, sub='Residual Diagnostics')
> par(opar)
> dev.off()
null device
1
> if (n > n25) {
+ postscript(file="/var/www/html/freestat/rcomp/tmp/10iub41291114246.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
+ plot(kp3:nmkm3,gqarr[,2], main='Goldfeld-Quandt test',ylab='2-sided p-value',xlab='breakpoint')
+ grid()
+ dev.off()
+ }
null device
1
>
> #Note: the /var/www/html/freestat/rcomp/createtable file can be downloaded at http://www.wessa.net/cretab
> load(file="/var/www/html/freestat/rcomp/createtable")
>
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a, 'Multiple Linear Regression - Estimated Regression Equation', 1, TRUE)
> a<-table.row.end(a)
> myeq <- colnames(x)[1]
> myeq <- paste(myeq, '[t] = ', sep='')
> for (i in 1:k){
+ if (mysum$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/11xmrd1291114246.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/127vqy1291114246.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/13ew5a1291114246.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/147nmd1291114246.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/15an3i1291114246.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/16of1r1291114246.tab")
+ }
>
> try(system("convert tmp/1m2dv1291114246.ps tmp/1m2dv1291114246.png",intern=TRUE))
character(0)
> try(system("convert tmp/2m2dv1291114246.ps tmp/2m2dv1291114246.png",intern=TRUE))
character(0)
> try(system("convert tmp/3fbcg1291114246.ps tmp/3fbcg1291114246.png",intern=TRUE))
character(0)
> try(system("convert tmp/4fbcg1291114246.ps tmp/4fbcg1291114246.png",intern=TRUE))
character(0)
> try(system("convert tmp/5fbcg1291114246.ps tmp/5fbcg1291114246.png",intern=TRUE))
character(0)
> try(system("convert tmp/68kuj1291114246.ps tmp/68kuj1291114246.png",intern=TRUE))
character(0)
> try(system("convert tmp/78kuj1291114246.ps tmp/78kuj1291114246.png",intern=TRUE))
character(0)
> try(system("convert tmp/8iub41291114246.ps tmp/8iub41291114246.png",intern=TRUE))
character(0)
> try(system("convert tmp/9iub41291114246.ps tmp/9iub41291114246.png",intern=TRUE))
character(0)
> try(system("convert tmp/10iub41291114246.ps tmp/10iub41291114246.png",intern=TRUE))
character(0)
>
>
> proc.time()
user system elapsed
6.091 2.753 6.425