R version 2.12.0 (2010-10-15)
Copyright (C) 2010 The R Foundation for Statistical Computing
ISBN 3-900051-07-0
Platform: i486-pc-linux-gnu (32-bit)
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Type 'q()' to quit R.
> x <- array(list(65
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+ ,49)
+ ,dim=c(6
+ ,164)
+ ,dimnames=list(c('BloggedComputation'
+ ,'TotalTime'
+ ,'Shared'
+ ,'Charachters'
+ ,'Writing'
+ ,'Hyperlinks')
+ ,1:164))
> y <- array(NA,dim=c(6,164),dimnames=list(c('BloggedComputation','TotalTime','Shared','Charachters','Writing','Hyperlinks'),1:164))
> 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 = 'Do not include Seasonal Dummies'
> par1 = '4'
> library(lattice)
> library(lmtest)
Loading required package: zoo
> 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
Charachters BloggedComputation TotalTime Shared Writing Hyperlinks t
1 95556 65 146455 1 114468 127 1
2 54565 54 84944 4 88594 90 2
3 63016 58 113337 9 74151 68 3
4 79774 75 128655 2 77921 111 4
5 31258 41 74398 1 53212 51 5
6 52491 0 35523 2 34956 33 6
7 91256 111 293403 0 149703 123 7
8 22807 1 32750 0 6853 5 8
9 77411 36 106539 5 58907 63 9
10 48821 60 130539 0 67067 66 10
11 52295 63 154991 0 110563 99 11
12 63262 71 126683 7 58126 72 12
13 50466 38 100672 6 57113 55 13
14 62932 76 179562 3 77993 116 14
15 38439 61 125971 4 68091 71 15
16 70817 125 234509 0 124676 125 16
17 105965 84 158980 4 109522 123 17
18 73795 69 184217 3 75865 74 18
19 82043 77 107342 0 79746 116 19
20 74349 95 141371 5 77844 117 20
21 82204 78 154730 0 98681 98 21
22 55709 76 264020 1 105531 101 22
23 37137 40 90938 3 51428 43 23
24 70780 81 101324 5 65703 103 24
25 55027 102 130232 0 72562 107 25
26 56699 70 137793 0 81728 77 26
27 65911 75 161678 4 95580 87 27
28 56316 93 151503 0 98278 99 28
29 26982 42 105324 0 46629 46 29
30 54628 95 175914 0 115189 96 30
31 96750 87 181853 3 124865 92 31
32 53009 44 114928 4 59392 96 32
33 64664 84 190410 1 127818 96 33
34 36990 28 61499 4 17821 15 34
35 85224 87 223004 1 154076 147 35
36 37048 71 167131 0 64881 56 36
37 59635 68 233482 0 136506 81 37
38 42051 50 121185 2 66524 69 38
39 26998 30 78776 1 45988 34 39
40 63717 86 188967 2 107445 98 40
41 55071 75 199512 8 102772 82 41
42 40001 46 102531 5 46657 64 42
43 54506 52 118958 3 97563 61 43
44 35838 31 68948 4 36663 45 44
45 50838 30 93125 1 55369 37 45
46 86997 70 277108 2 77921 64 46
47 33032 20 78800 2 56968 21 47
48 61704 84 157250 0 77519 104 48
49 117986 81 210554 6 129805 126 49
50 56733 79 127324 3 72761 104 50
51 55064 70 114397 0 81278 87 51
52 5950 8 24188 0 15049 7 52
53 84607 67 246209 6 113935 130 53
54 32551 21 65029 5 25109 21 54
55 31701 30 98030 3 45824 35 55
56 71170 70 173587 1 89644 97 56
57 101773 87 172684 5 109011 103 57
58 101653 87 191381 5 134245 210 58
59 81493 112 191276 0 136692 151 59
60 55901 54 134043 9 50741 57 60
61 109104 96 233406 6 149510 117 61
62 114425 93 195304 6 147888 152 62
63 36311 49 127619 5 54987 52 63
64 70027 49 162810 6 74467 83 64
65 73713 38 129100 2 100033 87 65
66 40671 64 108715 0 85505 80 66
67 89041 62 106469 3 62426 88 67
68 57231 66 142069 8 82932 83 68
69 78792 98 143937 2 79169 140 69
70 59155 97 84256 5 65469 76 70
71 55827 56 118807 11 63572 70 71
72 22618 22 69471 6 23824 26 72
73 58425 51 122433 5 73831 66 73
74 65724 56 131122 1 63551 89 74
75 56979 94 94763 0 56756 100 75
76 72369 98 188780 3 81399 98 76
77 79194 76 191467 3 117881 109 77
78 202316 57 105615 6 70711 51 78
79 44970 75 89318 1 50495 82 79
80 49319 48 107335 0 53845 65 80
81 36252 48 98599 1 51390 46 81
82 75741 109 260646 0 104953 104 82
83 38417 27 131876 5 65983 36 83
84 64102 83 119291 2 76839 123 84
85 56622 49 80953 0 55792 59 85
86 15430 24 99768 0 25155 27 86
87 72571 43 84572 5 55291 84 87
88 67271 44 202373 1 84279 61 88
89 43460 49 166790 0 99692 46 89
90 99501 106 99946 1 59633 125 90
91 28340 42 116900 1 63249 58 91
92 76013 108 142146 2 82928 152 92
93 37361 27 99246 4 50000 52 93
94 48204 79 156833 1 69455 85 94
95 76168 49 175078 4 84068 95 95
96 85168 64 130533 0 76195 78 96
97 125410 75 142339 2 114634 144 97
98 123328 115 176789 0 139357 149 98
99 83038 92 181379 7 110044 101 99
100 120087 106 228548 7 155118 205 100
101 91939 73 142141 6 83061 61 101
102 103646 105 167845 0 127122 145 102
103 29467 30 103012 0 45653 28 103
104 43750 13 43287 4 19630 49 104
105 34497 69 125366 4 67229 68 105
106 66477 72 118372 0 86060 142 106
107 71181 80 135171 0 88003 82 107
108 74482 106 175568 0 95815 105 108
109 174949 28 74112 0 85499 52 109
110 46765 70 88817 0 27220 56 110
111 90257 51 164767 4 109882 81 111
112 51370 90 141933 0 72579 100 112
113 1168 12 22938 0 5841 11 113
114 51360 84 115199 0 68369 87 114
115 25162 23 61857 4 24610 31 115
116 21067 57 91185 0 30995 67 116
117 58233 84 213765 1 150662 150 117
118 855 4 21054 0 6622 4 118
119 85903 56 167105 5 93694 75 119
120 14116 18 31414 0 13155 39 120
121 57637 86 178863 1 111908 88 121
122 94137 39 126681 7 57550 67 122
123 62147 16 64320 5 16356 24 123
124 62832 18 67746 2 40174 58 124
125 8773 16 38214 0 13983 16 125
126 63785 42 90961 1 52316 49 126
127 65196 75 181510 0 99585 109 127
128 73087 30 116775 0 86271 124 128
129 72631 104 223914 2 131012 115 129
130 86281 121 185139 0 130274 128 130
131 162365 106 242879 2 159051 159 131
132 56530 57 139144 0 76506 75 132
133 35606 28 75812 0 49145 30 133
134 70111 56 178218 4 66398 83 134
135 92046 81 246834 4 127546 135 135
136 63989 2 50999 8 6802 8 136
137 104911 88 223842 0 99509 115 137
138 43448 41 93577 4 43106 60 138
139 60029 83 155383 0 108303 99 139
140 38650 55 111664 1 64167 98 140
141 47261 3 75426 0 8579 36 141
142 73586 54 243551 9 97811 93 142
143 83042 89 136548 0 84365 158 143
144 37238 41 173260 3 10901 16 144
145 63958 94 185039 7 91346 100 145
146 78956 101 67507 5 33660 49 146
147 99518 70 139350 2 93634 89 147
148 111436 111 172964 1 109348 153 148
149 0 0 0 9 0 0 149
150 6023 4 14688 0 7953 5 150
151 0 0 98 0 0 0 151
152 0 0 455 0 0 0 152
153 0 0 0 1 0 0 153
154 0 0 0 0 0 0 154
155 42564 42 128066 2 63538 80 155
156 38885 97 176460 1 108281 122 156
157 0 0 0 0 0 0 157
158 0 0 203 0 0 0 158
159 1644 7 7199 0 4245 6 159
160 6179 12 46660 0 21509 13 160
161 3926 0 17547 0 7670 3 161
162 23238 37 73567 0 10641 18 162
163 0 0 969 0 0 0 163
164 49288 39 101060 2 41243 49 164
> k <- length(x[1,])
> df <- as.data.frame(x)
> (mylm <- lm(df))
Call:
lm(formula = df)
Coefficients:
(Intercept) BloggedComputation TotalTime Shared
4792.85969 74.05169 -0.05308 2588.89390
Writing Hyperlinks t
0.44302 205.63412 42.21277
> (mysum <- summary(mylm))
Call:
lm(formula = df)
Residuals:
Min 1Q Median 3Q Max
-46553 -11651 -5860 10196 138268
Coefficients:
Estimate Std. Error t value Pr(>|t|)
(Intercept) 4792.85969 5943.14372 0.806 0.421202
BloggedComputation 74.05169 113.13465 0.655 0.513719
TotalTime -0.05308 0.05889 -0.901 0.368811
Shared 2588.89390 678.58744 3.815 0.000195 ***
Writing 0.44302 0.11809 3.752 0.000247 ***
Hyperlinks 205.63412 93.05624 2.210 0.028567 *
t 42.21277 38.45448 1.098 0.274002
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
Residual standard error: 21870 on 157 degrees of freedom
Multiple R-squared: 0.5904, Adjusted R-squared: 0.5748
F-statistic: 37.72 on 6 and 157 DF, p-value: < 2.2e-16
> if (n > n25) {
+ kp3 <- k + 3
+ nmkm3 <- n - k - 3
+ gqarr <- array(NA, dim=c(nmkm3-kp3+1,3))
+ numgqtests <- 0
+ numsignificant1 <- 0
+ numsignificant5 <- 0
+ numsignificant10 <- 0
+ for (mypoint in kp3:nmkm3) {
+ j <- 0
+ numgqtests <- numgqtests + 1
+ for (myalt in c('greater', 'two.sided', 'less')) {
+ j <- j + 1
+ gqarr[mypoint-kp3+1,j] <- gqtest(mylm, point=mypoint, alternative=myalt)$p.value
+ }
+ if (gqarr[mypoint-kp3+1,2] < 0.01) numsignificant1 <- numsignificant1 + 1
+ if (gqarr[mypoint-kp3+1,2] < 0.05) numsignificant5 <- numsignificant5 + 1
+ if (gqarr[mypoint-kp3+1,2] < 0.10) numsignificant10 <- numsignificant10 + 1
+ }
+ gqarr
+ }
[,1] [,2] [,3]
[1,] 1.150091e-03 2.300181e-03 9.988499e-01
[2,] 6.902179e-03 1.380436e-02 9.930978e-01
[3,] 1.507889e-03 3.015778e-03 9.984921e-01
[4,] 8.052298e-04 1.610460e-03 9.991948e-01
[5,] 3.208059e-02 6.416117e-02 9.679194e-01
[6,] 1.498422e-02 2.996844e-02 9.850158e-01
[7,] 1.888563e-02 3.777125e-02 9.811144e-01
[8,] 8.146504e-02 1.629301e-01 9.185350e-01
[9,] 6.170855e-02 1.234171e-01 9.382915e-01
[10,] 5.006602e-02 1.001320e-01 9.499340e-01
[11,] 3.025562e-02 6.051124e-02 9.697444e-01
[12,] 2.387987e-02 4.775973e-02 9.761201e-01
[13,] 3.290702e-02 6.581403e-02 9.670930e-01
[14,] 2.143001e-02 4.286002e-02 9.785700e-01
[15,] 1.273226e-02 2.546453e-02 9.872677e-01
[16,] 7.854688e-03 1.570938e-02 9.921453e-01
[17,] 4.477728e-03 8.955456e-03 9.955223e-01
[18,] 2.475058e-03 4.950115e-03 9.975249e-01
[19,] 1.443184e-03 2.886369e-03 9.985568e-01
[20,] 9.086112e-04 1.817222e-03 9.990914e-01
[21,] 5.252732e-04 1.050546e-03 9.994747e-01
[22,] 1.096054e-03 2.192107e-03 9.989039e-01
[23,] 1.003559e-03 2.007118e-03 9.989964e-01
[24,] 6.387002e-04 1.277400e-03 9.993613e-01
[25,] 4.864412e-04 9.728825e-04 9.995136e-01
[26,] 3.340443e-04 6.680887e-04 9.996660e-01
[27,] 1.794922e-04 3.589843e-04 9.998205e-01
[28,] 1.028533e-04 2.057065e-04 9.998971e-01
[29,] 5.993247e-05 1.198649e-04 9.999401e-01
[30,] 3.171178e-05 6.342355e-05 9.999683e-01
[31,] 1.656099e-05 3.312198e-05 9.999834e-01
[32,] 1.445941e-05 2.891881e-05 9.999855e-01
[33,] 7.726891e-06 1.545378e-05 9.999923e-01
[34,] 4.129571e-06 8.259142e-06 9.999959e-01
[35,] 2.006170e-06 4.012340e-06 9.999980e-01
[36,] 2.356527e-06 4.713054e-06 9.999976e-01
[37,] 3.020488e-05 6.040976e-05 9.999698e-01
[38,] 1.660128e-05 3.320255e-05 9.999834e-01
[39,] 8.831236e-06 1.766247e-05 9.999912e-01
[40,] 2.044935e-05 4.089871e-05 9.999796e-01
[41,] 1.234440e-05 2.468880e-05 9.999877e-01
[42,] 6.757534e-06 1.351507e-05 9.999932e-01
[43,] 4.066946e-06 8.133891e-06 9.999959e-01
[44,] 2.699112e-06 5.398225e-06 9.999973e-01
[45,] 1.406249e-06 2.812497e-06 9.999986e-01
[46,] 7.620455e-07 1.524091e-06 9.999992e-01
[47,] 4.476271e-07 8.952542e-07 9.999996e-01
[48,] 9.808401e-07 1.961680e-06 9.999990e-01
[49,] 8.797612e-07 1.759522e-06 9.999991e-01
[50,] 5.227948e-07 1.045590e-06 9.999995e-01
[51,] 2.703780e-07 5.407559e-07 9.999997e-01
[52,] 2.226415e-07 4.452831e-07 9.999998e-01
[53,] 1.451629e-07 2.903259e-07 9.999999e-01
[54,] 1.108738e-07 2.217475e-07 9.999999e-01
[55,] 5.661821e-08 1.132364e-07 9.999999e-01
[56,] 3.313452e-08 6.626904e-08 1.000000e+00
[57,] 2.707965e-08 5.415931e-08 1.000000e+00
[58,] 1.307539e-07 2.615079e-07 9.999999e-01
[59,] 1.319250e-07 2.638500e-07 9.999999e-01
[60,] 6.962855e-08 1.392571e-07 9.999999e-01
[61,] 4.217339e-08 8.434679e-08 1.000000e+00
[62,] 4.214328e-08 8.428656e-08 1.000000e+00
[63,] 3.453963e-08 6.907926e-08 1.000000e+00
[64,] 2.098024e-08 4.196048e-08 1.000000e+00
[65,] 1.323690e-08 2.647379e-08 1.000000e+00
[66,] 6.953785e-09 1.390757e-08 1.000000e+00
[67,] 3.708764e-09 7.417528e-09 1.000000e+00
[68,] 2.118395e-09 4.236790e-09 1.000000e+00
[69,] 2.791725e-01 5.583451e-01 7.208275e-01
[70,] 2.487490e-01 4.974981e-01 7.512510e-01
[71,] 2.136186e-01 4.272373e-01 7.863814e-01
[72,] 1.877966e-01 3.755933e-01 8.122034e-01
[73,] 1.585008e-01 3.170015e-01 8.414992e-01
[74,] 1.528840e-01 3.057680e-01 8.471160e-01
[75,] 1.348763e-01 2.697526e-01 8.651237e-01
[76,] 1.142002e-01 2.284003e-01 8.857998e-01
[77,] 9.938642e-02 1.987728e-01 9.006136e-01
[78,] 8.251924e-02 1.650385e-01 9.174808e-01
[79,] 6.893301e-02 1.378660e-01 9.310670e-01
[80,] 6.584335e-02 1.316867e-01 9.341567e-01
[81,] 8.134875e-02 1.626975e-01 9.186513e-01
[82,] 8.925112e-02 1.785022e-01 9.107489e-01
[83,] 7.400245e-02 1.480049e-01 9.259975e-01
[84,] 6.920573e-02 1.384115e-01 9.307943e-01
[85,] 6.115738e-02 1.223148e-01 9.388426e-01
[86,] 4.949307e-02 9.898614e-02 9.505069e-01
[87,] 5.051223e-02 1.010245e-01 9.494878e-01
[88,] 6.058370e-02 1.211674e-01 9.394163e-01
[89,] 5.711664e-02 1.142333e-01 9.428834e-01
[90,] 5.097576e-02 1.019515e-01 9.490242e-01
[91,] 4.543890e-02 9.087780e-02 9.545611e-01
[92,] 3.894685e-02 7.789370e-02 9.610531e-01
[93,] 3.041203e-02 6.082407e-02 9.695880e-01
[94,] 2.493034e-02 4.986069e-02 9.750697e-01
[95,] 1.876536e-02 3.753072e-02 9.812346e-01
[96,] 2.747783e-02 5.495567e-02 9.725222e-01
[97,] 2.293835e-02 4.587671e-02 9.770616e-01
[98,] 1.722701e-02 3.445402e-02 9.827730e-01
[99,] 1.280066e-02 2.560131e-02 9.871993e-01
[100,] 8.511804e-01 2.976392e-01 1.488196e-01
[101,] 8.224774e-01 3.550452e-01 1.775226e-01
[102,] 8.032781e-01 3.934438e-01 1.967219e-01
[103,] 7.861308e-01 4.277385e-01 2.138692e-01
[104,] 7.733373e-01 4.533254e-01 2.266627e-01
[105,] 7.438328e-01 5.123345e-01 2.561672e-01
[106,] 7.279992e-01 5.440016e-01 2.720008e-01
[107,] 7.755105e-01 4.489790e-01 2.244895e-01
[108,] 8.897848e-01 2.204303e-01 1.102152e-01
[109,] 8.896474e-01 2.207052e-01 1.103526e-01
[110,] 8.651167e-01 2.697666e-01 1.348833e-01
[111,] 8.804951e-01 2.390097e-01 1.195049e-01
[112,] 8.882500e-01 2.235001e-01 1.117500e-01
[113,] 8.876820e-01 2.246360e-01 1.123180e-01
[114,] 8.797633e-01 2.404735e-01 1.202367e-01
[115,] 8.613992e-01 2.772016e-01 1.386008e-01
[116,] 8.653763e-01 2.692474e-01 1.346237e-01
[117,] 8.412392e-01 3.175215e-01 1.587608e-01
[118,] 8.312382e-01 3.375236e-01 1.687618e-01
[119,] 7.906706e-01 4.186589e-01 2.093294e-01
[120,] 8.163921e-01 3.672159e-01 1.836079e-01
[121,] 8.134897e-01 3.730207e-01 1.865103e-01
[122,] 9.620247e-01 7.595069e-02 3.797534e-02
[123,] 9.486068e-01 1.027864e-01 5.139318e-02
[124,] 9.300458e-01 1.399084e-01 6.995418e-02
[125,] 9.062227e-01 1.875547e-01 9.377734e-02
[126,] 8.746855e-01 2.506291e-01 1.253145e-01
[127,] 9.392515e-01 1.214970e-01 6.074849e-02
[128,] 9.386104e-01 1.227792e-01 6.138962e-02
[129,] 9.146620e-01 1.706761e-01 8.533804e-02
[130,] 8.999504e-01 2.000992e-01 1.000496e-01
[131,] 9.250649e-01 1.498703e-01 7.493514e-02
[132,] 9.297008e-01 1.405985e-01 7.029923e-02
[133,] 9.084006e-01 1.831988e-01 9.159939e-02
[134,] 8.697358e-01 2.605285e-01 1.302642e-01
[135,] 8.196417e-01 3.607166e-01 1.803583e-01
[136,] 8.288636e-01 3.422728e-01 1.711364e-01
[137,] 7.763511e-01 4.472978e-01 2.236489e-01
[138,] 9.973354e-01 5.329173e-03 2.664586e-03
[139,] 9.999390e-01 1.219079e-04 6.095396e-05
[140,] 9.999786e-01 4.280144e-05 2.140072e-05
[141,] 9.999624e-01 7.526763e-05 3.763381e-05
[142,] 9.998634e-01 2.732747e-04 1.366373e-04
[143,] 9.996251e-01 7.497348e-04 3.748674e-04
[144,] 9.999773e-01 4.546571e-05 2.273286e-05
[145,] 9.996040e-01 7.919617e-04 3.959809e-04
> postscript(file="/var/www/rcomp/tmp/1obh41321619320.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/rcomp/tmp/2lyy81321619320.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> plot(mysum$resid, type='b', pch=19, main='Residuals', ylab='value of Residuals', xlab='time or index')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/rcomp/tmp/32p6q1321619320.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> hist(mysum$resid, main='Residual Histogram', xlab='values of Residuals')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/rcomp/tmp/4pc531321619320.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> densityplot(~mysum$resid,col='black',main='Residual Density Plot', xlab='values of Residuals')
> dev.off()
null device
1
> postscript(file="/var/www/rcomp/tmp/5s5nt1321619320.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> qqnorm(mysum$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 = 164
Frequency = 1
1 2 3 4 5 6
14264.87045 -17914.05397 -10316.51200 13563.21517 -9483.46774 21880.39784
7 8 9 10 11 12
1906.20935 15276.42832 23230.65932 2807.55155 -18740.46720 749.86323
13 14 15 16 17 18
-4491.73414 -4722.02088 -19939.40893 -12399.09710 18503.27549 16316.93163
19 20 21 22 23 24
17260.83492 -2309.69128 15091.35421 -11737.62522 -6154.75030 1121.23668
25 26 27 28 29 30
-5611.48972 897.57256 -7583.80058 -12401.28239 -6671.76481 -19901.16925
31 32 33 34 35 36
11855.45594 -6701.29509 -16591.63066 10617.42178 -16728.38836 -5910.63785
37 38 39 40 41 42
-16494.13149 -10454.48669 -7435.62532 -12033.36215 -29520.32009 -11304.26514
43 44 45 46 47 48
-13171.51744 -5299.87680 12139.81909 36927.53131 -5777.52750 1282.39692
49 50 51 52 53 54
17352.49883 -10649.90284 -4891.47971 -8452.97202 -7058.06474 -1011.53155
55 56 57 58 59 60
-7696.88435 5793.45850 14878.12486 -17473.71294 -15539.97384 -5809.42241
61 62 63 64 65 66
1187.07959 -1812.87254 -15994.06740 1953.94574 2829.96685 -20208.13430
67 68 69 70 71 72
28961.21299 -22298.55667 2429.01702 -8880.47950 -20839.92050 -14590.43852
73 74 75 76 77 78
-5952.66095 11575.25770 1381.54273 3150.39269 -6719.23710 138268.17934
79 80 81 82 83 84
-5792.06352 6070.94028 -5096.17414 5366.88289 -14458.52663 -8563.48061
85 86 87 88 89 90
12059.83995 -6171.42582 10697.43371 13776.44161 -13490.44334 33652.50972
91 92 93 94 95 96
-19736.02334 -6289.36658 -11288.99305 -8920.61046 5894.23794 28716.24828
97 98 99 100 101 102
32949.25498 22888.29570 -10762.73729 -13643.71840 20146.47082 9546.12092
103 104 105 106 107 108
-2410.79917 6773.71568 -27306.29782 -9165.70101 7272.54790 2559.63108
109 110 111 112 113 114
118844.42624 13284.63973 10055.27500 -9999.43812 -12915.72595 -6530.11848
115 116 117 118 119 120
-10538.34977 -15512.65180 -46553.48090 -11853.92851 10933.89500 -9255.65017
121 122 123 124 125 126
-19400.82450 30634.35627 29265.25221 20165.08452 -9937.93271 19549.03504
127 128 129 130 131 132
-7410.15074 3148.96545 -20290.79723 -7168.39256 48747.55662 13.10584
133 134 135 136 137 138
-792.01537 8134.97695 -5964.36758 30644.25450 31966.69850 -7030.08027
139 140 141 142 143 144
-16868.70826 -21367.07899 29093.76195 -14029.39560 3004.01477 16640.04215
145 146 147 148 149 150
-23249.18261 26171.27441 25771.49348 18861.95582 -34382.60679 -9169.90590
151 152 153 154 155 156
-11161.78587 -11185.05075 -13840.30668 -11293.62555 -14861.87826 -45957.11292
157 158 159 160 161 162
-11420.26384 -11451.70232 -13111.37931 -15982.15168 -10746.65479 4355.77983
163 164
-11622.11045 6522.76000
> postscript(file="/var/www/rcomp/tmp/63i4w1321619320.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 = 164
Frequency = 1
lag(myerror, k = 1) myerror
0 14264.87045 NA
1 -17914.05397 14264.87045
2 -10316.51200 -17914.05397
3 13563.21517 -10316.51200
4 -9483.46774 13563.21517
5 21880.39784 -9483.46774
6 1906.20935 21880.39784
7 15276.42832 1906.20935
8 23230.65932 15276.42832
9 2807.55155 23230.65932
10 -18740.46720 2807.55155
11 749.86323 -18740.46720
12 -4491.73414 749.86323
13 -4722.02088 -4491.73414
14 -19939.40893 -4722.02088
15 -12399.09710 -19939.40893
16 18503.27549 -12399.09710
17 16316.93163 18503.27549
18 17260.83492 16316.93163
19 -2309.69128 17260.83492
20 15091.35421 -2309.69128
21 -11737.62522 15091.35421
22 -6154.75030 -11737.62522
23 1121.23668 -6154.75030
24 -5611.48972 1121.23668
25 897.57256 -5611.48972
26 -7583.80058 897.57256
27 -12401.28239 -7583.80058
28 -6671.76481 -12401.28239
29 -19901.16925 -6671.76481
30 11855.45594 -19901.16925
31 -6701.29509 11855.45594
32 -16591.63066 -6701.29509
33 10617.42178 -16591.63066
34 -16728.38836 10617.42178
35 -5910.63785 -16728.38836
36 -16494.13149 -5910.63785
37 -10454.48669 -16494.13149
38 -7435.62532 -10454.48669
39 -12033.36215 -7435.62532
40 -29520.32009 -12033.36215
41 -11304.26514 -29520.32009
42 -13171.51744 -11304.26514
43 -5299.87680 -13171.51744
44 12139.81909 -5299.87680
45 36927.53131 12139.81909
46 -5777.52750 36927.53131
47 1282.39692 -5777.52750
48 17352.49883 1282.39692
49 -10649.90284 17352.49883
50 -4891.47971 -10649.90284
51 -8452.97202 -4891.47971
52 -7058.06474 -8452.97202
53 -1011.53155 -7058.06474
54 -7696.88435 -1011.53155
55 5793.45850 -7696.88435
56 14878.12486 5793.45850
57 -17473.71294 14878.12486
58 -15539.97384 -17473.71294
59 -5809.42241 -15539.97384
60 1187.07959 -5809.42241
61 -1812.87254 1187.07959
62 -15994.06740 -1812.87254
63 1953.94574 -15994.06740
64 2829.96685 1953.94574
65 -20208.13430 2829.96685
66 28961.21299 -20208.13430
67 -22298.55667 28961.21299
68 2429.01702 -22298.55667
69 -8880.47950 2429.01702
70 -20839.92050 -8880.47950
71 -14590.43852 -20839.92050
72 -5952.66095 -14590.43852
73 11575.25770 -5952.66095
74 1381.54273 11575.25770
75 3150.39269 1381.54273
76 -6719.23710 3150.39269
77 138268.17934 -6719.23710
78 -5792.06352 138268.17934
79 6070.94028 -5792.06352
80 -5096.17414 6070.94028
81 5366.88289 -5096.17414
82 -14458.52663 5366.88289
83 -8563.48061 -14458.52663
84 12059.83995 -8563.48061
85 -6171.42582 12059.83995
86 10697.43371 -6171.42582
87 13776.44161 10697.43371
88 -13490.44334 13776.44161
89 33652.50972 -13490.44334
90 -19736.02334 33652.50972
91 -6289.36658 -19736.02334
92 -11288.99305 -6289.36658
93 -8920.61046 -11288.99305
94 5894.23794 -8920.61046
95 28716.24828 5894.23794
96 32949.25498 28716.24828
97 22888.29570 32949.25498
98 -10762.73729 22888.29570
99 -13643.71840 -10762.73729
100 20146.47082 -13643.71840
101 9546.12092 20146.47082
102 -2410.79917 9546.12092
103 6773.71568 -2410.79917
104 -27306.29782 6773.71568
105 -9165.70101 -27306.29782
106 7272.54790 -9165.70101
107 2559.63108 7272.54790
108 118844.42624 2559.63108
109 13284.63973 118844.42624
110 10055.27500 13284.63973
111 -9999.43812 10055.27500
112 -12915.72595 -9999.43812
113 -6530.11848 -12915.72595
114 -10538.34977 -6530.11848
115 -15512.65180 -10538.34977
116 -46553.48090 -15512.65180
117 -11853.92851 -46553.48090
118 10933.89500 -11853.92851
119 -9255.65017 10933.89500
120 -19400.82450 -9255.65017
121 30634.35627 -19400.82450
122 29265.25221 30634.35627
123 20165.08452 29265.25221
124 -9937.93271 20165.08452
125 19549.03504 -9937.93271
126 -7410.15074 19549.03504
127 3148.96545 -7410.15074
128 -20290.79723 3148.96545
129 -7168.39256 -20290.79723
130 48747.55662 -7168.39256
131 13.10584 48747.55662
132 -792.01537 13.10584
133 8134.97695 -792.01537
134 -5964.36758 8134.97695
135 30644.25450 -5964.36758
136 31966.69850 30644.25450
137 -7030.08027 31966.69850
138 -16868.70826 -7030.08027
139 -21367.07899 -16868.70826
140 29093.76195 -21367.07899
141 -14029.39560 29093.76195
142 3004.01477 -14029.39560
143 16640.04215 3004.01477
144 -23249.18261 16640.04215
145 26171.27441 -23249.18261
146 25771.49348 26171.27441
147 18861.95582 25771.49348
148 -34382.60679 18861.95582
149 -9169.90590 -34382.60679
150 -11161.78587 -9169.90590
151 -11185.05075 -11161.78587
152 -13840.30668 -11185.05075
153 -11293.62555 -13840.30668
154 -14861.87826 -11293.62555
155 -45957.11292 -14861.87826
156 -11420.26384 -45957.11292
157 -11451.70232 -11420.26384
158 -13111.37931 -11451.70232
159 -15982.15168 -13111.37931
160 -10746.65479 -15982.15168
161 4355.77983 -10746.65479
162 -11622.11045 4355.77983
163 6522.76000 -11622.11045
164 NA 6522.76000
> dum1 <- dum[2:length(myerror),]
> dum1
lag(myerror, k = 1) myerror
[1,] -17914.05397 14264.87045
[2,] -10316.51200 -17914.05397
[3,] 13563.21517 -10316.51200
[4,] -9483.46774 13563.21517
[5,] 21880.39784 -9483.46774
[6,] 1906.20935 21880.39784
[7,] 15276.42832 1906.20935
[8,] 23230.65932 15276.42832
[9,] 2807.55155 23230.65932
[10,] -18740.46720 2807.55155
[11,] 749.86323 -18740.46720
[12,] -4491.73414 749.86323
[13,] -4722.02088 -4491.73414
[14,] -19939.40893 -4722.02088
[15,] -12399.09710 -19939.40893
[16,] 18503.27549 -12399.09710
[17,] 16316.93163 18503.27549
[18,] 17260.83492 16316.93163
[19,] -2309.69128 17260.83492
[20,] 15091.35421 -2309.69128
[21,] -11737.62522 15091.35421
[22,] -6154.75030 -11737.62522
[23,] 1121.23668 -6154.75030
[24,] -5611.48972 1121.23668
[25,] 897.57256 -5611.48972
[26,] -7583.80058 897.57256
[27,] -12401.28239 -7583.80058
[28,] -6671.76481 -12401.28239
[29,] -19901.16925 -6671.76481
[30,] 11855.45594 -19901.16925
[31,] -6701.29509 11855.45594
[32,] -16591.63066 -6701.29509
[33,] 10617.42178 -16591.63066
[34,] -16728.38836 10617.42178
[35,] -5910.63785 -16728.38836
[36,] -16494.13149 -5910.63785
[37,] -10454.48669 -16494.13149
[38,] -7435.62532 -10454.48669
[39,] -12033.36215 -7435.62532
[40,] -29520.32009 -12033.36215
[41,] -11304.26514 -29520.32009
[42,] -13171.51744 -11304.26514
[43,] -5299.87680 -13171.51744
[44,] 12139.81909 -5299.87680
[45,] 36927.53131 12139.81909
[46,] -5777.52750 36927.53131
[47,] 1282.39692 -5777.52750
[48,] 17352.49883 1282.39692
[49,] -10649.90284 17352.49883
[50,] -4891.47971 -10649.90284
[51,] -8452.97202 -4891.47971
[52,] -7058.06474 -8452.97202
[53,] -1011.53155 -7058.06474
[54,] -7696.88435 -1011.53155
[55,] 5793.45850 -7696.88435
[56,] 14878.12486 5793.45850
[57,] -17473.71294 14878.12486
[58,] -15539.97384 -17473.71294
[59,] -5809.42241 -15539.97384
[60,] 1187.07959 -5809.42241
[61,] -1812.87254 1187.07959
[62,] -15994.06740 -1812.87254
[63,] 1953.94574 -15994.06740
[64,] 2829.96685 1953.94574
[65,] -20208.13430 2829.96685
[66,] 28961.21299 -20208.13430
[67,] -22298.55667 28961.21299
[68,] 2429.01702 -22298.55667
[69,] -8880.47950 2429.01702
[70,] -20839.92050 -8880.47950
[71,] -14590.43852 -20839.92050
[72,] -5952.66095 -14590.43852
[73,] 11575.25770 -5952.66095
[74,] 1381.54273 11575.25770
[75,] 3150.39269 1381.54273
[76,] -6719.23710 3150.39269
[77,] 138268.17934 -6719.23710
[78,] -5792.06352 138268.17934
[79,] 6070.94028 -5792.06352
[80,] -5096.17414 6070.94028
[81,] 5366.88289 -5096.17414
[82,] -14458.52663 5366.88289
[83,] -8563.48061 -14458.52663
[84,] 12059.83995 -8563.48061
[85,] -6171.42582 12059.83995
[86,] 10697.43371 -6171.42582
[87,] 13776.44161 10697.43371
[88,] -13490.44334 13776.44161
[89,] 33652.50972 -13490.44334
[90,] -19736.02334 33652.50972
[91,] -6289.36658 -19736.02334
[92,] -11288.99305 -6289.36658
[93,] -8920.61046 -11288.99305
[94,] 5894.23794 -8920.61046
[95,] 28716.24828 5894.23794
[96,] 32949.25498 28716.24828
[97,] 22888.29570 32949.25498
[98,] -10762.73729 22888.29570
[99,] -13643.71840 -10762.73729
[100,] 20146.47082 -13643.71840
[101,] 9546.12092 20146.47082
[102,] -2410.79917 9546.12092
[103,] 6773.71568 -2410.79917
[104,] -27306.29782 6773.71568
[105,] -9165.70101 -27306.29782
[106,] 7272.54790 -9165.70101
[107,] 2559.63108 7272.54790
[108,] 118844.42624 2559.63108
[109,] 13284.63973 118844.42624
[110,] 10055.27500 13284.63973
[111,] -9999.43812 10055.27500
[112,] -12915.72595 -9999.43812
[113,] -6530.11848 -12915.72595
[114,] -10538.34977 -6530.11848
[115,] -15512.65180 -10538.34977
[116,] -46553.48090 -15512.65180
[117,] -11853.92851 -46553.48090
[118,] 10933.89500 -11853.92851
[119,] -9255.65017 10933.89500
[120,] -19400.82450 -9255.65017
[121,] 30634.35627 -19400.82450
[122,] 29265.25221 30634.35627
[123,] 20165.08452 29265.25221
[124,] -9937.93271 20165.08452
[125,] 19549.03504 -9937.93271
[126,] -7410.15074 19549.03504
[127,] 3148.96545 -7410.15074
[128,] -20290.79723 3148.96545
[129,] -7168.39256 -20290.79723
[130,] 48747.55662 -7168.39256
[131,] 13.10584 48747.55662
[132,] -792.01537 13.10584
[133,] 8134.97695 -792.01537
[134,] -5964.36758 8134.97695
[135,] 30644.25450 -5964.36758
[136,] 31966.69850 30644.25450
[137,] -7030.08027 31966.69850
[138,] -16868.70826 -7030.08027
[139,] -21367.07899 -16868.70826
[140,] 29093.76195 -21367.07899
[141,] -14029.39560 29093.76195
[142,] 3004.01477 -14029.39560
[143,] 16640.04215 3004.01477
[144,] -23249.18261 16640.04215
[145,] 26171.27441 -23249.18261
[146,] 25771.49348 26171.27441
[147,] 18861.95582 25771.49348
[148,] -34382.60679 18861.95582
[149,] -9169.90590 -34382.60679
[150,] -11161.78587 -9169.90590
[151,] -11185.05075 -11161.78587
[152,] -13840.30668 -11185.05075
[153,] -11293.62555 -13840.30668
[154,] -14861.87826 -11293.62555
[155,] -45957.11292 -14861.87826
[156,] -11420.26384 -45957.11292
[157,] -11451.70232 -11420.26384
[158,] -13111.37931 -11451.70232
[159,] -15982.15168 -13111.37931
[160,] -10746.65479 -15982.15168
[161,] 4355.77983 -10746.65479
[162,] -11622.11045 4355.77983
[163,] 6522.76000 -11622.11045
> z <- as.data.frame(dum1)
> z
lag(myerror, k = 1) myerror
1 -17914.05397 14264.87045
2 -10316.51200 -17914.05397
3 13563.21517 -10316.51200
4 -9483.46774 13563.21517
5 21880.39784 -9483.46774
6 1906.20935 21880.39784
7 15276.42832 1906.20935
8 23230.65932 15276.42832
9 2807.55155 23230.65932
10 -18740.46720 2807.55155
11 749.86323 -18740.46720
12 -4491.73414 749.86323
13 -4722.02088 -4491.73414
14 -19939.40893 -4722.02088
15 -12399.09710 -19939.40893
16 18503.27549 -12399.09710
17 16316.93163 18503.27549
18 17260.83492 16316.93163
19 -2309.69128 17260.83492
20 15091.35421 -2309.69128
21 -11737.62522 15091.35421
22 -6154.75030 -11737.62522
23 1121.23668 -6154.75030
24 -5611.48972 1121.23668
25 897.57256 -5611.48972
26 -7583.80058 897.57256
27 -12401.28239 -7583.80058
28 -6671.76481 -12401.28239
29 -19901.16925 -6671.76481
30 11855.45594 -19901.16925
31 -6701.29509 11855.45594
32 -16591.63066 -6701.29509
33 10617.42178 -16591.63066
34 -16728.38836 10617.42178
35 -5910.63785 -16728.38836
36 -16494.13149 -5910.63785
37 -10454.48669 -16494.13149
38 -7435.62532 -10454.48669
39 -12033.36215 -7435.62532
40 -29520.32009 -12033.36215
41 -11304.26514 -29520.32009
42 -13171.51744 -11304.26514
43 -5299.87680 -13171.51744
44 12139.81909 -5299.87680
45 36927.53131 12139.81909
46 -5777.52750 36927.53131
47 1282.39692 -5777.52750
48 17352.49883 1282.39692
49 -10649.90284 17352.49883
50 -4891.47971 -10649.90284
51 -8452.97202 -4891.47971
52 -7058.06474 -8452.97202
53 -1011.53155 -7058.06474
54 -7696.88435 -1011.53155
55 5793.45850 -7696.88435
56 14878.12486 5793.45850
57 -17473.71294 14878.12486
58 -15539.97384 -17473.71294
59 -5809.42241 -15539.97384
60 1187.07959 -5809.42241
61 -1812.87254 1187.07959
62 -15994.06740 -1812.87254
63 1953.94574 -15994.06740
64 2829.96685 1953.94574
65 -20208.13430 2829.96685
66 28961.21299 -20208.13430
67 -22298.55667 28961.21299
68 2429.01702 -22298.55667
69 -8880.47950 2429.01702
70 -20839.92050 -8880.47950
71 -14590.43852 -20839.92050
72 -5952.66095 -14590.43852
73 11575.25770 -5952.66095
74 1381.54273 11575.25770
75 3150.39269 1381.54273
76 -6719.23710 3150.39269
77 138268.17934 -6719.23710
78 -5792.06352 138268.17934
79 6070.94028 -5792.06352
80 -5096.17414 6070.94028
81 5366.88289 -5096.17414
82 -14458.52663 5366.88289
83 -8563.48061 -14458.52663
84 12059.83995 -8563.48061
85 -6171.42582 12059.83995
86 10697.43371 -6171.42582
87 13776.44161 10697.43371
88 -13490.44334 13776.44161
89 33652.50972 -13490.44334
90 -19736.02334 33652.50972
91 -6289.36658 -19736.02334
92 -11288.99305 -6289.36658
93 -8920.61046 -11288.99305
94 5894.23794 -8920.61046
95 28716.24828 5894.23794
96 32949.25498 28716.24828
97 22888.29570 32949.25498
98 -10762.73729 22888.29570
99 -13643.71840 -10762.73729
100 20146.47082 -13643.71840
101 9546.12092 20146.47082
102 -2410.79917 9546.12092
103 6773.71568 -2410.79917
104 -27306.29782 6773.71568
105 -9165.70101 -27306.29782
106 7272.54790 -9165.70101
107 2559.63108 7272.54790
108 118844.42624 2559.63108
109 13284.63973 118844.42624
110 10055.27500 13284.63973
111 -9999.43812 10055.27500
112 -12915.72595 -9999.43812
113 -6530.11848 -12915.72595
114 -10538.34977 -6530.11848
115 -15512.65180 -10538.34977
116 -46553.48090 -15512.65180
117 -11853.92851 -46553.48090
118 10933.89500 -11853.92851
119 -9255.65017 10933.89500
120 -19400.82450 -9255.65017
121 30634.35627 -19400.82450
122 29265.25221 30634.35627
123 20165.08452 29265.25221
124 -9937.93271 20165.08452
125 19549.03504 -9937.93271
126 -7410.15074 19549.03504
127 3148.96545 -7410.15074
128 -20290.79723 3148.96545
129 -7168.39256 -20290.79723
130 48747.55662 -7168.39256
131 13.10584 48747.55662
132 -792.01537 13.10584
133 8134.97695 -792.01537
134 -5964.36758 8134.97695
135 30644.25450 -5964.36758
136 31966.69850 30644.25450
137 -7030.08027 31966.69850
138 -16868.70826 -7030.08027
139 -21367.07899 -16868.70826
140 29093.76195 -21367.07899
141 -14029.39560 29093.76195
142 3004.01477 -14029.39560
143 16640.04215 3004.01477
144 -23249.18261 16640.04215
145 26171.27441 -23249.18261
146 25771.49348 26171.27441
147 18861.95582 25771.49348
148 -34382.60679 18861.95582
149 -9169.90590 -34382.60679
150 -11161.78587 -9169.90590
151 -11185.05075 -11161.78587
152 -13840.30668 -11185.05075
153 -11293.62555 -13840.30668
154 -14861.87826 -11293.62555
155 -45957.11292 -14861.87826
156 -11420.26384 -45957.11292
157 -11451.70232 -11420.26384
158 -13111.37931 -11451.70232
159 -15982.15168 -13111.37931
160 -10746.65479 -15982.15168
161 4355.77983 -10746.65479
162 -11622.11045 4355.77983
163 6522.76000 -11622.11045
> 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/rcomp/tmp/71m601321619320.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/rcomp/tmp/8rv0f1321619320.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/rcomp/tmp/96ijs1321619320.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/rcomp/tmp/10gi0i1321619320.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/rcomp/createtable file can be downloaded at http://www.wessa.net/cretab
> load(file="/var/www/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$coefficients)[i] != 't') myeq <- paste(myeq, '[t]', sep='')
+ }
+ }
> myeq <- paste(myeq, ' + e[t]')
> a<-table.row.start(a)
> a<-table.element(a, myeq)
> a<-table.row.end(a)
> a<-table.end(a)
> table.save(a,file="/var/www/rcomp/tmp/11868y1321619320.tab")
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a,hyperlink('http://www.xycoon.com/ols1.htm','Multiple Linear Regression - Ordinary Least Squares',''), 6, TRUE)
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a,'Variable',header=TRUE)
> a<-table.element(a,'Parameter',header=TRUE)
> a<-table.element(a,'S.D.',header=TRUE)
> a<-table.element(a,'T-STAT
H0: parameter = 0',header=TRUE)
> a<-table.element(a,'2-tail p-value',header=TRUE)
> a<-table.element(a,'1-tail p-value',header=TRUE)
> a<-table.row.end(a)
> for (i in 1:k){
+ a<-table.row.start(a)
+ a<-table.element(a,rownames(mysum$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$coefficients[i,4]/2,6))
+ a<-table.row.end(a)
+ }
> a<-table.end(a)
> table.save(a,file="/var/www/rcomp/tmp/12ie1b1321619320.tab")
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a, 'Multiple Linear Regression - Regression Statistics', 2, TRUE)
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a, 'Multiple R',1,TRUE)
> a<-table.element(a, sqrt(mysum$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$sigma)
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a, 'Sum Squared Residuals',1,TRUE)
> a<-table.element(a, sum(myerror*myerror))
> a<-table.row.end(a)
> a<-table.end(a)
> table.save(a,file="/var/www/rcomp/tmp/13jp5n1321619320.tab")
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a, 'Multiple Linear Regression - Actuals, Interpolation, and Residuals', 4, TRUE)
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a, 'Time or Index', 1, TRUE)
> a<-table.element(a, 'Actuals', 1, TRUE)
> a<-table.element(a, 'Interpolation
Forecast', 1, TRUE)
> a<-table.element(a, 'Residuals
Prediction Error', 1, TRUE)
> a<-table.row.end(a)
> for (i in 1:n) {
+ a<-table.row.start(a)
+ a<-table.element(a,i, 1, TRUE)
+ a<-table.element(a,x[i])
+ a<-table.element(a,x[i]-mysum$resid[i])
+ a<-table.element(a,mysum$resid[i])
+ a<-table.row.end(a)
+ }
> a<-table.end(a)
> table.save(a,file="/var/www/rcomp/tmp/1479j91321619320.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/rcomp/tmp/15wpan1321619320.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/rcomp/tmp/16la3s1321619320.tab")
+ }
>
> try(system("convert tmp/1obh41321619320.ps tmp/1obh41321619320.png",intern=TRUE))
character(0)
> try(system("convert tmp/2lyy81321619320.ps tmp/2lyy81321619320.png",intern=TRUE))
character(0)
> try(system("convert tmp/32p6q1321619320.ps tmp/32p6q1321619320.png",intern=TRUE))
character(0)
> try(system("convert tmp/4pc531321619320.ps tmp/4pc531321619320.png",intern=TRUE))
character(0)
> try(system("convert tmp/5s5nt1321619320.ps tmp/5s5nt1321619320.png",intern=TRUE))
character(0)
> try(system("convert tmp/63i4w1321619320.ps tmp/63i4w1321619320.png",intern=TRUE))
character(0)
> try(system("convert tmp/71m601321619320.ps tmp/71m601321619320.png",intern=TRUE))
character(0)
> try(system("convert tmp/8rv0f1321619320.ps tmp/8rv0f1321619320.png",intern=TRUE))
character(0)
> try(system("convert tmp/96ijs1321619320.ps tmp/96ijs1321619320.png",intern=TRUE))
character(0)
> try(system("convert tmp/10gi0i1321619320.ps tmp/10gi0i1321619320.png",intern=TRUE))
character(0)
>
>
> proc.time()
user system elapsed
5.610 0.430 6.018