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 'license()' or 'licence()' for distribution details.
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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(279055
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+ ,dim=c(5
+ ,164)
+ ,dimnames=list(c('Tijd_RFC'
+ ,'#Logins'
+ ,'#Gedeelde_Compendia'
+ ,'#Blogs'
+ ,'#Reviews+120tekens')
+ ,1:164))
> y <- array(NA,dim=c(5,164),dimnames=list(c('Tijd_RFC','#Logins','#Gedeelde_Compendia','#Blogs','#Reviews+120tekens'),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 = 'No Linear Trend'
> par2 = 'Do not include Seasonal Dummies'
> par1 = '1'
> 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
Tijd_RFC #Logins #Gedeelde_Compendia #Blogs #Reviews+120tekens
1 279055 73 3 96 130
2 212408 75 4 75 143
3 233939 83 16 70 118
4 222117 106 2 134 146
5 179751 55 1 72 73
6 70849 28 3 8 89
7 605767 135 0 173 146
8 33186 19 0 1 22
9 227332 62 7 88 132
10 258874 48 0 98 92
11 359064 120 0 112 147
12 264989 131 7 125 203
13 212638 87 10 57 113
14 368577 85 4 139 171
15 269455 88 10 87 87
16 397992 190 0 176 208
17 335567 76 8 114 153
18 428322 172 4 121 97
19 182016 58 3 103 95
20 267365 89 8 135 197
21 279428 73 0 123 160
22 508849 111 1 99 148
23 206722 47 5 74 84
24 200004 58 9 103 227
25 257139 133 1 158 154
26 270941 138 0 116 151
27 324969 134 5 114 142
28 329962 92 0 150 148
29 190867 60 0 64 110
30 393860 79 0 150 149
31 327660 89 3 143 179
32 269239 83 6 50 149
33 391045 105 1 145 187
34 130446 49 4 56 153
35 430118 104 4 141 163
36 273950 56 0 83 127
37 428077 128 0 112 151
38 254312 93 2 79 100
39 120351 35 1 33 46
40 395643 211 2 152 156
41 345875 86 10 126 128
42 216827 82 10 97 111
43 224524 83 5 84 119
44 182485 69 6 68 148
45 157164 85 1 50 65
46 459455 157 2 101 134
47 78800 42 2 20 66
48 217932 84 0 101 201
49 368086 123 10 150 177
50 230299 70 3 129 156
51 244782 81 0 99 158
52 24188 24 0 8 7
53 400109 334 8 88 175
54 65029 17 5 21 61
55 101097 64 3 30 41
56 309810 67 1 102 133
57 369627 90 5 163 228
58 367127 204 6 132 140
59 377704 154 0 161 155
60 280106 90 12 90 141
61 400971 153 10 160 181
62 315924 122 12 139 75
63 291391 124 11 104 97
64 295075 93 8 103 142
65 280018 81 3 66 136
66 267432 71 0 163 87
67 217181 141 6 93 140
68 258166 159 10 85 169
69 260919 87 2 150 129
70 182961 73 5 143 92
71 256967 74 13 107 160
72 73566 32 6 22 67
73 272362 93 7 85 179
74 229056 62 2 101 90
75 229851 70 5 131 144
76 371391 91 4 140 144
77 398210 104 3 156 144
78 220419 111 6 81 134
79 231884 72 2 137 146
80 217714 72 0 102 121
81 200046 53 1 72 112
82 483074 131 1 161 145
83 146100 72 5 30 99
84 295224 109 2 120 96
85 80953 25 0 49 27
86 217384 63 0 121 77
87 179344 62 6 76 137
88 415550 221 1 85 151
89 389059 129 4 151 126
90 180679 106 1 165 159
91 299505 104 1 89 101
92 292260 84 3 168 144
93 199481 68 10 48 102
94 282361 78 1 149 135
95 329281 89 4 75 147
96 234577 48 5 107 155
97 297995 67 7 116 138
98 329583 89 0 173 113
99 416463 163 12 155 248
100 415683 119 13 165 116
101 297080 142 9 121 176
102 318283 70 0 156 140
103 224033 199 0 86 59
104 43287 14 4 13 64
105 238089 87 4 120 40
106 263322 160 0 117 98
107 299566 60 0 133 139
108 321797 95 0 169 135
109 193926 95 0 39 97
110 175138 105 0 125 142
111 354041 78 5 82 155
112 303273 91 1 148 115
113 23668 13 0 12 0
114 196743 79 0 146 103
115 61857 25 4 23 30
116 217543 54 0 87 130
117 440711 128 1 164 102
118 21054 16 0 4 0
119 252805 52 5 81 77
120 31961 22 0 18 9
121 360436 125 3 118 150
122 251948 77 7 76 163
123 187003 96 14 55 148
124 180842 58 3 62 94
125 38214 34 0 16 21
126 280392 56 3 98 151
127 358276 84 0 137 187
128 211775 67 0 50 171
129 447335 90 4 152 170
130 348017 99 0 163 145
131 441946 133 3 142 198
132 215177 43 0 80 152
133 130177 47 0 59 112
134 316128 363 4 94 173
135 466139 198 5 128 177
136 162279 62 16 63 153
137 416643 140 6 127 161
138 178322 86 5 60 115
139 292443 54 2 118 147
140 283913 100 1 110 124
141 244802 126 1 45 57
142 387072 125 9 96 144
143 246963 92 1 128 126
144 173260 63 3 41 78
145 346748 108 11 146 153
146 176654 59 5 147 196
147 268189 95 2 121 130
148 314070 112 1 185 159
149 1 0 9 0 0
150 14688 10 0 4 0
151 98 1 0 0 0
152 455 2 0 0 0
153 0 0 1 0 0
154 0 0 0 0 0
155 291650 94 2 85 94
156 415421 168 3 164 129
157 0 0 0 0 0
158 203 4 0 0 0
159 7199 5 0 7 0
160 46660 20 0 12 13
161 17547 5 0 0 4
162 121550 46 0 37 89
163 969 2 0 0 0
164 242774 75 2 62 71
> k <- length(x[1,])
> df <- as.data.frame(x)
> (mylm <- lm(df))
Call:
lm(formula = df)
Coefficients:
(Intercept) `#Logins` `#Gedeelde_Compendia`
13561.3 755.6 198.8
`#Blogs` `#Reviews+120tekens`
1240.9 424.4
> (mysum <- summary(mylm))
Call:
lm(formula = df)
Residuals:
Min 1Q Median 3Q Max
-185385 -28150 -7310 30413 225572
Coefficients:
Estimate Std. Error t value Pr(>|t|)
(Intercept) 13561.3 11426.6 1.187 0.23707
`#Logins` 755.6 109.1 6.924 1.02e-10 ***
`#Gedeelde_Compendia` 198.8 1320.0 0.151 0.88045
`#Blogs` 1240.9 143.4 8.654 5.21e-15 ***
`#Reviews+120tekens` 424.4 136.2 3.115 0.00218 **
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
Residual standard error: 59710 on 159 degrees of freedom
Multiple R-squared: 0.7799, Adjusted R-squared: 0.7744
F-statistic: 140.9 on 4 and 159 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,] 0.9822106 3.557876e-02 1.778938e-02
[2,] 0.9692661 6.146787e-02 3.073394e-02
[3,] 0.9479516 1.040968e-01 5.204838e-02
[4,] 0.9114934 1.770133e-01 8.850663e-02
[5,] 0.9193185 1.613631e-01 8.068155e-02
[6,] 0.8759504 2.480991e-01 1.240496e-01
[7,] 0.8440891 3.118218e-01 1.559109e-01
[8,] 0.7926548 4.146903e-01 2.073452e-01
[9,] 0.8160526 3.678948e-01 1.839474e-01
[10,] 0.7755418 4.489164e-01 2.244582e-01
[11,] 0.7411588 5.176825e-01 2.588412e-01
[12,] 0.8386496 3.227008e-01 1.613504e-01
[13,] 0.8166378 3.667244e-01 1.833622e-01
[14,] 0.7633504 4.732992e-01 2.366496e-01
[15,] 0.9956522 8.695602e-03 4.347801e-03
[16,] 0.9931861 1.362773e-02 6.813865e-03
[17,] 0.9912845 1.743105e-02 8.715524e-03
[18,] 0.9987347 2.530500e-03 1.265250e-03
[19,] 0.9987528 2.494495e-03 1.247247e-03
[20,] 0.9979891 4.021833e-03 2.010917e-03
[21,] 0.9968786 6.242854e-03 3.121427e-03
[22,] 0.9951680 9.664030e-03 4.832015e-03
[23,] 0.9949380 1.012403e-02 5.062017e-03
[24,] 0.9924148 1.517050e-02 7.585249e-03
[25,] 0.9940219 1.195627e-02 5.978134e-03
[26,] 0.9925916 1.481682e-02 7.408410e-03
[27,] 0.9908512 1.829769e-02 9.148844e-03
[28,] 0.9933391 1.332186e-02 6.660928e-03
[29,] 0.9927599 1.448011e-02 7.240056e-03
[30,] 0.9960928 7.814435e-03 3.907217e-03
[31,] 0.9945194 1.096112e-02 5.480562e-03
[32,] 0.9924676 1.506474e-02 7.532369e-03
[33,] 0.9925623 1.487541e-02 7.437704e-03
[34,] 0.9910143 1.797138e-02 8.985690e-03
[35,] 0.9891476 2.170473e-02 1.085237e-02
[36,] 0.9853098 2.938045e-02 1.469022e-02
[37,] 0.9809158 3.816833e-02 1.908416e-02
[38,] 0.9768765 4.624705e-02 2.312352e-02
[39,] 0.9929859 1.402828e-02 7.014141e-03
[40,] 0.9910204 1.795919e-02 8.979594e-03
[41,] 0.9906264 1.874713e-02 9.373566e-03
[42,] 0.9870815 2.583695e-02 1.291848e-02
[43,] 0.9876041 2.479188e-02 1.239594e-02
[44,] 0.9835454 3.290914e-02 1.645457e-02
[45,] 0.9815462 3.690762e-02 1.845381e-02
[46,] 0.9808393 3.832146e-02 1.916073e-02
[47,] 0.9751380 4.972402e-02 2.486201e-02
[48,] 0.9696752 6.064960e-02 3.032480e-02
[49,] 0.9688783 6.224330e-02 3.112165e-02
[50,] 0.9598184 8.036315e-02 4.018158e-02
[51,] 0.9532622 9.347553e-02 4.673776e-02
[52,] 0.9460422 1.079157e-01 5.395784e-02
[53,] 0.9350889 1.298221e-01 6.491105e-02
[54,] 0.9193073 1.613853e-01 8.069265e-02
[55,] 0.9060506 1.878988e-01 9.394938e-02
[56,] 0.8858838 2.282324e-01 1.141162e-01
[57,] 0.8651637 2.696726e-01 1.348363e-01
[58,] 0.8715355 2.569290e-01 1.284645e-01
[59,] 0.8765189 2.469623e-01 1.234811e-01
[60,] 0.8920669 2.158662e-01 1.079331e-01
[61,] 0.8848374 2.303252e-01 1.151626e-01
[62,] 0.8911923 2.176154e-01 1.088077e-01
[63,] 0.9332227 1.335546e-01 6.677732e-02
[64,] 0.9190253 1.619495e-01 8.097474e-02
[65,] 0.9037471 1.925057e-01 9.625286e-02
[66,] 0.8836142 2.327716e-01 1.163858e-01
[67,] 0.8601406 2.797189e-01 1.398594e-01
[68,] 0.8620241 2.759518e-01 1.379759e-01
[69,] 0.8555530 2.888940e-01 1.444470e-01
[70,] 0.8470844 3.058313e-01 1.529156e-01
[71,] 0.8295588 3.408825e-01 1.704412e-01
[72,] 0.8395187 3.209627e-01 1.604813e-01
[73,] 0.8181224 3.637553e-01 1.818776e-01
[74,] 0.7869012 4.261976e-01 2.130988e-01
[75,] 0.8559793 2.880414e-01 1.440207e-01
[76,] 0.8286967 3.426065e-01 1.713033e-01
[77,] 0.8004229 3.991542e-01 1.995771e-01
[78,] 0.7759838 4.480324e-01 2.240162e-01
[79,] 0.7502791 4.994418e-01 2.497209e-01
[80,] 0.7276051 5.447898e-01 2.723949e-01
[81,] 0.7411947 5.176106e-01 2.588053e-01
[82,] 0.7196971 5.606058e-01 2.803029e-01
[83,] 0.9425641 1.148719e-01 5.743593e-02
[84,] 0.9417475 1.165050e-01 5.825251e-02
[85,] 0.9404670 1.190661e-01 5.953304e-02
[86,] 0.9283730 1.432540e-01 7.162702e-02
[87,] 0.9168651 1.662699e-01 8.313494e-02
[88,] 0.9401264 1.197472e-01 5.987361e-02
[89,] 0.9273512 1.452976e-01 7.264881e-02
[90,] 0.9135569 1.728862e-01 8.644312e-02
[91,] 0.8946742 2.106516e-01 1.053258e-01
[92,] 0.8771336 2.457327e-01 1.228664e-01
[93,] 0.8707858 2.584285e-01 1.292142e-01
[94,] 0.8658857 2.682285e-01 1.341143e-01
[95,] 0.8383763 3.232475e-01 1.616237e-01
[96,] 0.8448947 3.102105e-01 1.551053e-01
[97,] 0.8222862 3.554276e-01 1.777138e-01
[98,] 0.7898609 4.202782e-01 2.101391e-01
[99,] 0.7808626 4.382749e-01 2.191374e-01
[100,] 0.7454187 5.091626e-01 2.545813e-01
[101,] 0.7160868 5.678265e-01 2.839132e-01
[102,] 0.6808785 6.382430e-01 3.191215e-01
[103,] 0.8370070 3.259859e-01 1.629930e-01
[104,] 0.9020570 1.958860e-01 9.794301e-02
[105,] 0.8813310 2.373381e-01 1.186690e-01
[106,] 0.8558628 2.882744e-01 1.441372e-01
[107,] 0.9265792 1.468417e-01 7.342085e-02
[108,] 0.9078745 1.842511e-01 9.212554e-02
[109,] 0.8844939 2.310122e-01 1.155061e-01
[110,] 0.8936978 2.126043e-01 1.063022e-01
[111,] 0.8678623 2.642755e-01 1.321377e-01
[112,] 0.8701532 2.596936e-01 1.298468e-01
[113,] 0.8442416 3.115167e-01 1.557584e-01
[114,] 0.8266444 3.467112e-01 1.733556e-01
[115,] 0.7920048 4.159904e-01 2.079952e-01
[116,] 0.7623284 4.753432e-01 2.376716e-01
[117,] 0.7177052 5.645896e-01 2.822948e-01
[118,] 0.6783213 6.433573e-01 3.216787e-01
[119,] 0.6426862 7.146276e-01 3.573138e-01
[120,] 0.6008803 7.982394e-01 3.991197e-01
[121,] 0.5568092 8.863815e-01 4.431908e-01
[122,] 0.6596369 6.807262e-01 3.403631e-01
[123,] 0.6041954 7.916091e-01 3.958046e-01
[124,] 0.6545746 6.908507e-01 3.454254e-01
[125,] 0.6207707 7.584585e-01 3.792293e-01
[126,] 0.5666371 8.667259e-01 4.333629e-01
[127,] 0.9992679 1.464295e-03 7.321473e-04
[128,] 0.9990149 1.970141e-03 9.850707e-04
[129,] 0.9991470 1.705955e-03 8.529774e-04
[130,] 0.9989067 2.186694e-03 1.093347e-03
[131,] 0.9994742 1.051571e-03 5.257856e-04
[132,] 0.9999935 1.301781e-05 6.508906e-06
[133,] 0.9999853 2.935654e-05 1.467827e-05
[134,] 0.9999999 2.508919e-07 1.254459e-07
[135,] 0.9999997 6.632370e-07 3.316185e-07
[136,] 0.9999989 2.144836e-06 1.072418e-06
[137,] 0.9999971 5.745599e-06 2.872800e-06
[138,] 0.9999971 5.894224e-06 2.947112e-06
[139,] 0.9999945 1.095455e-05 5.477275e-06
[140,] 0.9999804 3.926949e-05 1.963474e-05
[141,] 0.9999817 3.662996e-05 1.831498e-05
[142,] 0.9999974 5.165506e-06 2.582753e-06
[143,] 0.9999899 2.025491e-05 1.012746e-05
[144,] 0.9999508 9.836765e-05 4.918382e-05
[145,] 0.9997656 4.687612e-04 2.343806e-04
[146,] 0.9999722 5.558431e-05 2.779215e-05
[147,] 0.9997859 4.281185e-04 2.140593e-04
[148,] 0.9997661 4.677551e-04 2.338775e-04
[149,] 0.9987796 2.440755e-03 1.220377e-03
> postscript(file="/var/www/rcomp/tmp/1dkje1324656017.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/2xk3p1324656017.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> plot(mysum$resid, type='b', pch=19, main='Residuals', ylab='value of Residuals', xlab='time or index')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/rcomp/tmp/39mc21324656017.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> hist(mysum$resid, main='Residual Histogram', xlab='values of Residuals')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/rcomp/tmp/4g4621324656017.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> densityplot(~mysum$resid,col='black',main='Residual Density Plot', xlab='values of Residuals')
> dev.off()
null device
1
> postscript(file="/var/www/rcomp/tmp/595qa1324656017.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> qqnorm(mysum$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
35452.38974 -12363.23803 17550.44819 -100162.53408 4115.17600
6 7 8 9 10
-12159.30084 213580.50841 -5307.68488 323.31027 48400.82262
11 12 13 14 15
53478.82180 -90194.47341 12673.20263 44953.25899 42542.26484
16 17 18 19 20
-65783.07346 56607.81477 92702.62301 -44086.65692 -66146.25271
21 22 23 24 25
-9811.99995 225571.79519 29185.61607 -83307.10763 -118517.23075
26 27 28 29 30
-54905.10595 7451.86617 -2044.45617 5877.79412 71251.45232
31 32 33 34 35
-7145.43646 66500.88012 38671.71592 -55348.00764 93051.79547
36 37 38 39 40
61192.63987 114749.91313 29622.39503 19677.48132 -32549.25338
41 42 43 44 45
54681.23137 -28145.57043 -7473.64893 -31586.36309 -10444.86513
46 47 48 49 50
144682.54995 -19717.31252 -69719.01419 -1637.62005 -63018.55552
51 52 53 54 55
-19873.18228 -20404.09403 -50858.03212 -14314.92424 -16041.04811
56 57 58 59 60
62420.20784 -11942.41769 -24964.81965 -17767.05921 24646.50090
61 62 63 64 65
-5525.39929 3492.30991 11741.13471 21588.68968 65050.47773
66 67 68 69 70
-38952.95544 -78917.17062 -54707.15753 -59644.52246 -103233.93581
71 72 73 74 75
-15759.79068 -21097.16356 5708.67462 4733.45865 -61253.64492
76 77 78 79 80
53450.74273 50792.60261 -35575.95889 -68429.09808 -28162.43640
81 82 83 84 85
9371.28996 109025.54758 -2093.03115 9267.74305 -23756.97827
86 87 88 89 90
-26596.89153 -34697.35718 65260.22338 36396.53374 -185384.93209
91 92 93 94 95
53870.15687 -54936.50245 29707.48879 -32508.94637 92234.49903
96 97 98 99 100
-14792.72398 29918.36006 -13843.92592 -20214.44634 55658.13655
101 102 103 104 105
-50391.18312 -1151.42752 -71635.45741 -24937.62505 -7878.53353
106 107 108 109 110
-57896.23082 16651.23669 -30535.75131 19030.32465 -133123.14023
111 112 113 114 115
113025.93373 -11691.17517 -14605.85963 -101381.60134 -12659.13741
116 117 118 119 120
60.25208 83454.09368 -9559.67947 65775.33429 -24377.26571
121 122 123 124 125
41758.28032 15341.07905 -32928.05033 6038.84576 -29801.56887
126 127 128 129 130
38240.63848 31895.15515 12982.97717 104226.67976 -4136.43532
131 132 133 134 135
67074.00025 5355.50192 -39634.37067 -162551.30112 68041.51930
136 137 138 139 140
-44409.37957 70199.70427 -24464.31787 28881.89169 5482.13383
141 142 143 144 145
55814.37252 97046.24022 -48607.54088 27526.79620 3306.97016
146 147 148 149 150
-148059.88219 -22858.49623 -81344.42957 -15349.88430 -11392.32521
151 152 153 154 155
-14218.86517 -14617.42421 -13760.14815 -13561.30613 61305.84750
156 157 158 159 160
16086.35272 -13561.30613 -16380.54230 -18826.10147 -2419.44098
161 162 163 164
-1489.53767 -10446.69524 -14103.42421 65085.44288
> postscript(file="/var/www/rcomp/tmp/65cgh1324656017.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 35452.38974 NA
1 -12363.23803 35452.38974
2 17550.44819 -12363.23803
3 -100162.53408 17550.44819
4 4115.17600 -100162.53408
5 -12159.30084 4115.17600
6 213580.50841 -12159.30084
7 -5307.68488 213580.50841
8 323.31027 -5307.68488
9 48400.82262 323.31027
10 53478.82180 48400.82262
11 -90194.47341 53478.82180
12 12673.20263 -90194.47341
13 44953.25899 12673.20263
14 42542.26484 44953.25899
15 -65783.07346 42542.26484
16 56607.81477 -65783.07346
17 92702.62301 56607.81477
18 -44086.65692 92702.62301
19 -66146.25271 -44086.65692
20 -9811.99995 -66146.25271
21 225571.79519 -9811.99995
22 29185.61607 225571.79519
23 -83307.10763 29185.61607
24 -118517.23075 -83307.10763
25 -54905.10595 -118517.23075
26 7451.86617 -54905.10595
27 -2044.45617 7451.86617
28 5877.79412 -2044.45617
29 71251.45232 5877.79412
30 -7145.43646 71251.45232
31 66500.88012 -7145.43646
32 38671.71592 66500.88012
33 -55348.00764 38671.71592
34 93051.79547 -55348.00764
35 61192.63987 93051.79547
36 114749.91313 61192.63987
37 29622.39503 114749.91313
38 19677.48132 29622.39503
39 -32549.25338 19677.48132
40 54681.23137 -32549.25338
41 -28145.57043 54681.23137
42 -7473.64893 -28145.57043
43 -31586.36309 -7473.64893
44 -10444.86513 -31586.36309
45 144682.54995 -10444.86513
46 -19717.31252 144682.54995
47 -69719.01419 -19717.31252
48 -1637.62005 -69719.01419
49 -63018.55552 -1637.62005
50 -19873.18228 -63018.55552
51 -20404.09403 -19873.18228
52 -50858.03212 -20404.09403
53 -14314.92424 -50858.03212
54 -16041.04811 -14314.92424
55 62420.20784 -16041.04811
56 -11942.41769 62420.20784
57 -24964.81965 -11942.41769
58 -17767.05921 -24964.81965
59 24646.50090 -17767.05921
60 -5525.39929 24646.50090
61 3492.30991 -5525.39929
62 11741.13471 3492.30991
63 21588.68968 11741.13471
64 65050.47773 21588.68968
65 -38952.95544 65050.47773
66 -78917.17062 -38952.95544
67 -54707.15753 -78917.17062
68 -59644.52246 -54707.15753
69 -103233.93581 -59644.52246
70 -15759.79068 -103233.93581
71 -21097.16356 -15759.79068
72 5708.67462 -21097.16356
73 4733.45865 5708.67462
74 -61253.64492 4733.45865
75 53450.74273 -61253.64492
76 50792.60261 53450.74273
77 -35575.95889 50792.60261
78 -68429.09808 -35575.95889
79 -28162.43640 -68429.09808
80 9371.28996 -28162.43640
81 109025.54758 9371.28996
82 -2093.03115 109025.54758
83 9267.74305 -2093.03115
84 -23756.97827 9267.74305
85 -26596.89153 -23756.97827
86 -34697.35718 -26596.89153
87 65260.22338 -34697.35718
88 36396.53374 65260.22338
89 -185384.93209 36396.53374
90 53870.15687 -185384.93209
91 -54936.50245 53870.15687
92 29707.48879 -54936.50245
93 -32508.94637 29707.48879
94 92234.49903 -32508.94637
95 -14792.72398 92234.49903
96 29918.36006 -14792.72398
97 -13843.92592 29918.36006
98 -20214.44634 -13843.92592
99 55658.13655 -20214.44634
100 -50391.18312 55658.13655
101 -1151.42752 -50391.18312
102 -71635.45741 -1151.42752
103 -24937.62505 -71635.45741
104 -7878.53353 -24937.62505
105 -57896.23082 -7878.53353
106 16651.23669 -57896.23082
107 -30535.75131 16651.23669
108 19030.32465 -30535.75131
109 -133123.14023 19030.32465
110 113025.93373 -133123.14023
111 -11691.17517 113025.93373
112 -14605.85963 -11691.17517
113 -101381.60134 -14605.85963
114 -12659.13741 -101381.60134
115 60.25208 -12659.13741
116 83454.09368 60.25208
117 -9559.67947 83454.09368
118 65775.33429 -9559.67947
119 -24377.26571 65775.33429
120 41758.28032 -24377.26571
121 15341.07905 41758.28032
122 -32928.05033 15341.07905
123 6038.84576 -32928.05033
124 -29801.56887 6038.84576
125 38240.63848 -29801.56887
126 31895.15515 38240.63848
127 12982.97717 31895.15515
128 104226.67976 12982.97717
129 -4136.43532 104226.67976
130 67074.00025 -4136.43532
131 5355.50192 67074.00025
132 -39634.37067 5355.50192
133 -162551.30112 -39634.37067
134 68041.51930 -162551.30112
135 -44409.37957 68041.51930
136 70199.70427 -44409.37957
137 -24464.31787 70199.70427
138 28881.89169 -24464.31787
139 5482.13383 28881.89169
140 55814.37252 5482.13383
141 97046.24022 55814.37252
142 -48607.54088 97046.24022
143 27526.79620 -48607.54088
144 3306.97016 27526.79620
145 -148059.88219 3306.97016
146 -22858.49623 -148059.88219
147 -81344.42957 -22858.49623
148 -15349.88430 -81344.42957
149 -11392.32521 -15349.88430
150 -14218.86517 -11392.32521
151 -14617.42421 -14218.86517
152 -13760.14815 -14617.42421
153 -13561.30613 -13760.14815
154 61305.84750 -13561.30613
155 16086.35272 61305.84750
156 -13561.30613 16086.35272
157 -16380.54230 -13561.30613
158 -18826.10147 -16380.54230
159 -2419.44098 -18826.10147
160 -1489.53767 -2419.44098
161 -10446.69524 -1489.53767
162 -14103.42421 -10446.69524
163 65085.44288 -14103.42421
164 NA 65085.44288
> dum1 <- dum[2:length(myerror),]
> dum1
lag(myerror, k = 1) myerror
[1,] -12363.23803 35452.38974
[2,] 17550.44819 -12363.23803
[3,] -100162.53408 17550.44819
[4,] 4115.17600 -100162.53408
[5,] -12159.30084 4115.17600
[6,] 213580.50841 -12159.30084
[7,] -5307.68488 213580.50841
[8,] 323.31027 -5307.68488
[9,] 48400.82262 323.31027
[10,] 53478.82180 48400.82262
[11,] -90194.47341 53478.82180
[12,] 12673.20263 -90194.47341
[13,] 44953.25899 12673.20263
[14,] 42542.26484 44953.25899
[15,] -65783.07346 42542.26484
[16,] 56607.81477 -65783.07346
[17,] 92702.62301 56607.81477
[18,] -44086.65692 92702.62301
[19,] -66146.25271 -44086.65692
[20,] -9811.99995 -66146.25271
[21,] 225571.79519 -9811.99995
[22,] 29185.61607 225571.79519
[23,] -83307.10763 29185.61607
[24,] -118517.23075 -83307.10763
[25,] -54905.10595 -118517.23075
[26,] 7451.86617 -54905.10595
[27,] -2044.45617 7451.86617
[28,] 5877.79412 -2044.45617
[29,] 71251.45232 5877.79412
[30,] -7145.43646 71251.45232
[31,] 66500.88012 -7145.43646
[32,] 38671.71592 66500.88012
[33,] -55348.00764 38671.71592
[34,] 93051.79547 -55348.00764
[35,] 61192.63987 93051.79547
[36,] 114749.91313 61192.63987
[37,] 29622.39503 114749.91313
[38,] 19677.48132 29622.39503
[39,] -32549.25338 19677.48132
[40,] 54681.23137 -32549.25338
[41,] -28145.57043 54681.23137
[42,] -7473.64893 -28145.57043
[43,] -31586.36309 -7473.64893
[44,] -10444.86513 -31586.36309
[45,] 144682.54995 -10444.86513
[46,] -19717.31252 144682.54995
[47,] -69719.01419 -19717.31252
[48,] -1637.62005 -69719.01419
[49,] -63018.55552 -1637.62005
[50,] -19873.18228 -63018.55552
[51,] -20404.09403 -19873.18228
[52,] -50858.03212 -20404.09403
[53,] -14314.92424 -50858.03212
[54,] -16041.04811 -14314.92424
[55,] 62420.20784 -16041.04811
[56,] -11942.41769 62420.20784
[57,] -24964.81965 -11942.41769
[58,] -17767.05921 -24964.81965
[59,] 24646.50090 -17767.05921
[60,] -5525.39929 24646.50090
[61,] 3492.30991 -5525.39929
[62,] 11741.13471 3492.30991
[63,] 21588.68968 11741.13471
[64,] 65050.47773 21588.68968
[65,] -38952.95544 65050.47773
[66,] -78917.17062 -38952.95544
[67,] -54707.15753 -78917.17062
[68,] -59644.52246 -54707.15753
[69,] -103233.93581 -59644.52246
[70,] -15759.79068 -103233.93581
[71,] -21097.16356 -15759.79068
[72,] 5708.67462 -21097.16356
[73,] 4733.45865 5708.67462
[74,] -61253.64492 4733.45865
[75,] 53450.74273 -61253.64492
[76,] 50792.60261 53450.74273
[77,] -35575.95889 50792.60261
[78,] -68429.09808 -35575.95889
[79,] -28162.43640 -68429.09808
[80,] 9371.28996 -28162.43640
[81,] 109025.54758 9371.28996
[82,] -2093.03115 109025.54758
[83,] 9267.74305 -2093.03115
[84,] -23756.97827 9267.74305
[85,] -26596.89153 -23756.97827
[86,] -34697.35718 -26596.89153
[87,] 65260.22338 -34697.35718
[88,] 36396.53374 65260.22338
[89,] -185384.93209 36396.53374
[90,] 53870.15687 -185384.93209
[91,] -54936.50245 53870.15687
[92,] 29707.48879 -54936.50245
[93,] -32508.94637 29707.48879
[94,] 92234.49903 -32508.94637
[95,] -14792.72398 92234.49903
[96,] 29918.36006 -14792.72398
[97,] -13843.92592 29918.36006
[98,] -20214.44634 -13843.92592
[99,] 55658.13655 -20214.44634
[100,] -50391.18312 55658.13655
[101,] -1151.42752 -50391.18312
[102,] -71635.45741 -1151.42752
[103,] -24937.62505 -71635.45741
[104,] -7878.53353 -24937.62505
[105,] -57896.23082 -7878.53353
[106,] 16651.23669 -57896.23082
[107,] -30535.75131 16651.23669
[108,] 19030.32465 -30535.75131
[109,] -133123.14023 19030.32465
[110,] 113025.93373 -133123.14023
[111,] -11691.17517 113025.93373
[112,] -14605.85963 -11691.17517
[113,] -101381.60134 -14605.85963
[114,] -12659.13741 -101381.60134
[115,] 60.25208 -12659.13741
[116,] 83454.09368 60.25208
[117,] -9559.67947 83454.09368
[118,] 65775.33429 -9559.67947
[119,] -24377.26571 65775.33429
[120,] 41758.28032 -24377.26571
[121,] 15341.07905 41758.28032
[122,] -32928.05033 15341.07905
[123,] 6038.84576 -32928.05033
[124,] -29801.56887 6038.84576
[125,] 38240.63848 -29801.56887
[126,] 31895.15515 38240.63848
[127,] 12982.97717 31895.15515
[128,] 104226.67976 12982.97717
[129,] -4136.43532 104226.67976
[130,] 67074.00025 -4136.43532
[131,] 5355.50192 67074.00025
[132,] -39634.37067 5355.50192
[133,] -162551.30112 -39634.37067
[134,] 68041.51930 -162551.30112
[135,] -44409.37957 68041.51930
[136,] 70199.70427 -44409.37957
[137,] -24464.31787 70199.70427
[138,] 28881.89169 -24464.31787
[139,] 5482.13383 28881.89169
[140,] 55814.37252 5482.13383
[141,] 97046.24022 55814.37252
[142,] -48607.54088 97046.24022
[143,] 27526.79620 -48607.54088
[144,] 3306.97016 27526.79620
[145,] -148059.88219 3306.97016
[146,] -22858.49623 -148059.88219
[147,] -81344.42957 -22858.49623
[148,] -15349.88430 -81344.42957
[149,] -11392.32521 -15349.88430
[150,] -14218.86517 -11392.32521
[151,] -14617.42421 -14218.86517
[152,] -13760.14815 -14617.42421
[153,] -13561.30613 -13760.14815
[154,] 61305.84750 -13561.30613
[155,] 16086.35272 61305.84750
[156,] -13561.30613 16086.35272
[157,] -16380.54230 -13561.30613
[158,] -18826.10147 -16380.54230
[159,] -2419.44098 -18826.10147
[160,] -1489.53767 -2419.44098
[161,] -10446.69524 -1489.53767
[162,] -14103.42421 -10446.69524
[163,] 65085.44288 -14103.42421
> z <- as.data.frame(dum1)
> z
lag(myerror, k = 1) myerror
1 -12363.23803 35452.38974
2 17550.44819 -12363.23803
3 -100162.53408 17550.44819
4 4115.17600 -100162.53408
5 -12159.30084 4115.17600
6 213580.50841 -12159.30084
7 -5307.68488 213580.50841
8 323.31027 -5307.68488
9 48400.82262 323.31027
10 53478.82180 48400.82262
11 -90194.47341 53478.82180
12 12673.20263 -90194.47341
13 44953.25899 12673.20263
14 42542.26484 44953.25899
15 -65783.07346 42542.26484
16 56607.81477 -65783.07346
17 92702.62301 56607.81477
18 -44086.65692 92702.62301
19 -66146.25271 -44086.65692
20 -9811.99995 -66146.25271
21 225571.79519 -9811.99995
22 29185.61607 225571.79519
23 -83307.10763 29185.61607
24 -118517.23075 -83307.10763
25 -54905.10595 -118517.23075
26 7451.86617 -54905.10595
27 -2044.45617 7451.86617
28 5877.79412 -2044.45617
29 71251.45232 5877.79412
30 -7145.43646 71251.45232
31 66500.88012 -7145.43646
32 38671.71592 66500.88012
33 -55348.00764 38671.71592
34 93051.79547 -55348.00764
35 61192.63987 93051.79547
36 114749.91313 61192.63987
37 29622.39503 114749.91313
38 19677.48132 29622.39503
39 -32549.25338 19677.48132
40 54681.23137 -32549.25338
41 -28145.57043 54681.23137
42 -7473.64893 -28145.57043
43 -31586.36309 -7473.64893
44 -10444.86513 -31586.36309
45 144682.54995 -10444.86513
46 -19717.31252 144682.54995
47 -69719.01419 -19717.31252
48 -1637.62005 -69719.01419
49 -63018.55552 -1637.62005
50 -19873.18228 -63018.55552
51 -20404.09403 -19873.18228
52 -50858.03212 -20404.09403
53 -14314.92424 -50858.03212
54 -16041.04811 -14314.92424
55 62420.20784 -16041.04811
56 -11942.41769 62420.20784
57 -24964.81965 -11942.41769
58 -17767.05921 -24964.81965
59 24646.50090 -17767.05921
60 -5525.39929 24646.50090
61 3492.30991 -5525.39929
62 11741.13471 3492.30991
63 21588.68968 11741.13471
64 65050.47773 21588.68968
65 -38952.95544 65050.47773
66 -78917.17062 -38952.95544
67 -54707.15753 -78917.17062
68 -59644.52246 -54707.15753
69 -103233.93581 -59644.52246
70 -15759.79068 -103233.93581
71 -21097.16356 -15759.79068
72 5708.67462 -21097.16356
73 4733.45865 5708.67462
74 -61253.64492 4733.45865
75 53450.74273 -61253.64492
76 50792.60261 53450.74273
77 -35575.95889 50792.60261
78 -68429.09808 -35575.95889
79 -28162.43640 -68429.09808
80 9371.28996 -28162.43640
81 109025.54758 9371.28996
82 -2093.03115 109025.54758
83 9267.74305 -2093.03115
84 -23756.97827 9267.74305
85 -26596.89153 -23756.97827
86 -34697.35718 -26596.89153
87 65260.22338 -34697.35718
88 36396.53374 65260.22338
89 -185384.93209 36396.53374
90 53870.15687 -185384.93209
91 -54936.50245 53870.15687
92 29707.48879 -54936.50245
93 -32508.94637 29707.48879
94 92234.49903 -32508.94637
95 -14792.72398 92234.49903
96 29918.36006 -14792.72398
97 -13843.92592 29918.36006
98 -20214.44634 -13843.92592
99 55658.13655 -20214.44634
100 -50391.18312 55658.13655
101 -1151.42752 -50391.18312
102 -71635.45741 -1151.42752
103 -24937.62505 -71635.45741
104 -7878.53353 -24937.62505
105 -57896.23082 -7878.53353
106 16651.23669 -57896.23082
107 -30535.75131 16651.23669
108 19030.32465 -30535.75131
109 -133123.14023 19030.32465
110 113025.93373 -133123.14023
111 -11691.17517 113025.93373
112 -14605.85963 -11691.17517
113 -101381.60134 -14605.85963
114 -12659.13741 -101381.60134
115 60.25208 -12659.13741
116 83454.09368 60.25208
117 -9559.67947 83454.09368
118 65775.33429 -9559.67947
119 -24377.26571 65775.33429
120 41758.28032 -24377.26571
121 15341.07905 41758.28032
122 -32928.05033 15341.07905
123 6038.84576 -32928.05033
124 -29801.56887 6038.84576
125 38240.63848 -29801.56887
126 31895.15515 38240.63848
127 12982.97717 31895.15515
128 104226.67976 12982.97717
129 -4136.43532 104226.67976
130 67074.00025 -4136.43532
131 5355.50192 67074.00025
132 -39634.37067 5355.50192
133 -162551.30112 -39634.37067
134 68041.51930 -162551.30112
135 -44409.37957 68041.51930
136 70199.70427 -44409.37957
137 -24464.31787 70199.70427
138 28881.89169 -24464.31787
139 5482.13383 28881.89169
140 55814.37252 5482.13383
141 97046.24022 55814.37252
142 -48607.54088 97046.24022
143 27526.79620 -48607.54088
144 3306.97016 27526.79620
145 -148059.88219 3306.97016
146 -22858.49623 -148059.88219
147 -81344.42957 -22858.49623
148 -15349.88430 -81344.42957
149 -11392.32521 -15349.88430
150 -14218.86517 -11392.32521
151 -14617.42421 -14218.86517
152 -13760.14815 -14617.42421
153 -13561.30613 -13760.14815
154 61305.84750 -13561.30613
155 16086.35272 61305.84750
156 -13561.30613 16086.35272
157 -16380.54230 -13561.30613
158 -18826.10147 -16380.54230
159 -2419.44098 -18826.10147
160 -1489.53767 -2419.44098
161 -10446.69524 -1489.53767
162 -14103.42421 -10446.69524
163 65085.44288 -14103.42421
> 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/7q5g31324656017.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/8ehxr1324656017.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/92h601324656017.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/1019pb1324656017.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$coefficients)[i] != 't') myeq <- paste(myeq, '[t]', sep='')
+ }
+ }
> myeq <- paste(myeq, ' + e[t]')
> a<-table.row.start(a)
> a<-table.element(a, myeq)
> a<-table.row.end(a)
> a<-table.end(a)
> table.save(a,file="/var/www/rcomp/tmp/11w1ec1324656017.tab")
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a,hyperlink('http://www.xycoon.com/ols1.htm','Multiple Linear Regression - Ordinary Least Squares',''), 6, TRUE)
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a,'Variable',header=TRUE)
> a<-table.element(a,'Parameter',header=TRUE)
> a<-table.element(a,'S.D.',header=TRUE)
> a<-table.element(a,'T-STAT
H0: parameter = 0',header=TRUE)
> a<-table.element(a,'2-tail p-value',header=TRUE)
> a<-table.element(a,'1-tail p-value',header=TRUE)
> a<-table.row.end(a)
> for (i in 1:k){
+ a<-table.row.start(a)
+ a<-table.element(a,rownames(mysum$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$coefficients[i,4]/2,6))
+ a<-table.row.end(a)
+ }
> a<-table.end(a)
> table.save(a,file="/var/www/rcomp/tmp/126kff1324656017.tab")
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a, 'Multiple Linear Regression - Regression Statistics', 2, TRUE)
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a, 'Multiple R',1,TRUE)
> a<-table.element(a, sqrt(mysum$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$sigma)
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a, 'Sum Squared Residuals',1,TRUE)
> a<-table.element(a, sum(myerror*myerror))
> a<-table.row.end(a)
> a<-table.end(a)
> table.save(a,file="/var/www/rcomp/tmp/13q5pv1324656017.tab")
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a, 'Multiple Linear Regression - Actuals, Interpolation, and Residuals', 4, TRUE)
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a, 'Time or Index', 1, TRUE)
> a<-table.element(a, 'Actuals', 1, TRUE)
> a<-table.element(a, 'Interpolation
Forecast', 1, TRUE)
> a<-table.element(a, 'Residuals
Prediction Error', 1, TRUE)
> a<-table.row.end(a)
> for (i in 1:n) {
+ a<-table.row.start(a)
+ a<-table.element(a,i, 1, TRUE)
+ a<-table.element(a,x[i])
+ a<-table.element(a,x[i]-mysum$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/14i5d81324656017.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/15btbp1324656017.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/16b9hd1324656017.tab")
+ }
>
> try(system("convert tmp/1dkje1324656017.ps tmp/1dkje1324656017.png",intern=TRUE))
character(0)
> try(system("convert tmp/2xk3p1324656017.ps tmp/2xk3p1324656017.png",intern=TRUE))
character(0)
> try(system("convert tmp/39mc21324656017.ps tmp/39mc21324656017.png",intern=TRUE))
character(0)
> try(system("convert tmp/4g4621324656017.ps tmp/4g4621324656017.png",intern=TRUE))
character(0)
> try(system("convert tmp/595qa1324656017.ps tmp/595qa1324656017.png",intern=TRUE))
character(0)
> try(system("convert tmp/65cgh1324656017.ps tmp/65cgh1324656017.png",intern=TRUE))
character(0)
> try(system("convert tmp/7q5g31324656017.ps tmp/7q5g31324656017.png",intern=TRUE))
character(0)
> try(system("convert tmp/8ehxr1324656017.ps tmp/8ehxr1324656017.png",intern=TRUE))
character(0)
> try(system("convert tmp/92h601324656017.ps tmp/92h601324656017.png",intern=TRUE))
character(0)
> try(system("convert tmp/1019pb1324656017.ps tmp/1019pb1324656017.png",intern=TRUE))
character(0)
>
>
> proc.time()
user system elapsed
5.750 0.380 6.146