R version 2.13.0 (2011-04-13)
Copyright (C) 2011 The R Foundation for Statistical Computing
ISBN 3-900051-07-0
Platform: i486-pc-linux-gnu (32-bit)
R is free software and comes with ABSOLUTELY NO WARRANTY.
You are welcome to redistribute it under certain conditions.
Type 'license()' or 'licence()' for distribution details.
R is a collaborative project with many contributors.
Type 'contributors()' for more information and
'citation()' on how to cite R or R packages in publications.
Type 'demo()' for some demos, 'help()' for on-line help, or
'help.start()' for an HTML browser interface to help.
Type 'q()' to quit R.
> x <- array(list(170650
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+ ,49)
+ ,dim=c(6
+ ,164)
+ ,dimnames=list(c('Total_time_RFC'
+ ,'Blogged_Comp'
+ ,'Feedback'
+ ,'reviews'
+ ,'characters'
+ ,'Hyperlinks')
+ ,1:164))
> y <- array(NA,dim=c(6,164),dimnames=list(c('Total_time_RFC','Blogged_Comp','Feedback','reviews','characters','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 = '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
Total_time_RFC Blogged_Comp Feedback reviews characters Hyperlinks
1 170650 65 26 99 95556 127
2 86621 54 20 77 54565 90
3 127843 58 27 102 63016 68
4 152526 99 25 96 79774 111
5 92389 41 17 49 31258 51
6 38138 0 16 64 52491 33
7 316392 112 20 76 91256 123
8 32750 1 18 67 22807 5
9 123444 40 19 72 77411 63
10 137034 60 22 83 48821 66
11 176816 68 30 113 52295 99
12 143205 74 40 151 63262 72
13 113286 38 26 88 50466 55
14 195452 77 36 123 62932 116
15 144513 62 31 118 38439 71
16 263581 126 41 157 70817 125
17 183271 85 24 92 105965 123
18 210763 74 27 103 73795 74
19 113853 78 19 72 82043 116
20 159968 100 30 115 74349 117
21 174585 79 31 115 82204 98
22 294675 77 26 92 55709 101
23 96213 42 15 56 37137 43
24 116390 83 33 132 70780 103
25 146342 103 28 107 55027 107
26 152647 71 27 102 56699 77
27 166661 77 21 78 65911 87
28 175505 100 27 103 56316 99
29 112485 45 21 81 26982 46
30 198790 101 30 114 54628 96
31 191822 87 30 115 96750 92
32 140267 44 33 118 53009 96
33 221991 97 35 133 64664 96
34 75339 32 26 99 36990 15
35 247985 89 27 103 85224 147
36 167351 71 25 93 37048 56
37 266609 70 30 114 59635 81
38 122024 50 20 76 42051 69
39 80964 30 8 27 26998 34
40 215183 90 24 92 63717 98
41 225469 78 25 96 55071 82
42 125382 48 28 104 40001 64
43 141437 57 23 84 54506 61
44 81106 31 21 79 35838 45
45 93125 30 21 57 50838 37
46 318668 72 26 99 86997 64
47 78800 20 26 82 33032 21
48 161048 84 30 113 61704 104
49 236367 94 34 129 117986 126
50 131108 79 30 110 56733 104
51 131096 72 18 78 55064 87
52 24188 8 4 12 5950 7
53 267003 67 31 114 84607 130
54 65029 21 18 67 32551 21
55 100147 30 14 52 31701 35
56 178549 70 21 80 71170 97
57 186965 89 37 138 101773 103
58 197266 87 24 92 101653 210
59 217300 116 29 105 81493 151
60 149594 54 24 91 55901 57
61 263413 112 31 118 109104 117
62 209228 94 21 77 114425 152
63 145699 51 31 122 36311 52
64 187197 52 26 99 70027 83
65 150752 38 24 92 73713 87
66 131218 65 18 70 40671 80
67 118697 64 21 81 89041 88
68 147913 66 29 107 57231 83
69 155015 99 24 92 68608 120
70 96487 100 21 77 59155 76
71 128780 56 30 115 55827 70
72 71972 22 20 76 22618 26
73 140266 51 30 115 58425 66
74 148454 62 24 92 65724 89
75 110655 97 26 100 56979 100
76 204822 99 27 103 72369 98
77 216052 77 24 92 79194 109
78 113421 58 23 87 202316 51
79 103660 77 26 100 44970 82
80 128390 52 25 95 49319 65
81 105502 48 18 69 36252 46
82 299359 111 30 115 75741 104
83 141493 28 25 95 38417 36
84 148356 86 27 55 64102 123
85 80953 49 8 28 56622 59
86 109237 24 21 79 15430 27
87 102104 46 26 99 72571 84
88 233139 44 24 92 67271 61
89 176507 49 30 98 43460 46
90 118217 108 27 103 99501 125
91 142694 44 24 89 28340 58
92 152193 110 25 95 76013 152
93 126500 30 21 78 37361 52
94 174710 82 24 92 48204 85
95 187772 49 24 92 76168 95
96 140903 64 24 92 85168 78
97 155350 75 24 83 125410 144
98 202077 123 24 92 123328 149
99 213875 104 40 151 83038 101
100 252952 106 22 83 120087 205
101 166981 73 31 118 91939 61
102 190562 110 26 98 103646 145
103 106351 30 20 76 29467 28
104 43287 13 19 71 43750 49
105 127493 69 15 57 34497 68
106 132143 75 22 83 66477 142
107 157469 82 25 95 71181 82
108 197727 108 28 108 74482 105
109 88077 28 23 91 174949 52
110 94968 83 25 99 46765 56
111 191753 52 26 100 90257 81
112 153332 90 32 119 51370 100
113 22938 12 1 0 1168 11
114 125927 87 24 91 51360 87
115 61857 23 11 32 25162 31
116 103749 57 31 117 21067 67
117 269909 93 26 99 58233 150
118 21054 4 0 0 855 4
119 174409 56 19 68 85903 75
120 31414 18 8 25 14116 39
121 200405 87 27 102 57637 88
122 139456 40 31 115 94137 67
123 78001 16 24 92 62147 24
124 82724 22 20 71 62832 58
125 38214 16 8 27 8773 16
126 91390 42 22 83 63785 49
127 197612 79 33 126 65196 109
128 137161 31 33 125 73087 124
129 251103 105 31 119 72631 115
130 209835 123 33 127 86281 128
131 269470 114 35 133 162365 159
132 139215 57 21 79 56530 75
133 77796 28 24 92 35606 30
134 197114 56 25 96 70111 83
135 291962 84 31 117 92046 135
136 56727 2 22 84 63989 8
137 254843 91 27 100 104911 115
138 105908 41 24 87 43448 60
139 170155 84 27 101 60029 99
140 136745 65 26 95 38650 98
141 86706 3 16 64 47261 36
142 251448 68 23 88 73586 93
143 152366 93 24 91 83042 158
144 173260 41 21 79 37238 16
145 212582 105 30 114 63958 100
146 87850 117 37 140 78956 49
147 148636 70 24 89 99518 89
148 185455 114 29 111 111436 153
149 0 0 0 0 0 0
150 14688 4 0 0 6023 5
151 98 0 0 0 0 0
152 455 0 0 0 0 0
153 0 0 0 0 0 0
154 0 0 0 0 0 0
155 137891 42 20 74 42564 80
156 201052 97 31 123 38885 122
157 0 0 0 0 0 0
158 203 0 0 0 0 0
159 7199 7 0 0 1644 6
160 46660 12 5 15 6179 13
161 17547 0 1 4 3926 3
162 73567 37 23 82 23238 18
163 969 0 0 0 0 0
164 106662 39 16 54 49288 49
> k <- length(x[1,])
> df <- as.data.frame(x)
> (mylm <- lm(df))
Call:
lm(formula = df)
Coefficients:
(Intercept) Blogged_Comp Feedback reviews characters
8103.6544 617.0127 1255.0633 258.4153 0.1737
Hyperlinks
457.6269
> (mysum <- summary(mylm))
Call:
lm(formula = df)
Residuals:
Min 1Q Median 3Q Max
-111195 -21999 -5745 15712 163528
Coefficients:
Estimate Std. Error t value Pr(>|t|)
(Intercept) 8103.6544 8723.3860 0.929 0.35433
Blogged_Comp 617.0127 199.6739 3.090 0.00237 **
Feedback 1255.0633 2333.5879 0.538 0.59145
reviews 258.4153 614.4599 0.421 0.67465
characters 0.1737 0.1405 1.236 0.21815
Hyperlinks 457.6269 152.1422 3.008 0.00306 **
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
Residual standard error: 40690 on 158 degrees of freedom
Multiple R-squared: 0.691, Adjusted R-squared: 0.6813
F-statistic: 70.68 on 5 and 158 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,] 0.7612836 4.774328e-01 2.387164e-01
[2,] 0.6552950 6.894099e-01 3.447050e-01
[3,] 0.7698556 4.602889e-01 2.301444e-01
[4,] 0.6739050 6.521900e-01 3.260950e-01
[5,] 0.5721032 8.557937e-01 4.278968e-01
[6,] 0.4839219 9.678437e-01 5.160781e-01
[7,] 0.4178003 8.356005e-01 5.821997e-01
[8,] 0.3286887 6.573774e-01 6.713113e-01
[9,] 0.2794902 5.589803e-01 7.205098e-01
[10,] 0.2786302 5.572604e-01 7.213698e-01
[11,] 0.3983104 7.966208e-01 6.016896e-01
[12,] 0.4290765 8.581530e-01 5.709235e-01
[13,] 0.3584450 7.168901e-01 6.415550e-01
[14,] 0.8576552 2.846896e-01 1.423448e-01
[15,] 0.8149458 3.701085e-01 1.850542e-01
[16,] 0.8349091 3.301817e-01 1.650909e-01
[17,] 0.8579064 2.841871e-01 1.420936e-01
[18,] 0.8169833 3.660333e-01 1.830167e-01
[19,] 0.7715982 4.568035e-01 2.284018e-01
[20,] 0.7269542 5.460915e-01 2.730458e-01
[21,] 0.6900098 6.199803e-01 3.099902e-01
[22,] 0.6326206 7.347587e-01 3.673794e-01
[23,] 0.5731835 8.536331e-01 4.268165e-01
[24,] 0.5246223 9.507554e-01 4.753777e-01
[25,] 0.4851846 9.703692e-01 5.148154e-01
[26,] 0.4333050 8.666101e-01 5.666950e-01
[27,] 0.4753015 9.506030e-01 5.246985e-01
[28,] 0.4359159 8.718317e-01 5.640841e-01
[29,] 0.7614304 4.771393e-01 2.385696e-01
[30,] 0.7170260 5.659481e-01 2.829740e-01
[31,] 0.6709946 6.580108e-01 3.290054e-01
[32,] 0.6536879 6.926242e-01 3.463121e-01
[33,] 0.7159484 5.681033e-01 2.840516e-01
[34,] 0.6701744 6.596513e-01 3.298256e-01
[35,] 0.6213767 7.572467e-01 3.786233e-01
[36,] 0.5748159 8.503683e-01 4.251841e-01
[37,] 0.5546876 8.906248e-01 4.453124e-01
[38,] 0.9561199 8.776015e-02 4.388007e-02
[39,] 0.9450291 1.099418e-01 5.497088e-02
[40,] 0.9346298 1.307403e-01 6.537016e-02
[41,] 0.9189227 1.621547e-01 8.107734e-02
[42,] 0.9228112 1.543776e-01 7.718878e-02
[43,] 0.9047202 1.905596e-01 9.527979e-02
[44,] 0.8821072 2.357855e-01 1.178928e-01
[45,] 0.9449478 1.101044e-01 5.505219e-02
[46,] 0.9307261 1.385477e-01 6.927386e-02
[47,] 0.9186250 1.627499e-01 8.137497e-02
[48,] 0.9036205 1.927591e-01 9.637954e-02
[49,] 0.8994969 2.010063e-01 1.005031e-01
[50,] 0.8865513 2.268975e-01 1.134487e-01
[51,] 0.8707243 2.585514e-01 1.292757e-01
[52,] 0.8486493 3.027014e-01 1.513507e-01
[53,] 0.8447354 3.105292e-01 1.552646e-01
[54,] 0.8229157 3.541685e-01 1.770843e-01
[55,] 0.7998910 4.002180e-01 2.001090e-01
[56,] 0.8004871 3.990258e-01 1.995129e-01
[57,] 0.7737189 4.525621e-01 2.262811e-01
[58,] 0.7369310 5.261380e-01 2.630690e-01
[59,] 0.7420759 5.158482e-01 2.579241e-01
[60,] 0.7065653 5.868694e-01 2.934347e-01
[61,] 0.7033656 5.932688e-01 2.966344e-01
[62,] 0.7994156 4.011688e-01 2.005844e-01
[63,] 0.7752052 4.495896e-01 2.247948e-01
[64,] 0.7413385 5.173230e-01 2.586615e-01
[65,] 0.7039806 5.920388e-01 2.960194e-01
[66,] 0.6631608 6.736783e-01 3.368392e-01
[67,] 0.7415103 5.169794e-01 2.584897e-01
[68,] 0.7102735 5.794530e-01 2.897265e-01
[69,] 0.7123281 5.753437e-01 2.876719e-01
[70,] 0.7665053 4.669894e-01 2.334947e-01
[71,] 0.7949829 4.100343e-01 2.050171e-01
[72,] 0.7616369 4.767262e-01 2.383631e-01
[73,] 0.7244933 5.510134e-01 2.755067e-01
[74,] 0.8661124 2.677751e-01 1.338876e-01
[75,] 0.8633373 2.733255e-01 1.366627e-01
[76,] 0.8553555 2.892890e-01 1.446445e-01
[77,] 0.8299166 3.401668e-01 1.700834e-01
[78,] 0.8106040 3.787920e-01 1.893960e-01
[79,] 0.8153743 3.692515e-01 1.846257e-01
[80,] 0.9412655 1.174689e-01 5.873447e-02
[81,] 0.9455995 1.088010e-01 5.440050e-02
[82,] 0.9801545 3.969097e-02 1.984548e-02
[83,] 0.9763192 4.736152e-02 2.368076e-02
[84,] 0.9845019 3.099613e-02 1.549807e-02
[85,] 0.9813997 3.720061e-02 1.860031e-02
[86,] 0.9764736 4.705278e-02 2.352639e-02
[87,] 0.9759862 4.802764e-02 2.401382e-02
[88,] 0.9689429 6.211421e-02 3.105711e-02
[89,] 0.9689192 6.216161e-02 3.108081e-02
[90,] 0.9644050 7.119004e-02 3.559502e-02
[91,] 0.9544882 9.102360e-02 4.551180e-02
[92,] 0.9447473 1.105053e-01 5.525266e-02
[93,] 0.9314887 1.370226e-01 6.851129e-02
[94,] 0.9267159 1.465682e-01 7.328412e-02
[95,] 0.9164668 1.670663e-01 8.353316e-02
[96,] 0.9200602 1.598795e-01 7.993976e-02
[97,] 0.9007739 1.984522e-01 9.922611e-02
[98,] 0.9296138 1.407724e-01 7.038621e-02
[99,] 0.9117022 1.765956e-01 8.829778e-02
[100,] 0.8902491 2.195018e-01 1.097509e-01
[101,] 0.9080103 1.839794e-01 9.198971e-02
[102,] 0.9163505 1.672990e-01 8.364950e-02
[103,] 0.9115485 1.769031e-01 8.845155e-02
[104,] 0.9016152 1.967697e-01 9.838484e-02
[105,] 0.8773807 2.452386e-01 1.226193e-01
[106,] 0.8743215 2.513571e-01 1.256785e-01
[107,] 0.8456738 3.086525e-01 1.543262e-01
[108,] 0.8363943 3.272114e-01 1.636057e-01
[109,] 0.8699477 2.601047e-01 1.300523e-01
[110,] 0.8406207 3.187585e-01 1.593793e-01
[111,] 0.8370941 3.258119e-01 1.629059e-01
[112,] 0.8141957 3.716086e-01 1.858043e-01
[113,] 0.7995692 4.008616e-01 2.004308e-01
[114,] 0.7603598 4.792803e-01 2.396402e-01
[115,] 0.7206690 5.586620e-01 2.793310e-01
[116,] 0.6895613 6.208774e-01 3.104387e-01
[117,] 0.6384756 7.230488e-01 3.615244e-01
[118,] 0.6068820 7.862360e-01 3.931180e-01
[119,] 0.5518093 8.963814e-01 4.481907e-01
[120,] 0.6325524 7.348952e-01 3.674476e-01
[121,] 0.6622380 6.755240e-01 3.377620e-01
[122,] 0.6101987 7.796025e-01 3.898013e-01
[123,] 0.5555556 8.888888e-01 4.444444e-01
[124,] 0.4947075 9.894150e-01 5.052925e-01
[125,] 0.4623100 9.246200e-01 5.376900e-01
[126,] 0.4478357 8.956715e-01 5.521643e-01
[127,] 0.5884702 8.230596e-01 4.115298e-01
[128,] 0.6085607 7.828786e-01 3.914393e-01
[129,] 0.7305227 5.389546e-01 2.694773e-01
[130,] 0.7042610 5.914781e-01 2.957390e-01
[131,] 0.6434720 7.130560e-01 3.565280e-01
[132,] 0.6112862 7.774277e-01 3.887138e-01
[133,] 0.7330209 5.339582e-01 2.669791e-01
[134,] 0.9306003 1.387993e-01 6.939966e-02
[135,] 0.9331633 1.336734e-01 6.683669e-02
[136,] 0.9999027 1.945893e-04 9.729466e-05
[137,] 0.9999996 7.633778e-07 3.816889e-07
[138,] 0.9999988 2.444200e-06 1.222100e-06
[139,] 0.9999999 1.088466e-07 5.442331e-08
[140,] 1.0000000 4.163569e-08 2.081784e-08
[141,] 0.9999998 3.199077e-07 1.599539e-07
[142,] 0.9999994 1.267170e-06 6.335848e-07
[143,] 0.9999950 1.002181e-05 5.010905e-06
[144,] 0.9999621 7.579565e-05 3.789782e-05
[145,] 0.9997397 5.206995e-04 2.603498e-04
[146,] 0.9983526 3.294833e-03 1.647416e-03
[147,] 0.9974304 5.139100e-03 2.569550e-03
> postscript(file="/var/wessaorg/rcomp/tmp/1gsyj1321985446.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/wessaorg/rcomp/tmp/2rhre1321985446.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> plot(mysum$resid, type='b', pch=19, main='Residuals', ylab='value of Residuals', xlab='time or index')
> grid()
> dev.off()
null device
1
> postscript(file="/var/wessaorg/rcomp/tmp/3adsu1321985446.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> hist(mysum$resid, main='Residual Histogram', xlab='values of Residuals')
> grid()
> dev.off()
null device
1
> postscript(file="/var/wessaorg/rcomp/tmp/4aum91321985446.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> densityplot(~mysum$resid,col='black',main='Residual Density Plot', xlab='values of Residuals')
> dev.off()
null device
1
> postscript(file="/var/wessaorg/rcomp/tmp/5tzi51321985446.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> qqnorm(mysum$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
-10487.58725 -50463.03554 -18354.76262 -37496.90046 -3777.99344
6 7 8 9 10
-30802.78091 122306.01279 -22124.54264 5933.65980 4167.84681
11 12 13 14 15
5515.77953 -43716.36831 -7569.98555 -1142.79930 -10412.42906
16 17 18 19 20
16203.14962 -5864.97900 49816.92246 -52162.46623 -43660.74957
21 22 23 24 25
-10010.77230 126760.49354 2770.25235 -77881.19624 -46628.51569
26 27 28 29 30
-4593.52891 13274.67122 -9888.59183 3591.13854 7837.66435
31 32 33 34 35
3764.82031 -20033.29726 20578.60669 -24012.09246 42392.15062
36 37 38 39 40
27969.19021 100778.92240 -550.16118 17084.32305 41739.62643
41 42 43 44 45
65964.59234 -10590.12291 10209.25576 -19713.20236 -336.01181
46 47 48 49 50
163528.21695 -10812.27507 -24046.57222 16105.40020 -49262.97420
51 52 53 54 55
-13556.33159 -1209.68785 75008.41797 -11200.01905 21002.18757
56 57 58 59 60
23475.35677 -22961.41519 -32168.70212 -9161.71418 18741.56858
61 62 63 64 65
44314.06335 7439.94012 5591.52004 38649.65450 12691.22992
66 67 68 69 70
-1344.97216 -31917.90612 -12882.81953 -34898.67537 -64625.03008
71 72 73 74 75
-22975.10253 -10273.01678 -7024.71274 -3942.92034 -71430.01118
76 77 78 79 80
17715.20451 42908.08372 -40292.14882 -55761.92986 -6035.08307
81 82 83 84 85
13.39985 94650.51852 37040.69808 -28330.67994 -11493.65712
86 87 88 89 90
24518.32523 -43640.69960 104393.20262 46594.80687 -91510.71379
91 92 93 94 95
22857.27909 -62468.17457 23088.34562 14845.94234 38836.72714
96 97 98 99 100
-11070.79096 -38277.19373 -25419.10692 -8262.32857 15716.71522
101 102 103 104 105
553.62554 -27724.97876 17065.19633 -45053.06874 6150.29596
106 107 108 109 110
-47824.21734 -7042.78551 -1050.39230 -43864.36641 -55055.95668
111 112 113 114 115
40349.25124 -35900.10591 938.39286 -38227.04641 -1069.12464
116 117 118 119 120
-42985.53508 67451.33390 8503.30351 41093.83168 -24595.67626
121 122 123 124 125
28095.47362 -8962.18524 -15646.38606 -19856.76323 -5625.17077
126 127 128 129 130
-25188.98872 5583.33012 -33227.43690 43314.07242 -21957.28208
131 132 133 134 135
11770.65662 5031.18433 -21392.05912 48114.32490 85122.92752
136 137 138 139 140
-16702.61906 60016.49037 -15099.83584 -5494.37538 -20205.16858
141 142 143 144 145
15449.56781 94441.86636 -53483.68586 79298.71965 15710.81187
146 147 148 149 150
-111195.23648 -13790.60935 -47438.48368 -8103.65439 782.17619
151 152 153 154 155
-8005.65439 -7648.65439 -8103.65439 -8103.65439 15646.78523
156 157 158 159 160
-177.37813 -8103.65439 -7900.65439 -8255.01015 13978.42129
161 162 163 164
5099.93182 -19695.54654 -7134.65439 9476.09373
> postscript(file="/var/wessaorg/rcomp/tmp/6ug2u1321985446.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 -10487.58725 NA
1 -50463.03554 -10487.58725
2 -18354.76262 -50463.03554
3 -37496.90046 -18354.76262
4 -3777.99344 -37496.90046
5 -30802.78091 -3777.99344
6 122306.01279 -30802.78091
7 -22124.54264 122306.01279
8 5933.65980 -22124.54264
9 4167.84681 5933.65980
10 5515.77953 4167.84681
11 -43716.36831 5515.77953
12 -7569.98555 -43716.36831
13 -1142.79930 -7569.98555
14 -10412.42906 -1142.79930
15 16203.14962 -10412.42906
16 -5864.97900 16203.14962
17 49816.92246 -5864.97900
18 -52162.46623 49816.92246
19 -43660.74957 -52162.46623
20 -10010.77230 -43660.74957
21 126760.49354 -10010.77230
22 2770.25235 126760.49354
23 -77881.19624 2770.25235
24 -46628.51569 -77881.19624
25 -4593.52891 -46628.51569
26 13274.67122 -4593.52891
27 -9888.59183 13274.67122
28 3591.13854 -9888.59183
29 7837.66435 3591.13854
30 3764.82031 7837.66435
31 -20033.29726 3764.82031
32 20578.60669 -20033.29726
33 -24012.09246 20578.60669
34 42392.15062 -24012.09246
35 27969.19021 42392.15062
36 100778.92240 27969.19021
37 -550.16118 100778.92240
38 17084.32305 -550.16118
39 41739.62643 17084.32305
40 65964.59234 41739.62643
41 -10590.12291 65964.59234
42 10209.25576 -10590.12291
43 -19713.20236 10209.25576
44 -336.01181 -19713.20236
45 163528.21695 -336.01181
46 -10812.27507 163528.21695
47 -24046.57222 -10812.27507
48 16105.40020 -24046.57222
49 -49262.97420 16105.40020
50 -13556.33159 -49262.97420
51 -1209.68785 -13556.33159
52 75008.41797 -1209.68785
53 -11200.01905 75008.41797
54 21002.18757 -11200.01905
55 23475.35677 21002.18757
56 -22961.41519 23475.35677
57 -32168.70212 -22961.41519
58 -9161.71418 -32168.70212
59 18741.56858 -9161.71418
60 44314.06335 18741.56858
61 7439.94012 44314.06335
62 5591.52004 7439.94012
63 38649.65450 5591.52004
64 12691.22992 38649.65450
65 -1344.97216 12691.22992
66 -31917.90612 -1344.97216
67 -12882.81953 -31917.90612
68 -34898.67537 -12882.81953
69 -64625.03008 -34898.67537
70 -22975.10253 -64625.03008
71 -10273.01678 -22975.10253
72 -7024.71274 -10273.01678
73 -3942.92034 -7024.71274
74 -71430.01118 -3942.92034
75 17715.20451 -71430.01118
76 42908.08372 17715.20451
77 -40292.14882 42908.08372
78 -55761.92986 -40292.14882
79 -6035.08307 -55761.92986
80 13.39985 -6035.08307
81 94650.51852 13.39985
82 37040.69808 94650.51852
83 -28330.67994 37040.69808
84 -11493.65712 -28330.67994
85 24518.32523 -11493.65712
86 -43640.69960 24518.32523
87 104393.20262 -43640.69960
88 46594.80687 104393.20262
89 -91510.71379 46594.80687
90 22857.27909 -91510.71379
91 -62468.17457 22857.27909
92 23088.34562 -62468.17457
93 14845.94234 23088.34562
94 38836.72714 14845.94234
95 -11070.79096 38836.72714
96 -38277.19373 -11070.79096
97 -25419.10692 -38277.19373
98 -8262.32857 -25419.10692
99 15716.71522 -8262.32857
100 553.62554 15716.71522
101 -27724.97876 553.62554
102 17065.19633 -27724.97876
103 -45053.06874 17065.19633
104 6150.29596 -45053.06874
105 -47824.21734 6150.29596
106 -7042.78551 -47824.21734
107 -1050.39230 -7042.78551
108 -43864.36641 -1050.39230
109 -55055.95668 -43864.36641
110 40349.25124 -55055.95668
111 -35900.10591 40349.25124
112 938.39286 -35900.10591
113 -38227.04641 938.39286
114 -1069.12464 -38227.04641
115 -42985.53508 -1069.12464
116 67451.33390 -42985.53508
117 8503.30351 67451.33390
118 41093.83168 8503.30351
119 -24595.67626 41093.83168
120 28095.47362 -24595.67626
121 -8962.18524 28095.47362
122 -15646.38606 -8962.18524
123 -19856.76323 -15646.38606
124 -5625.17077 -19856.76323
125 -25188.98872 -5625.17077
126 5583.33012 -25188.98872
127 -33227.43690 5583.33012
128 43314.07242 -33227.43690
129 -21957.28208 43314.07242
130 11770.65662 -21957.28208
131 5031.18433 11770.65662
132 -21392.05912 5031.18433
133 48114.32490 -21392.05912
134 85122.92752 48114.32490
135 -16702.61906 85122.92752
136 60016.49037 -16702.61906
137 -15099.83584 60016.49037
138 -5494.37538 -15099.83584
139 -20205.16858 -5494.37538
140 15449.56781 -20205.16858
141 94441.86636 15449.56781
142 -53483.68586 94441.86636
143 79298.71965 -53483.68586
144 15710.81187 79298.71965
145 -111195.23648 15710.81187
146 -13790.60935 -111195.23648
147 -47438.48368 -13790.60935
148 -8103.65439 -47438.48368
149 782.17619 -8103.65439
150 -8005.65439 782.17619
151 -7648.65439 -8005.65439
152 -8103.65439 -7648.65439
153 -8103.65439 -8103.65439
154 15646.78523 -8103.65439
155 -177.37813 15646.78523
156 -8103.65439 -177.37813
157 -7900.65439 -8103.65439
158 -8255.01015 -7900.65439
159 13978.42129 -8255.01015
160 5099.93182 13978.42129
161 -19695.54654 5099.93182
162 -7134.65439 -19695.54654
163 9476.09373 -7134.65439
164 NA 9476.09373
> dum1 <- dum[2:length(myerror),]
> dum1
lag(myerror, k = 1) myerror
[1,] -50463.03554 -10487.58725
[2,] -18354.76262 -50463.03554
[3,] -37496.90046 -18354.76262
[4,] -3777.99344 -37496.90046
[5,] -30802.78091 -3777.99344
[6,] 122306.01279 -30802.78091
[7,] -22124.54264 122306.01279
[8,] 5933.65980 -22124.54264
[9,] 4167.84681 5933.65980
[10,] 5515.77953 4167.84681
[11,] -43716.36831 5515.77953
[12,] -7569.98555 -43716.36831
[13,] -1142.79930 -7569.98555
[14,] -10412.42906 -1142.79930
[15,] 16203.14962 -10412.42906
[16,] -5864.97900 16203.14962
[17,] 49816.92246 -5864.97900
[18,] -52162.46623 49816.92246
[19,] -43660.74957 -52162.46623
[20,] -10010.77230 -43660.74957
[21,] 126760.49354 -10010.77230
[22,] 2770.25235 126760.49354
[23,] -77881.19624 2770.25235
[24,] -46628.51569 -77881.19624
[25,] -4593.52891 -46628.51569
[26,] 13274.67122 -4593.52891
[27,] -9888.59183 13274.67122
[28,] 3591.13854 -9888.59183
[29,] 7837.66435 3591.13854
[30,] 3764.82031 7837.66435
[31,] -20033.29726 3764.82031
[32,] 20578.60669 -20033.29726
[33,] -24012.09246 20578.60669
[34,] 42392.15062 -24012.09246
[35,] 27969.19021 42392.15062
[36,] 100778.92240 27969.19021
[37,] -550.16118 100778.92240
[38,] 17084.32305 -550.16118
[39,] 41739.62643 17084.32305
[40,] 65964.59234 41739.62643
[41,] -10590.12291 65964.59234
[42,] 10209.25576 -10590.12291
[43,] -19713.20236 10209.25576
[44,] -336.01181 -19713.20236
[45,] 163528.21695 -336.01181
[46,] -10812.27507 163528.21695
[47,] -24046.57222 -10812.27507
[48,] 16105.40020 -24046.57222
[49,] -49262.97420 16105.40020
[50,] -13556.33159 -49262.97420
[51,] -1209.68785 -13556.33159
[52,] 75008.41797 -1209.68785
[53,] -11200.01905 75008.41797
[54,] 21002.18757 -11200.01905
[55,] 23475.35677 21002.18757
[56,] -22961.41519 23475.35677
[57,] -32168.70212 -22961.41519
[58,] -9161.71418 -32168.70212
[59,] 18741.56858 -9161.71418
[60,] 44314.06335 18741.56858
[61,] 7439.94012 44314.06335
[62,] 5591.52004 7439.94012
[63,] 38649.65450 5591.52004
[64,] 12691.22992 38649.65450
[65,] -1344.97216 12691.22992
[66,] -31917.90612 -1344.97216
[67,] -12882.81953 -31917.90612
[68,] -34898.67537 -12882.81953
[69,] -64625.03008 -34898.67537
[70,] -22975.10253 -64625.03008
[71,] -10273.01678 -22975.10253
[72,] -7024.71274 -10273.01678
[73,] -3942.92034 -7024.71274
[74,] -71430.01118 -3942.92034
[75,] 17715.20451 -71430.01118
[76,] 42908.08372 17715.20451
[77,] -40292.14882 42908.08372
[78,] -55761.92986 -40292.14882
[79,] -6035.08307 -55761.92986
[80,] 13.39985 -6035.08307
[81,] 94650.51852 13.39985
[82,] 37040.69808 94650.51852
[83,] -28330.67994 37040.69808
[84,] -11493.65712 -28330.67994
[85,] 24518.32523 -11493.65712
[86,] -43640.69960 24518.32523
[87,] 104393.20262 -43640.69960
[88,] 46594.80687 104393.20262
[89,] -91510.71379 46594.80687
[90,] 22857.27909 -91510.71379
[91,] -62468.17457 22857.27909
[92,] 23088.34562 -62468.17457
[93,] 14845.94234 23088.34562
[94,] 38836.72714 14845.94234
[95,] -11070.79096 38836.72714
[96,] -38277.19373 -11070.79096
[97,] -25419.10692 -38277.19373
[98,] -8262.32857 -25419.10692
[99,] 15716.71522 -8262.32857
[100,] 553.62554 15716.71522
[101,] -27724.97876 553.62554
[102,] 17065.19633 -27724.97876
[103,] -45053.06874 17065.19633
[104,] 6150.29596 -45053.06874
[105,] -47824.21734 6150.29596
[106,] -7042.78551 -47824.21734
[107,] -1050.39230 -7042.78551
[108,] -43864.36641 -1050.39230
[109,] -55055.95668 -43864.36641
[110,] 40349.25124 -55055.95668
[111,] -35900.10591 40349.25124
[112,] 938.39286 -35900.10591
[113,] -38227.04641 938.39286
[114,] -1069.12464 -38227.04641
[115,] -42985.53508 -1069.12464
[116,] 67451.33390 -42985.53508
[117,] 8503.30351 67451.33390
[118,] 41093.83168 8503.30351
[119,] -24595.67626 41093.83168
[120,] 28095.47362 -24595.67626
[121,] -8962.18524 28095.47362
[122,] -15646.38606 -8962.18524
[123,] -19856.76323 -15646.38606
[124,] -5625.17077 -19856.76323
[125,] -25188.98872 -5625.17077
[126,] 5583.33012 -25188.98872
[127,] -33227.43690 5583.33012
[128,] 43314.07242 -33227.43690
[129,] -21957.28208 43314.07242
[130,] 11770.65662 -21957.28208
[131,] 5031.18433 11770.65662
[132,] -21392.05912 5031.18433
[133,] 48114.32490 -21392.05912
[134,] 85122.92752 48114.32490
[135,] -16702.61906 85122.92752
[136,] 60016.49037 -16702.61906
[137,] -15099.83584 60016.49037
[138,] -5494.37538 -15099.83584
[139,] -20205.16858 -5494.37538
[140,] 15449.56781 -20205.16858
[141,] 94441.86636 15449.56781
[142,] -53483.68586 94441.86636
[143,] 79298.71965 -53483.68586
[144,] 15710.81187 79298.71965
[145,] -111195.23648 15710.81187
[146,] -13790.60935 -111195.23648
[147,] -47438.48368 -13790.60935
[148,] -8103.65439 -47438.48368
[149,] 782.17619 -8103.65439
[150,] -8005.65439 782.17619
[151,] -7648.65439 -8005.65439
[152,] -8103.65439 -7648.65439
[153,] -8103.65439 -8103.65439
[154,] 15646.78523 -8103.65439
[155,] -177.37813 15646.78523
[156,] -8103.65439 -177.37813
[157,] -7900.65439 -8103.65439
[158,] -8255.01015 -7900.65439
[159,] 13978.42129 -8255.01015
[160,] 5099.93182 13978.42129
[161,] -19695.54654 5099.93182
[162,] -7134.65439 -19695.54654
[163,] 9476.09373 -7134.65439
> z <- as.data.frame(dum1)
> z
lag(myerror, k = 1) myerror
1 -50463.03554 -10487.58725
2 -18354.76262 -50463.03554
3 -37496.90046 -18354.76262
4 -3777.99344 -37496.90046
5 -30802.78091 -3777.99344
6 122306.01279 -30802.78091
7 -22124.54264 122306.01279
8 5933.65980 -22124.54264
9 4167.84681 5933.65980
10 5515.77953 4167.84681
11 -43716.36831 5515.77953
12 -7569.98555 -43716.36831
13 -1142.79930 -7569.98555
14 -10412.42906 -1142.79930
15 16203.14962 -10412.42906
16 -5864.97900 16203.14962
17 49816.92246 -5864.97900
18 -52162.46623 49816.92246
19 -43660.74957 -52162.46623
20 -10010.77230 -43660.74957
21 126760.49354 -10010.77230
22 2770.25235 126760.49354
23 -77881.19624 2770.25235
24 -46628.51569 -77881.19624
25 -4593.52891 -46628.51569
26 13274.67122 -4593.52891
27 -9888.59183 13274.67122
28 3591.13854 -9888.59183
29 7837.66435 3591.13854
30 3764.82031 7837.66435
31 -20033.29726 3764.82031
32 20578.60669 -20033.29726
33 -24012.09246 20578.60669
34 42392.15062 -24012.09246
35 27969.19021 42392.15062
36 100778.92240 27969.19021
37 -550.16118 100778.92240
38 17084.32305 -550.16118
39 41739.62643 17084.32305
40 65964.59234 41739.62643
41 -10590.12291 65964.59234
42 10209.25576 -10590.12291
43 -19713.20236 10209.25576
44 -336.01181 -19713.20236
45 163528.21695 -336.01181
46 -10812.27507 163528.21695
47 -24046.57222 -10812.27507
48 16105.40020 -24046.57222
49 -49262.97420 16105.40020
50 -13556.33159 -49262.97420
51 -1209.68785 -13556.33159
52 75008.41797 -1209.68785
53 -11200.01905 75008.41797
54 21002.18757 -11200.01905
55 23475.35677 21002.18757
56 -22961.41519 23475.35677
57 -32168.70212 -22961.41519
58 -9161.71418 -32168.70212
59 18741.56858 -9161.71418
60 44314.06335 18741.56858
61 7439.94012 44314.06335
62 5591.52004 7439.94012
63 38649.65450 5591.52004
64 12691.22992 38649.65450
65 -1344.97216 12691.22992
66 -31917.90612 -1344.97216
67 -12882.81953 -31917.90612
68 -34898.67537 -12882.81953
69 -64625.03008 -34898.67537
70 -22975.10253 -64625.03008
71 -10273.01678 -22975.10253
72 -7024.71274 -10273.01678
73 -3942.92034 -7024.71274
74 -71430.01118 -3942.92034
75 17715.20451 -71430.01118
76 42908.08372 17715.20451
77 -40292.14882 42908.08372
78 -55761.92986 -40292.14882
79 -6035.08307 -55761.92986
80 13.39985 -6035.08307
81 94650.51852 13.39985
82 37040.69808 94650.51852
83 -28330.67994 37040.69808
84 -11493.65712 -28330.67994
85 24518.32523 -11493.65712
86 -43640.69960 24518.32523
87 104393.20262 -43640.69960
88 46594.80687 104393.20262
89 -91510.71379 46594.80687
90 22857.27909 -91510.71379
91 -62468.17457 22857.27909
92 23088.34562 -62468.17457
93 14845.94234 23088.34562
94 38836.72714 14845.94234
95 -11070.79096 38836.72714
96 -38277.19373 -11070.79096
97 -25419.10692 -38277.19373
98 -8262.32857 -25419.10692
99 15716.71522 -8262.32857
100 553.62554 15716.71522
101 -27724.97876 553.62554
102 17065.19633 -27724.97876
103 -45053.06874 17065.19633
104 6150.29596 -45053.06874
105 -47824.21734 6150.29596
106 -7042.78551 -47824.21734
107 -1050.39230 -7042.78551
108 -43864.36641 -1050.39230
109 -55055.95668 -43864.36641
110 40349.25124 -55055.95668
111 -35900.10591 40349.25124
112 938.39286 -35900.10591
113 -38227.04641 938.39286
114 -1069.12464 -38227.04641
115 -42985.53508 -1069.12464
116 67451.33390 -42985.53508
117 8503.30351 67451.33390
118 41093.83168 8503.30351
119 -24595.67626 41093.83168
120 28095.47362 -24595.67626
121 -8962.18524 28095.47362
122 -15646.38606 -8962.18524
123 -19856.76323 -15646.38606
124 -5625.17077 -19856.76323
125 -25188.98872 -5625.17077
126 5583.33012 -25188.98872
127 -33227.43690 5583.33012
128 43314.07242 -33227.43690
129 -21957.28208 43314.07242
130 11770.65662 -21957.28208
131 5031.18433 11770.65662
132 -21392.05912 5031.18433
133 48114.32490 -21392.05912
134 85122.92752 48114.32490
135 -16702.61906 85122.92752
136 60016.49037 -16702.61906
137 -15099.83584 60016.49037
138 -5494.37538 -15099.83584
139 -20205.16858 -5494.37538
140 15449.56781 -20205.16858
141 94441.86636 15449.56781
142 -53483.68586 94441.86636
143 79298.71965 -53483.68586
144 15710.81187 79298.71965
145 -111195.23648 15710.81187
146 -13790.60935 -111195.23648
147 -47438.48368 -13790.60935
148 -8103.65439 -47438.48368
149 782.17619 -8103.65439
150 -8005.65439 782.17619
151 -7648.65439 -8005.65439
152 -8103.65439 -7648.65439
153 -8103.65439 -8103.65439
154 15646.78523 -8103.65439
155 -177.37813 15646.78523
156 -8103.65439 -177.37813
157 -7900.65439 -8103.65439
158 -8255.01015 -7900.65439
159 13978.42129 -8255.01015
160 5099.93182 13978.42129
161 -19695.54654 5099.93182
162 -7134.65439 -19695.54654
163 9476.09373 -7134.65439
> 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/wessaorg/rcomp/tmp/7aofz1321985446.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/wessaorg/rcomp/tmp/83nik1321985446.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/wessaorg/rcomp/tmp/9gg371321985446.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/wessaorg/rcomp/tmp/10yum81321985446.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/wessaorg/rcomp/createtable file can be downloaded at http://www.wessa.net/cretab
> load(file="/var/wessaorg/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$coefficients)[i] != 't') myeq <- paste(myeq, '[t]', sep='')
+ }
+ }
> myeq <- paste(myeq, ' + e[t]')
> a<-table.row.start(a)
> a<-table.element(a, myeq)
> a<-table.row.end(a)
> a<-table.end(a)
> table.save(a,file="/var/wessaorg/rcomp/tmp/118e3i1321985446.tab")
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a,hyperlink('http://www.xycoon.com/ols1.htm','Multiple Linear Regression - Ordinary Least Squares',''), 6, TRUE)
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a,'Variable',header=TRUE)
> a<-table.element(a,'Parameter',header=TRUE)
> a<-table.element(a,'S.D.',header=TRUE)
> a<-table.element(a,'T-STAT
H0: parameter = 0',header=TRUE)
> a<-table.element(a,'2-tail p-value',header=TRUE)
> a<-table.element(a,'1-tail p-value',header=TRUE)
> a<-table.row.end(a)
> for (i in 1:k){
+ a<-table.row.start(a)
+ a<-table.element(a,rownames(mysum$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$coefficients[i,4]/2,6))
+ a<-table.row.end(a)
+ }
> a<-table.end(a)
> table.save(a,file="/var/wessaorg/rcomp/tmp/128qr11321985446.tab")
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a, 'Multiple Linear Regression - Regression Statistics', 2, TRUE)
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a, 'Multiple R',1,TRUE)
> a<-table.element(a, sqrt(mysum$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$sigma)
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a, 'Sum Squared Residuals',1,TRUE)
> a<-table.element(a, sum(myerror*myerror))
> a<-table.row.end(a)
> a<-table.end(a)
> table.save(a,file="/var/wessaorg/rcomp/tmp/13pa6k1321985446.tab")
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a, 'Multiple Linear Regression - Actuals, Interpolation, and Residuals', 4, TRUE)
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a, 'Time or Index', 1, TRUE)
> a<-table.element(a, 'Actuals', 1, TRUE)
> a<-table.element(a, 'Interpolation
Forecast', 1, TRUE)
> a<-table.element(a, 'Residuals
Prediction Error', 1, TRUE)
> a<-table.row.end(a)
> for (i in 1:n) {
+ a<-table.row.start(a)
+ a<-table.element(a,i, 1, TRUE)
+ a<-table.element(a,x[i])
+ a<-table.element(a,x[i]-mysum$resid[i])
+ a<-table.element(a,mysum$resid[i])
+ a<-table.row.end(a)
+ }
> a<-table.end(a)
> table.save(a,file="/var/wessaorg/rcomp/tmp/14r9f11321985446.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/wessaorg/rcomp/tmp/15yv111321985446.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/wessaorg/rcomp/tmp/16jjmz1321985446.tab")
+ }
>
> try(system("convert tmp/1gsyj1321985446.ps tmp/1gsyj1321985446.png",intern=TRUE))
character(0)
> try(system("convert tmp/2rhre1321985446.ps tmp/2rhre1321985446.png",intern=TRUE))
character(0)
> try(system("convert tmp/3adsu1321985446.ps tmp/3adsu1321985446.png",intern=TRUE))
character(0)
> try(system("convert tmp/4aum91321985446.ps tmp/4aum91321985446.png",intern=TRUE))
character(0)
> try(system("convert tmp/5tzi51321985446.ps tmp/5tzi51321985446.png",intern=TRUE))
character(0)
> try(system("convert tmp/6ug2u1321985446.ps tmp/6ug2u1321985446.png",intern=TRUE))
character(0)
> try(system("convert tmp/7aofz1321985446.ps tmp/7aofz1321985446.png",intern=TRUE))
character(0)
> try(system("convert tmp/83nik1321985446.ps tmp/83nik1321985446.png",intern=TRUE))
character(0)
> try(system("convert tmp/9gg371321985446.ps tmp/9gg371321985446.png",intern=TRUE))
character(0)
> try(system("convert tmp/10yum81321985446.ps tmp/10yum81321985446.png",intern=TRUE))
character(0)
>
>
> proc.time()
user system elapsed
4.991 0.516 5.594