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)
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> x <- array(list(279055
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+ ,dim=c(7
+ ,164)
+ ,dimnames=list(c('Time_RFC'
+ ,'Pageviews'
+ ,'Logins'
+ ,'Bloggend_computations'
+ ,'Reviewed_compendiums'
+ ,'Long_fbmessages_PR'
+ ,'Time_compendium')
+ ,1:164))
> y <- array(NA,dim=c(7,164),dimnames=list(c('Time_RFC','Pageviews','Logins','Bloggend_computations','Reviewed_compendiums','Long_fbmessages_PR','Time_compendium'),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 = '1'
> #'GNU S' R Code compiled by R2WASP v. 1.0.44 ()
> #Author: Prof. Dr. P. Wessa
> #To cite this work: AUTHOR(S), (YEAR), YOUR SOFTWARE TITLE (vNUMBER) in Free Statistics Software (v$_version), Office for Research Development and Education, URL http://www.wessa.net/rwasp_YOURPAGE.wasp/
> #Source of accompanying publication: Office for Research, Development, and Education
> #Technical description: Write here your technical program description (don't use hard returns!)
> library(lattice)
> library(lmtest)
Loading required package: zoo
> 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
Time_RFC Pageviews Logins Bloggend_computations Reviewed_compendiums
1 279055 1818 73 96 42
2 212408 1433 75 75 38
3 233939 2059 83 70 46
4 222117 2733 106 134 42
5 189911 1399 56 83 30
6 70849 631 28 8 35
7 605767 5460 135 173 40
8 33186 381 19 1 18
9 227332 2150 62 88 38
10 267925 2042 49 104 37
11 371987 2536 122 114 46
12 264989 2377 131 125 60
13 212638 2100 87 57 37
14 368577 3020 85 139 55
15 269455 2265 88 87 44
16 398124 5139 191 176 63
17 335567 2363 77 114 40
18 428322 3548 172 121 43
19 182016 1477 58 103 32
20 267365 2398 89 135 52
21 279428 2546 73 123 49
22 508849 3150 111 99 41
23 217270 1694 48 77 25
24 200004 1787 58 103 57
25 257139 3792 133 158 45
26 270941 3108 138 116 42
27 324969 3230 134 114 45
28 329962 2348 92 150 43
29 190867 1780 60 64 36
30 393860 3218 79 150 45
31 327660 2692 89 143 50
32 269239 2187 83 50 50
33 396136 2577 106 145 51
34 130446 1293 49 56 42
35 430118 3567 104 141 44
36 273950 2764 56 83 42
37 428077 3755 128 112 44
38 254312 2075 93 79 40
39 120351 995 35 33 17
40 395658 3750 212 152 43
41 345875 3413 86 126 41
42 216827 2053 82 97 41
43 224524 1984 83 84 40
44 182485 1825 69 68 49
45 157164 2599 85 50 52
46 459455 5572 157 101 42
47 78800 918 42 20 26
48 255072 2685 85 107 59
49 368086 4145 123 150 50
50 230299 2841 70 129 50
51 244782 2175 81 99 47
52 24188 496 24 8 4
53 400109 2699 334 88 51
54 65029 744 17 21 18
55 101097 1161 64 30 14
56 309810 3333 67 102 41
57 375638 2970 91 166 61
58 367127 3968 204 132 40
59 381998 2878 155 161 44
60 280106 2399 90 90 40
61 400971 4121 153 160 51
62 315924 3294 122 139 29
63 291391 3132 124 104 43
64 295075 2868 93 103 42
65 280018 1778 81 66 41
66 267432 2109 71 163 30
67 217181 2148 141 93 39
68 258166 3009 159 85 51
69 264771 2562 88 154 40
70 182961 1737 73 143 29
71 256967 2680 74 107 47
72 73566 893 32 22 23
73 272362 2389 93 85 48
74 229056 2197 62 101 38
75 229851 2227 70 131 42
76 371391 2370 91 140 46
77 398210 3226 104 156 40
78 220419 1978 111 81 45
79 231884 2516 72 137 42
80 219381 2147 73 102 41
81 206169 2150 54 74 37
82 483074 4228 131 161 47
83 146100 1380 72 30 26
84 295224 2449 109 120 48
85 80953 870 25 49 8
86 217384 2700 63 121 27
87 179344 1574 62 76 38
88 415550 4046 222 85 41
89 389059 3259 129 151 61
90 180679 3098 106 165 45
91 299505 2615 104 89 41
92 292260 2404 84 168 42
93 199481 1932 68 48 35
94 282361 3147 78 149 36
95 329281 2598 89 75 40
96 234577 2108 48 107 40
97 297995 2193 67 116 38
98 342490 2478 90 181 43
99 416463 4198 163 155 65
100 415683 4069 119 165 33
101 297080 2842 142 121 51
102 331792 2562 71 176 45
103 229772 2449 202 86 36
104 43287 602 14 13 19
105 238089 2579 87 120 25
106 263322 2591 160 117 44
107 302082 2957 61 133 45
108 321797 2786 95 169 44
109 193926 1477 96 39 35
110 175138 3350 105 125 46
111 354041 2107 78 82 44
112 303273 2332 91 148 45
113 23668 400 13 12 1
114 196743 2233 79 146 40
115 61857 530 25 23 11
116 217543 2033 54 87 51
117 440711 3246 128 164 38
118 21054 387 16 4 0
119 252805 2137 52 81 30
120 31961 492 22 18 8
121 360436 3838 125 118 43
122 251948 2193 77 76 48
123 187320 1796 97 55 49
124 180842 1907 58 62 32
125 38214 568 34 16 8
126 280392 2602 56 98 43
127 358276 2819 84 137 52
128 211775 1464 67 50 53
129 447335 3946 90 152 49
130 348017 2554 99 163 48
131 441946 3506 133 142 56
132 215177 1552 43 80 45
133 130177 1389 47 59 40
134 318037 3101 365 94 48
135 466139 4541 198 128 50
136 162279 1872 62 63 43
137 416643 4403 140 127 46
138 178322 2113 86 60 40
139 292443 2046 54 118 45
140 283913 2564 100 110 46
141 244931 2073 127 46 37
142 387072 4112 125 96 45
143 246963 2340 93 128 39
144 173260 2035 63 41 21
145 346748 3241 108 146 50
146 178402 1991 60 147 55
147 268750 2828 96 121 40
148 314070 2748 112 185 48
149 1 2 0 0 0
150 14688 207 10 4 0
151 98 5 1 0 0
152 455 8 2 0 0
153 0 0 0 0 0
154 0 0 0 0 0
155 291847 2449 95 85 46
156 415421 3490 168 164 52
157 0 0 0 0 0
158 203 4 4 0 0
159 7199 151 5 7 0
160 46660 475 21 12 5
161 17547 141 5 0 1
162 121550 1145 46 37 48
163 969 29 2 0 0
164 242774 2080 75 62 34
Long_fbmessages_PR Time_compendium t
1 130 186099 1
2 143 113854 2
3 118 99776 3
4 146 106194 4
5 73 100792 5
6 89 47552 6
7 146 250931 7
8 22 6853 8
9 132 115466 9
10 92 110896 10
11 147 169351 11
12 203 94853 12
13 113 72591 13
14 171 101345 14
15 87 113713 15
16 208 165354 16
17 153 164263 17
18 97 135213 18
19 95 111669 19
20 197 134163 20
21 160 140303 21
22 148 150773 22
23 84 111848 23
24 227 102509 24
25 154 96785 25
26 151 116136 26
27 142 158376 27
28 148 153990 28
29 110 64057 29
30 149 230054 30
31 179 184531 31
32 149 114198 32
33 187 198299 33
34 153 33750 34
35 163 189723 35
36 127 100826 36
37 151 188355 37
38 100 104470 38
39 46 58391 39
40 156 164808 40
41 128 134097 41
42 111 80238 42
43 119 133252 43
44 148 54518 44
45 65 121850 45
46 134 79367 46
47 66 56968 47
48 201 106314 48
49 177 191889 49
50 156 104864 50
51 158 160792 51
52 7 15049 52
53 175 191179 53
54 61 25109 54
55 41 45824 55
56 133 129711 56
57 228 210012 57
58 140 194679 58
59 155 197680 59
60 141 81180 60
61 181 197765 61
62 75 214738 62
63 97 96252 63
64 142 124527 64
65 136 153242 65
66 87 145707 66
67 140 113963 67
68 169 134904 68
69 129 114268 69
70 92 94333 70
71 160 102204 71
72 67 23824 72
73 179 111563 73
74 90 91313 74
75 144 89770 75
76 144 100125 76
77 144 165278 77
78 134 181712 78
79 146 80906 79
80 121 75881 80
81 112 83963 81
82 145 175721 82
83 99 68580 83
84 96 136323 84
85 27 55792 85
86 77 25157 86
87 137 100922 87
88 151 118845 88
89 126 170492 89
90 159 81716 90
91 101 115750 91
92 144 105590 92
93 102 92795 93
94 135 82390 94
95 147 135599 95
96 155 127667 96
97 138 163073 97
98 113 211381 98
99 248 189944 99
100 116 226168 100
101 176 117495 101
102 140 195894 102
103 59 80684 103
104 64 19630 104
105 40 88634 105
106 98 139292 106
107 139 128602 107
108 135 135848 108
109 97 178377 109
110 142 106330 110
111 155 178303 111
112 115 116938 112
113 0 5841 113
114 103 106020 114
115 30 24610 115
116 130 74151 116
117 102 232241 117
118 0 6622 118
119 77 127097 119
120 9 13155 120
121 150 160501 121
122 163 91502 122
123 148 24469 123
124 94 88229 124
125 21 13983 125
126 151 80716 126
127 187 157384 127
128 171 122975 128
129 170 191469 129
130 145 231257 130
131 198 258287 131
132 152 122531 132
133 112 61394 133
134 173 86480 134
135 177 195791 135
136 153 18284 136
137 161 147581 137
138 115 72558 138
139 147 147341 139
140 124 114651 140
141 57 100187 141
142 144 130332 142
143 126 134218 143
144 78 10901 144
145 153 145758 145
146 196 75767 146
147 130 134969 147
148 159 169216 148
149 0 0 149
150 0 7953 150
151 0 0 151
152 0 0 152
153 0 0 153
154 0 0 154
155 94 105406 155
156 129 174586 156
157 0 0 157
158 0 0 158
159 0 4245 159
160 13 21509 160
161 4 7670 161
162 89 15673 162
163 0 0 163
164 71 75882 164
> k <- length(x[1,])
> df <- as.data.frame(x)
> (mylm <- lm(df))
Call:
lm(formula = df)
Coefficients:
(Intercept) Pageviews Logins
-1811.181 59.075 92.396
Bloggend_computations Reviewed_compendiums Long_fbmessages_PR
23.541 208.021 75.873
Time_compendium t
0.800 -5.924
> (mysum <- summary(mylm))
Call:
lm(formula = df)
Residuals:
Min 1Q Median 3Q Max
-138351 -16197 1595 19993 171743
Coefficients:
Estimate Std. Error t value Pr(>|t|)
(Intercept) -1811.1806 11188.1937 -0.162 0.872
Pageviews 59.0752 5.6258 10.501 <2e-16 ***
Logins 92.3962 83.9086 1.101 0.273
Bloggend_computations 23.5412 117.8615 0.200 0.842
Reviewed_compendiums 208.0207 515.3942 0.404 0.687
Long_fbmessages_PR 75.8730 139.3704 0.544 0.587
Time_compendium 0.8000 0.0837 9.558 <2e-16 ***
t -5.9238 66.5608 -0.089 0.929
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
Residual standard error: 37860 on 156 degrees of freedom
Multiple R-squared: 0.9135, Adjusted R-squared: 0.9096
F-statistic: 235.2 on 7 and 156 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,] 0.4556631 9.113261e-01 5.443369e-01
[2,] 0.2964595 5.929190e-01 7.035405e-01
[3,] 0.1977926 3.955852e-01 8.022074e-01
[4,] 0.2985541 5.971083e-01 7.014459e-01
[5,] 0.3263167 6.526334e-01 6.736833e-01
[6,] 0.7206060 5.587880e-01 2.793940e-01
[7,] 0.6883072 6.233855e-01 3.116928e-01
[8,] 0.8074014 3.851971e-01 1.925986e-01
[9,] 0.8778059 2.443882e-01 1.221941e-01
[10,] 0.8453299 3.093402e-01 1.546701e-01
[11,] 0.8237709 3.524583e-01 1.762291e-01
[12,] 0.9970764 5.847254e-03 2.923627e-03
[13,] 0.9969465 6.106918e-03 3.053459e-03
[14,] 0.9956508 8.698362e-03 4.349181e-03
[15,] 0.9980497 3.900635e-03 1.950318e-03
[16,] 0.9983452 3.309639e-03 1.654819e-03
[17,] 0.9989990 2.001925e-03 1.000963e-03
[18,] 0.9987834 2.433246e-03 1.216623e-03
[19,] 0.9980639 3.872191e-03 1.936096e-03
[20,] 0.9986742 2.651515e-03 1.325758e-03
[21,] 0.9981341 3.731741e-03 1.865871e-03
[22,] 0.9973318 5.336400e-03 2.668200e-03
[23,] 0.9973636 5.272840e-03 2.636420e-03
[24,] 0.9961517 7.696647e-03 3.848323e-03
[25,] 0.9952792 9.441661e-03 4.720830e-03
[26,] 0.9932288 1.354243e-02 6.771215e-03
[27,] 0.9916942 1.661165e-02 8.305826e-03
[28,] 0.9893129 2.137428e-02 1.068714e-02
[29,] 0.9859896 2.802081e-02 1.401041e-02
[30,] 0.9806945 3.861098e-02 1.930549e-02
[31,] 0.9746224 5.075517e-02 2.537758e-02
[32,] 0.9664845 6.703108e-02 3.351554e-02
[33,] 0.9676440 6.471196e-02 3.235598e-02
[34,] 0.9578671 8.426583e-02 4.213292e-02
[35,] 0.9961274 7.745289e-03 3.872644e-03
[36,] 0.9959643 8.071378e-03 4.035689e-03
[37,] 0.9955287 8.942511e-03 4.471256e-03
[38,] 0.9937869 1.242622e-02 6.213110e-03
[39,] 0.9965681 6.863705e-03 3.431853e-03
[40,] 0.9962713 7.457413e-03 3.728706e-03
[41,] 0.9958338 8.332449e-03 4.166225e-03
[42,] 0.9945497 1.090069e-02 5.450343e-03
[43,] 0.9941825 1.163495e-02 5.817477e-03
[44,] 0.9918111 1.637770e-02 8.188851e-03
[45,] 0.9888819 2.223625e-02 1.111812e-02
[46,] 0.9849712 3.005754e-02 1.502877e-02
[47,] 0.9802063 3.958749e-02 1.979375e-02
[48,] 0.9862850 2.743005e-02 1.371502e-02
[49,] 0.9852019 2.959625e-02 1.479813e-02
[50,] 0.9906623 1.867548e-02 9.337739e-03
[51,] 0.9893038 2.139232e-02 1.069616e-02
[52,] 0.9935582 1.288358e-02 6.441788e-03
[53,] 0.9927430 1.451409e-02 7.257044e-03
[54,] 0.9903088 1.938234e-02 9.691172e-03
[55,] 0.9901929 1.961430e-02 9.807148e-03
[56,] 0.9887531 2.249383e-02 1.124692e-02
[57,] 0.9861122 2.777559e-02 1.388780e-02
[58,] 0.9902890 1.942192e-02 9.710958e-03
[59,] 0.9875290 2.494195e-02 1.247098e-02
[60,] 0.9834992 3.300170e-02 1.650085e-02
[61,] 0.9788791 4.224188e-02 2.112094e-02
[62,] 0.9726403 5.471933e-02 2.735967e-02
[63,] 0.9670516 6.589687e-02 3.294844e-02
[64,] 0.9622145 7.557097e-02 3.778548e-02
[65,] 0.9532224 9.355516e-02 4.677758e-02
[66,] 0.9986122 2.775522e-03 1.387761e-03
[67,] 0.9990887 1.822560e-03 9.112800e-04
[68,] 0.9995620 8.760818e-04 4.380409e-04
[69,] 0.9993371 1.325753e-03 6.628765e-04
[70,] 0.9990736 1.852826e-03 9.264132e-04
[71,] 0.9986534 2.693258e-03 1.346629e-03
[72,] 0.9994154 1.169239e-03 5.846195e-04
[73,] 0.9991204 1.759281e-03 8.796407e-04
[74,] 0.9988544 2.291239e-03 1.145620e-03
[75,] 0.9983897 3.220642e-03 1.610321e-03
[76,] 0.9981466 3.706757e-03 1.853379e-03
[77,] 0.9973786 5.242856e-03 2.621428e-03
[78,] 0.9981603 3.679349e-03 1.839675e-03
[79,] 0.9978838 4.232316e-03 2.116158e-03
[80,] 0.9997703 4.593974e-04 2.296987e-04
[81,] 0.9997529 4.941948e-04 2.470974e-04
[82,] 0.9998172 3.655919e-04 1.827960e-04
[83,] 0.9997124 5.751540e-04 2.875770e-04
[84,] 0.9996032 7.935606e-04 3.967803e-04
[85,] 0.9997497 5.006754e-04 2.503377e-04
[86,] 0.9996115 7.769017e-04 3.884508e-04
[87,] 0.9995200 9.599636e-04 4.799818e-04
[88,] 0.9992847 1.430520e-03 7.152598e-04
[89,] 0.9990520 1.895921e-03 9.479607e-04
[90,] 0.9987671 2.465721e-03 1.232860e-03
[91,] 0.9981853 3.629498e-03 1.814749e-03
[92,] 0.9973439 5.312114e-03 2.656057e-03
[93,] 0.9961060 7.787953e-03 3.893977e-03
[94,] 0.9944094 1.118112e-02 5.590561e-03
[95,] 0.9921979 1.560429e-02 7.802144e-03
[96,] 0.9909490 1.810205e-02 9.051025e-03
[97,] 0.9874110 2.517806e-02 1.258903e-02
[98,] 0.9863497 2.730052e-02 1.365026e-02
[99,] 0.9944659 1.106812e-02 5.534060e-03
[100,] 0.9999986 2.806713e-06 1.403356e-06
[101,] 0.9999998 3.173018e-07 1.586509e-07
[102,] 1.0000000 9.039639e-08 4.519819e-08
[103,] 0.9999999 1.989073e-07 9.945367e-08
[104,] 1.0000000 6.968692e-08 3.484346e-08
[105,] 0.9999999 1.494985e-07 7.474926e-08
[106,] 0.9999998 3.103077e-07 1.551539e-07
[107,] 0.9999999 1.282619e-07 6.413096e-08
[108,] 0.9999999 2.949987e-07 1.474993e-07
[109,] 0.9999997 5.826891e-07 2.913446e-07
[110,] 0.9999994 1.266064e-06 6.330318e-07
[111,] 0.9999995 1.030660e-06 5.153301e-07
[112,] 0.9999992 1.675725e-06 8.378627e-07
[113,] 0.9999991 1.894541e-06 9.472704e-07
[114,] 0.9999989 2.206534e-06 1.103267e-06
[115,] 0.9999981 3.823269e-06 1.911634e-06
[116,] 0.9999987 2.636264e-06 1.318132e-06
[117,] 0.9999997 5.370618e-07 2.685309e-07
[118,] 0.9999993 1.303365e-06 6.516824e-07
[119,] 0.9999997 5.204102e-07 2.602051e-07
[120,] 0.9999993 1.330471e-06 6.652353e-07
[121,] 0.9999983 3.382596e-06 1.691298e-06
[122,] 0.9999975 5.025141e-06 2.512571e-06
[123,] 0.9999958 8.326288e-06 4.163144e-06
[124,] 0.9999936 1.284856e-05 6.424280e-06
[125,] 0.9999890 2.195781e-05 1.097891e-05
[126,] 0.9999964 7.140588e-06 3.570294e-06
[127,] 0.9999903 1.948238e-05 9.741192e-06
[128,] 0.9999872 2.552497e-05 1.276248e-05
[129,] 1.0000000 8.175579e-10 4.087789e-10
[130,] 1.0000000 2.657620e-09 1.328810e-09
[131,] 1.0000000 1.016050e-08 5.080249e-09
[132,] 1.0000000 4.048882e-08 2.024441e-08
[133,] 0.9999999 1.837079e-07 9.185393e-08
[134,] 0.9999996 8.882408e-07 4.441204e-07
[135,] 0.9999984 3.151519e-06 1.575760e-06
[136,] 0.9999999 2.164103e-07 1.082052e-07
[137,] 0.9999999 1.973062e-07 9.865312e-08
[138,] 0.9999998 3.069081e-07 1.534540e-07
[139,] 0.9999985 3.038472e-06 1.519236e-06
[140,] 0.9999897 2.063749e-05 1.031875e-05
[141,] 0.9999059 1.881672e-04 9.408360e-05
[142,] 0.9992342 1.531677e-03 7.658383e-04
[143,] 0.9942341 1.153190e-02 5.765948e-03
> postscript(file="/var/wessaorg/rcomp/tmp/1cii41324660989.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$resid)
> grid()
> dev.off()
null device
1
> postscript(file="/var/wessaorg/rcomp/tmp/2mk5i1324660989.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> plot(mysum$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/3p1b51324660989.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> hist(mysum$resid, main='Residual Histogram', xlab='values of Residuals')
> grid()
> dev.off()
null device
1
> postscript(file="/var/wessaorg/rcomp/tmp/4msba1324660989.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> densityplot(~mysum$resid,col='black',main='Residual Density Plot', xlab='values of Residuals')
> dev.off()
null device
1
> postscript(file="/var/wessaorg/rcomp/tmp/5v5kk1324660989.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
-3008.13124 11044.90681 6474.09321 -55217.10692 9566.09709
6 7 8 9 10
-19430.43330 48383.63743 -138.03441 -15906.43708 38795.97024
11 12 13 14 15
53892.13143 7638.52489 6745.81049 75448.17681 20648.22449
16 17 18 19 20
-86516.08050 36748.72414 77427.41006 -14296.12664 -16861.40132
21 22 23 24 25
-13255.32045 171742.89762 11845.82303 -22479.73160 -79395.07815
26 27 28 29 30
-39281.74110 -25770.85543 37835.12638 13566.28155 -9791.23157
31 32 33 34 35
-12569.52576 20133.56417 49264.97581 2883.68440 35191.04181
36 37 38 39 40
6530.43256 22525.78340 23832.10414 5864.24394 382.88183
41 42 43 44 45
9876.94197 6605.65719 -24210.89614 3732.62701 -116552.40973
46 47 48 49 50
33091.36054 -33682.57718 -24395.27749 -66914.02735 -51057.68640
51 52 53 54 55
-41803.95083 -18802.09237 33031.15733 -7316.43708 -14653.50668
56 57 58 59 60
-15923.30006 -7977.05809 -61768.18921 16974.54415 46155.11592
61 62 63 64 65
-40759.65016 -74545.98540 1341.67474 -2310.52080 26701.92450
66 67 68 69 70
5242.28694 -32625.33562 -65422.02966 -5637.07150 -16015.96502
71 72 73 74 75
-12157.32148 -9351.86583 10066.14695 5628.71519 -482.87195
76 77 78 79 80
121347.18506 45152.66000 -71215.99659 -8885.65197 7272.34892
81 82 83 84 85
-8646.80240 58354.22747 -8262.60212 13636.36864 -19936.62053
86 87 88 89 90
19948.04084 -17866.93921 41291.31709 24757.22766 -100466.30579
91 92 93 94 95
26878.95091 36750.19803 -8957.47351 4462.40252 40237.42873
96 97 98 99 100
-16740.36296 13076.41908 -703.29428 -32136.69892 -33766.77120
101 102 103 104 105
-2327.91660 -4541.94788 -9681.66859 -15960.56977 -1837.50385
106 107 108 109 110
-32860.38829 -1712.42982 18836.23800 -57998.53167 -138350.73110
111 112 113 114 115
59348.14824 44457.18053 -3845.89720 -44371.88260 5936.16723
116 117 118 119 120
13111.73895 34336.65579 -6167.92533 8607.47909 -9909.24973
121 122 123 124 125
-26818.27420 20473.81734 32506.45113 -20457.79651 -10750.88330
126 127 128 129 130
36781.35383 32409.97107 -1886.73008 28641.96946 -19252.79251
131 132 133 134 135
-11513.60745 1312.55972 -20943.83286 9218.53054 -1278.71898
136 137 138 139 140
11914.93762 3385.30512 -28325.32465 28057.69432 12559.27624
141 142 143 144 145
20127.73060 8447.32493 -25265.95088 29912.78209 5925.80118
146 147 148 149 150
-32469.70775 -33508.67768 -17703.23968 2576.68116 -2221.21940
151 152 153 154 155
2415.90692 2509.20885 2717.52699 2723.45083 38098.33852
156 157 158 159 160
32329.68925 2741.22232 2344.26052 -2990.99351 -97.86896
161 162 163 164
4872.93772 22282.59794 1847.79077 41126.84193
> postscript(file="/var/wessaorg/rcomp/tmp/6f07i1324660989.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 -3008.13124 NA
1 11044.90681 -3008.13124
2 6474.09321 11044.90681
3 -55217.10692 6474.09321
4 9566.09709 -55217.10692
5 -19430.43330 9566.09709
6 48383.63743 -19430.43330
7 -138.03441 48383.63743
8 -15906.43708 -138.03441
9 38795.97024 -15906.43708
10 53892.13143 38795.97024
11 7638.52489 53892.13143
12 6745.81049 7638.52489
13 75448.17681 6745.81049
14 20648.22449 75448.17681
15 -86516.08050 20648.22449
16 36748.72414 -86516.08050
17 77427.41006 36748.72414
18 -14296.12664 77427.41006
19 -16861.40132 -14296.12664
20 -13255.32045 -16861.40132
21 171742.89762 -13255.32045
22 11845.82303 171742.89762
23 -22479.73160 11845.82303
24 -79395.07815 -22479.73160
25 -39281.74110 -79395.07815
26 -25770.85543 -39281.74110
27 37835.12638 -25770.85543
28 13566.28155 37835.12638
29 -9791.23157 13566.28155
30 -12569.52576 -9791.23157
31 20133.56417 -12569.52576
32 49264.97581 20133.56417
33 2883.68440 49264.97581
34 35191.04181 2883.68440
35 6530.43256 35191.04181
36 22525.78340 6530.43256
37 23832.10414 22525.78340
38 5864.24394 23832.10414
39 382.88183 5864.24394
40 9876.94197 382.88183
41 6605.65719 9876.94197
42 -24210.89614 6605.65719
43 3732.62701 -24210.89614
44 -116552.40973 3732.62701
45 33091.36054 -116552.40973
46 -33682.57718 33091.36054
47 -24395.27749 -33682.57718
48 -66914.02735 -24395.27749
49 -51057.68640 -66914.02735
50 -41803.95083 -51057.68640
51 -18802.09237 -41803.95083
52 33031.15733 -18802.09237
53 -7316.43708 33031.15733
54 -14653.50668 -7316.43708
55 -15923.30006 -14653.50668
56 -7977.05809 -15923.30006
57 -61768.18921 -7977.05809
58 16974.54415 -61768.18921
59 46155.11592 16974.54415
60 -40759.65016 46155.11592
61 -74545.98540 -40759.65016
62 1341.67474 -74545.98540
63 -2310.52080 1341.67474
64 26701.92450 -2310.52080
65 5242.28694 26701.92450
66 -32625.33562 5242.28694
67 -65422.02966 -32625.33562
68 -5637.07150 -65422.02966
69 -16015.96502 -5637.07150
70 -12157.32148 -16015.96502
71 -9351.86583 -12157.32148
72 10066.14695 -9351.86583
73 5628.71519 10066.14695
74 -482.87195 5628.71519
75 121347.18506 -482.87195
76 45152.66000 121347.18506
77 -71215.99659 45152.66000
78 -8885.65197 -71215.99659
79 7272.34892 -8885.65197
80 -8646.80240 7272.34892
81 58354.22747 -8646.80240
82 -8262.60212 58354.22747
83 13636.36864 -8262.60212
84 -19936.62053 13636.36864
85 19948.04084 -19936.62053
86 -17866.93921 19948.04084
87 41291.31709 -17866.93921
88 24757.22766 41291.31709
89 -100466.30579 24757.22766
90 26878.95091 -100466.30579
91 36750.19803 26878.95091
92 -8957.47351 36750.19803
93 4462.40252 -8957.47351
94 40237.42873 4462.40252
95 -16740.36296 40237.42873
96 13076.41908 -16740.36296
97 -703.29428 13076.41908
98 -32136.69892 -703.29428
99 -33766.77120 -32136.69892
100 -2327.91660 -33766.77120
101 -4541.94788 -2327.91660
102 -9681.66859 -4541.94788
103 -15960.56977 -9681.66859
104 -1837.50385 -15960.56977
105 -32860.38829 -1837.50385
106 -1712.42982 -32860.38829
107 18836.23800 -1712.42982
108 -57998.53167 18836.23800
109 -138350.73110 -57998.53167
110 59348.14824 -138350.73110
111 44457.18053 59348.14824
112 -3845.89720 44457.18053
113 -44371.88260 -3845.89720
114 5936.16723 -44371.88260
115 13111.73895 5936.16723
116 34336.65579 13111.73895
117 -6167.92533 34336.65579
118 8607.47909 -6167.92533
119 -9909.24973 8607.47909
120 -26818.27420 -9909.24973
121 20473.81734 -26818.27420
122 32506.45113 20473.81734
123 -20457.79651 32506.45113
124 -10750.88330 -20457.79651
125 36781.35383 -10750.88330
126 32409.97107 36781.35383
127 -1886.73008 32409.97107
128 28641.96946 -1886.73008
129 -19252.79251 28641.96946
130 -11513.60745 -19252.79251
131 1312.55972 -11513.60745
132 -20943.83286 1312.55972
133 9218.53054 -20943.83286
134 -1278.71898 9218.53054
135 11914.93762 -1278.71898
136 3385.30512 11914.93762
137 -28325.32465 3385.30512
138 28057.69432 -28325.32465
139 12559.27624 28057.69432
140 20127.73060 12559.27624
141 8447.32493 20127.73060
142 -25265.95088 8447.32493
143 29912.78209 -25265.95088
144 5925.80118 29912.78209
145 -32469.70775 5925.80118
146 -33508.67768 -32469.70775
147 -17703.23968 -33508.67768
148 2576.68116 -17703.23968
149 -2221.21940 2576.68116
150 2415.90692 -2221.21940
151 2509.20885 2415.90692
152 2717.52699 2509.20885
153 2723.45083 2717.52699
154 38098.33852 2723.45083
155 32329.68925 38098.33852
156 2741.22232 32329.68925
157 2344.26052 2741.22232
158 -2990.99351 2344.26052
159 -97.86896 -2990.99351
160 4872.93772 -97.86896
161 22282.59794 4872.93772
162 1847.79077 22282.59794
163 41126.84193 1847.79077
164 NA 41126.84193
> dum1 <- dum[2:length(myerror),]
> dum1
lag(myerror, k = 1) myerror
[1,] 11044.90681 -3008.13124
[2,] 6474.09321 11044.90681
[3,] -55217.10692 6474.09321
[4,] 9566.09709 -55217.10692
[5,] -19430.43330 9566.09709
[6,] 48383.63743 -19430.43330
[7,] -138.03441 48383.63743
[8,] -15906.43708 -138.03441
[9,] 38795.97024 -15906.43708
[10,] 53892.13143 38795.97024
[11,] 7638.52489 53892.13143
[12,] 6745.81049 7638.52489
[13,] 75448.17681 6745.81049
[14,] 20648.22449 75448.17681
[15,] -86516.08050 20648.22449
[16,] 36748.72414 -86516.08050
[17,] 77427.41006 36748.72414
[18,] -14296.12664 77427.41006
[19,] -16861.40132 -14296.12664
[20,] -13255.32045 -16861.40132
[21,] 171742.89762 -13255.32045
[22,] 11845.82303 171742.89762
[23,] -22479.73160 11845.82303
[24,] -79395.07815 -22479.73160
[25,] -39281.74110 -79395.07815
[26,] -25770.85543 -39281.74110
[27,] 37835.12638 -25770.85543
[28,] 13566.28155 37835.12638
[29,] -9791.23157 13566.28155
[30,] -12569.52576 -9791.23157
[31,] 20133.56417 -12569.52576
[32,] 49264.97581 20133.56417
[33,] 2883.68440 49264.97581
[34,] 35191.04181 2883.68440
[35,] 6530.43256 35191.04181
[36,] 22525.78340 6530.43256
[37,] 23832.10414 22525.78340
[38,] 5864.24394 23832.10414
[39,] 382.88183 5864.24394
[40,] 9876.94197 382.88183
[41,] 6605.65719 9876.94197
[42,] -24210.89614 6605.65719
[43,] 3732.62701 -24210.89614
[44,] -116552.40973 3732.62701
[45,] 33091.36054 -116552.40973
[46,] -33682.57718 33091.36054
[47,] -24395.27749 -33682.57718
[48,] -66914.02735 -24395.27749
[49,] -51057.68640 -66914.02735
[50,] -41803.95083 -51057.68640
[51,] -18802.09237 -41803.95083
[52,] 33031.15733 -18802.09237
[53,] -7316.43708 33031.15733
[54,] -14653.50668 -7316.43708
[55,] -15923.30006 -14653.50668
[56,] -7977.05809 -15923.30006
[57,] -61768.18921 -7977.05809
[58,] 16974.54415 -61768.18921
[59,] 46155.11592 16974.54415
[60,] -40759.65016 46155.11592
[61,] -74545.98540 -40759.65016
[62,] 1341.67474 -74545.98540
[63,] -2310.52080 1341.67474
[64,] 26701.92450 -2310.52080
[65,] 5242.28694 26701.92450
[66,] -32625.33562 5242.28694
[67,] -65422.02966 -32625.33562
[68,] -5637.07150 -65422.02966
[69,] -16015.96502 -5637.07150
[70,] -12157.32148 -16015.96502
[71,] -9351.86583 -12157.32148
[72,] 10066.14695 -9351.86583
[73,] 5628.71519 10066.14695
[74,] -482.87195 5628.71519
[75,] 121347.18506 -482.87195
[76,] 45152.66000 121347.18506
[77,] -71215.99659 45152.66000
[78,] -8885.65197 -71215.99659
[79,] 7272.34892 -8885.65197
[80,] -8646.80240 7272.34892
[81,] 58354.22747 -8646.80240
[82,] -8262.60212 58354.22747
[83,] 13636.36864 -8262.60212
[84,] -19936.62053 13636.36864
[85,] 19948.04084 -19936.62053
[86,] -17866.93921 19948.04084
[87,] 41291.31709 -17866.93921
[88,] 24757.22766 41291.31709
[89,] -100466.30579 24757.22766
[90,] 26878.95091 -100466.30579
[91,] 36750.19803 26878.95091
[92,] -8957.47351 36750.19803
[93,] 4462.40252 -8957.47351
[94,] 40237.42873 4462.40252
[95,] -16740.36296 40237.42873
[96,] 13076.41908 -16740.36296
[97,] -703.29428 13076.41908
[98,] -32136.69892 -703.29428
[99,] -33766.77120 -32136.69892
[100,] -2327.91660 -33766.77120
[101,] -4541.94788 -2327.91660
[102,] -9681.66859 -4541.94788
[103,] -15960.56977 -9681.66859
[104,] -1837.50385 -15960.56977
[105,] -32860.38829 -1837.50385
[106,] -1712.42982 -32860.38829
[107,] 18836.23800 -1712.42982
[108,] -57998.53167 18836.23800
[109,] -138350.73110 -57998.53167
[110,] 59348.14824 -138350.73110
[111,] 44457.18053 59348.14824
[112,] -3845.89720 44457.18053
[113,] -44371.88260 -3845.89720
[114,] 5936.16723 -44371.88260
[115,] 13111.73895 5936.16723
[116,] 34336.65579 13111.73895
[117,] -6167.92533 34336.65579
[118,] 8607.47909 -6167.92533
[119,] -9909.24973 8607.47909
[120,] -26818.27420 -9909.24973
[121,] 20473.81734 -26818.27420
[122,] 32506.45113 20473.81734
[123,] -20457.79651 32506.45113
[124,] -10750.88330 -20457.79651
[125,] 36781.35383 -10750.88330
[126,] 32409.97107 36781.35383
[127,] -1886.73008 32409.97107
[128,] 28641.96946 -1886.73008
[129,] -19252.79251 28641.96946
[130,] -11513.60745 -19252.79251
[131,] 1312.55972 -11513.60745
[132,] -20943.83286 1312.55972
[133,] 9218.53054 -20943.83286
[134,] -1278.71898 9218.53054
[135,] 11914.93762 -1278.71898
[136,] 3385.30512 11914.93762
[137,] -28325.32465 3385.30512
[138,] 28057.69432 -28325.32465
[139,] 12559.27624 28057.69432
[140,] 20127.73060 12559.27624
[141,] 8447.32493 20127.73060
[142,] -25265.95088 8447.32493
[143,] 29912.78209 -25265.95088
[144,] 5925.80118 29912.78209
[145,] -32469.70775 5925.80118
[146,] -33508.67768 -32469.70775
[147,] -17703.23968 -33508.67768
[148,] 2576.68116 -17703.23968
[149,] -2221.21940 2576.68116
[150,] 2415.90692 -2221.21940
[151,] 2509.20885 2415.90692
[152,] 2717.52699 2509.20885
[153,] 2723.45083 2717.52699
[154,] 38098.33852 2723.45083
[155,] 32329.68925 38098.33852
[156,] 2741.22232 32329.68925
[157,] 2344.26052 2741.22232
[158,] -2990.99351 2344.26052
[159,] -97.86896 -2990.99351
[160,] 4872.93772 -97.86896
[161,] 22282.59794 4872.93772
[162,] 1847.79077 22282.59794
[163,] 41126.84193 1847.79077
> z <- as.data.frame(dum1)
> z
lag(myerror, k = 1) myerror
1 11044.90681 -3008.13124
2 6474.09321 11044.90681
3 -55217.10692 6474.09321
4 9566.09709 -55217.10692
5 -19430.43330 9566.09709
6 48383.63743 -19430.43330
7 -138.03441 48383.63743
8 -15906.43708 -138.03441
9 38795.97024 -15906.43708
10 53892.13143 38795.97024
11 7638.52489 53892.13143
12 6745.81049 7638.52489
13 75448.17681 6745.81049
14 20648.22449 75448.17681
15 -86516.08050 20648.22449
16 36748.72414 -86516.08050
17 77427.41006 36748.72414
18 -14296.12664 77427.41006
19 -16861.40132 -14296.12664
20 -13255.32045 -16861.40132
21 171742.89762 -13255.32045
22 11845.82303 171742.89762
23 -22479.73160 11845.82303
24 -79395.07815 -22479.73160
25 -39281.74110 -79395.07815
26 -25770.85543 -39281.74110
27 37835.12638 -25770.85543
28 13566.28155 37835.12638
29 -9791.23157 13566.28155
30 -12569.52576 -9791.23157
31 20133.56417 -12569.52576
32 49264.97581 20133.56417
33 2883.68440 49264.97581
34 35191.04181 2883.68440
35 6530.43256 35191.04181
36 22525.78340 6530.43256
37 23832.10414 22525.78340
38 5864.24394 23832.10414
39 382.88183 5864.24394
40 9876.94197 382.88183
41 6605.65719 9876.94197
42 -24210.89614 6605.65719
43 3732.62701 -24210.89614
44 -116552.40973 3732.62701
45 33091.36054 -116552.40973
46 -33682.57718 33091.36054
47 -24395.27749 -33682.57718
48 -66914.02735 -24395.27749
49 -51057.68640 -66914.02735
50 -41803.95083 -51057.68640
51 -18802.09237 -41803.95083
52 33031.15733 -18802.09237
53 -7316.43708 33031.15733
54 -14653.50668 -7316.43708
55 -15923.30006 -14653.50668
56 -7977.05809 -15923.30006
57 -61768.18921 -7977.05809
58 16974.54415 -61768.18921
59 46155.11592 16974.54415
60 -40759.65016 46155.11592
61 -74545.98540 -40759.65016
62 1341.67474 -74545.98540
63 -2310.52080 1341.67474
64 26701.92450 -2310.52080
65 5242.28694 26701.92450
66 -32625.33562 5242.28694
67 -65422.02966 -32625.33562
68 -5637.07150 -65422.02966
69 -16015.96502 -5637.07150
70 -12157.32148 -16015.96502
71 -9351.86583 -12157.32148
72 10066.14695 -9351.86583
73 5628.71519 10066.14695
74 -482.87195 5628.71519
75 121347.18506 -482.87195
76 45152.66000 121347.18506
77 -71215.99659 45152.66000
78 -8885.65197 -71215.99659
79 7272.34892 -8885.65197
80 -8646.80240 7272.34892
81 58354.22747 -8646.80240
82 -8262.60212 58354.22747
83 13636.36864 -8262.60212
84 -19936.62053 13636.36864
85 19948.04084 -19936.62053
86 -17866.93921 19948.04084
87 41291.31709 -17866.93921
88 24757.22766 41291.31709
89 -100466.30579 24757.22766
90 26878.95091 -100466.30579
91 36750.19803 26878.95091
92 -8957.47351 36750.19803
93 4462.40252 -8957.47351
94 40237.42873 4462.40252
95 -16740.36296 40237.42873
96 13076.41908 -16740.36296
97 -703.29428 13076.41908
98 -32136.69892 -703.29428
99 -33766.77120 -32136.69892
100 -2327.91660 -33766.77120
101 -4541.94788 -2327.91660
102 -9681.66859 -4541.94788
103 -15960.56977 -9681.66859
104 -1837.50385 -15960.56977
105 -32860.38829 -1837.50385
106 -1712.42982 -32860.38829
107 18836.23800 -1712.42982
108 -57998.53167 18836.23800
109 -138350.73110 -57998.53167
110 59348.14824 -138350.73110
111 44457.18053 59348.14824
112 -3845.89720 44457.18053
113 -44371.88260 -3845.89720
114 5936.16723 -44371.88260
115 13111.73895 5936.16723
116 34336.65579 13111.73895
117 -6167.92533 34336.65579
118 8607.47909 -6167.92533
119 -9909.24973 8607.47909
120 -26818.27420 -9909.24973
121 20473.81734 -26818.27420
122 32506.45113 20473.81734
123 -20457.79651 32506.45113
124 -10750.88330 -20457.79651
125 36781.35383 -10750.88330
126 32409.97107 36781.35383
127 -1886.73008 32409.97107
128 28641.96946 -1886.73008
129 -19252.79251 28641.96946
130 -11513.60745 -19252.79251
131 1312.55972 -11513.60745
132 -20943.83286 1312.55972
133 9218.53054 -20943.83286
134 -1278.71898 9218.53054
135 11914.93762 -1278.71898
136 3385.30512 11914.93762
137 -28325.32465 3385.30512
138 28057.69432 -28325.32465
139 12559.27624 28057.69432
140 20127.73060 12559.27624
141 8447.32493 20127.73060
142 -25265.95088 8447.32493
143 29912.78209 -25265.95088
144 5925.80118 29912.78209
145 -32469.70775 5925.80118
146 -33508.67768 -32469.70775
147 -17703.23968 -33508.67768
148 2576.68116 -17703.23968
149 -2221.21940 2576.68116
150 2415.90692 -2221.21940
151 2509.20885 2415.90692
152 2717.52699 2509.20885
153 2723.45083 2717.52699
154 38098.33852 2723.45083
155 32329.68925 38098.33852
156 2741.22232 32329.68925
157 2344.26052 2741.22232
158 -2990.99351 2344.26052
159 -97.86896 -2990.99351
160 4872.93772 -97.86896
161 22282.59794 4872.93772
162 1847.79077 22282.59794
163 41126.84193 1847.79077
> 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/7qvhx1324660989.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> acf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/wessaorg/rcomp/tmp/89gfm1324660989.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> pacf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Partial Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/wessaorg/rcomp/tmp/9zxrl1324660989.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> opar <- par(mfrow = c(2,2), oma = c(0, 0, 1.1, 0))
> plot(mylm, las = 1, sub='Residual Diagnostics')
> par(opar)
> dev.off()
null device
1
> if (n > n25) {
+ postscript(file="/var/wessaorg/rcomp/tmp/10ix481324660989.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
+ plot(kp3:nmkm3,gqarr[,2], main='Goldfeld-Quandt test',ylab='2-sided p-value',xlab='breakpoint')
+ grid()
+ dev.off()
+ }
null device
1
>
> #Note: the /var/wessaorg/rcomp/createtable file can be downloaded at http://www.wessa.net/cretab
> load(file="/var/wessaorg/rcomp/createtable")
>
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a, 'Multiple Linear Regression - Estimated Regression Equation', 1, TRUE)
> a<-table.row.end(a)
> myeq <- colnames(x)[1]
> myeq <- paste(myeq, '[t] = ', sep='')
> for (i in 1:k){
+ if (mysum$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/11ygdk1324660989.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/128pv31324660989.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/13ugna1324660989.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/14gvs71324660989.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/15r9411324660989.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/16qkoq1324660989.tab")
+ }
>
> try(system("convert tmp/1cii41324660989.ps tmp/1cii41324660989.png",intern=TRUE))
character(0)
> try(system("convert tmp/2mk5i1324660989.ps tmp/2mk5i1324660989.png",intern=TRUE))
character(0)
> try(system("convert tmp/3p1b51324660989.ps tmp/3p1b51324660989.png",intern=TRUE))
character(0)
> try(system("convert tmp/4msba1324660989.ps tmp/4msba1324660989.png",intern=TRUE))
character(0)
> try(system("convert tmp/5v5kk1324660989.ps tmp/5v5kk1324660989.png",intern=TRUE))
character(0)
> try(system("convert tmp/6f07i1324660989.ps tmp/6f07i1324660989.png",intern=TRUE))
character(0)
> try(system("convert tmp/7qvhx1324660989.ps tmp/7qvhx1324660989.png",intern=TRUE))
character(0)
> try(system("convert tmp/89gfm1324660989.ps tmp/89gfm1324660989.png",intern=TRUE))
character(0)
> try(system("convert tmp/9zxrl1324660989.ps tmp/9zxrl1324660989.png",intern=TRUE))
character(0)
> try(system("convert tmp/10ix481324660989.ps tmp/10ix481324660989.png",intern=TRUE))
character(0)
>
>
> proc.time()
user system elapsed
5.236 0.754 6.012