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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> x <- array(list(165119
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+ ,dim=c(8
+ ,164)
+ ,dimnames=list(c('WritingTime'
+ ,'Logins'
+ ,'CompendiumViews'
+ ,'BloggedComputations'
+ ,'ReviewedCompendiums'
+ ,'LongFeedbackmessages'
+ ,'Characters'
+ ,'Time_in_RFC')
+ ,1:164))
> y <- array(NA,dim=c(8,164),dimnames=list(c('WritingTime','Logins','CompendiumViews','BloggedComputations','ReviewedCompendiums','LongFeedbackmessages','Characters','Time_in_RFC'),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'
> #'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
WritingTime Logins CompendiumViews BloggedComputations ReviewedCompendiums
1 165119 62 438 92 34
2 107269 59 330 58 30
3 93497 62 609 62 38
4 100269 94 1015 108 34
5 91627 44 294 55 25
6 47552 27 164 8 31
7 233933 103 1912 134 29
8 6853 19 111 1 18
9 104380 51 698 64 30
10 98431 38 556 77 29
11 156949 97 717 86 39
12 81817 96 495 93 50
13 59238 57 544 44 33
14 101138 66 959 106 46
15 107158 72 540 63 38
16 155499 162 1486 160 52
17 156274 58 635 104 32
18 121777 130 940 86 35
19 105037 49 452 93 25
20 118661 71 617 119 42
21 131187 63 695 107 40
22 145026 90 1046 86 35
23 107016 34 405 50 25
24 87242 43 477 92 46
25 91699 97 1012 123 36
26 110087 106 842 81 35
27 145447 122 994 93 38
28 143307 76 530 113 35
29 61678 45 515 52 28
30 210080 53 766 113 37
31 165005 66 734 112 40
32 97806 67 551 44 42
33 184471 79 718 123 44
34 27786 33 280 38 33
35 184458 83 1055 111 35
36 98765 51 950 77 37
37 178441 106 1038 92 39
38 100619 74 552 74 32
39 58391 31 275 33 17
40 151672 162 986 105 34
41 124437 72 1336 108 33
42 79929 60 565 66 35
43 123064 67 571 69 32
44 50466 49 404 62 35
45 100991 73 985 50 45
46 79367 135 1851 91 38
47 56968 42 330 20 26
48 106257 69 611 101 45
49 178412 99 1249 129 44
50 98520 50 812 93 40
51 153670 68 501 89 33
52 15049 24 218 8 4
53 174478 282 787 80 41
54 25109 17 255 21 18
55 45824 64 454 30 14
56 116772 46 944 86 33
57 189150 75 600 116 49
58 194404 160 977 106 32
59 185881 120 872 127 37
60 67508 74 690 75 32
61 188597 124 1176 138 41
62 203618 107 1013 114 25
63 87232 89 894 55 42
64 110875 78 777 67 35
65 144756 61 521 45 33
66 129825 60 409 88 28
67 92189 114 493 67 31
68 121158 129 757 75 40
69 96219 67 736 114 32
70 84128 60 511 123 25
71 97960 59 789 86 42
72 23824 32 385 22 23
73 103515 67 644 67 42
74 91313 50 664 77 38
75 85407 49 505 105 34
76 95871 70 878 119 38
77 143846 78 769 88 32
78 155387 101 499 78 37
79 74429 55 546 112 34
80 74004 57 551 66 33
81 71987 41 565 58 25
82 150629 102 1087 132 40
83 68580 66 649 30 26
84 119855 87 540 100 40
85 55792 25 437 49 8
86 25157 47 732 26 27
87 90895 48 308 67 32
88 117510 160 1243 57 33
89 144774 95 783 95 50
90 77529 96 933 139 37
91 103123 79 710 73 33
92 104669 68 563 134 34
93 82414 56 508 37 28
94 82390 68 968 108 36
95 128446 70 838 58 32
96 111542 35 523 78 32
97 136048 44 500 88 31
98 197257 69 694 142 35
99 162079 130 1060 127 58
100 206286 100 1232 139 27
101 109858 104 735 108 45
102 182125 58 757 128 37
103 74168 159 574 62 32
104 19630 14 214 13 19
105 88634 68 661 89 22
106 128321 121 640 83 35
107 118936 43 1015 116 36
108 127044 81 893 157 36
109 178377 54 293 28 23
110 69581 77 446 83 36
111 168019 58 538 72 36
112 113598 78 627 134 42
113 5841 11 156 12 1
114 93116 66 577 106 32
115 24610 25 192 23 11
116 60611 43 437 83 40
117 226620 99 1054 126 34
118 6622 16 146 4 0
119 121996 45 751 71 27
120 13155 19 200 18 8
121 154158 105 1050 98 35
122 78489 58 601 66 44
123 22007 74 430 44 40
124 72530 45 467 29 28
125 13983 34 276 16 8
126 73397 33 528 56 35
127 143878 71 898 112 47
128 119956 55 411 46 46
129 181558 70 1362 129 42
130 208236 91 743 139 48
131 237085 106 1069 136 49
132 110297 31 431 66 35
133 61394 35 380 42 32
134 81420 281 790 70 36
135 191154 154 1367 97 42
136 11798 40 449 49 35
137 135724 120 1495 113 42
138 68614 72 651 55 34
139 139926 45 494 100 36
140 105203 72 667 80 36
141 80338 107 510 29 32
142 121376 105 1472 95 33
143 124922 76 675 114 35
144 10901 63 716 41 21
145 135471 89 814 128 40
146 66395 52 556 142 49
147 134041 75 887 88 33
148 153554 92 663 147 39
149 0 0 0 0 0
150 7953 10 85 4 0
151 0 1 0 0 0
152 0 2 0 0 0
153 0 0 0 0 0
154 0 0 0 0 0
155 98922 75 607 56 33
156 165395 121 934 121 42
157 0 0 0 0 0
158 0 4 0 0 0
159 4245 5 74 7 0
160 21509 20 259 12 5
161 7670 5 69 0 1
162 15167 38 267 37 38
163 0 2 0 0 0
164 63891 58 517 47 28
LongFeedbackmessages Characters Time_in_RFC
1 104 124252 252101
2 111 98956 134577
3 93 98073 198520
4 119 106816 189326
5 57 41449 137449
6 80 76173 65295
7 107 177551 439387
8 22 22807 33186
9 103 126938 178368
10 72 61680 186657
11 127 72117 265539
12 168 79738 191088
13 100 57793 138866
14 143 91677 296878
15 79 64631 192648
16 183 106385 333462
17 123 161961 243571
18 81 112669 263451
19 74 114029 155679
20 158 124550 227053
21 133 105416 240028
22 128 72875 388549
23 84 81964 156540
24 184 104880 148421
25 127 76302 177732
26 128 96740 191441
27 118 93071 249893
28 125 78912 236812
29 89 35224 142329
30 122 90694 259667
31 151 125369 231625
32 122 80849 176062
33 162 104434 286683
34 121 65702 87485
35 132 108179 322865
36 110 63583 247082
37 135 95066 346011
38 80 62486 191653
39 46 31081 114673
40 127 94584 284224
41 103 87408 284195
42 95 68966 155363
43 100 88766 177306
44 102 57139 144571
45 45 90586 140319
46 122 109249 405267
47 66 33032 78800
48 159 96056 201970
49 153 146648 302674
50 131 80613 164733
51 113 87026 194221
52 7 5950 24188
53 147 131106 346142
54 61 32551 65029
55 41 31701 101097
56 108 91072 246088
57 184 159803 273108
58 115 143950 282220
59 132 112368 275505
60 113 82124 214872
61 141 144068 335121
62 65 162627 267171
63 94 55062 189637
64 121 95329 229512
65 112 105612 209798
66 81 62853 201345
67 116 125976 163833
68 132 79146 204250
69 104 108461 197813
70 80 99971 132955
71 145 77826 216092
72 67 22618 73566
73 159 84892 213198
74 90 92059 181713
75 120 77993 148698
76 126 104155 300103
77 118 109840 251437
78 112 238712 197295
79 123 67486 158163
80 98 68007 155529
81 78 48194 132672
82 119 134796 377213
83 99 38692 145905
84 81 93587 223701
85 27 56622 80953
86 77 15986 130805
87 118 113402 135082
88 122 97967 305270
89 103 74844 271806
90 129 136051 150949
91 69 50548 225805
92 121 112215 197389
93 81 59591 156583
94 135 59938 232718
95 116 137639 261601
96 123 143372 178489
97 111 138599 200657
98 100 174110 259244
99 221 135062 313075
100 95 175681 346933
101 153 130307 246440
102 118 139141 252444
103 50 44244 159965
104 64 43750 43287
105 34 48029 172239
106 76 95216 185198
107 112 92288 227681
108 115 94588 260464
109 69 197426 106288
110 108 151244 109632
111 130 139206 268905
112 110 106271 266805
113 0 1168 23623
114 83 71764 152474
115 30 25162 61857
116 106 45635 144889
117 91 101817 346600
118 0 855 21054
119 69 100174 224051
120 9 14116 31414
121 123 85008 261043
122 150 124254 206108
123 125 105793 154984
124 81 117129 112933
125 21 8773 38214
126 124 94747 158671
127 168 107549 302148
128 149 97392 177918
129 147 126893 350552
130 145 118850 275578
131 172 234853 368746
132 126 74783 172464
133 89 66089 94381
134 137 95684 244295
135 149 139537 382487
136 121 144253 114525
137 149 153824 345884
138 93 63995 147989
139 119 84891 216638
140 102 61263 192862
141 45 106221 184818
142 104 113587 336707
143 111 113864 215836
144 78 37238 173260
145 120 119906 271773
146 176 135096 130908
147 109 151611 204009
148 132 144645 245514
149 0 0 1
150 0 6023 14688
151 0 0 98
152 0 0 455
153 0 0 0
154 0 0 0
155 78 77457 195765
156 104 62464 326038
157 0 0 0
158 0 0 203
159 0 1644 7199
160 13 6179 46660
161 4 3926 17547
162 65 42087 107465
163 0 0 969
164 55 87656 173102
> k <- length(x[1,])
> df <- as.data.frame(x)
> (mylm <- lm(df))
Call:
lm(formula = df)
Coefficients:
(Intercept) Logins CompendiumViews
2486.3466 -12.8062 -52.9314
BloggedComputations ReviewedCompendiums LongFeedbackmessages
318.6957 -215.1712 -173.0705
Characters Time_in_RFC
0.3898 0.5232
> (mysum <- summary(mylm))
Call:
lm(formula = df)
Residuals:
Min 1Q Median 3Q Max
-77736 -9702 -242 12199 70677
Coefficients:
Estimate Std. Error t value Pr(>|t|)
(Intercept) 2486.34657 5087.87316 0.489 0.62575
Logins -12.80625 62.67964 -0.204 0.83838
CompendiumViews -52.93140 11.54440 -4.585 9.26e-06 ***
BloggedComputations 318.69567 85.72836 3.718 0.00028 ***
ReviewedCompendiums -215.17117 366.29087 -0.587 0.55776
LongFeedbackmessages -173.07048 102.01144 -1.697 0.09177 .
Characters 0.38983 0.06062 6.430 1.48e-09 ***
Time_in_RFC 0.52317 0.05401 9.687 < 2e-16 ***
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
Residual standard error: 23730 on 156 degrees of freedom
Multiple R-squared: 0.8368, Adjusted R-squared: 0.8295
F-statistic: 114.3 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,] 0.071480069 1.429601e-01 9.285199e-01
[2,] 0.121694593 2.433892e-01 8.783054e-01
[3,] 0.061111418 1.222228e-01 9.388886e-01
[4,] 0.050428654 1.008573e-01 9.495713e-01
[5,] 0.037133759 7.426752e-02 9.628662e-01
[6,] 0.017248863 3.449773e-02 9.827511e-01
[7,] 0.009003693 1.800739e-02 9.909963e-01
[8,] 0.080971073 1.619421e-01 9.190289e-01
[9,] 0.050292563 1.005851e-01 9.497074e-01
[10,] 0.034305069 6.861014e-02 9.656949e-01
[11,] 0.021874099 4.374820e-02 9.781259e-01
[12,] 0.094500742 1.890015e-01 9.054993e-01
[13,] 0.074438989 1.488780e-01 9.255610e-01
[14,] 0.053616803 1.072336e-01 9.463832e-01
[15,] 0.035046435 7.009287e-02 9.649536e-01
[16,] 0.023095498 4.619100e-02 9.769045e-01
[17,] 0.023514661 4.702932e-02 9.764853e-01
[18,] 0.015702571 3.140514e-02 9.842974e-01
[19,] 0.009761032 1.952206e-02 9.902390e-01
[20,] 0.323555538 6.471111e-01 6.764445e-01
[21,] 0.346163152 6.923263e-01 6.538368e-01
[22,] 0.340409321 6.808186e-01 6.595907e-01
[23,] 0.346805474 6.936109e-01 6.531945e-01
[24,] 0.334436757 6.688735e-01 6.655632e-01
[25,] 0.305456554 6.109131e-01 6.945434e-01
[26,] 0.256898587 5.137972e-01 7.431014e-01
[27,] 0.223925350 4.478507e-01 7.760747e-01
[28,] 0.182474178 3.649484e-01 8.175258e-01
[29,] 0.150573938 3.011479e-01 8.494261e-01
[30,] 0.122215615 2.444312e-01 8.777844e-01
[31,] 0.096682805 1.933656e-01 9.033172e-01
[32,] 0.074175586 1.483512e-01 9.258244e-01
[33,] 0.074071222 1.481424e-01 9.259288e-01
[34,] 0.077275996 1.545520e-01 9.227240e-01
[35,] 0.139258733 2.785175e-01 8.607413e-01
[36,] 0.539635303 9.207294e-01 4.603647e-01
[37,] 0.564067528 8.718649e-01 4.359325e-01
[38,] 0.517348147 9.653037e-01 4.826519e-01
[39,] 0.497905606 9.958112e-01 5.020944e-01
[40,] 0.481895414 9.637908e-01 5.181046e-01
[41,] 0.545318277 9.093634e-01 4.546817e-01
[42,] 0.497112452 9.942249e-01 5.028875e-01
[43,] 0.448766778 8.975336e-01 5.512332e-01
[44,] 0.401079916 8.021598e-01 5.989201e-01
[45,] 0.353605963 7.072119e-01 6.463940e-01
[46,] 0.308168132 6.163363e-01 6.918319e-01
[47,] 0.286605194 5.732104e-01 7.133948e-01
[48,] 0.305775168 6.115503e-01 6.942248e-01
[49,] 0.318376320 6.367526e-01 6.816237e-01
[50,] 0.411715781 8.234316e-01 5.882842e-01
[51,] 0.371350006 7.427000e-01 6.286500e-01
[52,] 0.370741852 7.414837e-01 6.292581e-01
[53,] 0.365755874 7.315117e-01 6.342441e-01
[54,] 0.322275431 6.445509e-01 6.777246e-01
[55,] 0.382078908 7.641578e-01 6.179211e-01
[56,] 0.345174002 6.903480e-01 6.548260e-01
[57,] 0.334905307 6.698106e-01 6.650947e-01
[58,] 0.373445019 7.468900e-01 6.265550e-01
[59,] 0.435063067 8.701261e-01 5.649369e-01
[60,] 0.483467219 9.669344e-01 5.165328e-01
[61,] 0.438470354 8.769407e-01 5.615296e-01
[62,] 0.395722194 7.914444e-01 6.042778e-01
[63,] 0.358560897 7.171218e-01 6.414391e-01
[64,] 0.330848247 6.616965e-01 6.691518e-01
[65,] 0.298946088 5.978922e-01 7.010539e-01
[66,] 0.607794737 7.844105e-01 3.922053e-01
[67,] 0.567343044 8.653139e-01 4.326570e-01
[68,] 0.561577824 8.768444e-01 4.384222e-01
[69,] 0.540115611 9.197688e-01 4.598844e-01
[70,] 0.497459102 9.949182e-01 5.025409e-01
[71,] 0.465598828 9.311977e-01 5.344012e-01
[72,] 0.685212210 6.295756e-01 3.147878e-01
[73,] 0.693144197 6.137116e-01 3.068558e-01
[74,] 0.670555240 6.588895e-01 3.294448e-01
[75,] 0.629088381 7.418232e-01 3.709116e-01
[76,] 0.590229121 8.195418e-01 4.097709e-01
[77,] 0.549365083 9.012698e-01 4.506349e-01
[78,] 0.506010104 9.879798e-01 4.939899e-01
[79,] 0.476039220 9.520784e-01 5.239608e-01
[80,] 0.473751155 9.475023e-01 5.262488e-01
[81,] 0.427922621 8.558452e-01 5.720774e-01
[82,] 0.445835803 8.916716e-01 5.541642e-01
[83,] 0.413722736 8.274455e-01 5.862773e-01
[84,] 0.381792173 7.635843e-01 6.182078e-01
[85,] 0.348582152 6.971643e-01 6.514178e-01
[86,] 0.311842828 6.236857e-01 6.881572e-01
[87,] 0.271872986 5.437460e-01 7.281270e-01
[88,] 0.237438534 4.748771e-01 7.625615e-01
[89,] 0.227320794 4.546416e-01 7.726792e-01
[90,] 0.203636238 4.072725e-01 7.963638e-01
[91,] 0.217011763 4.340235e-01 7.829882e-01
[92,] 0.206388208 4.127764e-01 7.936118e-01
[93,] 0.185494637 3.709893e-01 8.145054e-01
[94,] 0.159447260 3.188945e-01 8.405527e-01
[95,] 0.132601189 2.652024e-01 8.673988e-01
[96,] 0.145578027 2.911561e-01 8.544220e-01
[97,] 0.124690868 2.493817e-01 8.753091e-01
[98,] 0.120268213 2.405364e-01 8.797318e-01
[99,] 0.487406400 9.748128e-01 5.125936e-01
[100,] 0.489684781 9.793696e-01 5.103152e-01
[101,] 0.441163276 8.823266e-01 5.588367e-01
[102,] 0.685081772 6.298365e-01 3.149182e-01
[103,] 0.640836287 7.183274e-01 3.591637e-01
[104,] 0.593370588 8.132588e-01 4.066294e-01
[105,] 0.549934168 9.001317e-01 4.500658e-01
[106,] 0.509278289 9.814434e-01 4.907217e-01
[107,] 0.566259456 8.674811e-01 4.337405e-01
[108,] 0.514046624 9.719068e-01 4.859534e-01
[109,] 0.460653645 9.213073e-01 5.393464e-01
[110,] 0.410283563 8.205671e-01 5.897164e-01
[111,] 0.510484968 9.790301e-01 4.895150e-01
[112,] 0.536226610 9.275468e-01 4.637734e-01
[113,] 0.774605902 4.507882e-01 2.253941e-01
[114,] 0.774543681 4.509126e-01 2.254563e-01
[115,] 0.749972070 5.000559e-01 2.500279e-01
[116,] 0.707176219 5.856476e-01 2.928238e-01
[117,] 0.718897327 5.622053e-01 2.811027e-01
[118,] 0.735702053 5.285959e-01 2.642979e-01
[119,] 0.692644584 6.147108e-01 3.073554e-01
[120,] 0.828620838 3.427583e-01 1.713792e-01
[121,] 0.810716546 3.785669e-01 1.892835e-01
[122,] 0.813872946 3.722541e-01 1.861271e-01
[123,] 0.877233191 2.455336e-01 1.227668e-01
[124,] 0.893863677 2.122726e-01 1.061363e-01
[125,] 0.916794717 1.664106e-01 8.320528e-02
[126,] 0.951310789 9.737842e-02 4.868921e-02
[127,] 0.934306677 1.313866e-01 6.569332e-02
[128,] 0.949038470 1.019231e-01 5.096153e-02
[129,] 0.972386333 5.522733e-02 2.761367e-02
[130,] 0.993217041 1.356592e-02 6.782959e-03
[131,] 0.999592553 8.148935e-04 4.074467e-04
[132,] 0.999186551 1.626897e-03 8.134486e-04
[133,] 0.998293138 3.413725e-03 1.706862e-03
[134,] 0.999999331 1.338122e-06 6.690608e-07
[135,] 0.999997062 5.876717e-06 2.938359e-06
[136,] 0.999999999 2.250937e-09 1.125469e-09
[137,] 0.999999999 2.537379e-09 1.268689e-09
[138,] 1.000000000 2.982780e-12 1.491390e-12
[139,] 1.000000000 1.056608e-10 5.283040e-11
[140,] 1.000000000 3.739557e-11 1.869779e-11
[141,] 0.999999999 2.827702e-09 1.413851e-09
[142,] 0.999999891 2.181552e-07 1.090776e-07
[143,] 0.999993819 1.236193e-05 6.180964e-06
> postscript(file="/var/www/rcomp/tmp/1xiqs1324654997.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$resid)
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/rcomp/tmp/2y12r1324654997.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> plot(mysum$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/3r2hp1324654997.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> hist(mysum$resid, main='Residual Histogram', xlab='values of Residuals')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/rcomp/tmp/4wqph1324654997.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> densityplot(~mysum$resid,col='black',main='Residual Density Plot', xlab='values of Residuals')
> dev.off()
null device
1
> postscript(file="/var/www/rcomp/tmp/577e81324654997.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> qqnorm(mysum$resid, main='Residual Normal Q-Q Plot')
> qqline(mysum$resid)
> grid()
> dev.off()
null device
1
> (myerror <- as.ts(mysum$resid))
Time Series:
Start = 1
End = 164
Frequency = 1
1 2 3 4 5 6
2277.53560 21204.91029 -13538.21856 5514.61316 14915.04405 8203.87145
7 8 9 10 11 12
16936.05676 -8405.38680 577.23496 -1675.01265 29585.64355 -14098.51789
13 14 15 16 17 18
1481.73954 -39932.15445 9965.58589 9684.18815 -7394.97620 -16897.92860
19 20 21 22 23 24
-10247.11515 -19139.94744 -2849.63230 -30350.59488 16536.03929 4443.07204
25 26 27 28 29 30
11819.55012 19528.15684 29079.14339 8345.10007 3690.16714 70676.52761
31 32 33 34 35 36
31210.83415 17844.76105 28611.68716 -14907.09417 22794.30628 -4375.79533
37 38 39 40 41 42
16609.70097 820.50093 -149.55222 13714.84573 1340.90446 2890.14249
43 44 45 46 47 48
26497.64096 -22492.87145 44389.57756 -77735.87693 29027.59450 -1101.63903
49 50 51 52 53 54
22623.36978 23686.32599 41331.33513 8957.78836 -6171.60077 -2634.77717
55 56 57 58 59 60
3486.83295 -1021.47006 19625.42343 34923.11858 33480.15744 -39396.23192
61 62 63 64 65 66
7704.43283 33246.96004 20306.84313 399.79861 31841.11326 11915.05681
67 68 69 70 71 72
-12169.64256 30232.22602 -23668.98552 -19046.05681 1325.41554 4354.86162
73 74 75 76 77 78
6545.53737 -7126.99616 -3298.21667 -64793.48227 7962.74828 -13181.41095
79 80 81 82 83 84
-14596.70829 -3438.44704 12129.20790 -55773.45209 23042.79777 -15694.39497
85 86 87 88 89 90
3110.10639 -1796.52434 -3596.53797 -4981.91722 11881.67600 -20362.50860
91 92 93 94 95 96
-2831.68233 -28606.27695 10636.19486 -16412.58555 -10827.03235 -8768.39303
97 98 99 100 101 102
-580.47341 8470.65958 11176.99131 -1745.40659 -30375.52789 21729.27837
103 104 105 106 107 108
-1055.83696 -29.40247 -4572.66404 21485.28969 5795.09137 -22662.84133
109 110 111 112 113 114
67489.61443 -24641.03691 7102.72365 -50343.11362 -4670.47880 1739.66338
115 116 117 118 119 120
-9334.84686 -11284.22360 43079.47110 -554.33193 -1305.53894 -2896.89257
121 122 123 124 125 126
36472.81836 -33315.53506 -62876.96983 1397.03960 3385.53479 -9520.89814
127 128 129 130 131 132
-6671.63475 29906.95254 12563.28767 46863.01706 5040.08877 19944.80679
133 134 135 136 137 138
13232.81725 -31611.59755 12407.70288 -69703.24661 -28201.57658 5020.93798
139 140 141 142 143 144
14204.97821 14066.31043 -26450.47149 -27460.63585 -7757.84187 -53088.66101
145 146 147 148 149 150
-23132.94931 -31397.74046 11552.06328 -13103.80995 -2486.86974 -1213.12997
151 152 153 154 155 156
-2524.81080 -2698.77560 -2486.34657 -2486.34657 -334.30498 7447.51321
157 158 159 160 161 162
-2486.34657 -2541.32472 -898.42762 5669.65555 -903.09517 -37694.66542
163 164
-2967.68406 -34654.35365
> postscript(file="/var/www/rcomp/tmp/60uzd1324654997.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 2277.53560 NA
1 21204.91029 2277.53560
2 -13538.21856 21204.91029
3 5514.61316 -13538.21856
4 14915.04405 5514.61316
5 8203.87145 14915.04405
6 16936.05676 8203.87145
7 -8405.38680 16936.05676
8 577.23496 -8405.38680
9 -1675.01265 577.23496
10 29585.64355 -1675.01265
11 -14098.51789 29585.64355
12 1481.73954 -14098.51789
13 -39932.15445 1481.73954
14 9965.58589 -39932.15445
15 9684.18815 9965.58589
16 -7394.97620 9684.18815
17 -16897.92860 -7394.97620
18 -10247.11515 -16897.92860
19 -19139.94744 -10247.11515
20 -2849.63230 -19139.94744
21 -30350.59488 -2849.63230
22 16536.03929 -30350.59488
23 4443.07204 16536.03929
24 11819.55012 4443.07204
25 19528.15684 11819.55012
26 29079.14339 19528.15684
27 8345.10007 29079.14339
28 3690.16714 8345.10007
29 70676.52761 3690.16714
30 31210.83415 70676.52761
31 17844.76105 31210.83415
32 28611.68716 17844.76105
33 -14907.09417 28611.68716
34 22794.30628 -14907.09417
35 -4375.79533 22794.30628
36 16609.70097 -4375.79533
37 820.50093 16609.70097
38 -149.55222 820.50093
39 13714.84573 -149.55222
40 1340.90446 13714.84573
41 2890.14249 1340.90446
42 26497.64096 2890.14249
43 -22492.87145 26497.64096
44 44389.57756 -22492.87145
45 -77735.87693 44389.57756
46 29027.59450 -77735.87693
47 -1101.63903 29027.59450
48 22623.36978 -1101.63903
49 23686.32599 22623.36978
50 41331.33513 23686.32599
51 8957.78836 41331.33513
52 -6171.60077 8957.78836
53 -2634.77717 -6171.60077
54 3486.83295 -2634.77717
55 -1021.47006 3486.83295
56 19625.42343 -1021.47006
57 34923.11858 19625.42343
58 33480.15744 34923.11858
59 -39396.23192 33480.15744
60 7704.43283 -39396.23192
61 33246.96004 7704.43283
62 20306.84313 33246.96004
63 399.79861 20306.84313
64 31841.11326 399.79861
65 11915.05681 31841.11326
66 -12169.64256 11915.05681
67 30232.22602 -12169.64256
68 -23668.98552 30232.22602
69 -19046.05681 -23668.98552
70 1325.41554 -19046.05681
71 4354.86162 1325.41554
72 6545.53737 4354.86162
73 -7126.99616 6545.53737
74 -3298.21667 -7126.99616
75 -64793.48227 -3298.21667
76 7962.74828 -64793.48227
77 -13181.41095 7962.74828
78 -14596.70829 -13181.41095
79 -3438.44704 -14596.70829
80 12129.20790 -3438.44704
81 -55773.45209 12129.20790
82 23042.79777 -55773.45209
83 -15694.39497 23042.79777
84 3110.10639 -15694.39497
85 -1796.52434 3110.10639
86 -3596.53797 -1796.52434
87 -4981.91722 -3596.53797
88 11881.67600 -4981.91722
89 -20362.50860 11881.67600
90 -2831.68233 -20362.50860
91 -28606.27695 -2831.68233
92 10636.19486 -28606.27695
93 -16412.58555 10636.19486
94 -10827.03235 -16412.58555
95 -8768.39303 -10827.03235
96 -580.47341 -8768.39303
97 8470.65958 -580.47341
98 11176.99131 8470.65958
99 -1745.40659 11176.99131
100 -30375.52789 -1745.40659
101 21729.27837 -30375.52789
102 -1055.83696 21729.27837
103 -29.40247 -1055.83696
104 -4572.66404 -29.40247
105 21485.28969 -4572.66404
106 5795.09137 21485.28969
107 -22662.84133 5795.09137
108 67489.61443 -22662.84133
109 -24641.03691 67489.61443
110 7102.72365 -24641.03691
111 -50343.11362 7102.72365
112 -4670.47880 -50343.11362
113 1739.66338 -4670.47880
114 -9334.84686 1739.66338
115 -11284.22360 -9334.84686
116 43079.47110 -11284.22360
117 -554.33193 43079.47110
118 -1305.53894 -554.33193
119 -2896.89257 -1305.53894
120 36472.81836 -2896.89257
121 -33315.53506 36472.81836
122 -62876.96983 -33315.53506
123 1397.03960 -62876.96983
124 3385.53479 1397.03960
125 -9520.89814 3385.53479
126 -6671.63475 -9520.89814
127 29906.95254 -6671.63475
128 12563.28767 29906.95254
129 46863.01706 12563.28767
130 5040.08877 46863.01706
131 19944.80679 5040.08877
132 13232.81725 19944.80679
133 -31611.59755 13232.81725
134 12407.70288 -31611.59755
135 -69703.24661 12407.70288
136 -28201.57658 -69703.24661
137 5020.93798 -28201.57658
138 14204.97821 5020.93798
139 14066.31043 14204.97821
140 -26450.47149 14066.31043
141 -27460.63585 -26450.47149
142 -7757.84187 -27460.63585
143 -53088.66101 -7757.84187
144 -23132.94931 -53088.66101
145 -31397.74046 -23132.94931
146 11552.06328 -31397.74046
147 -13103.80995 11552.06328
148 -2486.86974 -13103.80995
149 -1213.12997 -2486.86974
150 -2524.81080 -1213.12997
151 -2698.77560 -2524.81080
152 -2486.34657 -2698.77560
153 -2486.34657 -2486.34657
154 -334.30498 -2486.34657
155 7447.51321 -334.30498
156 -2486.34657 7447.51321
157 -2541.32472 -2486.34657
158 -898.42762 -2541.32472
159 5669.65555 -898.42762
160 -903.09517 5669.65555
161 -37694.66542 -903.09517
162 -2967.68406 -37694.66542
163 -34654.35365 -2967.68406
164 NA -34654.35365
> dum1 <- dum[2:length(myerror),]
> dum1
lag(myerror, k = 1) myerror
[1,] 21204.91029 2277.53560
[2,] -13538.21856 21204.91029
[3,] 5514.61316 -13538.21856
[4,] 14915.04405 5514.61316
[5,] 8203.87145 14915.04405
[6,] 16936.05676 8203.87145
[7,] -8405.38680 16936.05676
[8,] 577.23496 -8405.38680
[9,] -1675.01265 577.23496
[10,] 29585.64355 -1675.01265
[11,] -14098.51789 29585.64355
[12,] 1481.73954 -14098.51789
[13,] -39932.15445 1481.73954
[14,] 9965.58589 -39932.15445
[15,] 9684.18815 9965.58589
[16,] -7394.97620 9684.18815
[17,] -16897.92860 -7394.97620
[18,] -10247.11515 -16897.92860
[19,] -19139.94744 -10247.11515
[20,] -2849.63230 -19139.94744
[21,] -30350.59488 -2849.63230
[22,] 16536.03929 -30350.59488
[23,] 4443.07204 16536.03929
[24,] 11819.55012 4443.07204
[25,] 19528.15684 11819.55012
[26,] 29079.14339 19528.15684
[27,] 8345.10007 29079.14339
[28,] 3690.16714 8345.10007
[29,] 70676.52761 3690.16714
[30,] 31210.83415 70676.52761
[31,] 17844.76105 31210.83415
[32,] 28611.68716 17844.76105
[33,] -14907.09417 28611.68716
[34,] 22794.30628 -14907.09417
[35,] -4375.79533 22794.30628
[36,] 16609.70097 -4375.79533
[37,] 820.50093 16609.70097
[38,] -149.55222 820.50093
[39,] 13714.84573 -149.55222
[40,] 1340.90446 13714.84573
[41,] 2890.14249 1340.90446
[42,] 26497.64096 2890.14249
[43,] -22492.87145 26497.64096
[44,] 44389.57756 -22492.87145
[45,] -77735.87693 44389.57756
[46,] 29027.59450 -77735.87693
[47,] -1101.63903 29027.59450
[48,] 22623.36978 -1101.63903
[49,] 23686.32599 22623.36978
[50,] 41331.33513 23686.32599
[51,] 8957.78836 41331.33513
[52,] -6171.60077 8957.78836
[53,] -2634.77717 -6171.60077
[54,] 3486.83295 -2634.77717
[55,] -1021.47006 3486.83295
[56,] 19625.42343 -1021.47006
[57,] 34923.11858 19625.42343
[58,] 33480.15744 34923.11858
[59,] -39396.23192 33480.15744
[60,] 7704.43283 -39396.23192
[61,] 33246.96004 7704.43283
[62,] 20306.84313 33246.96004
[63,] 399.79861 20306.84313
[64,] 31841.11326 399.79861
[65,] 11915.05681 31841.11326
[66,] -12169.64256 11915.05681
[67,] 30232.22602 -12169.64256
[68,] -23668.98552 30232.22602
[69,] -19046.05681 -23668.98552
[70,] 1325.41554 -19046.05681
[71,] 4354.86162 1325.41554
[72,] 6545.53737 4354.86162
[73,] -7126.99616 6545.53737
[74,] -3298.21667 -7126.99616
[75,] -64793.48227 -3298.21667
[76,] 7962.74828 -64793.48227
[77,] -13181.41095 7962.74828
[78,] -14596.70829 -13181.41095
[79,] -3438.44704 -14596.70829
[80,] 12129.20790 -3438.44704
[81,] -55773.45209 12129.20790
[82,] 23042.79777 -55773.45209
[83,] -15694.39497 23042.79777
[84,] 3110.10639 -15694.39497
[85,] -1796.52434 3110.10639
[86,] -3596.53797 -1796.52434
[87,] -4981.91722 -3596.53797
[88,] 11881.67600 -4981.91722
[89,] -20362.50860 11881.67600
[90,] -2831.68233 -20362.50860
[91,] -28606.27695 -2831.68233
[92,] 10636.19486 -28606.27695
[93,] -16412.58555 10636.19486
[94,] -10827.03235 -16412.58555
[95,] -8768.39303 -10827.03235
[96,] -580.47341 -8768.39303
[97,] 8470.65958 -580.47341
[98,] 11176.99131 8470.65958
[99,] -1745.40659 11176.99131
[100,] -30375.52789 -1745.40659
[101,] 21729.27837 -30375.52789
[102,] -1055.83696 21729.27837
[103,] -29.40247 -1055.83696
[104,] -4572.66404 -29.40247
[105,] 21485.28969 -4572.66404
[106,] 5795.09137 21485.28969
[107,] -22662.84133 5795.09137
[108,] 67489.61443 -22662.84133
[109,] -24641.03691 67489.61443
[110,] 7102.72365 -24641.03691
[111,] -50343.11362 7102.72365
[112,] -4670.47880 -50343.11362
[113,] 1739.66338 -4670.47880
[114,] -9334.84686 1739.66338
[115,] -11284.22360 -9334.84686
[116,] 43079.47110 -11284.22360
[117,] -554.33193 43079.47110
[118,] -1305.53894 -554.33193
[119,] -2896.89257 -1305.53894
[120,] 36472.81836 -2896.89257
[121,] -33315.53506 36472.81836
[122,] -62876.96983 -33315.53506
[123,] 1397.03960 -62876.96983
[124,] 3385.53479 1397.03960
[125,] -9520.89814 3385.53479
[126,] -6671.63475 -9520.89814
[127,] 29906.95254 -6671.63475
[128,] 12563.28767 29906.95254
[129,] 46863.01706 12563.28767
[130,] 5040.08877 46863.01706
[131,] 19944.80679 5040.08877
[132,] 13232.81725 19944.80679
[133,] -31611.59755 13232.81725
[134,] 12407.70288 -31611.59755
[135,] -69703.24661 12407.70288
[136,] -28201.57658 -69703.24661
[137,] 5020.93798 -28201.57658
[138,] 14204.97821 5020.93798
[139,] 14066.31043 14204.97821
[140,] -26450.47149 14066.31043
[141,] -27460.63585 -26450.47149
[142,] -7757.84187 -27460.63585
[143,] -53088.66101 -7757.84187
[144,] -23132.94931 -53088.66101
[145,] -31397.74046 -23132.94931
[146,] 11552.06328 -31397.74046
[147,] -13103.80995 11552.06328
[148,] -2486.86974 -13103.80995
[149,] -1213.12997 -2486.86974
[150,] -2524.81080 -1213.12997
[151,] -2698.77560 -2524.81080
[152,] -2486.34657 -2698.77560
[153,] -2486.34657 -2486.34657
[154,] -334.30498 -2486.34657
[155,] 7447.51321 -334.30498
[156,] -2486.34657 7447.51321
[157,] -2541.32472 -2486.34657
[158,] -898.42762 -2541.32472
[159,] 5669.65555 -898.42762
[160,] -903.09517 5669.65555
[161,] -37694.66542 -903.09517
[162,] -2967.68406 -37694.66542
[163,] -34654.35365 -2967.68406
> z <- as.data.frame(dum1)
> z
lag(myerror, k = 1) myerror
1 21204.91029 2277.53560
2 -13538.21856 21204.91029
3 5514.61316 -13538.21856
4 14915.04405 5514.61316
5 8203.87145 14915.04405
6 16936.05676 8203.87145
7 -8405.38680 16936.05676
8 577.23496 -8405.38680
9 -1675.01265 577.23496
10 29585.64355 -1675.01265
11 -14098.51789 29585.64355
12 1481.73954 -14098.51789
13 -39932.15445 1481.73954
14 9965.58589 -39932.15445
15 9684.18815 9965.58589
16 -7394.97620 9684.18815
17 -16897.92860 -7394.97620
18 -10247.11515 -16897.92860
19 -19139.94744 -10247.11515
20 -2849.63230 -19139.94744
21 -30350.59488 -2849.63230
22 16536.03929 -30350.59488
23 4443.07204 16536.03929
24 11819.55012 4443.07204
25 19528.15684 11819.55012
26 29079.14339 19528.15684
27 8345.10007 29079.14339
28 3690.16714 8345.10007
29 70676.52761 3690.16714
30 31210.83415 70676.52761
31 17844.76105 31210.83415
32 28611.68716 17844.76105
33 -14907.09417 28611.68716
34 22794.30628 -14907.09417
35 -4375.79533 22794.30628
36 16609.70097 -4375.79533
37 820.50093 16609.70097
38 -149.55222 820.50093
39 13714.84573 -149.55222
40 1340.90446 13714.84573
41 2890.14249 1340.90446
42 26497.64096 2890.14249
43 -22492.87145 26497.64096
44 44389.57756 -22492.87145
45 -77735.87693 44389.57756
46 29027.59450 -77735.87693
47 -1101.63903 29027.59450
48 22623.36978 -1101.63903
49 23686.32599 22623.36978
50 41331.33513 23686.32599
51 8957.78836 41331.33513
52 -6171.60077 8957.78836
53 -2634.77717 -6171.60077
54 3486.83295 -2634.77717
55 -1021.47006 3486.83295
56 19625.42343 -1021.47006
57 34923.11858 19625.42343
58 33480.15744 34923.11858
59 -39396.23192 33480.15744
60 7704.43283 -39396.23192
61 33246.96004 7704.43283
62 20306.84313 33246.96004
63 399.79861 20306.84313
64 31841.11326 399.79861
65 11915.05681 31841.11326
66 -12169.64256 11915.05681
67 30232.22602 -12169.64256
68 -23668.98552 30232.22602
69 -19046.05681 -23668.98552
70 1325.41554 -19046.05681
71 4354.86162 1325.41554
72 6545.53737 4354.86162
73 -7126.99616 6545.53737
74 -3298.21667 -7126.99616
75 -64793.48227 -3298.21667
76 7962.74828 -64793.48227
77 -13181.41095 7962.74828
78 -14596.70829 -13181.41095
79 -3438.44704 -14596.70829
80 12129.20790 -3438.44704
81 -55773.45209 12129.20790
82 23042.79777 -55773.45209
83 -15694.39497 23042.79777
84 3110.10639 -15694.39497
85 -1796.52434 3110.10639
86 -3596.53797 -1796.52434
87 -4981.91722 -3596.53797
88 11881.67600 -4981.91722
89 -20362.50860 11881.67600
90 -2831.68233 -20362.50860
91 -28606.27695 -2831.68233
92 10636.19486 -28606.27695
93 -16412.58555 10636.19486
94 -10827.03235 -16412.58555
95 -8768.39303 -10827.03235
96 -580.47341 -8768.39303
97 8470.65958 -580.47341
98 11176.99131 8470.65958
99 -1745.40659 11176.99131
100 -30375.52789 -1745.40659
101 21729.27837 -30375.52789
102 -1055.83696 21729.27837
103 -29.40247 -1055.83696
104 -4572.66404 -29.40247
105 21485.28969 -4572.66404
106 5795.09137 21485.28969
107 -22662.84133 5795.09137
108 67489.61443 -22662.84133
109 -24641.03691 67489.61443
110 7102.72365 -24641.03691
111 -50343.11362 7102.72365
112 -4670.47880 -50343.11362
113 1739.66338 -4670.47880
114 -9334.84686 1739.66338
115 -11284.22360 -9334.84686
116 43079.47110 -11284.22360
117 -554.33193 43079.47110
118 -1305.53894 -554.33193
119 -2896.89257 -1305.53894
120 36472.81836 -2896.89257
121 -33315.53506 36472.81836
122 -62876.96983 -33315.53506
123 1397.03960 -62876.96983
124 3385.53479 1397.03960
125 -9520.89814 3385.53479
126 -6671.63475 -9520.89814
127 29906.95254 -6671.63475
128 12563.28767 29906.95254
129 46863.01706 12563.28767
130 5040.08877 46863.01706
131 19944.80679 5040.08877
132 13232.81725 19944.80679
133 -31611.59755 13232.81725
134 12407.70288 -31611.59755
135 -69703.24661 12407.70288
136 -28201.57658 -69703.24661
137 5020.93798 -28201.57658
138 14204.97821 5020.93798
139 14066.31043 14204.97821
140 -26450.47149 14066.31043
141 -27460.63585 -26450.47149
142 -7757.84187 -27460.63585
143 -53088.66101 -7757.84187
144 -23132.94931 -53088.66101
145 -31397.74046 -23132.94931
146 11552.06328 -31397.74046
147 -13103.80995 11552.06328
148 -2486.86974 -13103.80995
149 -1213.12997 -2486.86974
150 -2524.81080 -1213.12997
151 -2698.77560 -2524.81080
152 -2486.34657 -2698.77560
153 -2486.34657 -2486.34657
154 -334.30498 -2486.34657
155 7447.51321 -334.30498
156 -2486.34657 7447.51321
157 -2541.32472 -2486.34657
158 -898.42762 -2541.32472
159 5669.65555 -898.42762
160 -903.09517 5669.65555
161 -37694.66542 -903.09517
162 -2967.68406 -37694.66542
163 -34654.35365 -2967.68406
> 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/7okkt1324654997.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> acf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/rcomp/tmp/8gume1324654997.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> pacf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Partial Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/rcomp/tmp/9dc7b1324654997.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> opar <- par(mfrow = c(2,2), oma = c(0, 0, 1.1, 0))
> plot(mylm, las = 1, sub='Residual Diagnostics')
> par(opar)
> dev.off()
null device
1
> if (n > n25) {
+ postscript(file="/var/www/rcomp/tmp/10ea251324654997.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
+ plot(kp3:nmkm3,gqarr[,2], main='Goldfeld-Quandt test',ylab='2-sided p-value',xlab='breakpoint')
+ grid()
+ dev.off()
+ }
null device
1
>
> #Note: the /var/www/rcomp/createtable file can be downloaded at http://www.wessa.net/cretab
> load(file="/var/www/rcomp/createtable")
>
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a, 'Multiple Linear Regression - Estimated Regression Equation', 1, TRUE)
> a<-table.row.end(a)
> myeq <- colnames(x)[1]
> myeq <- paste(myeq, '[t] = ', sep='')
> for (i in 1:k){
+ if (mysum$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/11cju81324654997.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/12ajpi1324654997.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/13r4qr1324654997.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/14yp5n1324654997.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/15aphr1324654997.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/16k36x1324654997.tab")
+ }
>
> try(system("convert tmp/1xiqs1324654997.ps tmp/1xiqs1324654997.png",intern=TRUE))
character(0)
> try(system("convert tmp/2y12r1324654997.ps tmp/2y12r1324654997.png",intern=TRUE))
character(0)
> try(system("convert tmp/3r2hp1324654997.ps tmp/3r2hp1324654997.png",intern=TRUE))
character(0)
> try(system("convert tmp/4wqph1324654997.ps tmp/4wqph1324654997.png",intern=TRUE))
character(0)
> try(system("convert tmp/577e81324654997.ps tmp/577e81324654997.png",intern=TRUE))
character(0)
> try(system("convert tmp/60uzd1324654997.ps tmp/60uzd1324654997.png",intern=TRUE))
character(0)
> try(system("convert tmp/7okkt1324654997.ps tmp/7okkt1324654997.png",intern=TRUE))
character(0)
> try(system("convert tmp/8gume1324654997.ps tmp/8gume1324654997.png",intern=TRUE))
character(0)
> try(system("convert tmp/9dc7b1324654997.ps tmp/9dc7b1324654997.png",intern=TRUE))
character(0)
> try(system("convert tmp/10ea251324654997.ps tmp/10ea251324654997.png",intern=TRUE))
character(0)
>
>
> proc.time()
user system elapsed
5.420 0.360 5.791