R version 2.12.0 (2010-10-15)
Copyright (C) 2010 The R Foundation for Statistical Computing
ISBN 3-900051-07-0
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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 = '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
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
1 130 186099
2 143 113854
3 118 99776
4 146 106194
5 73 100792
6 89 47552
7 146 250931
8 22 6853
9 132 115466
10 92 110896
11 147 169351
12 203 94853
13 113 72591
14 171 101345
15 87 113713
16 208 165354
17 153 164263
18 97 135213
19 95 111669
20 197 134163
21 160 140303
22 148 150773
23 84 111848
24 227 102509
25 154 96785
26 151 116136
27 142 158376
28 148 153990
29 110 64057
30 149 230054
31 179 184531
32 149 114198
33 187 198299
34 153 33750
35 163 189723
36 127 100826
37 151 188355
38 100 104470
39 46 58391
40 156 164808
41 128 134097
42 111 80238
43 119 133252
44 148 54518
45 65 121850
46 134 79367
47 66 56968
48 201 106314
49 177 191889
50 156 104864
51 158 160792
52 7 15049
53 175 191179
54 61 25109
55 41 45824
56 133 129711
57 228 210012
58 140 194679
59 155 197680
60 141 81180
61 181 197765
62 75 214738
63 97 96252
64 142 124527
65 136 153242
66 87 145707
67 140 113963
68 169 134904
69 129 114268
70 92 94333
71 160 102204
72 67 23824
73 179 111563
74 90 91313
75 144 89770
76 144 100125
77 144 165278
78 134 181712
79 146 80906
80 121 75881
81 112 83963
82 145 175721
83 99 68580
84 96 136323
85 27 55792
86 77 25157
87 137 100922
88 151 118845
89 126 170492
90 159 81716
91 101 115750
92 144 105590
93 102 92795
94 135 82390
95 147 135599
96 155 127667
97 138 163073
98 113 211381
99 248 189944
100 116 226168
101 176 117495
102 140 195894
103 59 80684
104 64 19630
105 40 88634
106 98 139292
107 139 128602
108 135 135848
109 97 178377
110 142 106330
111 155 178303
112 115 116938
113 0 5841
114 103 106020
115 30 24610
116 130 74151
117 102 232241
118 0 6622
119 77 127097
120 9 13155
121 150 160501
122 163 91502
123 148 24469
124 94 88229
125 21 13983
126 151 80716
127 187 157384
128 171 122975
129 170 191469
130 145 231257
131 198 258287
132 152 122531
133 112 61394
134 173 86480
135 177 195791
136 153 18284
137 161 147581
138 115 72558
139 147 147341
140 124 114651
141 57 100187
142 144 130332
143 126 134218
144 78 10901
145 153 145758
146 196 75767
147 130 134969
148 159 169216
149 0 0
150 0 7953
151 0 0
152 0 0
153 0 0
154 0 0
155 94 105406
156 129 174586
157 0 0
158 0 0
159 0 4245
160 13 21509
161 4 7670
162 89 15673
163 0 0
164 71 75882
> k <- length(x[1,])
> df <- as.data.frame(x)
> (mylm <- lm(df))
Call:
lm(formula = df)
Coefficients:
(Intercept) Pageviews Logins
-2515.0957 59.0937 91.9400
Bloggend_computations Reviewed_compendiums Long_fbmessages_PR
22.7670 210.5724 76.8069
Time_compendium
0.8007
> (mysum <- summary(mylm))
Call:
lm(formula = df)
Residuals:
Min 1Q Median 3Q Max
-138544 -16140 1534 19887 172032
Coefficients:
Estimate Std. Error t value Pr(>|t|)
(Intercept) -2.515e+03 7.888e+03 -0.319 0.750
Pageviews 5.909e+01 5.604e+00 10.544 <2e-16 ***
Logins 9.194e+01 8.349e+01 1.101 0.272
Bloggend_computations 2.277e+01 1.172e+02 0.194 0.846
Reviewed_compendiums 2.106e+02 5.130e+02 0.410 0.682
Long_fbmessages_PR 7.681e+01 1.385e+02 0.554 0.580
Time_compendium 8.007e-01 8.303e-02 9.644 <2e-16 ***
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
Residual standard error: 37740 on 157 degrees of freedom
Multiple R-squared: 0.9135, Adjusted R-squared: 0.9101
F-statistic: 276.2 on 6 and 157 DF, p-value: < 2.2e-16
> if (n > n25) {
+ kp3 <- k + 3
+ nmkm3 <- n - k - 3
+ gqarr <- array(NA, dim=c(nmkm3-kp3+1,3))
+ numgqtests <- 0
+ numsignificant1 <- 0
+ numsignificant5 <- 0
+ numsignificant10 <- 0
+ for (mypoint in kp3:nmkm3) {
+ j <- 0
+ numgqtests <- numgqtests + 1
+ for (myalt in c('greater', 'two.sided', 'less')) {
+ j <- j + 1
+ gqarr[mypoint-kp3+1,j] <- gqtest(mylm, point=mypoint, alternative=myalt)$p.value
+ }
+ if (gqarr[mypoint-kp3+1,2] < 0.01) numsignificant1 <- numsignificant1 + 1
+ if (gqarr[mypoint-kp3+1,2] < 0.05) numsignificant5 <- numsignificant5 + 1
+ if (gqarr[mypoint-kp3+1,2] < 0.10) numsignificant10 <- numsignificant10 + 1
+ }
+ gqarr
+ }
[,1] [,2] [,3]
[1,] 0.4744551 9.489101e-01 5.255449e-01
[2,] 0.5093839 9.812323e-01 4.906161e-01
[3,] 0.4415970 8.831940e-01 5.584030e-01
[4,] 0.3144472 6.288943e-01 6.855528e-01
[5,] 0.5061846 9.876309e-01 4.938154e-01
[6,] 0.4338612 8.677224e-01 5.661388e-01
[7,] 0.7862095 4.275810e-01 2.137905e-01
[8,] 0.7235866 5.528269e-01 2.764134e-01
[9,] 0.8797733 2.404534e-01 1.202267e-01
[10,] 0.8717751 2.564497e-01 1.282249e-01
[11,] 0.8274841 3.450318e-01 1.725159e-01
[12,] 0.7891325 4.217350e-01 2.108675e-01
[13,] 0.9991629 1.674130e-03 8.370648e-04
[14,] 0.9985799 2.840158e-03 1.420079e-03
[15,] 0.9976987 4.602612e-03 2.301306e-03
[16,] 0.9987297 2.540607e-03 1.270304e-03
[17,] 0.9985753 2.849316e-03 1.424658e-03
[18,] 0.9987235 2.553013e-03 1.276506e-03
[19,] 0.9986168 2.766469e-03 1.383234e-03
[20,] 0.9979340 4.131970e-03 2.065985e-03
[21,] 0.9981217 3.756613e-03 1.878306e-03
[22,] 0.9973172 5.365626e-03 2.682813e-03
[23,] 0.9960851 7.829816e-03 3.914908e-03
[24,] 0.9960493 7.901428e-03 3.950714e-03
[25,] 0.9945217 1.095658e-02 5.478289e-03
[26,] 0.9932188 1.356243e-02 6.781216e-03
[27,] 0.9901658 1.966830e-02 9.834152e-03
[28,] 0.9872594 2.548116e-02 1.274058e-02
[29,] 0.9830599 3.388025e-02 1.694013e-02
[30,] 0.9769079 4.618429e-02 2.309214e-02
[31,] 0.9685686 6.286282e-02 3.143141e-02
[32,] 0.9585606 8.287889e-02 4.143945e-02
[33,] 0.9460273 1.079453e-01 5.397267e-02
[34,] 0.9466331 1.067337e-01 5.336685e-02
[35,] 0.9315927 1.368147e-01 6.840733e-02
[36,] 0.9944217 1.115659e-02 5.578293e-03
[37,] 0.9937031 1.259382e-02 6.296910e-03
[38,] 0.9940896 1.182086e-02 5.910429e-03
[39,] 0.9923246 1.535088e-02 7.675438e-03
[40,] 0.9967236 6.552865e-03 3.276433e-03
[41,] 0.9970181 5.963840e-03 2.981920e-03
[42,] 0.9973731 5.253877e-03 2.626938e-03
[43,] 0.9972264 5.547281e-03 2.773640e-03
[44,] 0.9968794 6.241154e-03 3.120577e-03
[45,] 0.9956972 8.605513e-03 4.302757e-03
[46,] 0.9945700 1.085997e-02 5.429983e-03
[47,] 0.9928860 1.422805e-02 7.114025e-03
[48,] 0.9902960 1.940791e-02 9.703954e-03
[49,] 0.9952426 9.514769e-03 4.757384e-03
[50,] 0.9939379 1.212422e-02 6.062112e-03
[51,] 0.9947896 1.042089e-02 5.210444e-03
[52,] 0.9949757 1.004861e-02 5.024305e-03
[53,] 0.9980731 3.853891e-03 1.926945e-03
[54,] 0.9973560 5.287952e-03 2.643976e-03
[55,] 0.9962312 7.537541e-03 3.768771e-03
[56,] 0.9954713 9.057462e-03 4.528731e-03
[57,] 0.9938760 1.224799e-02 6.123997e-03
[58,] 0.9932555 1.348892e-02 6.744462e-03
[59,] 0.9965120 6.975973e-03 3.487986e-03
[60,] 0.9950970 9.806053e-03 4.903026e-03
[61,] 0.9933975 1.320495e-02 6.602477e-03
[62,] 0.9912264 1.754715e-02 8.773575e-03
[63,] 0.9883713 2.325734e-02 1.162867e-02
[64,] 0.9846187 3.076256e-02 1.538128e-02
[65,] 0.9800666 3.986688e-02 1.993344e-02
[66,] 0.9737877 5.242452e-02 2.621226e-02
[67,] 0.9989462 2.107667e-03 1.053834e-03
[68,] 0.9991693 1.661393e-03 8.306967e-04
[69,] 0.9997204 5.591107e-04 2.795554e-04
[70,] 0.9995824 8.351550e-04 4.175775e-04
[71,] 0.9993775 1.244953e-03 6.224763e-04
[72,] 0.9991045 1.790965e-03 8.954827e-04
[73,] 0.9995184 9.632923e-04 4.816461e-04
[74,] 0.9992920 1.415905e-03 7.079525e-04
[75,] 0.9990023 1.995483e-03 9.977416e-04
[76,] 0.9986828 2.634417e-03 1.317209e-03
[77,] 0.9983496 3.300702e-03 1.650351e-03
[78,] 0.9978001 4.399821e-03 2.199911e-03
[79,] 0.9981338 3.732321e-03 1.866160e-03
[80,] 0.9976156 4.768899e-03 2.384449e-03
[81,] 0.9998111 3.777408e-04 1.888704e-04
[82,] 0.9997623 4.754809e-04 2.377404e-04
[83,] 0.9997868 4.264534e-04 2.132267e-04
[84,] 0.9996839 6.321525e-04 3.160763e-04
[85,] 0.9995319 9.361195e-04 4.680598e-04
[86,] 0.9995909 8.182198e-04 4.091099e-04
[87,] 0.9994124 1.175190e-03 5.875948e-04
[88,] 0.9991788 1.642325e-03 8.211624e-04
[89,] 0.9987656 2.468838e-03 1.234419e-03
[90,] 0.9985750 2.850092e-03 1.425046e-03
[91,] 0.9983551 3.289880e-03 1.644940e-03
[92,] 0.9975603 4.879368e-03 2.439684e-03
[93,] 0.9964358 7.128457e-03 3.564228e-03
[94,] 0.9950438 9.912453e-03 4.956226e-03
[95,] 0.9935162 1.296767e-02 6.483835e-03
[96,] 0.9908242 1.835157e-02 9.175783e-03
[97,] 0.9909282 1.814367e-02 9.071833e-03
[98,] 0.9873050 2.538994e-02 1.269497e-02
[99,] 0.9844506 3.109882e-02 1.554941e-02
[100,] 0.9952684 9.463280e-03 4.731640e-03
[101,] 0.9999995 1.093357e-06 5.466787e-07
[102,] 0.9999999 1.452439e-07 7.262196e-08
[103,] 1.0000000 5.732788e-08 2.866394e-08
[104,] 0.9999999 1.259842e-07 6.299208e-08
[105,] 1.0000000 2.904021e-08 1.452011e-08
[106,] 1.0000000 6.549597e-08 3.274798e-08
[107,] 0.9999999 1.429097e-07 7.145483e-08
[108,] 1.0000000 8.042230e-08 4.021115e-08
[109,] 0.9999999 1.783038e-07 8.915191e-08
[110,] 0.9999998 3.970853e-07 1.985426e-07
[111,] 0.9999996 7.091565e-07 3.545782e-07
[112,] 0.9999998 4.743704e-07 2.371852e-07
[113,] 0.9999996 8.322725e-07 4.161362e-07
[114,] 0.9999994 1.122327e-06 5.611637e-07
[115,] 0.9999995 1.056991e-06 5.284953e-07
[116,] 0.9999990 1.912299e-06 9.561497e-07
[117,] 0.9999994 1.283394e-06 6.416972e-07
[118,] 0.9999999 2.932285e-07 1.466142e-07
[119,] 0.9999996 7.042574e-07 3.521287e-07
[120,] 0.9999998 4.144493e-07 2.072246e-07
[121,] 0.9999995 9.387516e-07 4.693758e-07
[122,] 0.9999988 2.332908e-06 1.166454e-06
[123,] 0.9999984 3.154634e-06 1.577317e-06
[124,] 0.9999980 4.029802e-06 2.014901e-06
[125,] 0.9999972 5.681493e-06 2.840746e-06
[126,] 0.9999951 9.838562e-06 4.919281e-06
[127,] 0.9999984 3.192300e-06 1.596150e-06
[128,] 0.9999956 8.853306e-06 4.426653e-06
[129,] 0.9999946 1.085318e-05 5.426589e-06
[130,] 1.0000000 1.703647e-10 8.518235e-11
[131,] 1.0000000 5.328530e-10 2.664265e-10
[132,] 1.0000000 2.239838e-09 1.119919e-09
[133,] 1.0000000 8.796394e-09 4.398197e-09
[134,] 1.0000000 4.299114e-08 2.149557e-08
[135,] 0.9999999 2.168348e-07 1.084174e-07
[136,] 0.9999996 8.674212e-07 4.337106e-07
[137,] 1.0000000 7.617677e-08 3.808838e-08
[138,] 1.0000000 2.333558e-08 1.166779e-08
[139,] 1.0000000 3.389938e-08 1.694969e-08
[140,] 0.9999998 3.486180e-07 1.743090e-07
[141,] 0.9999985 2.951798e-06 1.475899e-06
[142,] 0.9999869 2.610290e-05 1.305145e-05
[143,] 0.9999019 1.961187e-04 9.805933e-05
[144,] 0.9992223 1.555332e-03 7.776660e-04
[145,] 0.9944463 1.110739e-02 5.553693e-03
> postscript(file="/var/www/rcomp/tmp/1ol9v1324657371.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$resid)
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/rcomp/tmp/2lk1m1324657371.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> plot(mysum$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/3tmz51324657371.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> hist(mysum$resid, main='Residual Histogram', xlab='values of Residuals')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/rcomp/tmp/42prl1324657371.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> densityplot(~mysum$resid,col='black',main='Residual Density Plot', xlab='values of Residuals')
> dev.off()
null device
1
> postscript(file="/var/www/rcomp/tmp/58pvq1324657371.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
-2601.1812 11488.7641 6913.5208 -54756.6471 10085.7075 -18962.0532
7 8 9 10 11 12
48718.3508 449.3976 -15504.0468 39244.1467 54249.0904 7971.7540
13 14 15 16 17 18
7164.5854 75785.4350 21052.0361 -86254.6954 37066.2462 77831.8590
19 20 21 22 23 24
-13878.1224 -16590.1913 -12971.6484 172032.1952 12239.4428 -22277.4103
25 26 27 28 29 30
-79055.8790 -38969.8265 -25500.7313 38127.0276 13900.8969 -9595.0035
31 32 33 34 35 36
-12377.7508 20333.6163 49436.2017 3153.2224 35374.7184 6760.1507
37 38 39 40 41 42
22694.8503 24104.1077 6231.1068 618.7109 10089.2495 6868.2448
43 44 45 46 47 48
-24006.3859 3923.0954 -116368.3262 33279.2580 -33409.1557 -24319.8942
49 50 51 52 53 54
-66838.2859 -50920.7832 -41714.1447 -18426.0112 33157.9533 -7043.4421
55 56 57 58 59 60
-14352.0365 -15827.0726 -8018.2380 -61661.4631 17069.1361 46276.7661
61 62 63 64 65 66
-40743.7253 -74408.4512 1480.7567 -2247.6267 26731.9671 5410.1943
67 68 69 70 71 72
-32535.5065 -65425.0580 -5536.1776 -15843.8855 -12151.1854 -9198.0514
73 74 75 76 77 78
10030.2742 5712.1992 -438.4952 121381.7417 45151.3255 -71270.5852
79 80 81 82 83 84
-8860.1077 7301.7210 -8641.0712 58294.5193 -8228.8733 13627.9669
85 86 87 88 89 90
-19789.5058 20055.8520 -17919.2717 41233.5306 24651.1279 -100499.8634
91 92 93 94 95 96
26828.0279 36714.0279 -9024.5887 4423.9718 40090.4724 -16879.7828
97 98 99 100 101 102
12940.1424 -814.7956 -32439.1661 -33906.7600 -2496.9977 -4710.1861
103 104 105 106 107 108
-9680.5273 -15990.0424 -1836.7593 -32974.6334 -1905.1158 18685.1319
109 110 111 112 113 114
-58204.3576 -138543.5733 59066.8575 44302.6717 -3810.3709 -44511.4584
115 116 117 118 119 120
5904.1319 12877.0235 34110.3327 -6164.6248 8411.7506 -9939.7708
121 122 123 124 125 126
-27121.1401 20166.6882 32254.2266 -20683.3353 -10820.3145 36482.3185
127 128 129 130 131 132
32031.1341 -2283.9688 28243.3685 -19622.3156 -11997.1072 940.7651
133 134 135 136 137 138
-21238.0054 8963.2109 -1705.4178 11589.7100 2982.5978 -28654.9010
139 140 141 142 143 144
27656.2229 12200.0279 19830.5309 8020.6084 -25626.4590 29652.1784
145 146 147 148 149 150
5495.8520 -32905.2045 -33912.7717 -18127.5608 2397.9084 -2407.8748
151 152 153 154 155 156
2225.6872 2313.4661 2515.0957 2515.0957 37665.5185 31867.4452
157 158 159 160 161 162
2515.0957 2113.9608 -3227.1678 -372.3410 4610.8805 21838.2592
163 164
1586.4985 40694.3483
> postscript(file="/var/www/rcomp/tmp/69fz21324657371.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 -2601.1812 NA
1 11488.7641 -2601.1812
2 6913.5208 11488.7641
3 -54756.6471 6913.5208
4 10085.7075 -54756.6471
5 -18962.0532 10085.7075
6 48718.3508 -18962.0532
7 449.3976 48718.3508
8 -15504.0468 449.3976
9 39244.1467 -15504.0468
10 54249.0904 39244.1467
11 7971.7540 54249.0904
12 7164.5854 7971.7540
13 75785.4350 7164.5854
14 21052.0361 75785.4350
15 -86254.6954 21052.0361
16 37066.2462 -86254.6954
17 77831.8590 37066.2462
18 -13878.1224 77831.8590
19 -16590.1913 -13878.1224
20 -12971.6484 -16590.1913
21 172032.1952 -12971.6484
22 12239.4428 172032.1952
23 -22277.4103 12239.4428
24 -79055.8790 -22277.4103
25 -38969.8265 -79055.8790
26 -25500.7313 -38969.8265
27 38127.0276 -25500.7313
28 13900.8969 38127.0276
29 -9595.0035 13900.8969
30 -12377.7508 -9595.0035
31 20333.6163 -12377.7508
32 49436.2017 20333.6163
33 3153.2224 49436.2017
34 35374.7184 3153.2224
35 6760.1507 35374.7184
36 22694.8503 6760.1507
37 24104.1077 22694.8503
38 6231.1068 24104.1077
39 618.7109 6231.1068
40 10089.2495 618.7109
41 6868.2448 10089.2495
42 -24006.3859 6868.2448
43 3923.0954 -24006.3859
44 -116368.3262 3923.0954
45 33279.2580 -116368.3262
46 -33409.1557 33279.2580
47 -24319.8942 -33409.1557
48 -66838.2859 -24319.8942
49 -50920.7832 -66838.2859
50 -41714.1447 -50920.7832
51 -18426.0112 -41714.1447
52 33157.9533 -18426.0112
53 -7043.4421 33157.9533
54 -14352.0365 -7043.4421
55 -15827.0726 -14352.0365
56 -8018.2380 -15827.0726
57 -61661.4631 -8018.2380
58 17069.1361 -61661.4631
59 46276.7661 17069.1361
60 -40743.7253 46276.7661
61 -74408.4512 -40743.7253
62 1480.7567 -74408.4512
63 -2247.6267 1480.7567
64 26731.9671 -2247.6267
65 5410.1943 26731.9671
66 -32535.5065 5410.1943
67 -65425.0580 -32535.5065
68 -5536.1776 -65425.0580
69 -15843.8855 -5536.1776
70 -12151.1854 -15843.8855
71 -9198.0514 -12151.1854
72 10030.2742 -9198.0514
73 5712.1992 10030.2742
74 -438.4952 5712.1992
75 121381.7417 -438.4952
76 45151.3255 121381.7417
77 -71270.5852 45151.3255
78 -8860.1077 -71270.5852
79 7301.7210 -8860.1077
80 -8641.0712 7301.7210
81 58294.5193 -8641.0712
82 -8228.8733 58294.5193
83 13627.9669 -8228.8733
84 -19789.5058 13627.9669
85 20055.8520 -19789.5058
86 -17919.2717 20055.8520
87 41233.5306 -17919.2717
88 24651.1279 41233.5306
89 -100499.8634 24651.1279
90 26828.0279 -100499.8634
91 36714.0279 26828.0279
92 -9024.5887 36714.0279
93 4423.9718 -9024.5887
94 40090.4724 4423.9718
95 -16879.7828 40090.4724
96 12940.1424 -16879.7828
97 -814.7956 12940.1424
98 -32439.1661 -814.7956
99 -33906.7600 -32439.1661
100 -2496.9977 -33906.7600
101 -4710.1861 -2496.9977
102 -9680.5273 -4710.1861
103 -15990.0424 -9680.5273
104 -1836.7593 -15990.0424
105 -32974.6334 -1836.7593
106 -1905.1158 -32974.6334
107 18685.1319 -1905.1158
108 -58204.3576 18685.1319
109 -138543.5733 -58204.3576
110 59066.8575 -138543.5733
111 44302.6717 59066.8575
112 -3810.3709 44302.6717
113 -44511.4584 -3810.3709
114 5904.1319 -44511.4584
115 12877.0235 5904.1319
116 34110.3327 12877.0235
117 -6164.6248 34110.3327
118 8411.7506 -6164.6248
119 -9939.7708 8411.7506
120 -27121.1401 -9939.7708
121 20166.6882 -27121.1401
122 32254.2266 20166.6882
123 -20683.3353 32254.2266
124 -10820.3145 -20683.3353
125 36482.3185 -10820.3145
126 32031.1341 36482.3185
127 -2283.9688 32031.1341
128 28243.3685 -2283.9688
129 -19622.3156 28243.3685
130 -11997.1072 -19622.3156
131 940.7651 -11997.1072
132 -21238.0054 940.7651
133 8963.2109 -21238.0054
134 -1705.4178 8963.2109
135 11589.7100 -1705.4178
136 2982.5978 11589.7100
137 -28654.9010 2982.5978
138 27656.2229 -28654.9010
139 12200.0279 27656.2229
140 19830.5309 12200.0279
141 8020.6084 19830.5309
142 -25626.4590 8020.6084
143 29652.1784 -25626.4590
144 5495.8520 29652.1784
145 -32905.2045 5495.8520
146 -33912.7717 -32905.2045
147 -18127.5608 -33912.7717
148 2397.9084 -18127.5608
149 -2407.8748 2397.9084
150 2225.6872 -2407.8748
151 2313.4661 2225.6872
152 2515.0957 2313.4661
153 2515.0957 2515.0957
154 37665.5185 2515.0957
155 31867.4452 37665.5185
156 2515.0957 31867.4452
157 2113.9608 2515.0957
158 -3227.1678 2113.9608
159 -372.3410 -3227.1678
160 4610.8805 -372.3410
161 21838.2592 4610.8805
162 1586.4985 21838.2592
163 40694.3483 1586.4985
164 NA 40694.3483
> dum1 <- dum[2:length(myerror),]
> dum1
lag(myerror, k = 1) myerror
[1,] 11488.7641 -2601.1812
[2,] 6913.5208 11488.7641
[3,] -54756.6471 6913.5208
[4,] 10085.7075 -54756.6471
[5,] -18962.0532 10085.7075
[6,] 48718.3508 -18962.0532
[7,] 449.3976 48718.3508
[8,] -15504.0468 449.3976
[9,] 39244.1467 -15504.0468
[10,] 54249.0904 39244.1467
[11,] 7971.7540 54249.0904
[12,] 7164.5854 7971.7540
[13,] 75785.4350 7164.5854
[14,] 21052.0361 75785.4350
[15,] -86254.6954 21052.0361
[16,] 37066.2462 -86254.6954
[17,] 77831.8590 37066.2462
[18,] -13878.1224 77831.8590
[19,] -16590.1913 -13878.1224
[20,] -12971.6484 -16590.1913
[21,] 172032.1952 -12971.6484
[22,] 12239.4428 172032.1952
[23,] -22277.4103 12239.4428
[24,] -79055.8790 -22277.4103
[25,] -38969.8265 -79055.8790
[26,] -25500.7313 -38969.8265
[27,] 38127.0276 -25500.7313
[28,] 13900.8969 38127.0276
[29,] -9595.0035 13900.8969
[30,] -12377.7508 -9595.0035
[31,] 20333.6163 -12377.7508
[32,] 49436.2017 20333.6163
[33,] 3153.2224 49436.2017
[34,] 35374.7184 3153.2224
[35,] 6760.1507 35374.7184
[36,] 22694.8503 6760.1507
[37,] 24104.1077 22694.8503
[38,] 6231.1068 24104.1077
[39,] 618.7109 6231.1068
[40,] 10089.2495 618.7109
[41,] 6868.2448 10089.2495
[42,] -24006.3859 6868.2448
[43,] 3923.0954 -24006.3859
[44,] -116368.3262 3923.0954
[45,] 33279.2580 -116368.3262
[46,] -33409.1557 33279.2580
[47,] -24319.8942 -33409.1557
[48,] -66838.2859 -24319.8942
[49,] -50920.7832 -66838.2859
[50,] -41714.1447 -50920.7832
[51,] -18426.0112 -41714.1447
[52,] 33157.9533 -18426.0112
[53,] -7043.4421 33157.9533
[54,] -14352.0365 -7043.4421
[55,] -15827.0726 -14352.0365
[56,] -8018.2380 -15827.0726
[57,] -61661.4631 -8018.2380
[58,] 17069.1361 -61661.4631
[59,] 46276.7661 17069.1361
[60,] -40743.7253 46276.7661
[61,] -74408.4512 -40743.7253
[62,] 1480.7567 -74408.4512
[63,] -2247.6267 1480.7567
[64,] 26731.9671 -2247.6267
[65,] 5410.1943 26731.9671
[66,] -32535.5065 5410.1943
[67,] -65425.0580 -32535.5065
[68,] -5536.1776 -65425.0580
[69,] -15843.8855 -5536.1776
[70,] -12151.1854 -15843.8855
[71,] -9198.0514 -12151.1854
[72,] 10030.2742 -9198.0514
[73,] 5712.1992 10030.2742
[74,] -438.4952 5712.1992
[75,] 121381.7417 -438.4952
[76,] 45151.3255 121381.7417
[77,] -71270.5852 45151.3255
[78,] -8860.1077 -71270.5852
[79,] 7301.7210 -8860.1077
[80,] -8641.0712 7301.7210
[81,] 58294.5193 -8641.0712
[82,] -8228.8733 58294.5193
[83,] 13627.9669 -8228.8733
[84,] -19789.5058 13627.9669
[85,] 20055.8520 -19789.5058
[86,] -17919.2717 20055.8520
[87,] 41233.5306 -17919.2717
[88,] 24651.1279 41233.5306
[89,] -100499.8634 24651.1279
[90,] 26828.0279 -100499.8634
[91,] 36714.0279 26828.0279
[92,] -9024.5887 36714.0279
[93,] 4423.9718 -9024.5887
[94,] 40090.4724 4423.9718
[95,] -16879.7828 40090.4724
[96,] 12940.1424 -16879.7828
[97,] -814.7956 12940.1424
[98,] -32439.1661 -814.7956
[99,] -33906.7600 -32439.1661
[100,] -2496.9977 -33906.7600
[101,] -4710.1861 -2496.9977
[102,] -9680.5273 -4710.1861
[103,] -15990.0424 -9680.5273
[104,] -1836.7593 -15990.0424
[105,] -32974.6334 -1836.7593
[106,] -1905.1158 -32974.6334
[107,] 18685.1319 -1905.1158
[108,] -58204.3576 18685.1319
[109,] -138543.5733 -58204.3576
[110,] 59066.8575 -138543.5733
[111,] 44302.6717 59066.8575
[112,] -3810.3709 44302.6717
[113,] -44511.4584 -3810.3709
[114,] 5904.1319 -44511.4584
[115,] 12877.0235 5904.1319
[116,] 34110.3327 12877.0235
[117,] -6164.6248 34110.3327
[118,] 8411.7506 -6164.6248
[119,] -9939.7708 8411.7506
[120,] -27121.1401 -9939.7708
[121,] 20166.6882 -27121.1401
[122,] 32254.2266 20166.6882
[123,] -20683.3353 32254.2266
[124,] -10820.3145 -20683.3353
[125,] 36482.3185 -10820.3145
[126,] 32031.1341 36482.3185
[127,] -2283.9688 32031.1341
[128,] 28243.3685 -2283.9688
[129,] -19622.3156 28243.3685
[130,] -11997.1072 -19622.3156
[131,] 940.7651 -11997.1072
[132,] -21238.0054 940.7651
[133,] 8963.2109 -21238.0054
[134,] -1705.4178 8963.2109
[135,] 11589.7100 -1705.4178
[136,] 2982.5978 11589.7100
[137,] -28654.9010 2982.5978
[138,] 27656.2229 -28654.9010
[139,] 12200.0279 27656.2229
[140,] 19830.5309 12200.0279
[141,] 8020.6084 19830.5309
[142,] -25626.4590 8020.6084
[143,] 29652.1784 -25626.4590
[144,] 5495.8520 29652.1784
[145,] -32905.2045 5495.8520
[146,] -33912.7717 -32905.2045
[147,] -18127.5608 -33912.7717
[148,] 2397.9084 -18127.5608
[149,] -2407.8748 2397.9084
[150,] 2225.6872 -2407.8748
[151,] 2313.4661 2225.6872
[152,] 2515.0957 2313.4661
[153,] 2515.0957 2515.0957
[154,] 37665.5185 2515.0957
[155,] 31867.4452 37665.5185
[156,] 2515.0957 31867.4452
[157,] 2113.9608 2515.0957
[158,] -3227.1678 2113.9608
[159,] -372.3410 -3227.1678
[160,] 4610.8805 -372.3410
[161,] 21838.2592 4610.8805
[162,] 1586.4985 21838.2592
[163,] 40694.3483 1586.4985
> z <- as.data.frame(dum1)
> z
lag(myerror, k = 1) myerror
1 11488.7641 -2601.1812
2 6913.5208 11488.7641
3 -54756.6471 6913.5208
4 10085.7075 -54756.6471
5 -18962.0532 10085.7075
6 48718.3508 -18962.0532
7 449.3976 48718.3508
8 -15504.0468 449.3976
9 39244.1467 -15504.0468
10 54249.0904 39244.1467
11 7971.7540 54249.0904
12 7164.5854 7971.7540
13 75785.4350 7164.5854
14 21052.0361 75785.4350
15 -86254.6954 21052.0361
16 37066.2462 -86254.6954
17 77831.8590 37066.2462
18 -13878.1224 77831.8590
19 -16590.1913 -13878.1224
20 -12971.6484 -16590.1913
21 172032.1952 -12971.6484
22 12239.4428 172032.1952
23 -22277.4103 12239.4428
24 -79055.8790 -22277.4103
25 -38969.8265 -79055.8790
26 -25500.7313 -38969.8265
27 38127.0276 -25500.7313
28 13900.8969 38127.0276
29 -9595.0035 13900.8969
30 -12377.7508 -9595.0035
31 20333.6163 -12377.7508
32 49436.2017 20333.6163
33 3153.2224 49436.2017
34 35374.7184 3153.2224
35 6760.1507 35374.7184
36 22694.8503 6760.1507
37 24104.1077 22694.8503
38 6231.1068 24104.1077
39 618.7109 6231.1068
40 10089.2495 618.7109
41 6868.2448 10089.2495
42 -24006.3859 6868.2448
43 3923.0954 -24006.3859
44 -116368.3262 3923.0954
45 33279.2580 -116368.3262
46 -33409.1557 33279.2580
47 -24319.8942 -33409.1557
48 -66838.2859 -24319.8942
49 -50920.7832 -66838.2859
50 -41714.1447 -50920.7832
51 -18426.0112 -41714.1447
52 33157.9533 -18426.0112
53 -7043.4421 33157.9533
54 -14352.0365 -7043.4421
55 -15827.0726 -14352.0365
56 -8018.2380 -15827.0726
57 -61661.4631 -8018.2380
58 17069.1361 -61661.4631
59 46276.7661 17069.1361
60 -40743.7253 46276.7661
61 -74408.4512 -40743.7253
62 1480.7567 -74408.4512
63 -2247.6267 1480.7567
64 26731.9671 -2247.6267
65 5410.1943 26731.9671
66 -32535.5065 5410.1943
67 -65425.0580 -32535.5065
68 -5536.1776 -65425.0580
69 -15843.8855 -5536.1776
70 -12151.1854 -15843.8855
71 -9198.0514 -12151.1854
72 10030.2742 -9198.0514
73 5712.1992 10030.2742
74 -438.4952 5712.1992
75 121381.7417 -438.4952
76 45151.3255 121381.7417
77 -71270.5852 45151.3255
78 -8860.1077 -71270.5852
79 7301.7210 -8860.1077
80 -8641.0712 7301.7210
81 58294.5193 -8641.0712
82 -8228.8733 58294.5193
83 13627.9669 -8228.8733
84 -19789.5058 13627.9669
85 20055.8520 -19789.5058
86 -17919.2717 20055.8520
87 41233.5306 -17919.2717
88 24651.1279 41233.5306
89 -100499.8634 24651.1279
90 26828.0279 -100499.8634
91 36714.0279 26828.0279
92 -9024.5887 36714.0279
93 4423.9718 -9024.5887
94 40090.4724 4423.9718
95 -16879.7828 40090.4724
96 12940.1424 -16879.7828
97 -814.7956 12940.1424
98 -32439.1661 -814.7956
99 -33906.7600 -32439.1661
100 -2496.9977 -33906.7600
101 -4710.1861 -2496.9977
102 -9680.5273 -4710.1861
103 -15990.0424 -9680.5273
104 -1836.7593 -15990.0424
105 -32974.6334 -1836.7593
106 -1905.1158 -32974.6334
107 18685.1319 -1905.1158
108 -58204.3576 18685.1319
109 -138543.5733 -58204.3576
110 59066.8575 -138543.5733
111 44302.6717 59066.8575
112 -3810.3709 44302.6717
113 -44511.4584 -3810.3709
114 5904.1319 -44511.4584
115 12877.0235 5904.1319
116 34110.3327 12877.0235
117 -6164.6248 34110.3327
118 8411.7506 -6164.6248
119 -9939.7708 8411.7506
120 -27121.1401 -9939.7708
121 20166.6882 -27121.1401
122 32254.2266 20166.6882
123 -20683.3353 32254.2266
124 -10820.3145 -20683.3353
125 36482.3185 -10820.3145
126 32031.1341 36482.3185
127 -2283.9688 32031.1341
128 28243.3685 -2283.9688
129 -19622.3156 28243.3685
130 -11997.1072 -19622.3156
131 940.7651 -11997.1072
132 -21238.0054 940.7651
133 8963.2109 -21238.0054
134 -1705.4178 8963.2109
135 11589.7100 -1705.4178
136 2982.5978 11589.7100
137 -28654.9010 2982.5978
138 27656.2229 -28654.9010
139 12200.0279 27656.2229
140 19830.5309 12200.0279
141 8020.6084 19830.5309
142 -25626.4590 8020.6084
143 29652.1784 -25626.4590
144 5495.8520 29652.1784
145 -32905.2045 5495.8520
146 -33912.7717 -32905.2045
147 -18127.5608 -33912.7717
148 2397.9084 -18127.5608
149 -2407.8748 2397.9084
150 2225.6872 -2407.8748
151 2313.4661 2225.6872
152 2515.0957 2313.4661
153 2515.0957 2515.0957
154 37665.5185 2515.0957
155 31867.4452 37665.5185
156 2515.0957 31867.4452
157 2113.9608 2515.0957
158 -3227.1678 2113.9608
159 -372.3410 -3227.1678
160 4610.8805 -372.3410
161 21838.2592 4610.8805
162 1586.4985 21838.2592
163 40694.3483 1586.4985
> 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/7kyks1324657371.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> acf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/rcomp/tmp/8otsd1324657371.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> pacf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Partial Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/rcomp/tmp/9f2801324657371.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> opar <- par(mfrow = c(2,2), oma = c(0, 0, 1.1, 0))
> plot(mylm, las = 1, sub='Residual Diagnostics')
> par(opar)
> dev.off()
null device
1
> if (n > n25) {
+ postscript(file="/var/www/rcomp/tmp/10m9ng1324657371.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
+ plot(kp3:nmkm3,gqarr[,2], main='Goldfeld-Quandt test',ylab='2-sided p-value',xlab='breakpoint')
+ grid()
+ dev.off()
+ }
null device
1
>
> #Note: the /var/www/rcomp/createtable file can be downloaded at http://www.wessa.net/cretab
> load(file="/var/www/rcomp/createtable")
>
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a, 'Multiple Linear Regression - Estimated Regression Equation', 1, TRUE)
> a<-table.row.end(a)
> myeq <- colnames(x)[1]
> myeq <- paste(myeq, '[t] = ', sep='')
> for (i in 1:k){
+ if (mysum$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/11wmly1324657371.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/12cdkk1324657371.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/132fac1324657371.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/14uaee1324657371.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/158y6x1324657371.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/16sza71324657371.tab")
+ }
>
> try(system("convert tmp/1ol9v1324657371.ps tmp/1ol9v1324657371.png",intern=TRUE))
character(0)
> try(system("convert tmp/2lk1m1324657371.ps tmp/2lk1m1324657371.png",intern=TRUE))
character(0)
> try(system("convert tmp/3tmz51324657371.ps tmp/3tmz51324657371.png",intern=TRUE))
character(0)
> try(system("convert tmp/42prl1324657371.ps tmp/42prl1324657371.png",intern=TRUE))
character(0)
> try(system("convert tmp/58pvq1324657371.ps tmp/58pvq1324657371.png",intern=TRUE))
character(0)
> try(system("convert tmp/69fz21324657371.ps tmp/69fz21324657371.png",intern=TRUE))
character(0)
> try(system("convert tmp/7kyks1324657371.ps tmp/7kyks1324657371.png",intern=TRUE))
character(0)
> try(system("convert tmp/8otsd1324657371.ps tmp/8otsd1324657371.png",intern=TRUE))
character(0)
> try(system("convert tmp/9f2801324657371.ps tmp/9f2801324657371.png",intern=TRUE))
character(0)
> try(system("convert tmp/10m9ng1324657371.ps tmp/10m9ng1324657371.png",intern=TRUE))
character(0)
>
>
> proc.time()
user system elapsed
4.870 0.200 5.075