R version 2.13.0 (2011-04-13)
Copyright (C) 2011 The R Foundation for Statistical Computing
ISBN 3-900051-07-0
Platform: i486-pc-linux-gnu (32-bit)
R is free software and comes with ABSOLUTELY NO WARRANTY.
You are welcome to redistribute it under certain conditions.
Type 'license()' or 'licence()' for distribution details.
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Type 'contributors()' for more information and
'citation()' on how to cite R or R packages in publications.
Type 'demo()' for some demos, 'help()' for on-line help, or
'help.start()' for an HTML browser interface to help.
Type 'q()' to quit R.
> x <- array(list(1173
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+ ,0
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+ ,16
+ ,49288)
+ ,dim=c(4
+ ,164)
+ ,dimnames=list(c('Karakters'
+ ,'Pag.bezoeken'
+ ,'TijdRFC'
+ ,'Compendiums')
+ ,1:164))
> y <- array(NA,dim=c(4,164),dimnames=list(c('Karakters','Pag.bezoeken','TijdRFC','Compendiums'),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
Karakters Pag.bezoeken TijdRFC Compendiums
1 1173 170650 26 95556
2 669 86621 20 54565
3 1154 127843 27 63016
4 1948 152526 25 79774
5 705 87411 15 31258
6 332 38138 16 52491
7 2726 316392 20 91256
8 345 32750 18 22807
9 1385 120378 19 77411
10 1161 130554 20 48821
11 1431 176816 30 52295
12 1228 140146 39 63262
13 1205 113286 26 50466
14 1732 195452 36 62932
15 1214 144513 31 38439
16 3221 263581 41 70817
17 1385 183271 24 105965
18 1953 203428 23 73795
19 883 113853 19 82043
20 1631 159968 30 74349
21 1459 174585 31 82204
22 1929 291865 26 55709
23 860 96213 15 37137
24 1165 116390 33 70780
25 2115 146342 28 55027
26 1939 152647 27 56699
27 1844 166058 21 65911
28 1346 175505 27 56316
29 1093 112485 21 26982
30 1625 197053 30 54628
31 1551 191822 30 96750
32 1267 139127 33 53009
33 1478 221991 35 64664
34 670 75339 26 36990
35 2040 247985 27 85224
36 1561 167351 25 37048
37 2078 266609 30 59635
38 1113 122024 20 42051
39 686 80964 8 26998
40 2065 215183 24 63717
41 2251 225469 25 55071
42 1106 125382 28 40001
43 1244 141437 23 54506
44 1021 81106 21 35838
45 1735 93125 21 50838
46 3681 318668 26 86997
47 918 78800 26 33032
48 1582 161048 30 61704
49 2900 236367 34 117986
50 1496 131108 30 56733
51 1116 131096 18 55064
52 496 24188 4 5950
53 1777 267003 31 84607
54 744 65029 18 32551
55 1101 98066 14 31701
56 1612 173587 20 71170
57 1849 182323 37 101773
58 2460 197266 24 101653
59 1701 217289 29 81493
60 1334 149594 24 55901
61 2549 257666 31 109104
62 2218 209228 21 114425
63 1633 145696 31 36311
64 1724 183567 26 70027
65 973 145919 24 73713
66 1171 125555 18 40671
67 1282 118697 21 89041
68 1977 146786 28 57231
69 1521 155015 24 68608
70 1071 96487 21 59155
71 1425 127968 30 55827
72 852 71972 20 22618
73 1363 135746 30 58425
74 1150 146344 24 65724
75 1100 110655 26 56979
76 1393 203795 27 72369
77 1521 211093 24 79194
78 1015 113421 23 202316
79 993 101553 24 44970
80 1189 128390 25 49319
81 1244 105502 18 36252
82 2622 294303 30 75741
83 1177 132798 22 38417
84 1333 146390 26 64102
85 870 80953 8 56622
86 1473 109237 21 15430
87 881 102104 26 72571
88 2489 233139 24 67271
89 1429 175839 30 43460
90 1995 118217 27 99501
91 1247 141091 24 28340
92 1357 152193 25 76013
93 1316 126476 21 37361
94 1980 170379 24 48204
95 1454 187772 24 76168
96 1030 130533 20 85168
97 1154 143569 20 125410
98 1521 202077 24 123328
99 2294 210046 40 83038
100 2274 252260 22 120087
101 1371 166981 31 91939
102 1624 190562 26 103646
103 999 106351 20 29467
104 602 43287 19 43750
105 1380 127493 15 34497
106 1207 132143 22 66477
107 1405 151620 22 71181
108 1800 197727 28 74482
109 682 75792 19 174949
110 1151 94968 25 46765
111 1270 191351 26 90257
112 1381 145048 32 51370
113 391 22938 1 1168
114 1264 125927 24 51360
115 530 61857 11 25162
116 1123 103749 31 21067
117 1980 261544 22 58233
118 387 21054 0 855
119 1485 174409 19 85903
120 449 31414 8 14116
121 2209 198752 27 57637
122 1135 138507 31 94137
123 813 78001 24 62147
124 1015 82724 20 62832
125 568 38214 8 8773
126 936 91390 22 63785
127 1585 197612 33 65196
128 871 137161 33 73087
129 2275 251103 31 72631
130 1637 209835 33 86281
131 2238 269470 35 162365
132 829 139144 21 56530
133 809 76470 20 35606
134 1904 197114 25 70111
135 3053 291962 31 92046
136 655 56727 22 63989
137 2617 254843 27 104911
138 1311 105810 24 43448
139 1154 170155 27 60029
140 1496 136745 26 38650
141 742 84342 16 47261
142 2831 251448 23 73586
143 1281 152366 24 83042
144 2035 173260 21 37238
145 1894 212582 30 63958
146 1268 87850 37 78956
147 1713 148636 24 99518
148 1568 185455 29 111436
149 0 0 0 0
150 207 14688 0 6023
151 5 98 0 0
152 8 455 0 0
153 0 0 0 0
154 0 0 0 0
155 1301 137891 20 42564
156 1761 188171 27 38885
157 0 0 0 0
158 4 203 0 0
159 151 7199 0 1644
160 474 46660 5 6179
161 141 17547 1 3926
162 705 73567 23 23238
163 29 969 0 0
164 1021 105477 16 49288
> k <- length(x[1,])
> df <- as.data.frame(x)
> (mylm <- lm(df))
Call:
lm(formula = df)
Coefficients:
(Intercept) Pag.bezoeken TijdRFC Compendiums
81.6238509 0.0082924 5.3955781 -0.0004715
> (mysum <- summary(mylm))
Call:
lm(formula = df)
Residuals:
Min 1Q Median 3Q Max
-686.9 -149.0 -32.8 118.4 857.6
Coefficients:
Estimate Std. Error t value Pr(>|t|)
(Intercept) 81.6238509 59.2158546 1.378 0.170
Pag.bezoeken 0.0082924 0.0004676 17.734 <2e-16 ***
TijdRFC 5.3955781 3.5575454 1.517 0.131
Compendiums -0.0004715 0.0008697 -0.542 0.589
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
Residual standard error: 279.3 on 160 degrees of freedom
Multiple R-squared: 0.834, Adjusted R-squared: 0.8309
F-statistic: 268 on 3 and 160 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,] 0.8807835 2.384330e-01 1.192165e-01
[2,] 0.7881703 4.236594e-01 2.118297e-01
[3,] 0.7811148 4.377704e-01 2.188852e-01
[4,] 0.6796490 6.407020e-01 3.203510e-01
[5,] 0.5835687 8.328627e-01 4.164313e-01
[6,] 0.4767999 9.535998e-01 5.232001e-01
[7,] 0.4204646 8.409292e-01 5.795354e-01
[8,] 0.3277495 6.554990e-01 6.722505e-01
[9,] 0.2487822 4.975644e-01 7.512178e-01
[10,] 0.7726810 4.546379e-01 2.273190e-01
[11,] 0.7670771 4.658457e-01 2.329229e-01
[12,] 0.7092640 5.814720e-01 2.907360e-01
[13,] 0.6469457 7.061087e-01 3.530543e-01
[14,] 0.5850942 8.298115e-01 4.149058e-01
[15,] 0.5441644 9.116713e-01 4.558356e-01
[16,] 0.8077683 3.844633e-01 1.922317e-01
[17,] 0.7646691 4.706617e-01 2.353309e-01
[18,] 0.7111574 5.776851e-01 2.888426e-01
[19,] 0.9161291 1.677417e-01 8.387086e-02
[20,] 0.9486503 1.026994e-01 5.134971e-02
[21,] 0.9545924 9.081514e-02 4.540757e-02
[22,] 0.9540463 9.190744e-02 4.595372e-02
[23,] 0.9380725 1.238551e-01 6.192753e-02
[24,] 0.9291593 1.416815e-01 7.084075e-02
[25,] 0.9219733 1.560533e-01 7.802667e-02
[26,] 0.9042679 1.914642e-01 9.573212e-02
[27,] 0.9560854 8.782929e-02 4.391464e-02
[28,] 0.9450811 1.098377e-01 5.491887e-02
[29,] 0.9327038 1.345925e-01 6.729623e-02
[30,] 0.9139760 1.720479e-01 8.602396e-02
[31,] 0.9116580 1.766840e-01 8.834199e-02
[32,] 0.8887846 2.224307e-01 1.112154e-01
[33,] 0.8626794 2.746412e-01 1.373206e-01
[34,] 0.8450428 3.099144e-01 1.549572e-01
[35,] 0.8402738 3.194524e-01 1.597262e-01
[36,] 0.8129478 3.741044e-01 1.870522e-01
[37,] 0.7790872 4.418255e-01 2.209128e-01
[38,] 0.7587467 4.825065e-01 2.412533e-01
[39,] 0.9398466 1.203067e-01 6.015336e-02
[40,] 0.9947916 1.041672e-02 5.208360e-03
[41,] 0.9928285 1.434300e-02 7.171500e-03
[42,] 0.9900660 1.986809e-02 9.934046e-03
[43,] 0.9979520 4.095905e-03 2.047952e-03
[44,] 0.9974530 5.093942e-03 2.546971e-03
[45,] 0.9965349 6.930159e-03 3.465080e-03
[46,] 0.9961986 7.602835e-03 3.801417e-03
[47,] 0.9991822 1.635648e-03 8.178240e-04
[48,] 0.9987948 2.410371e-03 1.205186e-03
[49,] 0.9984063 3.187483e-03 1.593741e-03
[50,] 0.9976846 4.630782e-03 2.315391e-03
[51,] 0.9967734 6.453112e-03 3.226556e-03
[52,] 0.9991979 1.604275e-03 8.021374e-04
[53,] 0.9992622 1.475637e-03 7.378185e-04
[54,] 0.9989501 2.099711e-03 1.049855e-03
[55,] 0.9986975 2.605012e-03 1.302506e-03
[56,] 0.9987869 2.426121e-03 1.213061e-03
[57,] 0.9986170 2.766085e-03 1.383042e-03
[58,] 0.9979986 4.002870e-03 2.001435e-03
[59,] 0.9988103 2.379382e-03 1.189691e-03
[60,] 0.9982743 3.451479e-03 1.725739e-03
[61,] 0.9977126 4.574862e-03 2.287431e-03
[62,] 0.9992431 1.513760e-03 7.568801e-04
[63,] 0.9989021 2.195741e-03 1.097871e-03
[64,] 0.9984721 3.055854e-03 1.527927e-03
[65,] 0.9980068 3.986492e-03 1.993246e-03
[66,] 0.9972581 5.483813e-03 2.741906e-03
[67,] 0.9961372 7.725575e-03 3.862788e-03
[68,] 0.9958948 8.210412e-03 4.105206e-03
[69,] 0.9943007 1.139861e-02 5.699304e-03
[70,] 0.9972420 5.515905e-03 2.757953e-03
[71,] 0.9982192 3.561695e-03 1.780847e-03
[72,] 0.9979592 4.081615e-03 2.040807e-03
[73,] 0.9971078 5.784476e-03 2.892238e-03
[74,] 0.9960116 7.976869e-03 3.988434e-03
[75,] 0.9953739 9.252236e-03 4.626118e-03
[76,] 0.9936615 1.267706e-02 6.338528e-03
[77,] 0.9917473 1.650545e-02 8.252723e-03
[78,] 0.9890283 2.194339e-02 1.097170e-02
[79,] 0.9859422 2.811565e-02 1.405783e-02
[80,] 0.9889911 2.201780e-02 1.100890e-02
[81,] 0.9863979 2.720414e-02 1.360207e-02
[82,] 0.9893936 2.121282e-02 1.060641e-02
[83,] 0.9891201 2.175976e-02 1.087988e-02
[84,] 0.9996482 7.036353e-04 3.518177e-04
[85,] 0.9995268 9.464458e-04 4.732229e-04
[86,] 0.9993099 1.380105e-03 6.900525e-04
[87,] 0.9990065 1.986918e-03 9.934589e-04
[88,] 0.9993355 1.329010e-03 6.645052e-04
[89,] 0.9993610 1.277985e-03 6.389926e-04
[90,] 0.9992082 1.583537e-03 7.917684e-04
[91,] 0.9989407 2.118649e-03 1.059324e-03
[92,] 0.9990043 1.991463e-03 9.957313e-04
[93,] 0.9991510 1.698084e-03 8.490421e-04
[94,] 0.9987373 2.525437e-03 1.262719e-03
[95,] 0.9984939 3.012231e-03 1.506115e-03
[96,] 0.9979312 4.137666e-03 2.068833e-03
[97,] 0.9970261 5.947886e-03 2.973943e-03
[98,] 0.9959993 8.001396e-03 4.000698e-03
[99,] 0.9950569 9.886147e-03 4.943073e-03
[100,] 0.9930425 1.391505e-02 6.957527e-03
[101,] 0.9902362 1.952757e-02 9.763784e-03
[102,] 0.9865311 2.693776e-02 1.346888e-02
[103,] 0.9827034 3.459313e-02 1.729657e-02
[104,] 0.9801654 3.966927e-02 1.983463e-02
[105,] 0.9909456 1.810874e-02 9.054368e-03
[106,] 0.9873755 2.524891e-02 1.262445e-02
[107,] 0.9835133 3.297343e-02 1.648672e-02
[108,] 0.9776184 4.476317e-02 2.238159e-02
[109,] 0.9710578 5.788439e-02 2.894219e-02
[110,] 0.9616829 7.663426e-02 3.831713e-02
[111,] 0.9806812 3.863757e-02 1.931879e-02
[112,] 0.9751610 4.967808e-02 2.483904e-02
[113,] 0.9689649 6.207013e-02 3.103506e-02
[114,] 0.9599121 8.017580e-02 4.008790e-02
[115,] 0.9652912 6.941757e-02 3.470879e-02
[116,] 0.9581846 8.363074e-02 4.181537e-02
[117,] 0.9454710 1.090580e-01 5.452899e-02
[118,] 0.9422360 1.155280e-01 5.776400e-02
[119,] 0.9312149 1.375701e-01 6.878505e-02
[120,] 0.9130951 1.738097e-01 8.690487e-02
[121,] 0.9182289 1.635423e-01 8.177113e-02
[122,] 0.9533940 9.321203e-02 4.660602e-02
[123,] 0.9427720 1.144559e-01 5.722797e-02
[124,] 0.9624557 7.508869e-02 3.754434e-02
[125,] 0.9668613 6.627736e-02 3.313868e-02
[126,] 0.9939590 1.208200e-02 6.041000e-03
[127,] 0.9905140 1.897191e-02 9.485956e-03
[128,] 0.9859327 2.813465e-02 1.406733e-02
[129,] 0.9844601 3.107981e-02 1.553990e-02
[130,] 0.9766984 4.660324e-02 2.330162e-02
[131,] 0.9711192 5.776166e-02 2.888083e-02
[132,] 0.9699609 6.007826e-02 3.003913e-02
[133,] 0.9965002 6.999585e-03 3.499792e-03
[134,] 0.9943429 1.131417e-02 5.657084e-03
[135,] 0.9915814 1.683726e-02 8.418632e-03
[136,] 0.9989363 2.127465e-03 1.063732e-03
[137,] 0.9989688 2.062448e-03 1.031224e-03
[138,] 0.9999915 1.706423e-05 8.532117e-06
[139,] 0.9999762 4.757814e-05 2.378907e-05
[140,] 0.9999815 3.691617e-05 1.845808e-05
[141,] 1.0000000 6.634795e-10 3.317398e-10
[142,] 1.0000000 2.120595e-10 1.060298e-10
[143,] 1.0000000 1.818421e-09 9.092106e-10
[144,] 1.0000000 4.366206e-09 2.183103e-09
[145,] 1.0000000 4.370575e-08 2.185288e-08
[146,] 0.9999998 4.136883e-07 2.068441e-07
[147,] 0.9999983 3.497754e-06 1.748877e-06
[148,] 0.9999863 2.747361e-05 1.373681e-05
[149,] 0.9998831 2.338338e-04 1.169169e-04
[150,] 0.9991656 1.668781e-03 8.343903e-04
[151,] 0.9942241 1.155172e-02 5.775862e-03
> postscript(file="/var/wessaorg/rcomp/tmp/1yw511321990451.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$resid)
> grid()
> dev.off()
null device
1
> postscript(file="/var/wessaorg/rcomp/tmp/2twww1321990451.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> plot(mysum$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/3hunn1321990451.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> hist(mysum$resid, main='Residual Histogram', xlab='values of Residuals')
> grid()
> dev.off()
null device
1
> postscript(file="/var/wessaorg/rcomp/tmp/490fr1321990451.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> densityplot(~mysum$resid,col='black',main='Residual Density Plot', xlab='values of Residuals')
> dev.off()
null device
1
> postscript(file="/var/wessaorg/rcomp/tmp/5tq801321990451.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
-418.959385 -213.107846 -103.722676 504.287421 -167.669266 -127.462003
7 8 9 10 11 12
-44.166881 -94.568401 239.131510 -88.126740 -254.068547 -196.375263
13 14 15 16 17 18
67.468828 -134.964620 -215.126662 765.820749 -295.919427 95.159025
19 20 21 22 23 24
-206.576659 96.039684 -198.862866 -686.911156 -82.887427 -26.462664
25 26 27 28 29 30
694.713804 472.613962 303.120885 -310.114715 -21.982801 -226.782311
31 32 33 34 35 36
-237.545865 -121.385690 -602.824976 -159.212142 -203.520282 -25.791252
37 38 39 40 41 42
-348.209192 -68.584187 -97.447411 99.534699 190.767065 -147.561245
43 44 45 46 47 48
-108.879622 170.400249 791.805556 857.578160 58.221761 32.122271
49 50 51 52 53 54
730.497938 192.053664 -123.886755 195.021994 -646.098704 41.354513
55 56 57 58 59 60
145.579447 16.562246 103.822913 660.995241 -300.526367 -91.258774
61 62 63 64 65 66
214.876945 342.009539 193.060142 12.891561 -413.386504 -29.724175
67 68 69 70 71 72
144.762980 554.071066 56.778856 103.847570 146.664717 76.306089
73 74 75 76 77 78
21.391135 -243.677269 -12.643204 -490.138906 -403.252535 -35.872836
79 80 81 82 83 84
-39.036206 -68.925050 207.480320 -26.266115 -106.431145 -72.614584
85 86 87 88 89 90
100.610313 379.504678 -153.383740 376.311594 -252.132196 834.301335
91 92 93 94 95 96
-120.742224 -85.724361 89.891243 378.754481 -278.291673 -201.816472
97 98 99 100 101 102
-166.943982 -307.680707 293.912667 38.444000 -219.217659 -129.263922
103 104 105 106 107 108
-58.549950 79.532574 176.481063 -57.770466 -19.064162 -37.219894
109 110 111 112 113 114
-48.157522 169.020062 -496.119007 -51.862245 114.319734 32.857004
115 116 117 118 119 120
-112.056500 23.715306 -361.704452 131.190663 -104.912535 70.368600
121 122 123 124 125 126
360.734225 -218.063061 -15.634906 169.105263 130.461146 7.901306
127 128 129 130 131 132
-282.622127 -491.616838 -21.895442 -322.039644 -190.478690 -493.119716
133 134 135 136 137 138
2.130102 85.989345 426.438001 14.437595 325.891927 242.945406
139 140 141 142 143 144
-455.999746 158.366216 -103.070649 574.858542 -154.449485 420.880736
145 146 147 148 149 150
-82.156567 295.475304 316.248999 -155.428607 -81.623851 6.416701
151 152 153 154 155 156
-77.436508 -77.396901 -81.623851 -81.623851 -11.918136 -8.364495
157 158 159 160 161 162
-81.623851 -79.307212 10.454106 -18.612853 -89.675552 -99.814748
163 164
-60.659205 1.624729
> postscript(file="/var/wessaorg/rcomp/tmp/6nq691321990451.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 -418.959385 NA
1 -213.107846 -418.959385
2 -103.722676 -213.107846
3 504.287421 -103.722676
4 -167.669266 504.287421
5 -127.462003 -167.669266
6 -44.166881 -127.462003
7 -94.568401 -44.166881
8 239.131510 -94.568401
9 -88.126740 239.131510
10 -254.068547 -88.126740
11 -196.375263 -254.068547
12 67.468828 -196.375263
13 -134.964620 67.468828
14 -215.126662 -134.964620
15 765.820749 -215.126662
16 -295.919427 765.820749
17 95.159025 -295.919427
18 -206.576659 95.159025
19 96.039684 -206.576659
20 -198.862866 96.039684
21 -686.911156 -198.862866
22 -82.887427 -686.911156
23 -26.462664 -82.887427
24 694.713804 -26.462664
25 472.613962 694.713804
26 303.120885 472.613962
27 -310.114715 303.120885
28 -21.982801 -310.114715
29 -226.782311 -21.982801
30 -237.545865 -226.782311
31 -121.385690 -237.545865
32 -602.824976 -121.385690
33 -159.212142 -602.824976
34 -203.520282 -159.212142
35 -25.791252 -203.520282
36 -348.209192 -25.791252
37 -68.584187 -348.209192
38 -97.447411 -68.584187
39 99.534699 -97.447411
40 190.767065 99.534699
41 -147.561245 190.767065
42 -108.879622 -147.561245
43 170.400249 -108.879622
44 791.805556 170.400249
45 857.578160 791.805556
46 58.221761 857.578160
47 32.122271 58.221761
48 730.497938 32.122271
49 192.053664 730.497938
50 -123.886755 192.053664
51 195.021994 -123.886755
52 -646.098704 195.021994
53 41.354513 -646.098704
54 145.579447 41.354513
55 16.562246 145.579447
56 103.822913 16.562246
57 660.995241 103.822913
58 -300.526367 660.995241
59 -91.258774 -300.526367
60 214.876945 -91.258774
61 342.009539 214.876945
62 193.060142 342.009539
63 12.891561 193.060142
64 -413.386504 12.891561
65 -29.724175 -413.386504
66 144.762980 -29.724175
67 554.071066 144.762980
68 56.778856 554.071066
69 103.847570 56.778856
70 146.664717 103.847570
71 76.306089 146.664717
72 21.391135 76.306089
73 -243.677269 21.391135
74 -12.643204 -243.677269
75 -490.138906 -12.643204
76 -403.252535 -490.138906
77 -35.872836 -403.252535
78 -39.036206 -35.872836
79 -68.925050 -39.036206
80 207.480320 -68.925050
81 -26.266115 207.480320
82 -106.431145 -26.266115
83 -72.614584 -106.431145
84 100.610313 -72.614584
85 379.504678 100.610313
86 -153.383740 379.504678
87 376.311594 -153.383740
88 -252.132196 376.311594
89 834.301335 -252.132196
90 -120.742224 834.301335
91 -85.724361 -120.742224
92 89.891243 -85.724361
93 378.754481 89.891243
94 -278.291673 378.754481
95 -201.816472 -278.291673
96 -166.943982 -201.816472
97 -307.680707 -166.943982
98 293.912667 -307.680707
99 38.444000 293.912667
100 -219.217659 38.444000
101 -129.263922 -219.217659
102 -58.549950 -129.263922
103 79.532574 -58.549950
104 176.481063 79.532574
105 -57.770466 176.481063
106 -19.064162 -57.770466
107 -37.219894 -19.064162
108 -48.157522 -37.219894
109 169.020062 -48.157522
110 -496.119007 169.020062
111 -51.862245 -496.119007
112 114.319734 -51.862245
113 32.857004 114.319734
114 -112.056500 32.857004
115 23.715306 -112.056500
116 -361.704452 23.715306
117 131.190663 -361.704452
118 -104.912535 131.190663
119 70.368600 -104.912535
120 360.734225 70.368600
121 -218.063061 360.734225
122 -15.634906 -218.063061
123 169.105263 -15.634906
124 130.461146 169.105263
125 7.901306 130.461146
126 -282.622127 7.901306
127 -491.616838 -282.622127
128 -21.895442 -491.616838
129 -322.039644 -21.895442
130 -190.478690 -322.039644
131 -493.119716 -190.478690
132 2.130102 -493.119716
133 85.989345 2.130102
134 426.438001 85.989345
135 14.437595 426.438001
136 325.891927 14.437595
137 242.945406 325.891927
138 -455.999746 242.945406
139 158.366216 -455.999746
140 -103.070649 158.366216
141 574.858542 -103.070649
142 -154.449485 574.858542
143 420.880736 -154.449485
144 -82.156567 420.880736
145 295.475304 -82.156567
146 316.248999 295.475304
147 -155.428607 316.248999
148 -81.623851 -155.428607
149 6.416701 -81.623851
150 -77.436508 6.416701
151 -77.396901 -77.436508
152 -81.623851 -77.396901
153 -81.623851 -81.623851
154 -11.918136 -81.623851
155 -8.364495 -11.918136
156 -81.623851 -8.364495
157 -79.307212 -81.623851
158 10.454106 -79.307212
159 -18.612853 10.454106
160 -89.675552 -18.612853
161 -99.814748 -89.675552
162 -60.659205 -99.814748
163 1.624729 -60.659205
164 NA 1.624729
> dum1 <- dum[2:length(myerror),]
> dum1
lag(myerror, k = 1) myerror
[1,] -213.107846 -418.959385
[2,] -103.722676 -213.107846
[3,] 504.287421 -103.722676
[4,] -167.669266 504.287421
[5,] -127.462003 -167.669266
[6,] -44.166881 -127.462003
[7,] -94.568401 -44.166881
[8,] 239.131510 -94.568401
[9,] -88.126740 239.131510
[10,] -254.068547 -88.126740
[11,] -196.375263 -254.068547
[12,] 67.468828 -196.375263
[13,] -134.964620 67.468828
[14,] -215.126662 -134.964620
[15,] 765.820749 -215.126662
[16,] -295.919427 765.820749
[17,] 95.159025 -295.919427
[18,] -206.576659 95.159025
[19,] 96.039684 -206.576659
[20,] -198.862866 96.039684
[21,] -686.911156 -198.862866
[22,] -82.887427 -686.911156
[23,] -26.462664 -82.887427
[24,] 694.713804 -26.462664
[25,] 472.613962 694.713804
[26,] 303.120885 472.613962
[27,] -310.114715 303.120885
[28,] -21.982801 -310.114715
[29,] -226.782311 -21.982801
[30,] -237.545865 -226.782311
[31,] -121.385690 -237.545865
[32,] -602.824976 -121.385690
[33,] -159.212142 -602.824976
[34,] -203.520282 -159.212142
[35,] -25.791252 -203.520282
[36,] -348.209192 -25.791252
[37,] -68.584187 -348.209192
[38,] -97.447411 -68.584187
[39,] 99.534699 -97.447411
[40,] 190.767065 99.534699
[41,] -147.561245 190.767065
[42,] -108.879622 -147.561245
[43,] 170.400249 -108.879622
[44,] 791.805556 170.400249
[45,] 857.578160 791.805556
[46,] 58.221761 857.578160
[47,] 32.122271 58.221761
[48,] 730.497938 32.122271
[49,] 192.053664 730.497938
[50,] -123.886755 192.053664
[51,] 195.021994 -123.886755
[52,] -646.098704 195.021994
[53,] 41.354513 -646.098704
[54,] 145.579447 41.354513
[55,] 16.562246 145.579447
[56,] 103.822913 16.562246
[57,] 660.995241 103.822913
[58,] -300.526367 660.995241
[59,] -91.258774 -300.526367
[60,] 214.876945 -91.258774
[61,] 342.009539 214.876945
[62,] 193.060142 342.009539
[63,] 12.891561 193.060142
[64,] -413.386504 12.891561
[65,] -29.724175 -413.386504
[66,] 144.762980 -29.724175
[67,] 554.071066 144.762980
[68,] 56.778856 554.071066
[69,] 103.847570 56.778856
[70,] 146.664717 103.847570
[71,] 76.306089 146.664717
[72,] 21.391135 76.306089
[73,] -243.677269 21.391135
[74,] -12.643204 -243.677269
[75,] -490.138906 -12.643204
[76,] -403.252535 -490.138906
[77,] -35.872836 -403.252535
[78,] -39.036206 -35.872836
[79,] -68.925050 -39.036206
[80,] 207.480320 -68.925050
[81,] -26.266115 207.480320
[82,] -106.431145 -26.266115
[83,] -72.614584 -106.431145
[84,] 100.610313 -72.614584
[85,] 379.504678 100.610313
[86,] -153.383740 379.504678
[87,] 376.311594 -153.383740
[88,] -252.132196 376.311594
[89,] 834.301335 -252.132196
[90,] -120.742224 834.301335
[91,] -85.724361 -120.742224
[92,] 89.891243 -85.724361
[93,] 378.754481 89.891243
[94,] -278.291673 378.754481
[95,] -201.816472 -278.291673
[96,] -166.943982 -201.816472
[97,] -307.680707 -166.943982
[98,] 293.912667 -307.680707
[99,] 38.444000 293.912667
[100,] -219.217659 38.444000
[101,] -129.263922 -219.217659
[102,] -58.549950 -129.263922
[103,] 79.532574 -58.549950
[104,] 176.481063 79.532574
[105,] -57.770466 176.481063
[106,] -19.064162 -57.770466
[107,] -37.219894 -19.064162
[108,] -48.157522 -37.219894
[109,] 169.020062 -48.157522
[110,] -496.119007 169.020062
[111,] -51.862245 -496.119007
[112,] 114.319734 -51.862245
[113,] 32.857004 114.319734
[114,] -112.056500 32.857004
[115,] 23.715306 -112.056500
[116,] -361.704452 23.715306
[117,] 131.190663 -361.704452
[118,] -104.912535 131.190663
[119,] 70.368600 -104.912535
[120,] 360.734225 70.368600
[121,] -218.063061 360.734225
[122,] -15.634906 -218.063061
[123,] 169.105263 -15.634906
[124,] 130.461146 169.105263
[125,] 7.901306 130.461146
[126,] -282.622127 7.901306
[127,] -491.616838 -282.622127
[128,] -21.895442 -491.616838
[129,] -322.039644 -21.895442
[130,] -190.478690 -322.039644
[131,] -493.119716 -190.478690
[132,] 2.130102 -493.119716
[133,] 85.989345 2.130102
[134,] 426.438001 85.989345
[135,] 14.437595 426.438001
[136,] 325.891927 14.437595
[137,] 242.945406 325.891927
[138,] -455.999746 242.945406
[139,] 158.366216 -455.999746
[140,] -103.070649 158.366216
[141,] 574.858542 -103.070649
[142,] -154.449485 574.858542
[143,] 420.880736 -154.449485
[144,] -82.156567 420.880736
[145,] 295.475304 -82.156567
[146,] 316.248999 295.475304
[147,] -155.428607 316.248999
[148,] -81.623851 -155.428607
[149,] 6.416701 -81.623851
[150,] -77.436508 6.416701
[151,] -77.396901 -77.436508
[152,] -81.623851 -77.396901
[153,] -81.623851 -81.623851
[154,] -11.918136 -81.623851
[155,] -8.364495 -11.918136
[156,] -81.623851 -8.364495
[157,] -79.307212 -81.623851
[158,] 10.454106 -79.307212
[159,] -18.612853 10.454106
[160,] -89.675552 -18.612853
[161,] -99.814748 -89.675552
[162,] -60.659205 -99.814748
[163,] 1.624729 -60.659205
> z <- as.data.frame(dum1)
> z
lag(myerror, k = 1) myerror
1 -213.107846 -418.959385
2 -103.722676 -213.107846
3 504.287421 -103.722676
4 -167.669266 504.287421
5 -127.462003 -167.669266
6 -44.166881 -127.462003
7 -94.568401 -44.166881
8 239.131510 -94.568401
9 -88.126740 239.131510
10 -254.068547 -88.126740
11 -196.375263 -254.068547
12 67.468828 -196.375263
13 -134.964620 67.468828
14 -215.126662 -134.964620
15 765.820749 -215.126662
16 -295.919427 765.820749
17 95.159025 -295.919427
18 -206.576659 95.159025
19 96.039684 -206.576659
20 -198.862866 96.039684
21 -686.911156 -198.862866
22 -82.887427 -686.911156
23 -26.462664 -82.887427
24 694.713804 -26.462664
25 472.613962 694.713804
26 303.120885 472.613962
27 -310.114715 303.120885
28 -21.982801 -310.114715
29 -226.782311 -21.982801
30 -237.545865 -226.782311
31 -121.385690 -237.545865
32 -602.824976 -121.385690
33 -159.212142 -602.824976
34 -203.520282 -159.212142
35 -25.791252 -203.520282
36 -348.209192 -25.791252
37 -68.584187 -348.209192
38 -97.447411 -68.584187
39 99.534699 -97.447411
40 190.767065 99.534699
41 -147.561245 190.767065
42 -108.879622 -147.561245
43 170.400249 -108.879622
44 791.805556 170.400249
45 857.578160 791.805556
46 58.221761 857.578160
47 32.122271 58.221761
48 730.497938 32.122271
49 192.053664 730.497938
50 -123.886755 192.053664
51 195.021994 -123.886755
52 -646.098704 195.021994
53 41.354513 -646.098704
54 145.579447 41.354513
55 16.562246 145.579447
56 103.822913 16.562246
57 660.995241 103.822913
58 -300.526367 660.995241
59 -91.258774 -300.526367
60 214.876945 -91.258774
61 342.009539 214.876945
62 193.060142 342.009539
63 12.891561 193.060142
64 -413.386504 12.891561
65 -29.724175 -413.386504
66 144.762980 -29.724175
67 554.071066 144.762980
68 56.778856 554.071066
69 103.847570 56.778856
70 146.664717 103.847570
71 76.306089 146.664717
72 21.391135 76.306089
73 -243.677269 21.391135
74 -12.643204 -243.677269
75 -490.138906 -12.643204
76 -403.252535 -490.138906
77 -35.872836 -403.252535
78 -39.036206 -35.872836
79 -68.925050 -39.036206
80 207.480320 -68.925050
81 -26.266115 207.480320
82 -106.431145 -26.266115
83 -72.614584 -106.431145
84 100.610313 -72.614584
85 379.504678 100.610313
86 -153.383740 379.504678
87 376.311594 -153.383740
88 -252.132196 376.311594
89 834.301335 -252.132196
90 -120.742224 834.301335
91 -85.724361 -120.742224
92 89.891243 -85.724361
93 378.754481 89.891243
94 -278.291673 378.754481
95 -201.816472 -278.291673
96 -166.943982 -201.816472
97 -307.680707 -166.943982
98 293.912667 -307.680707
99 38.444000 293.912667
100 -219.217659 38.444000
101 -129.263922 -219.217659
102 -58.549950 -129.263922
103 79.532574 -58.549950
104 176.481063 79.532574
105 -57.770466 176.481063
106 -19.064162 -57.770466
107 -37.219894 -19.064162
108 -48.157522 -37.219894
109 169.020062 -48.157522
110 -496.119007 169.020062
111 -51.862245 -496.119007
112 114.319734 -51.862245
113 32.857004 114.319734
114 -112.056500 32.857004
115 23.715306 -112.056500
116 -361.704452 23.715306
117 131.190663 -361.704452
118 -104.912535 131.190663
119 70.368600 -104.912535
120 360.734225 70.368600
121 -218.063061 360.734225
122 -15.634906 -218.063061
123 169.105263 -15.634906
124 130.461146 169.105263
125 7.901306 130.461146
126 -282.622127 7.901306
127 -491.616838 -282.622127
128 -21.895442 -491.616838
129 -322.039644 -21.895442
130 -190.478690 -322.039644
131 -493.119716 -190.478690
132 2.130102 -493.119716
133 85.989345 2.130102
134 426.438001 85.989345
135 14.437595 426.438001
136 325.891927 14.437595
137 242.945406 325.891927
138 -455.999746 242.945406
139 158.366216 -455.999746
140 -103.070649 158.366216
141 574.858542 -103.070649
142 -154.449485 574.858542
143 420.880736 -154.449485
144 -82.156567 420.880736
145 295.475304 -82.156567
146 316.248999 295.475304
147 -155.428607 316.248999
148 -81.623851 -155.428607
149 6.416701 -81.623851
150 -77.436508 6.416701
151 -77.396901 -77.436508
152 -81.623851 -77.396901
153 -81.623851 -81.623851
154 -11.918136 -81.623851
155 -8.364495 -11.918136
156 -81.623851 -8.364495
157 -79.307212 -81.623851
158 10.454106 -79.307212
159 -18.612853 10.454106
160 -89.675552 -18.612853
161 -99.814748 -89.675552
162 -60.659205 -99.814748
163 1.624729 -60.659205
> 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/79k5i1321990451.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> acf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/wessaorg/rcomp/tmp/8v76u1321990451.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> pacf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Partial Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/wessaorg/rcomp/tmp/94bvx1321990451.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> opar <- par(mfrow = c(2,2), oma = c(0, 0, 1.1, 0))
> plot(mylm, las = 1, sub='Residual Diagnostics')
> par(opar)
> dev.off()
null device
1
> if (n > n25) {
+ postscript(file="/var/wessaorg/rcomp/tmp/107sup1321990451.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
+ plot(kp3:nmkm3,gqarr[,2], main='Goldfeld-Quandt test',ylab='2-sided p-value',xlab='breakpoint')
+ grid()
+ dev.off()
+ }
null device
1
>
> #Note: the /var/wessaorg/rcomp/createtable file can be downloaded at http://www.wessa.net/cretab
> load(file="/var/wessaorg/rcomp/createtable")
>
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a, 'Multiple Linear Regression - Estimated Regression Equation', 1, TRUE)
> a<-table.row.end(a)
> myeq <- colnames(x)[1]
> myeq <- paste(myeq, '[t] = ', sep='')
> for (i in 1:k){
+ if (mysum$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/11micv1321990451.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/12jrnd1321990451.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/13ivd61321990451.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/14mjfw1321990451.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/154ke01321990451.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/16sluw1321990451.tab")
+ }
>
> try(system("convert tmp/1yw511321990451.ps tmp/1yw511321990451.png",intern=TRUE))
character(0)
> try(system("convert tmp/2twww1321990451.ps tmp/2twww1321990451.png",intern=TRUE))
character(0)
> try(system("convert tmp/3hunn1321990451.ps tmp/3hunn1321990451.png",intern=TRUE))
character(0)
> try(system("convert tmp/490fr1321990451.ps tmp/490fr1321990451.png",intern=TRUE))
character(0)
> try(system("convert tmp/5tq801321990451.ps tmp/5tq801321990451.png",intern=TRUE))
character(0)
> try(system("convert tmp/6nq691321990451.ps tmp/6nq691321990451.png",intern=TRUE))
character(0)
> try(system("convert tmp/79k5i1321990451.ps tmp/79k5i1321990451.png",intern=TRUE))
character(0)
> try(system("convert tmp/8v76u1321990451.ps tmp/8v76u1321990451.png",intern=TRUE))
character(0)
> try(system("convert tmp/94bvx1321990451.ps tmp/94bvx1321990451.png",intern=TRUE))
character(0)
> try(system("convert tmp/107sup1321990451.ps tmp/107sup1321990451.png",intern=TRUE))
character(0)
>
>
> proc.time()
user system elapsed
4.741 0.467 5.261