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(95556
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+ ,16)
+ ,dim=c(4
+ ,164)
+ ,dimnames=list(c('CompendiumWriting'
+ ,'Pageviews'
+ ,'TimeRFC'
+ ,'ReviewedCompendiums')
+ ,1:164))
> y <- array(NA,dim=c(4,164),dimnames=list(c('CompendiumWriting','Pageviews','TimeRFC','ReviewedCompendiums'),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
CompendiumWriting Pageviews TimeRFC ReviewedCompendiums
1 95556 1173 170650 26
2 54565 669 86621 20
3 63016 1154 127843 27
4 79774 1948 152526 25
5 31258 722 92389 17
6 52491 336 38778 16
7 91256 2727 316392 20
8 22807 345 32750 18
9 77411 1416 123444 19
10 48821 1208 137034 22
11 52295 1432 176816 30
12 63262 1246 143205 40
13 50466 1205 113286 26
14 62932 1732 195452 36
15 38439 1214 144513 31
16 70817 3222 263581 41
17 105965 1385 183271 24
18 73795 2011 210763 27
19 82043 884 113853 19
20 74349 1631 159968 30
21 82204 1460 174585 31
22 55709 1950 294675 26
23 37137 865 98759 16
24 70780 1165 116390 33
25 55027 2115 146342 28
26 56699 1940 152647 27
27 65911 1858 166661 21
28 56316 1347 175505 27
29 26982 1093 112485 21
30 54628 1650 198790 30
31 96750 1551 191822 30
32 53009 1273 140267 33
33 64664 1478 221991 35
34 36990 670 75339 26
35 85224 2040 247985 27
36 37048 1562 167351 25
37 59635 2079 266609 30
38 42051 1131 124188 20
39 26998 686 80964 8
40 63717 2066 215183 24
41 55071 2251 225469 25
42 40001 1107 125382 28
43 54506 1245 141437 23
44 35838 1049 84863 21
45 50838 1735 93125 21
46 86997 3681 318668 26
47 33032 918 78800 26
48 61704 1582 161048 30
49 117986 2900 236367 34
50 56733 1497 131108 30
51 55064 1121 131101 18
52 5950 496 24188 4
53 84607 1778 267003 31
54 32551 744 65029 18
55 31701 1104 100147 14
56 71170 1703 178549 21
57 101773 1871 186965 37
58 101653 2460 197266 24
59 81493 1705 217300 29
60 55901 1334 149594 24
61 109104 2664 263693 31
62 114425 2218 209228 21
63 36311 1635 145699 31
64 70027 1741 187197 26
65 73713 991 150752 24
66 40671 1195 131218 18
67 89041 1283 118697 21
68 57231 1992 147913 29
69 68608 1558 160065 24
70 59155 1071 96487 21
71 55827 1441 128780 30
72 22618 853 71972 20
73 58425 1425 140266 30
74 65724 1246 152455 24
75 56979 1100 110655 26
76 72369 1400 204822 27
77 79194 1556 216052 24
78 202316 1015 113421 23
79 44970 1002 103660 26
80 49319 1198 128906 25
81 36252 1244 105502 18
82 75741 2657 299359 30
83 38417 1232 141493 25
84 64102 1352 149880 27
85 56622 870 80953 8
86 15430 1474 109237 21
87 72571 881 102104 26
88 67271 2515 239765 24
89 43460 1444 176507 30
90 99501 1995 118217 27
91 28340 1258 142694 24
92 76013 1357 152193 25
93 37361 1329 126500 21
94 48204 2041 174710 24
95 76168 1454 187772 24
96 85168 1171 140903 24
97 125410 1219 155350 24
98 123328 1522 202077 24
99 83038 2314 213875 40
100 120087 2289 252952 22
101 91939 1371 166981 31
102 103646 1639 190790 26
103 29467 1000 106351 20
104 43750 602 43287 19
105 34497 1380 127493 15
106 66477 1208 132143 22
107 71181 1490 157469 25
108 74482 1801 197727 28
109 174949 728 88077 23
110 46765 1152 94968 25
111 90257 1277 191753 26
112 51370 1401 153332 32
113 1168 391 22938 1
114 51360 1264 125927 24
115 25162 530 61857 11
116 21067 1123 103749 31
117 58233 2055 269909 26
118 855 387 21054 0
119 85903 1486 174409 19
120 14116 449 31414 8
121 57637 2212 200405 27
122 94137 1148 139456 31
123 62147 814 78001 24
124 62832 1015 82724 20
125 8773 568 38214 8
126 63785 936 91390 22
127 65196 1586 197612 33
128 73087 871 137161 33
129 72631 2276 251103 31
130 86281 1670 215918 33
131 162365 2238 269470 35
132 56530 838 139215 21
133 35606 841 77796 24
134 70111 1904 197114 25
135 92046 3054 291962 31
136 63989 655 56727 22
137 104911 2617 254843 27
138 43448 1314 105908 24
139 60029 1154 170155 27
140 38650 1497 136745 26
141 47261 754 86706 16
142 73586 2849 253025 23
143 83042 1281 152366 24
144 37238 2035 173260 21
145 63958 1894 212582 30
146 78956 1268 87850 37
147 99518 1714 148636 24
148 111436 1568 185455 29
149 0 0 0 0
150 6023 207 14688 0
151 0 5 98 0
152 0 8 455 0
153 0 0 0 0
154 0 0 0 0
155 42564 1302 137891 20
156 38885 1831 201052 31
157 0 0 0 0
158 0 4 203 0
159 1644 151 7199 0
160 6179 474 46660 5
161 3926 141 17547 1
162 23238 705 73567 23
163 0 29 969 0
164 49288 1033 106662 16
> k <- length(x[1,])
> df <- as.data.frame(x)
> (mylm <- lm(df))
Call:
lm(formula = df)
Coefficients:
(Intercept) Pageviews TimeRFC
6722.2594 -3.6818 0.2236
ReviewedCompendiums
1131.0116
> (mysum <- summary(mylm))
Call:
lm(formula = df)
Residuals:
Min 1Q Median 3Q Max
-41103 -12718 -6524 8686 147962
Coefficients:
Estimate Std. Error t value Pr(>|t|)
(Intercept) 6722.25938 5379.45068 1.250 0.213264
Pageviews -3.68184 7.09225 -0.519 0.604384
TimeRFC 0.22355 0.07031 3.180 0.001771 **
ReviewedCompendiums 1131.01158 311.17955 3.635 0.000375 ***
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
Residual standard error: 25180 on 160 degrees of freedom
Multiple R-squared: 0.4454, Adjusted R-squared: 0.435
F-statistic: 42.83 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,] 2.948871e-01 5.897742e-01 7.051129e-01
[2,] 2.210815e-01 4.421631e-01 7.789185e-01
[3,] 2.051774e-01 4.103548e-01 7.948226e-01
[4,] 1.686222e-01 3.372443e-01 8.313778e-01
[5,] 2.008809e-01 4.017618e-01 7.991191e-01
[6,] 1.307033e-01 2.614066e-01 8.692967e-01
[7,] 8.702403e-02 1.740481e-01 9.129760e-01
[8,] 5.969757e-02 1.193951e-01 9.403024e-01
[9,] 6.030966e-02 1.206193e-01 9.396903e-01
[10,] 4.838683e-02 9.677366e-02 9.516132e-01
[11,] 1.055715e-01 2.111430e-01 8.944285e-01
[12,] 7.040730e-02 1.408146e-01 9.295927e-01
[13,] 7.148908e-02 1.429782e-01 9.285109e-01
[14,] 5.246884e-02 1.049377e-01 9.475312e-01
[15,] 4.007268e-02 8.014535e-02 9.599273e-01
[16,] 7.968202e-02 1.593640e-01 9.203180e-01
[17,] 7.428093e-02 1.485619e-01 9.257191e-01
[18,] 5.825588e-02 1.165118e-01 9.417441e-01
[19,] 4.334423e-02 8.668845e-02 9.566558e-01
[20,] 3.053533e-02 6.107066e-02 9.694647e-01
[21,] 2.017102e-02 4.034204e-02 9.798290e-01
[22,] 1.452391e-02 2.904782e-02 9.854761e-01
[23,] 2.035530e-02 4.071060e-02 9.796447e-01
[24,] 1.659650e-02 3.319299e-02 9.834035e-01
[25,] 2.105825e-02 4.211650e-02 9.789417e-01
[26,] 1.525813e-02 3.051626e-02 9.847419e-01
[27,] 1.147215e-02 2.294430e-02 9.885279e-01
[28,] 8.629742e-03 1.725948e-02 9.913703e-01
[29,] 5.852762e-03 1.170552e-02 9.941472e-01
[30,] 7.623341e-03 1.524668e-02 9.923767e-01
[31,] 7.685115e-03 1.537023e-02 9.923149e-01
[32,] 5.970866e-03 1.194173e-02 9.940291e-01
[33,] 5.207439e-03 1.041488e-02 9.947926e-01
[34,] 3.527806e-03 7.055611e-03 9.964722e-01
[35,] 2.948295e-03 5.896590e-03 9.970517e-01
[36,] 2.508149e-03 5.016297e-03 9.974919e-01
[37,] 1.613330e-03 3.226659e-03 9.983867e-01
[38,] 1.150968e-03 2.301935e-03 9.988490e-01
[39,] 7.235235e-04 1.447047e-03 9.992765e-01
[40,] 4.485263e-04 8.970527e-04 9.995515e-01
[41,] 3.454105e-04 6.908210e-04 9.996546e-01
[42,] 2.131643e-04 4.263287e-04 9.997868e-01
[43,] 6.619946e-04 1.323989e-03 9.993380e-01
[44,] 4.189671e-04 8.379341e-04 9.995810e-01
[45,] 2.589366e-04 5.178733e-04 9.997411e-01
[46,] 2.454290e-04 4.908580e-04 9.997546e-01
[47,] 1.644720e-04 3.289440e-04 9.998355e-01
[48,] 1.034944e-04 2.069889e-04 9.998965e-01
[49,] 7.032352e-05 1.406470e-04 9.999297e-01
[50,] 4.617936e-05 9.235872e-05 9.999538e-01
[51,] 6.283704e-05 1.256741e-04 9.999372e-01
[52,] 1.139147e-04 2.278294e-04 9.998861e-01
[53,] 7.556299e-05 1.511260e-04 9.999244e-01
[54,] 4.617296e-05 9.234591e-05 9.999538e-01
[55,] 4.501918e-05 9.003835e-05 9.999550e-01
[56,] 1.910195e-04 3.820389e-04 9.998090e-01
[57,] 2.600685e-04 5.201370e-04 9.997399e-01
[58,] 1.645776e-04 3.291553e-04 9.998354e-01
[59,] 1.320852e-04 2.641704e-04 9.998679e-01
[60,] 9.302938e-05 1.860588e-04 9.999070e-01
[61,] 2.032752e-04 4.065504e-04 9.997967e-01
[62,] 1.355129e-04 2.710258e-04 9.998645e-01
[63,] 8.716020e-05 1.743204e-04 9.999128e-01
[64,] 6.033961e-05 1.206792e-04 9.999397e-01
[65,] 3.814736e-05 7.629471e-05 9.999619e-01
[66,] 3.398645e-05 6.797290e-05 9.999660e-01
[67,] 2.141108e-05 4.282215e-05 9.999786e-01
[68,] 1.334320e-05 2.668640e-05 9.999867e-01
[69,] 8.096639e-06 1.619328e-05 9.999919e-01
[70,] 5.071152e-06 1.014230e-05 9.999949e-01
[71,] 3.108999e-06 6.217999e-06 9.999969e-01
[72,] 3.961940e-01 7.923880e-01 6.038060e-01
[73,] 3.617876e-01 7.235751e-01 6.382124e-01
[74,] 3.279123e-01 6.558246e-01 6.720877e-01
[75,] 2.969730e-01 5.939459e-01 7.030270e-01
[76,] 2.872769e-01 5.745538e-01 7.127231e-01
[77,] 2.866367e-01 5.732734e-01 7.133633e-01
[78,] 2.506728e-01 5.013456e-01 7.493272e-01
[79,] 2.456170e-01 4.912340e-01 7.543830e-01
[80,] 2.803388e-01 5.606776e-01 7.196612e-01
[81,] 2.591734e-01 5.183467e-01 7.408266e-01
[82,] 2.300937e-01 4.601875e-01 7.699063e-01
[83,] 2.570237e-01 5.140474e-01 7.429763e-01
[84,] 3.650936e-01 7.301872e-01 6.349064e-01
[85,] 4.093399e-01 8.186798e-01 5.906601e-01
[86,] 3.741465e-01 7.482930e-01 6.258535e-01
[87,] 3.516188e-01 7.032376e-01 6.483812e-01
[88,] 3.258713e-01 6.517426e-01 6.741287e-01
[89,] 2.897864e-01 5.795729e-01 7.102136e-01
[90,] 2.805446e-01 5.610891e-01 7.194554e-01
[91,] 4.694458e-01 9.388915e-01 5.305542e-01
[92,] 5.789909e-01 8.420181e-01 4.210091e-01
[93,] 5.393936e-01 9.212128e-01 4.606064e-01
[94,] 6.126105e-01 7.747791e-01 3.873895e-01
[95,] 5.870006e-01 8.259987e-01 4.129994e-01
[96,] 6.060460e-01 7.879080e-01 3.939540e-01
[97,] 5.951113e-01 8.097774e-01 4.048887e-01
[98,] 5.509374e-01 8.981253e-01 4.490626e-01
[99,] 5.169749e-01 9.660503e-01 4.830251e-01
[100,] 4.745051e-01 9.490102e-01 5.254949e-01
[101,] 4.294831e-01 8.589661e-01 5.705169e-01
[102,] 3.833225e-01 7.666451e-01 6.166775e-01
[103,] 9.969423e-01 6.115491e-03 3.057745e-03
[104,] 9.955791e-01 8.841848e-03 4.420924e-03
[105,] 9.944983e-01 1.100337e-02 5.501687e-03
[106,] 9.942108e-01 1.157848e-02 5.789240e-03
[107,] 9.924356e-01 1.512875e-02 7.564374e-03
[108,] 9.894752e-01 2.104963e-02 1.052482e-02
[109,] 9.855908e-01 2.881843e-02 1.440921e-02
[110,] 9.941249e-01 1.175016e-02 5.875082e-03
[111,] 9.957813e-01 8.437308e-03 4.218654e-03
[112,] 9.941209e-01 1.175828e-02 5.879139e-03
[113,] 9.944990e-01 1.100206e-02 5.501030e-03
[114,] 9.921293e-01 1.574141e-02 7.870706e-03
[115,] 9.905563e-01 1.888741e-02 9.443705e-03
[116,] 9.901758e-01 1.964841e-02 9.824207e-03
[117,] 9.872394e-01 2.552117e-02 1.276058e-02
[118,] 9.860224e-01 2.795524e-02 1.397762e-02
[119,] 9.814328e-01 3.713435e-02 1.856718e-02
[120,] 9.777840e-01 4.443200e-02 2.221600e-02
[121,] 9.764229e-01 4.715418e-02 2.357709e-02
[122,] 9.672956e-01 6.540876e-02 3.270438e-02
[123,] 9.659685e-01 6.806299e-02 3.403149e-02
[124,] 9.552041e-01 8.959181e-02 4.479590e-02
[125,] 9.962867e-01 7.426623e-03 3.713311e-03
[126,] 9.940971e-01 1.180589e-02 5.902944e-03
[127,] 9.921613e-01 1.567749e-02 7.838744e-03
[128,] 9.877753e-01 2.444949e-02 1.222474e-02
[129,] 9.813594e-01 3.728121e-02 1.864060e-02
[130,] 9.815928e-01 3.681437e-02 1.840719e-02
[131,] 9.832968e-01 3.340641e-02 1.670321e-02
[132,] 9.760230e-01 4.795409e-02 2.397705e-02
[133,] 9.654841e-01 6.903186e-02 3.451593e-02
[134,] 9.662312e-01 6.753752e-02 3.376876e-02
[135,] 9.520792e-01 9.584157e-02 4.792078e-02
[136,] 9.301914e-01 1.396172e-01 6.980860e-02
[137,] 9.357826e-01 1.284348e-01 6.421742e-02
[138,] 9.661155e-01 6.776907e-02 3.388454e-02
[139,] 9.557094e-01 8.858117e-02 4.429059e-02
[140,] 9.345812e-01 1.308377e-01 6.541885e-02
[141,] 9.936731e-01 1.265376e-02 6.326882e-03
[142,] 9.999917e-01 1.663795e-05 8.318976e-06
[143,] 9.999690e-01 6.197740e-05 3.098870e-05
[144,] 9.998978e-01 2.043048e-04 1.021524e-04
[145,] 9.996450e-01 7.099145e-04 3.549573e-04
[146,] 9.988260e-01 2.347935e-03 1.173967e-03
[147,] 9.963480e-01 7.303963e-03 3.651982e-03
[148,] 9.893289e-01 2.134224e-02 1.067112e-02
[149,] 9.737762e-01 5.244756e-02 2.622378e-02
[150,] 9.893515e-01 2.129704e-02 1.064852e-02
[151,] 9.608951e-01 7.820985e-02 3.910493e-02
> postscript(file="/var/wessaorg/rcomp/tmp/1g1sr1321984707.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$resid)
> grid()
> dev.off()
null device
1
> postscript(file="/var/wessaorg/rcomp/tmp/2lu921321984707.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> plot(mysum$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/3vc8v1321984707.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> hist(mysum$resid, main='Residual Histogram', xlab='values of Residuals')
> grid()
> dev.off()
null device
1
> postscript(file="/var/wessaorg/rcomp/tmp/4iyux1321984707.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> densityplot(~mysum$resid,col='black',main='Residual Density Plot', xlab='values of Residuals')
> dev.off()
null device
1
> postscript(file="/var/wessaorg/rcomp/tmp/5wnjv1321984707.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
25597.22629 8321.43163 1425.81499 17851.30312 -12686.83945 20240.78510
7 8 9 10 11 12
1224.07514 -10324.53504 26816.95057 -8969.96677 -22612.64077 -16126.79971
13 14 15 16 17 18
-6551.16528 -21823.25884 -31180.91921 -29337.69754 36227.35952 -3176.71413
19 20 21 22 23 24
31634.29256 3940.43501 6767.18176 -39114.92087 -6574.34615 5004.57733
25 26 27 28 29 30
-8291.42436 -7542.22443 5021.08823 -15218.48659 -24613.40864 -24389.31383
31 32 33 34 35 36
18925.88889 -17706.51569 -25828.25853 -13513.85165 38.03729 -29610.03217
37 38 39 40 41 42
-32963.82291 -10889.70666 -4346.20918 -10647.27454 -22042.59366 -22343.08349
43 44 45 46 47 48
-5264.04620 -9744.47889 5934.28153 -6817.32424 -17332.46667 -9126.41027
49 50 51 52 53 54
30646.55368 -7717.24422 2803.08885 -8877.37035 -10319.14661 -6327.49044
55 56 57 58 59 60
-9178.65296 7051.82711 18295.78376 32744.73568 -328.73347 -6495.88122
61 62 63 64 65 66
18179.91544 45344.64669 -32023.99749 -1539.59155 9794.37640 -11343.61069
67 68 69 70 71 72
36756.44051 -8022.50079 4695.04592 11054.96266 -8308.99996 -19673.30917
73 74 75 76 77 78
-8337.61816 2363.53720 163.40497 -5524.19905 2757.72257 147962.14101
79 80 81 82 83 84
-10642.67459 -10084.79592 -9833.35864 -22051.02208 -23675.45211 -1685.57853
85 86 87 88 89 90
25957.70791 -34036.53449 16860.66876 -10935.46469 -31334.38142 43159.14359
91 92 93 94 95 96
-32794.19773 11988.77995 -16498.56481 -17204.53373 5678.20244 24113.86260
97 98 99 100 101 102
61302.94695 49890.66779 -8216.95929 40362.49393 17874.38140 30900.64169
103 104 105 106 107 108
-19968.54499 8078.12678 -12610.70796 9779.42203 6467.00827 -1479.69837
109 110 111 112 113 114
125204.13477 -5221.28062 15963.53689 -20663.92507 -10373.48953 -6003.82414
115 116 117 118 119 120
-5878.21819 -39775.12625 -30667.85956 -9149.03488 24173.39349 -7023.84381
121 122 123 124 125 126
-16279.12179 25404.57784 13840.26282 18733.52619 -13448.85319 15196.34341
127 128 129 130 131 132
-17186.64286 1585.73576 -16907.12805 115.30364 64056.95138 -1979.80002
133 134 135 136 137 138
-12555.49959 -1941.39754 -3761.73629 22114.70160 20316.34332 -9256.46130
139 140 141 142 143 144
-11020.08236 -22536.35588 5835.43225 -5224.00812 19830.29755 -24475.44081
145 146 147 148 149 150
-17244.16339 15415.91079 38734.37890 36228.84204 -6722.25938 -3220.63877
151 152 153 154 155 156
-6725.75821 -6794.52047 -6722.25938 -6722.25938 -12810.43428 -41102.58565
157 158 159 160 161 162
-6722.25938 -6752.91292 -6131.64690 -14884.02436 -7330.78441 -23347.81993
163 164
-6832.10719 4428.47754
> postscript(file="/var/wessaorg/rcomp/tmp/6nmvc1321984707.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 25597.22629 NA
1 8321.43163 25597.22629
2 1425.81499 8321.43163
3 17851.30312 1425.81499
4 -12686.83945 17851.30312
5 20240.78510 -12686.83945
6 1224.07514 20240.78510
7 -10324.53504 1224.07514
8 26816.95057 -10324.53504
9 -8969.96677 26816.95057
10 -22612.64077 -8969.96677
11 -16126.79971 -22612.64077
12 -6551.16528 -16126.79971
13 -21823.25884 -6551.16528
14 -31180.91921 -21823.25884
15 -29337.69754 -31180.91921
16 36227.35952 -29337.69754
17 -3176.71413 36227.35952
18 31634.29256 -3176.71413
19 3940.43501 31634.29256
20 6767.18176 3940.43501
21 -39114.92087 6767.18176
22 -6574.34615 -39114.92087
23 5004.57733 -6574.34615
24 -8291.42436 5004.57733
25 -7542.22443 -8291.42436
26 5021.08823 -7542.22443
27 -15218.48659 5021.08823
28 -24613.40864 -15218.48659
29 -24389.31383 -24613.40864
30 18925.88889 -24389.31383
31 -17706.51569 18925.88889
32 -25828.25853 -17706.51569
33 -13513.85165 -25828.25853
34 38.03729 -13513.85165
35 -29610.03217 38.03729
36 -32963.82291 -29610.03217
37 -10889.70666 -32963.82291
38 -4346.20918 -10889.70666
39 -10647.27454 -4346.20918
40 -22042.59366 -10647.27454
41 -22343.08349 -22042.59366
42 -5264.04620 -22343.08349
43 -9744.47889 -5264.04620
44 5934.28153 -9744.47889
45 -6817.32424 5934.28153
46 -17332.46667 -6817.32424
47 -9126.41027 -17332.46667
48 30646.55368 -9126.41027
49 -7717.24422 30646.55368
50 2803.08885 -7717.24422
51 -8877.37035 2803.08885
52 -10319.14661 -8877.37035
53 -6327.49044 -10319.14661
54 -9178.65296 -6327.49044
55 7051.82711 -9178.65296
56 18295.78376 7051.82711
57 32744.73568 18295.78376
58 -328.73347 32744.73568
59 -6495.88122 -328.73347
60 18179.91544 -6495.88122
61 45344.64669 18179.91544
62 -32023.99749 45344.64669
63 -1539.59155 -32023.99749
64 9794.37640 -1539.59155
65 -11343.61069 9794.37640
66 36756.44051 -11343.61069
67 -8022.50079 36756.44051
68 4695.04592 -8022.50079
69 11054.96266 4695.04592
70 -8308.99996 11054.96266
71 -19673.30917 -8308.99996
72 -8337.61816 -19673.30917
73 2363.53720 -8337.61816
74 163.40497 2363.53720
75 -5524.19905 163.40497
76 2757.72257 -5524.19905
77 147962.14101 2757.72257
78 -10642.67459 147962.14101
79 -10084.79592 -10642.67459
80 -9833.35864 -10084.79592
81 -22051.02208 -9833.35864
82 -23675.45211 -22051.02208
83 -1685.57853 -23675.45211
84 25957.70791 -1685.57853
85 -34036.53449 25957.70791
86 16860.66876 -34036.53449
87 -10935.46469 16860.66876
88 -31334.38142 -10935.46469
89 43159.14359 -31334.38142
90 -32794.19773 43159.14359
91 11988.77995 -32794.19773
92 -16498.56481 11988.77995
93 -17204.53373 -16498.56481
94 5678.20244 -17204.53373
95 24113.86260 5678.20244
96 61302.94695 24113.86260
97 49890.66779 61302.94695
98 -8216.95929 49890.66779
99 40362.49393 -8216.95929
100 17874.38140 40362.49393
101 30900.64169 17874.38140
102 -19968.54499 30900.64169
103 8078.12678 -19968.54499
104 -12610.70796 8078.12678
105 9779.42203 -12610.70796
106 6467.00827 9779.42203
107 -1479.69837 6467.00827
108 125204.13477 -1479.69837
109 -5221.28062 125204.13477
110 15963.53689 -5221.28062
111 -20663.92507 15963.53689
112 -10373.48953 -20663.92507
113 -6003.82414 -10373.48953
114 -5878.21819 -6003.82414
115 -39775.12625 -5878.21819
116 -30667.85956 -39775.12625
117 -9149.03488 -30667.85956
118 24173.39349 -9149.03488
119 -7023.84381 24173.39349
120 -16279.12179 -7023.84381
121 25404.57784 -16279.12179
122 13840.26282 25404.57784
123 18733.52619 13840.26282
124 -13448.85319 18733.52619
125 15196.34341 -13448.85319
126 -17186.64286 15196.34341
127 1585.73576 -17186.64286
128 -16907.12805 1585.73576
129 115.30364 -16907.12805
130 64056.95138 115.30364
131 -1979.80002 64056.95138
132 -12555.49959 -1979.80002
133 -1941.39754 -12555.49959
134 -3761.73629 -1941.39754
135 22114.70160 -3761.73629
136 20316.34332 22114.70160
137 -9256.46130 20316.34332
138 -11020.08236 -9256.46130
139 -22536.35588 -11020.08236
140 5835.43225 -22536.35588
141 -5224.00812 5835.43225
142 19830.29755 -5224.00812
143 -24475.44081 19830.29755
144 -17244.16339 -24475.44081
145 15415.91079 -17244.16339
146 38734.37890 15415.91079
147 36228.84204 38734.37890
148 -6722.25938 36228.84204
149 -3220.63877 -6722.25938
150 -6725.75821 -3220.63877
151 -6794.52047 -6725.75821
152 -6722.25938 -6794.52047
153 -6722.25938 -6722.25938
154 -12810.43428 -6722.25938
155 -41102.58565 -12810.43428
156 -6722.25938 -41102.58565
157 -6752.91292 -6722.25938
158 -6131.64690 -6752.91292
159 -14884.02436 -6131.64690
160 -7330.78441 -14884.02436
161 -23347.81993 -7330.78441
162 -6832.10719 -23347.81993
163 4428.47754 -6832.10719
164 NA 4428.47754
> dum1 <- dum[2:length(myerror),]
> dum1
lag(myerror, k = 1) myerror
[1,] 8321.43163 25597.22629
[2,] 1425.81499 8321.43163
[3,] 17851.30312 1425.81499
[4,] -12686.83945 17851.30312
[5,] 20240.78510 -12686.83945
[6,] 1224.07514 20240.78510
[7,] -10324.53504 1224.07514
[8,] 26816.95057 -10324.53504
[9,] -8969.96677 26816.95057
[10,] -22612.64077 -8969.96677
[11,] -16126.79971 -22612.64077
[12,] -6551.16528 -16126.79971
[13,] -21823.25884 -6551.16528
[14,] -31180.91921 -21823.25884
[15,] -29337.69754 -31180.91921
[16,] 36227.35952 -29337.69754
[17,] -3176.71413 36227.35952
[18,] 31634.29256 -3176.71413
[19,] 3940.43501 31634.29256
[20,] 6767.18176 3940.43501
[21,] -39114.92087 6767.18176
[22,] -6574.34615 -39114.92087
[23,] 5004.57733 -6574.34615
[24,] -8291.42436 5004.57733
[25,] -7542.22443 -8291.42436
[26,] 5021.08823 -7542.22443
[27,] -15218.48659 5021.08823
[28,] -24613.40864 -15218.48659
[29,] -24389.31383 -24613.40864
[30,] 18925.88889 -24389.31383
[31,] -17706.51569 18925.88889
[32,] -25828.25853 -17706.51569
[33,] -13513.85165 -25828.25853
[34,] 38.03729 -13513.85165
[35,] -29610.03217 38.03729
[36,] -32963.82291 -29610.03217
[37,] -10889.70666 -32963.82291
[38,] -4346.20918 -10889.70666
[39,] -10647.27454 -4346.20918
[40,] -22042.59366 -10647.27454
[41,] -22343.08349 -22042.59366
[42,] -5264.04620 -22343.08349
[43,] -9744.47889 -5264.04620
[44,] 5934.28153 -9744.47889
[45,] -6817.32424 5934.28153
[46,] -17332.46667 -6817.32424
[47,] -9126.41027 -17332.46667
[48,] 30646.55368 -9126.41027
[49,] -7717.24422 30646.55368
[50,] 2803.08885 -7717.24422
[51,] -8877.37035 2803.08885
[52,] -10319.14661 -8877.37035
[53,] -6327.49044 -10319.14661
[54,] -9178.65296 -6327.49044
[55,] 7051.82711 -9178.65296
[56,] 18295.78376 7051.82711
[57,] 32744.73568 18295.78376
[58,] -328.73347 32744.73568
[59,] -6495.88122 -328.73347
[60,] 18179.91544 -6495.88122
[61,] 45344.64669 18179.91544
[62,] -32023.99749 45344.64669
[63,] -1539.59155 -32023.99749
[64,] 9794.37640 -1539.59155
[65,] -11343.61069 9794.37640
[66,] 36756.44051 -11343.61069
[67,] -8022.50079 36756.44051
[68,] 4695.04592 -8022.50079
[69,] 11054.96266 4695.04592
[70,] -8308.99996 11054.96266
[71,] -19673.30917 -8308.99996
[72,] -8337.61816 -19673.30917
[73,] 2363.53720 -8337.61816
[74,] 163.40497 2363.53720
[75,] -5524.19905 163.40497
[76,] 2757.72257 -5524.19905
[77,] 147962.14101 2757.72257
[78,] -10642.67459 147962.14101
[79,] -10084.79592 -10642.67459
[80,] -9833.35864 -10084.79592
[81,] -22051.02208 -9833.35864
[82,] -23675.45211 -22051.02208
[83,] -1685.57853 -23675.45211
[84,] 25957.70791 -1685.57853
[85,] -34036.53449 25957.70791
[86,] 16860.66876 -34036.53449
[87,] -10935.46469 16860.66876
[88,] -31334.38142 -10935.46469
[89,] 43159.14359 -31334.38142
[90,] -32794.19773 43159.14359
[91,] 11988.77995 -32794.19773
[92,] -16498.56481 11988.77995
[93,] -17204.53373 -16498.56481
[94,] 5678.20244 -17204.53373
[95,] 24113.86260 5678.20244
[96,] 61302.94695 24113.86260
[97,] 49890.66779 61302.94695
[98,] -8216.95929 49890.66779
[99,] 40362.49393 -8216.95929
[100,] 17874.38140 40362.49393
[101,] 30900.64169 17874.38140
[102,] -19968.54499 30900.64169
[103,] 8078.12678 -19968.54499
[104,] -12610.70796 8078.12678
[105,] 9779.42203 -12610.70796
[106,] 6467.00827 9779.42203
[107,] -1479.69837 6467.00827
[108,] 125204.13477 -1479.69837
[109,] -5221.28062 125204.13477
[110,] 15963.53689 -5221.28062
[111,] -20663.92507 15963.53689
[112,] -10373.48953 -20663.92507
[113,] -6003.82414 -10373.48953
[114,] -5878.21819 -6003.82414
[115,] -39775.12625 -5878.21819
[116,] -30667.85956 -39775.12625
[117,] -9149.03488 -30667.85956
[118,] 24173.39349 -9149.03488
[119,] -7023.84381 24173.39349
[120,] -16279.12179 -7023.84381
[121,] 25404.57784 -16279.12179
[122,] 13840.26282 25404.57784
[123,] 18733.52619 13840.26282
[124,] -13448.85319 18733.52619
[125,] 15196.34341 -13448.85319
[126,] -17186.64286 15196.34341
[127,] 1585.73576 -17186.64286
[128,] -16907.12805 1585.73576
[129,] 115.30364 -16907.12805
[130,] 64056.95138 115.30364
[131,] -1979.80002 64056.95138
[132,] -12555.49959 -1979.80002
[133,] -1941.39754 -12555.49959
[134,] -3761.73629 -1941.39754
[135,] 22114.70160 -3761.73629
[136,] 20316.34332 22114.70160
[137,] -9256.46130 20316.34332
[138,] -11020.08236 -9256.46130
[139,] -22536.35588 -11020.08236
[140,] 5835.43225 -22536.35588
[141,] -5224.00812 5835.43225
[142,] 19830.29755 -5224.00812
[143,] -24475.44081 19830.29755
[144,] -17244.16339 -24475.44081
[145,] 15415.91079 -17244.16339
[146,] 38734.37890 15415.91079
[147,] 36228.84204 38734.37890
[148,] -6722.25938 36228.84204
[149,] -3220.63877 -6722.25938
[150,] -6725.75821 -3220.63877
[151,] -6794.52047 -6725.75821
[152,] -6722.25938 -6794.52047
[153,] -6722.25938 -6722.25938
[154,] -12810.43428 -6722.25938
[155,] -41102.58565 -12810.43428
[156,] -6722.25938 -41102.58565
[157,] -6752.91292 -6722.25938
[158,] -6131.64690 -6752.91292
[159,] -14884.02436 -6131.64690
[160,] -7330.78441 -14884.02436
[161,] -23347.81993 -7330.78441
[162,] -6832.10719 -23347.81993
[163,] 4428.47754 -6832.10719
> z <- as.data.frame(dum1)
> z
lag(myerror, k = 1) myerror
1 8321.43163 25597.22629
2 1425.81499 8321.43163
3 17851.30312 1425.81499
4 -12686.83945 17851.30312
5 20240.78510 -12686.83945
6 1224.07514 20240.78510
7 -10324.53504 1224.07514
8 26816.95057 -10324.53504
9 -8969.96677 26816.95057
10 -22612.64077 -8969.96677
11 -16126.79971 -22612.64077
12 -6551.16528 -16126.79971
13 -21823.25884 -6551.16528
14 -31180.91921 -21823.25884
15 -29337.69754 -31180.91921
16 36227.35952 -29337.69754
17 -3176.71413 36227.35952
18 31634.29256 -3176.71413
19 3940.43501 31634.29256
20 6767.18176 3940.43501
21 -39114.92087 6767.18176
22 -6574.34615 -39114.92087
23 5004.57733 -6574.34615
24 -8291.42436 5004.57733
25 -7542.22443 -8291.42436
26 5021.08823 -7542.22443
27 -15218.48659 5021.08823
28 -24613.40864 -15218.48659
29 -24389.31383 -24613.40864
30 18925.88889 -24389.31383
31 -17706.51569 18925.88889
32 -25828.25853 -17706.51569
33 -13513.85165 -25828.25853
34 38.03729 -13513.85165
35 -29610.03217 38.03729
36 -32963.82291 -29610.03217
37 -10889.70666 -32963.82291
38 -4346.20918 -10889.70666
39 -10647.27454 -4346.20918
40 -22042.59366 -10647.27454
41 -22343.08349 -22042.59366
42 -5264.04620 -22343.08349
43 -9744.47889 -5264.04620
44 5934.28153 -9744.47889
45 -6817.32424 5934.28153
46 -17332.46667 -6817.32424
47 -9126.41027 -17332.46667
48 30646.55368 -9126.41027
49 -7717.24422 30646.55368
50 2803.08885 -7717.24422
51 -8877.37035 2803.08885
52 -10319.14661 -8877.37035
53 -6327.49044 -10319.14661
54 -9178.65296 -6327.49044
55 7051.82711 -9178.65296
56 18295.78376 7051.82711
57 32744.73568 18295.78376
58 -328.73347 32744.73568
59 -6495.88122 -328.73347
60 18179.91544 -6495.88122
61 45344.64669 18179.91544
62 -32023.99749 45344.64669
63 -1539.59155 -32023.99749
64 9794.37640 -1539.59155
65 -11343.61069 9794.37640
66 36756.44051 -11343.61069
67 -8022.50079 36756.44051
68 4695.04592 -8022.50079
69 11054.96266 4695.04592
70 -8308.99996 11054.96266
71 -19673.30917 -8308.99996
72 -8337.61816 -19673.30917
73 2363.53720 -8337.61816
74 163.40497 2363.53720
75 -5524.19905 163.40497
76 2757.72257 -5524.19905
77 147962.14101 2757.72257
78 -10642.67459 147962.14101
79 -10084.79592 -10642.67459
80 -9833.35864 -10084.79592
81 -22051.02208 -9833.35864
82 -23675.45211 -22051.02208
83 -1685.57853 -23675.45211
84 25957.70791 -1685.57853
85 -34036.53449 25957.70791
86 16860.66876 -34036.53449
87 -10935.46469 16860.66876
88 -31334.38142 -10935.46469
89 43159.14359 -31334.38142
90 -32794.19773 43159.14359
91 11988.77995 -32794.19773
92 -16498.56481 11988.77995
93 -17204.53373 -16498.56481
94 5678.20244 -17204.53373
95 24113.86260 5678.20244
96 61302.94695 24113.86260
97 49890.66779 61302.94695
98 -8216.95929 49890.66779
99 40362.49393 -8216.95929
100 17874.38140 40362.49393
101 30900.64169 17874.38140
102 -19968.54499 30900.64169
103 8078.12678 -19968.54499
104 -12610.70796 8078.12678
105 9779.42203 -12610.70796
106 6467.00827 9779.42203
107 -1479.69837 6467.00827
108 125204.13477 -1479.69837
109 -5221.28062 125204.13477
110 15963.53689 -5221.28062
111 -20663.92507 15963.53689
112 -10373.48953 -20663.92507
113 -6003.82414 -10373.48953
114 -5878.21819 -6003.82414
115 -39775.12625 -5878.21819
116 -30667.85956 -39775.12625
117 -9149.03488 -30667.85956
118 24173.39349 -9149.03488
119 -7023.84381 24173.39349
120 -16279.12179 -7023.84381
121 25404.57784 -16279.12179
122 13840.26282 25404.57784
123 18733.52619 13840.26282
124 -13448.85319 18733.52619
125 15196.34341 -13448.85319
126 -17186.64286 15196.34341
127 1585.73576 -17186.64286
128 -16907.12805 1585.73576
129 115.30364 -16907.12805
130 64056.95138 115.30364
131 -1979.80002 64056.95138
132 -12555.49959 -1979.80002
133 -1941.39754 -12555.49959
134 -3761.73629 -1941.39754
135 22114.70160 -3761.73629
136 20316.34332 22114.70160
137 -9256.46130 20316.34332
138 -11020.08236 -9256.46130
139 -22536.35588 -11020.08236
140 5835.43225 -22536.35588
141 -5224.00812 5835.43225
142 19830.29755 -5224.00812
143 -24475.44081 19830.29755
144 -17244.16339 -24475.44081
145 15415.91079 -17244.16339
146 38734.37890 15415.91079
147 36228.84204 38734.37890
148 -6722.25938 36228.84204
149 -3220.63877 -6722.25938
150 -6725.75821 -3220.63877
151 -6794.52047 -6725.75821
152 -6722.25938 -6794.52047
153 -6722.25938 -6722.25938
154 -12810.43428 -6722.25938
155 -41102.58565 -12810.43428
156 -6722.25938 -41102.58565
157 -6752.91292 -6722.25938
158 -6131.64690 -6752.91292
159 -14884.02436 -6131.64690
160 -7330.78441 -14884.02436
161 -23347.81993 -7330.78441
162 -6832.10719 -23347.81993
163 4428.47754 -6832.10719
> 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/7zdhc1321984707.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> acf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/wessaorg/rcomp/tmp/857bl1321984707.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> pacf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Partial Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/wessaorg/rcomp/tmp/984cu1321984707.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> opar <- par(mfrow = c(2,2), oma = c(0, 0, 1.1, 0))
> plot(mylm, las = 1, sub='Residual Diagnostics')
> par(opar)
> dev.off()
null device
1
> if (n > n25) {
+ postscript(file="/var/wessaorg/rcomp/tmp/10ymwu1321984707.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
+ plot(kp3:nmkm3,gqarr[,2], main='Goldfeld-Quandt test',ylab='2-sided p-value',xlab='breakpoint')
+ grid()
+ dev.off()
+ }
null device
1
>
> #Note: the /var/wessaorg/rcomp/createtable file can be downloaded at http://www.wessa.net/cretab
> load(file="/var/wessaorg/rcomp/createtable")
>
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a, 'Multiple Linear Regression - Estimated Regression Equation', 1, TRUE)
> a<-table.row.end(a)
> myeq <- colnames(x)[1]
> myeq <- paste(myeq, '[t] = ', sep='')
> for (i in 1:k){
+ if (mysum$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/11y5qh1321984707.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/123le01321984707.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/139yvw1321984707.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/14lr8l1321984707.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/154qx91321984707.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/16y9v61321984707.tab")
+ }
>
> try(system("convert tmp/1g1sr1321984707.ps tmp/1g1sr1321984707.png",intern=TRUE))
character(0)
> try(system("convert tmp/2lu921321984707.ps tmp/2lu921321984707.png",intern=TRUE))
character(0)
> try(system("convert tmp/3vc8v1321984707.ps tmp/3vc8v1321984707.png",intern=TRUE))
character(0)
> try(system("convert tmp/4iyux1321984707.ps tmp/4iyux1321984707.png",intern=TRUE))
character(0)
> try(system("convert tmp/5wnjv1321984707.ps tmp/5wnjv1321984707.png",intern=TRUE))
character(0)
> try(system("convert tmp/6nmvc1321984707.ps tmp/6nmvc1321984707.png",intern=TRUE))
character(0)
> try(system("convert tmp/7zdhc1321984707.ps tmp/7zdhc1321984707.png",intern=TRUE))
character(0)
> try(system("convert tmp/857bl1321984707.ps tmp/857bl1321984707.png",intern=TRUE))
character(0)
> try(system("convert tmp/984cu1321984707.ps tmp/984cu1321984707.png",intern=TRUE))
character(0)
> try(system("convert tmp/10ymwu1321984707.ps tmp/10ymwu1321984707.png",intern=TRUE))
character(0)
>
>
> proc.time()
user system elapsed
4.732 0.499 5.263