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
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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(1565
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+ ,21157)
+ ,dim=c(6
+ ,144)
+ ,dimnames=list(c('pageviews'
+ ,'time'
+ ,'blogs'
+ ,'peerreviews'
+ ,'peerreviews+'
+ ,'compcharachters')
+ ,1:144))
> y <- array(NA,dim=c(6,144),dimnames=list(c('pageviews','time','blogs','peerreviews','peerreviews+','compcharachters'),1:144))
> 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
pageviews time blogs peerreviews peerreviews+ compcharachters
1 1565 129404 20 18 63 18158
2 1134 130358 38 17 50 30461
3 192 7215 0 0 0 1423
4 2033 112861 49 22 51 25629
5 3283 219904 76 30 112 48758
6 5877 402036 104 31 118 129230
7 1322 117604 37 19 59 27376
8 1225 131822 57 25 90 26706
9 1463 99729 42 30 50 26505
10 2568 256310 62 26 79 49801
11 1810 113066 50 20 49 46580
12 1915 165392 66 30 91 48352
13 1452 78240 38 15 32 13899
14 2415 152673 48 22 82 39342
15 1254 134368 42 17 58 27465
16 1374 125769 47 19 65 55211
17 1504 123467 71 28 111 74098
18 999 56232 0 12 36 13497
19 2222 108458 50 28 89 38338
20 634 22762 12 13 28 52505
21 849 48633 16 14 35 10663
22 2189 182081 77 27 78 74484
23 1469 140857 29 25 67 28895
24 1791 93773 38 30 61 32827
25 1743 133398 50 21 58 36188
26 1180 113933 33 17 49 28173
27 1749 153851 49 22 77 54926
28 1101 140711 59 28 71 38900
29 2391 303844 55 26 85 88530
30 1826 163810 42 17 56 35482
31 1301 123344 40 23 71 26730
32 1433 157640 51 20 58 29806
33 1893 103274 45 16 34 41799
34 2525 193500 73 20 59 54289
35 2033 178768 51 21 77 36805
36 1 0 0 0 0 0
37 1817 181412 46 27 75 33146
38 1506 92342 44 14 39 23333
39 1820 100023 31 29 83 47686
40 1649 178277 71 31 123 77783
41 1672 145067 61 19 67 36042
42 1433 114146 28 30 105 34541
43 864 86039 21 23 76 75620
44 1683 125481 42 21 57 60610
45 1024 95535 44 22 82 55041
46 1029 129221 40 21 64 32087
47 629 61554 15 32 57 16356
48 1679 168048 46 20 80 40161
49 1715 159121 43 26 94 55459
50 2093 129362 47 25 72 36679
51 658 48188 12 22 39 22346
52 1234 95461 46 19 60 27377
53 2059 229864 56 24 84 50273
54 1725 191094 47 26 69 32104
55 1504 161082 50 27 102 27016
56 1454 111388 35 10 28 19715
57 1620 172614 45 26 65 33629
58 733 63205 25 23 67 27084
59 894 109102 47 21 80 32352
60 2343 137303 28 34 79 51845
61 1503 125304 48 29 107 26591
62 1627 88620 32 19 60 29677
63 1119 95808 28 19 53 54237
64 897 83419 31 23 59 20284
65 855 101723 13 22 80 22741
66 1229 94982 38 29 89 34178
67 1991 143566 48 31 115 69551
68 2393 113325 68 21 59 29653
69 820 81518 32 21 66 38071
70 340 31970 5 21 42 4157
71 2443 192268 53 15 35 28321
72 1030 91261 33 9 3 40195
73 1091 80820 54 23 72 48158
74 1414 85829 37 18 38 13310
75 2192 116322 52 31 107 78474
76 1082 56544 0 25 73 6386
77 1764 116173 52 24 80 31588
78 2072 118781 51 22 69 61254
79 816 60138 16 21 46 21152
80 1121 73422 33 26 52 41272
81 810 67751 48 22 58 34165
82 1699 214002 33 26 85 37054
83 751 51185 24 20 13 12368
84 1309 97181 37 25 61 23168
85 732 45100 17 19 49 16380
86 1327 115801 32 22 47 41242
87 2246 186310 55 25 93 48450
88 968 71960 39 22 65 20790
89 1015 80105 31 21 64 34585
90 1100 103613 26 20 64 35672
91 1300 98707 37 23 57 52168
92 1982 136234 66 22 61 53933
93 1091 136781 35 21 71 34474
94 1107 105863 24 12 43 43753
95 666 42228 22 9 18 36456
96 1903 179997 37 32 103 51183
97 1608 169406 86 24 76 52742
98 223 19349 13 1 0 3895
99 1807 160819 21 24 83 37076
100 1466 109510 32 25 73 24079
101 552 43803 8 4 4 2325
102 708 47062 38 15 41 29354
103 1079 110845 45 21 57 30341
104 957 92517 24 23 52 18992
105 585 58660 23 12 24 15292
106 596 27676 2 16 17 5842
107 980 98550 52 24 89 28918
108 585 43646 5 9 20 3738
109 0 0 0 0 0 0
110 975 75566 43 25 51 95352
111 750 57359 18 17 63 37478
112 1071 104330 44 18 48 26839
113 931 70369 45 21 70 26783
114 783 65494 29 17 32 33392
115 78 3616 0 0 0 0
116 0 0 0 0 0 0
117 874 143931 32 20 72 25446
118 1327 117946 65 26 56 59847
119 1831 137332 26 27 66 28162
120 750 84336 24 20 77 33298
121 778 43410 7 1 3 2781
122 1373 136250 62 24 73 37121
123 807 79015 30 14 37 22698
124 1562 101354 49 27 57 27615
125 685 57586 3 12 32 32689
126 285 19764 10 2 4 5752
127 1336 105757 42 16 55 23164
128 954 103651 23 23 84 20304
129 1283 113402 40 28 90 34409
130 256 11796 1 2 1 0
131 81 7627 0 0 0 0
132 1214 121085 29 17 38 92538
133 41 6836 0 1 0 0
134 1634 139563 46 17 36 46037
135 42 5118 5 0 0 0
136 528 40248 8 4 7 5444
137 0 0 0 0 0 0
138 890 95079 21 25 75 23924
139 1203 80763 21 26 52 52230
140 81 7131 0 0 0 0
141 61 4194 0 0 0 0
142 849 60378 15 15 45 8019
143 1035 109173 47 20 66 34542
144 964 83484 17 19 48 21157
> k <- length(x[1,])
> df <- as.data.frame(x)
> (mylm <- lm(df))
Call:
lm(formula = df)
Coefficients:
(Intercept) time blogs peerreviews
11.770626 0.008374 6.855946 13.955187
`peerreviews+` compcharachters
-3.909096 0.002807
> (mysum <- summary(mylm))
Call:
lm(formula = df)
Residuals:
Min 1Q Median 3Q Max
-821.33 -188.00 -30.82 139.78 1451.43
Coefficients:
Estimate Std. Error t value Pr(>|t|)
(Intercept) 11.7706258 70.8357380 0.166 0.86827
time 0.0083740 0.0008398 9.972 < 2e-16 ***
blogs 6.8559455 2.4000868 2.857 0.00495 **
peerreviews 13.9551869 7.2676865 1.920 0.05690 .
`peerreviews+` -3.9090955 2.2566770 -1.732 0.08547 .
compcharachters 0.0028073 0.0019207 1.462 0.14612
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
Residual standard error: 331.5 on 138 degrees of freedom
Multiple R-squared: 0.8088, Adjusted R-squared: 0.8018
F-statistic: 116.7 on 5 and 138 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,] 0.9804596 3.908071e-02 1.954035e-02
[2,] 0.9924975 1.500492e-02 7.502460e-03
[3,] 0.9876136 2.477281e-02 1.238640e-02
[4,] 0.9900227 1.995456e-02 9.977282e-03
[5,] 0.9905344 1.893111e-02 9.465555e-03
[6,] 0.9947102 1.057956e-02 5.289778e-03
[7,] 0.9951277 9.744629e-03 4.872315e-03
[8,] 0.9978102 4.379576e-03 2.189788e-03
[9,] 0.9971044 5.791259e-03 2.895629e-03
[10,] 0.9980530 3.893992e-03 1.946996e-03
[11,] 0.9997931 4.137371e-04 2.068686e-04
[12,] 0.9996246 7.508400e-04 3.754200e-04
[13,] 0.9994138 1.172323e-03 5.861614e-04
[14,] 0.9993939 1.212121e-03 6.060606e-04
[15,] 0.9993414 1.317204e-03 6.586018e-04
[16,] 0.9993856 1.228802e-03 6.144011e-04
[17,] 0.9989879 2.024182e-03 1.012091e-03
[18,] 0.9986964 2.607255e-03 1.303627e-03
[19,] 0.9983813 3.237352e-03 1.618676e-03
[20,] 0.9997666 4.668565e-04 2.334283e-04
[21,] 0.9999973 5.485034e-06 2.742517e-06
[22,] 0.9999949 1.014508e-05 5.072542e-06
[23,] 0.9999917 1.666595e-05 8.332974e-06
[24,] 0.9999927 1.468960e-05 7.344802e-06
[25,] 0.9999957 8.672844e-06 4.336422e-06
[26,] 0.9999940 1.201761e-05 6.008803e-06
[27,] 0.9999899 2.023568e-05 1.011784e-05
[28,] 0.9999817 3.651370e-05 1.825685e-05
[29,] 0.9999716 5.688798e-05 2.844399e-05
[30,] 0.9999666 6.671605e-05 3.335803e-05
[31,] 0.9999824 3.521226e-05 1.760613e-05
[32,] 0.9999937 1.260202e-05 6.301008e-06
[33,] 0.9999893 2.131854e-05 1.065927e-05
[34,] 0.9999831 3.370335e-05 1.685168e-05
[35,] 0.9999804 3.920182e-05 1.960091e-05
[36,] 0.9999686 6.283482e-05 3.141741e-05
[37,] 0.9999586 8.287554e-05 4.143777e-05
[38,] 0.9999741 5.189024e-05 2.594512e-05
[39,] 0.9999714 5.720400e-05 2.860200e-05
[40,] 0.9999542 9.151503e-05 4.575752e-05
[41,] 0.9999239 1.522423e-04 7.612115e-05
[42,] 0.9999636 7.274269e-05 3.637135e-05
[43,] 0.9999414 1.172203e-04 5.861014e-05
[44,] 0.9999041 1.918953e-04 9.594763e-05
[45,] 0.9999062 1.875038e-04 9.375192e-05
[46,] 0.9999095 1.809030e-04 9.045150e-05
[47,] 0.9998768 2.463247e-04 1.231623e-04
[48,] 0.9998376 3.247992e-04 1.623996e-04
[49,] 0.9998301 3.398705e-04 1.699353e-04
[50,] 0.9997468 5.064464e-04 2.532232e-04
[51,] 0.9998027 3.945128e-04 1.972564e-04
[52,] 0.9999646 7.083201e-05 3.541600e-05
[53,] 0.9999434 1.132025e-04 5.660125e-05
[54,] 0.9999787 4.256073e-05 2.128036e-05
[55,] 0.9999662 6.751991e-05 3.375996e-05
[56,] 0.9999519 9.613660e-05 4.806830e-05
[57,] 0.9999297 1.406167e-04 7.030833e-05
[58,] 0.9998847 2.305680e-04 1.152840e-04
[59,] 0.9998802 2.395772e-04 1.197886e-04
[60,] 0.9999970 6.037583e-06 3.018792e-06
[61,] 0.9999961 7.804938e-06 3.902469e-06
[62,] 0.9999946 1.088115e-05 5.440576e-06
[63,] 0.9999984 3.196536e-06 1.598268e-06
[64,] 0.9999977 4.582854e-06 2.291427e-06
[65,] 0.9999964 7.184702e-06 3.592351e-06
[66,] 0.9999974 5.229606e-06 2.614803e-06
[67,] 0.9999998 3.883117e-07 1.941559e-07
[68,] 0.9999999 1.776312e-07 8.881558e-08
[69,] 1.0000000 6.615227e-08 3.307613e-08
[70,] 1.0000000 5.962418e-10 2.981209e-10
[71,] 1.0000000 1.371399e-09 6.856994e-10
[72,] 1.0000000 2.965717e-09 1.482859e-09
[73,] 1.0000000 4.298021e-09 2.149011e-09
[74,] 1.0000000 1.263066e-09 6.315330e-10
[75,] 1.0000000 1.704238e-09 8.521192e-10
[76,] 1.0000000 3.661105e-09 1.830552e-09
[77,] 1.0000000 7.538847e-09 3.769424e-09
[78,] 1.0000000 1.549696e-08 7.748482e-09
[79,] 1.0000000 3.454768e-09 1.727384e-09
[80,] 1.0000000 7.377714e-09 3.688857e-09
[81,] 1.0000000 1.496217e-08 7.481083e-09
[82,] 1.0000000 3.355092e-08 1.677546e-08
[83,] 1.0000000 6.370026e-08 3.185013e-08
[84,] 1.0000000 3.410538e-09 1.705269e-09
[85,] 1.0000000 2.048845e-09 1.024422e-09
[86,] 1.0000000 4.319591e-09 2.159795e-09
[87,] 1.0000000 7.607893e-09 3.803946e-09
[88,] 1.0000000 1.758356e-08 8.791781e-09
[89,] 1.0000000 1.965810e-08 9.829052e-09
[90,] 1.0000000 4.704997e-08 2.352499e-08
[91,] 1.0000000 3.520015e-08 1.760007e-08
[92,] 1.0000000 2.885345e-08 1.442673e-08
[93,] 1.0000000 6.938955e-08 3.469477e-08
[94,] 0.9999999 1.474258e-07 7.371289e-08
[95,] 0.9999999 2.182828e-07 1.091414e-07
[96,] 0.9999999 2.254816e-07 1.127408e-07
[97,] 0.9999999 2.921143e-07 1.460572e-07
[98,] 0.9999998 4.742893e-07 2.371447e-07
[99,] 0.9999995 1.045132e-06 5.225659e-07
[100,] 0.9999988 2.440182e-06 1.220091e-06
[101,] 0.9999973 5.387849e-06 2.693925e-06
[102,] 0.9999953 9.425763e-06 4.712881e-06
[103,] 0.9999957 8.530867e-06 4.265433e-06
[104,] 0.9999925 1.509415e-05 7.547073e-06
[105,] 0.9999910 1.808194e-05 9.040972e-06
[106,] 0.9999871 2.571825e-05 1.285913e-05
[107,] 0.9999702 5.959507e-05 2.979753e-05
[108,] 0.9999351 1.298112e-04 6.490560e-05
[109,] 0.9999998 4.440113e-07 2.220057e-07
[110,] 0.9999996 8.769605e-07 4.384803e-07
[111,] 0.9999988 2.405715e-06 1.202858e-06
[112,] 0.9999971 5.744012e-06 2.872006e-06
[113,] 0.9999993 1.396949e-06 6.984745e-07
[114,] 0.9999991 1.720891e-06 8.604453e-07
[115,] 0.9999989 2.156519e-06 1.078260e-06
[116,] 0.9999961 7.750053e-06 3.875026e-06
[117,] 0.9999930 1.398565e-05 6.992823e-06
[118,] 0.9999750 5.008244e-05 2.504122e-05
[119,] 0.9999924 1.514941e-05 7.574703e-06
[120,] 0.9999714 5.720644e-05 2.860322e-05
[121,] 0.9999692 6.162990e-05 3.081495e-05
[122,] 0.9998757 2.485362e-04 1.242681e-04
[123,] 0.9994728 1.054369e-03 5.271845e-04
[124,] 0.9992763 1.447361e-03 7.236803e-04
[125,] 0.9986542 2.691542e-03 1.345771e-03
[126,] 0.9938781 1.224388e-02 6.121941e-03
[127,] 0.9955406 8.918845e-03 4.459423e-03
> postscript(file="/var/wessaorg/rcomp/tmp/1u9z21323946263.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$resid)
> grid()
> dev.off()
null device
1
> postscript(file="/var/wessaorg/rcomp/tmp/200co1323946263.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> plot(mysum$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/3jdyu1323946263.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> hist(mysum$resid, main='Residual Histogram', xlab='values of Residuals')
> grid()
> dev.off()
null device
1
> postscript(file="/var/wessaorg/rcomp/tmp/40wpc1323946263.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> densityplot(~mysum$resid,col='black',main='Residual Density Plot', xlab='values of Residuals')
> dev.off()
null device
1
> postscript(file="/var/wessaorg/rcomp/tmp/5dbss1323946263.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 = 144
Frequency = 1
1 2 3 4 5
2.765848e+02 -3.572122e+02 1.158161e+02 5.605905e+02 7.909841e+02
6 7 8 9 10
1.451433e+03 -3.962215e+01 -3.534710e+02 3.053981e+01 -2.090043e+02
11 12 13 14 15
2.902945e+02 -1.329236e+02 4.012655e+02 6.987458e+02 -2.585324e+02
16 17 18 19 20
-1.792418e+02 -1.933071e+02 4.517172e+02 8.087419e+02 1.299893e+02
21 22 23 24 25
2.317925e+02 -1.564056e+02 -8.921811e+01 4.610916e+02 1.034341e+02
26 27 28 29 30
-1.368754e+02 -4.726898e+01 -7.159900e+02 -8.213319e+02 3.659574e+01
31 32 33 34 35
-1.363549e+02 -3.845533e+02 5.001785e+02 1.915020e+02 7.918998e+01
36 37 38 39 40
-1.077063e+01 -2.059486e+02 3.108744e+02 5.439874e+02 -5.125879e+02
41 42 43 44 45
-7.719553e+01 1.682358e+02 -2.484024e+02 9.210999e+01 -2.304278e+02
46 47 48 49 50
-4.720609e+02 -2.707273e+02 -1.344997e+02 -7.512675e+01 5.053277e+02
51 52 53 54 55
-5.685993e+01 6.365088e-03 -4.092787e+02 -3.924559e+02 -2.533745e+02
56 57 58 59 60
1.840640e+02 -3.489098e+02 -1.145412e+02 -4.247742e+02 6.782842e+02
61 62 63 64 65
5.177100e+01 5.398194e+02 -9.725988e+01 -1.731323e+02 -1.558545e+02
66 67 68 69 70
8.584602e+00 2.696060e+02 8.203734e+02 -2.357285e+02 -1.143143e+02
71 72 73 74 75
3.057951e+02 -1.989459e+02 -1.424872e+02 2.898136e+02 6.150016e+02
76 77 78 79 80
5.152862e+02 3.120126e+02 5.066584e+02 1.831761e+01 -7.277873e+00
81 82 83 84 85
-2.744013e+02 -4.656551e+02 -1.169432e+02 5.430043e+01 1.064241e+02
86 87 88 89 90
-1.129447e+02 1.756433e+02 -2.503283e+01 -2.007207e+01 -8.674494e+01
91 92 93 94 95
-3.661573e+01 1.569470e+02 -4.184261e+02 -7.800980e+01 -7.794719e+00
96 97 98 99 100
-5.735223e+01 -5.978851e+02 -6.481625e+01 1.900017e+02 1.866887e+02
101 102 103 104 105
7.186367e+01 -8.985437e+01 -3.249220e+02 -1.650641e+02 -1.922499e+02
106 107 108 109 110
1.655298e+02 -2.817348e+02 1.155491e+02 -1.177063e+01 -3.815634e+02
111 112 113 114 115
3.832065e+01 -2.549945e+02 -7.316888e+01 -1.819287e+02 3.594895e+01
116 117 118 119 120
-1.177063e+01 -6.315239e+02 -4.300217e+02 2.931064e+02 -2.041245e+02
121 122 123 124 125
3.446869e+02 -3.585682e+02 -1.865775e+02 1.340536e+02 3.629702e+01
126 127 128 129 130
1.074443e+01 7.735852e+01 -1.330365e+02 -8.816078e+01 1.145923e+02
131 132 133 134 135
5.360788e+00 -3.590338e+02 -4.197056e+01 -8.759624e+01 -4.690854e+01
136 137 138 139 140
8.060463e+01 -1.177063e+01 -1.847972e+02 6.475757e+01 9.514298e+00
141 142 143 144
1.410877e+01 1.728540e+02 -3.312889e+02 -3.234801e-01
> postscript(file="/var/wessaorg/rcomp/tmp/6usmr1323946263.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 = 144
Frequency = 1
lag(myerror, k = 1) myerror
0 2.765848e+02 NA
1 -3.572122e+02 2.765848e+02
2 1.158161e+02 -3.572122e+02
3 5.605905e+02 1.158161e+02
4 7.909841e+02 5.605905e+02
5 1.451433e+03 7.909841e+02
6 -3.962215e+01 1.451433e+03
7 -3.534710e+02 -3.962215e+01
8 3.053981e+01 -3.534710e+02
9 -2.090043e+02 3.053981e+01
10 2.902945e+02 -2.090043e+02
11 -1.329236e+02 2.902945e+02
12 4.012655e+02 -1.329236e+02
13 6.987458e+02 4.012655e+02
14 -2.585324e+02 6.987458e+02
15 -1.792418e+02 -2.585324e+02
16 -1.933071e+02 -1.792418e+02
17 4.517172e+02 -1.933071e+02
18 8.087419e+02 4.517172e+02
19 1.299893e+02 8.087419e+02
20 2.317925e+02 1.299893e+02
21 -1.564056e+02 2.317925e+02
22 -8.921811e+01 -1.564056e+02
23 4.610916e+02 -8.921811e+01
24 1.034341e+02 4.610916e+02
25 -1.368754e+02 1.034341e+02
26 -4.726898e+01 -1.368754e+02
27 -7.159900e+02 -4.726898e+01
28 -8.213319e+02 -7.159900e+02
29 3.659574e+01 -8.213319e+02
30 -1.363549e+02 3.659574e+01
31 -3.845533e+02 -1.363549e+02
32 5.001785e+02 -3.845533e+02
33 1.915020e+02 5.001785e+02
34 7.918998e+01 1.915020e+02
35 -1.077063e+01 7.918998e+01
36 -2.059486e+02 -1.077063e+01
37 3.108744e+02 -2.059486e+02
38 5.439874e+02 3.108744e+02
39 -5.125879e+02 5.439874e+02
40 -7.719553e+01 -5.125879e+02
41 1.682358e+02 -7.719553e+01
42 -2.484024e+02 1.682358e+02
43 9.210999e+01 -2.484024e+02
44 -2.304278e+02 9.210999e+01
45 -4.720609e+02 -2.304278e+02
46 -2.707273e+02 -4.720609e+02
47 -1.344997e+02 -2.707273e+02
48 -7.512675e+01 -1.344997e+02
49 5.053277e+02 -7.512675e+01
50 -5.685993e+01 5.053277e+02
51 6.365088e-03 -5.685993e+01
52 -4.092787e+02 6.365088e-03
53 -3.924559e+02 -4.092787e+02
54 -2.533745e+02 -3.924559e+02
55 1.840640e+02 -2.533745e+02
56 -3.489098e+02 1.840640e+02
57 -1.145412e+02 -3.489098e+02
58 -4.247742e+02 -1.145412e+02
59 6.782842e+02 -4.247742e+02
60 5.177100e+01 6.782842e+02
61 5.398194e+02 5.177100e+01
62 -9.725988e+01 5.398194e+02
63 -1.731323e+02 -9.725988e+01
64 -1.558545e+02 -1.731323e+02
65 8.584602e+00 -1.558545e+02
66 2.696060e+02 8.584602e+00
67 8.203734e+02 2.696060e+02
68 -2.357285e+02 8.203734e+02
69 -1.143143e+02 -2.357285e+02
70 3.057951e+02 -1.143143e+02
71 -1.989459e+02 3.057951e+02
72 -1.424872e+02 -1.989459e+02
73 2.898136e+02 -1.424872e+02
74 6.150016e+02 2.898136e+02
75 5.152862e+02 6.150016e+02
76 3.120126e+02 5.152862e+02
77 5.066584e+02 3.120126e+02
78 1.831761e+01 5.066584e+02
79 -7.277873e+00 1.831761e+01
80 -2.744013e+02 -7.277873e+00
81 -4.656551e+02 -2.744013e+02
82 -1.169432e+02 -4.656551e+02
83 5.430043e+01 -1.169432e+02
84 1.064241e+02 5.430043e+01
85 -1.129447e+02 1.064241e+02
86 1.756433e+02 -1.129447e+02
87 -2.503283e+01 1.756433e+02
88 -2.007207e+01 -2.503283e+01
89 -8.674494e+01 -2.007207e+01
90 -3.661573e+01 -8.674494e+01
91 1.569470e+02 -3.661573e+01
92 -4.184261e+02 1.569470e+02
93 -7.800980e+01 -4.184261e+02
94 -7.794719e+00 -7.800980e+01
95 -5.735223e+01 -7.794719e+00
96 -5.978851e+02 -5.735223e+01
97 -6.481625e+01 -5.978851e+02
98 1.900017e+02 -6.481625e+01
99 1.866887e+02 1.900017e+02
100 7.186367e+01 1.866887e+02
101 -8.985437e+01 7.186367e+01
102 -3.249220e+02 -8.985437e+01
103 -1.650641e+02 -3.249220e+02
104 -1.922499e+02 -1.650641e+02
105 1.655298e+02 -1.922499e+02
106 -2.817348e+02 1.655298e+02
107 1.155491e+02 -2.817348e+02
108 -1.177063e+01 1.155491e+02
109 -3.815634e+02 -1.177063e+01
110 3.832065e+01 -3.815634e+02
111 -2.549945e+02 3.832065e+01
112 -7.316888e+01 -2.549945e+02
113 -1.819287e+02 -7.316888e+01
114 3.594895e+01 -1.819287e+02
115 -1.177063e+01 3.594895e+01
116 -6.315239e+02 -1.177063e+01
117 -4.300217e+02 -6.315239e+02
118 2.931064e+02 -4.300217e+02
119 -2.041245e+02 2.931064e+02
120 3.446869e+02 -2.041245e+02
121 -3.585682e+02 3.446869e+02
122 -1.865775e+02 -3.585682e+02
123 1.340536e+02 -1.865775e+02
124 3.629702e+01 1.340536e+02
125 1.074443e+01 3.629702e+01
126 7.735852e+01 1.074443e+01
127 -1.330365e+02 7.735852e+01
128 -8.816078e+01 -1.330365e+02
129 1.145923e+02 -8.816078e+01
130 5.360788e+00 1.145923e+02
131 -3.590338e+02 5.360788e+00
132 -4.197056e+01 -3.590338e+02
133 -8.759624e+01 -4.197056e+01
134 -4.690854e+01 -8.759624e+01
135 8.060463e+01 -4.690854e+01
136 -1.177063e+01 8.060463e+01
137 -1.847972e+02 -1.177063e+01
138 6.475757e+01 -1.847972e+02
139 9.514298e+00 6.475757e+01
140 1.410877e+01 9.514298e+00
141 1.728540e+02 1.410877e+01
142 -3.312889e+02 1.728540e+02
143 -3.234801e-01 -3.312889e+02
144 NA -3.234801e-01
> dum1 <- dum[2:length(myerror),]
> dum1
lag(myerror, k = 1) myerror
[1,] -3.572122e+02 2.765848e+02
[2,] 1.158161e+02 -3.572122e+02
[3,] 5.605905e+02 1.158161e+02
[4,] 7.909841e+02 5.605905e+02
[5,] 1.451433e+03 7.909841e+02
[6,] -3.962215e+01 1.451433e+03
[7,] -3.534710e+02 -3.962215e+01
[8,] 3.053981e+01 -3.534710e+02
[9,] -2.090043e+02 3.053981e+01
[10,] 2.902945e+02 -2.090043e+02
[11,] -1.329236e+02 2.902945e+02
[12,] 4.012655e+02 -1.329236e+02
[13,] 6.987458e+02 4.012655e+02
[14,] -2.585324e+02 6.987458e+02
[15,] -1.792418e+02 -2.585324e+02
[16,] -1.933071e+02 -1.792418e+02
[17,] 4.517172e+02 -1.933071e+02
[18,] 8.087419e+02 4.517172e+02
[19,] 1.299893e+02 8.087419e+02
[20,] 2.317925e+02 1.299893e+02
[21,] -1.564056e+02 2.317925e+02
[22,] -8.921811e+01 -1.564056e+02
[23,] 4.610916e+02 -8.921811e+01
[24,] 1.034341e+02 4.610916e+02
[25,] -1.368754e+02 1.034341e+02
[26,] -4.726898e+01 -1.368754e+02
[27,] -7.159900e+02 -4.726898e+01
[28,] -8.213319e+02 -7.159900e+02
[29,] 3.659574e+01 -8.213319e+02
[30,] -1.363549e+02 3.659574e+01
[31,] -3.845533e+02 -1.363549e+02
[32,] 5.001785e+02 -3.845533e+02
[33,] 1.915020e+02 5.001785e+02
[34,] 7.918998e+01 1.915020e+02
[35,] -1.077063e+01 7.918998e+01
[36,] -2.059486e+02 -1.077063e+01
[37,] 3.108744e+02 -2.059486e+02
[38,] 5.439874e+02 3.108744e+02
[39,] -5.125879e+02 5.439874e+02
[40,] -7.719553e+01 -5.125879e+02
[41,] 1.682358e+02 -7.719553e+01
[42,] -2.484024e+02 1.682358e+02
[43,] 9.210999e+01 -2.484024e+02
[44,] -2.304278e+02 9.210999e+01
[45,] -4.720609e+02 -2.304278e+02
[46,] -2.707273e+02 -4.720609e+02
[47,] -1.344997e+02 -2.707273e+02
[48,] -7.512675e+01 -1.344997e+02
[49,] 5.053277e+02 -7.512675e+01
[50,] -5.685993e+01 5.053277e+02
[51,] 6.365088e-03 -5.685993e+01
[52,] -4.092787e+02 6.365088e-03
[53,] -3.924559e+02 -4.092787e+02
[54,] -2.533745e+02 -3.924559e+02
[55,] 1.840640e+02 -2.533745e+02
[56,] -3.489098e+02 1.840640e+02
[57,] -1.145412e+02 -3.489098e+02
[58,] -4.247742e+02 -1.145412e+02
[59,] 6.782842e+02 -4.247742e+02
[60,] 5.177100e+01 6.782842e+02
[61,] 5.398194e+02 5.177100e+01
[62,] -9.725988e+01 5.398194e+02
[63,] -1.731323e+02 -9.725988e+01
[64,] -1.558545e+02 -1.731323e+02
[65,] 8.584602e+00 -1.558545e+02
[66,] 2.696060e+02 8.584602e+00
[67,] 8.203734e+02 2.696060e+02
[68,] -2.357285e+02 8.203734e+02
[69,] -1.143143e+02 -2.357285e+02
[70,] 3.057951e+02 -1.143143e+02
[71,] -1.989459e+02 3.057951e+02
[72,] -1.424872e+02 -1.989459e+02
[73,] 2.898136e+02 -1.424872e+02
[74,] 6.150016e+02 2.898136e+02
[75,] 5.152862e+02 6.150016e+02
[76,] 3.120126e+02 5.152862e+02
[77,] 5.066584e+02 3.120126e+02
[78,] 1.831761e+01 5.066584e+02
[79,] -7.277873e+00 1.831761e+01
[80,] -2.744013e+02 -7.277873e+00
[81,] -4.656551e+02 -2.744013e+02
[82,] -1.169432e+02 -4.656551e+02
[83,] 5.430043e+01 -1.169432e+02
[84,] 1.064241e+02 5.430043e+01
[85,] -1.129447e+02 1.064241e+02
[86,] 1.756433e+02 -1.129447e+02
[87,] -2.503283e+01 1.756433e+02
[88,] -2.007207e+01 -2.503283e+01
[89,] -8.674494e+01 -2.007207e+01
[90,] -3.661573e+01 -8.674494e+01
[91,] 1.569470e+02 -3.661573e+01
[92,] -4.184261e+02 1.569470e+02
[93,] -7.800980e+01 -4.184261e+02
[94,] -7.794719e+00 -7.800980e+01
[95,] -5.735223e+01 -7.794719e+00
[96,] -5.978851e+02 -5.735223e+01
[97,] -6.481625e+01 -5.978851e+02
[98,] 1.900017e+02 -6.481625e+01
[99,] 1.866887e+02 1.900017e+02
[100,] 7.186367e+01 1.866887e+02
[101,] -8.985437e+01 7.186367e+01
[102,] -3.249220e+02 -8.985437e+01
[103,] -1.650641e+02 -3.249220e+02
[104,] -1.922499e+02 -1.650641e+02
[105,] 1.655298e+02 -1.922499e+02
[106,] -2.817348e+02 1.655298e+02
[107,] 1.155491e+02 -2.817348e+02
[108,] -1.177063e+01 1.155491e+02
[109,] -3.815634e+02 -1.177063e+01
[110,] 3.832065e+01 -3.815634e+02
[111,] -2.549945e+02 3.832065e+01
[112,] -7.316888e+01 -2.549945e+02
[113,] -1.819287e+02 -7.316888e+01
[114,] 3.594895e+01 -1.819287e+02
[115,] -1.177063e+01 3.594895e+01
[116,] -6.315239e+02 -1.177063e+01
[117,] -4.300217e+02 -6.315239e+02
[118,] 2.931064e+02 -4.300217e+02
[119,] -2.041245e+02 2.931064e+02
[120,] 3.446869e+02 -2.041245e+02
[121,] -3.585682e+02 3.446869e+02
[122,] -1.865775e+02 -3.585682e+02
[123,] 1.340536e+02 -1.865775e+02
[124,] 3.629702e+01 1.340536e+02
[125,] 1.074443e+01 3.629702e+01
[126,] 7.735852e+01 1.074443e+01
[127,] -1.330365e+02 7.735852e+01
[128,] -8.816078e+01 -1.330365e+02
[129,] 1.145923e+02 -8.816078e+01
[130,] 5.360788e+00 1.145923e+02
[131,] -3.590338e+02 5.360788e+00
[132,] -4.197056e+01 -3.590338e+02
[133,] -8.759624e+01 -4.197056e+01
[134,] -4.690854e+01 -8.759624e+01
[135,] 8.060463e+01 -4.690854e+01
[136,] -1.177063e+01 8.060463e+01
[137,] -1.847972e+02 -1.177063e+01
[138,] 6.475757e+01 -1.847972e+02
[139,] 9.514298e+00 6.475757e+01
[140,] 1.410877e+01 9.514298e+00
[141,] 1.728540e+02 1.410877e+01
[142,] -3.312889e+02 1.728540e+02
[143,] -3.234801e-01 -3.312889e+02
> z <- as.data.frame(dum1)
> z
lag(myerror, k = 1) myerror
1 -3.572122e+02 2.765848e+02
2 1.158161e+02 -3.572122e+02
3 5.605905e+02 1.158161e+02
4 7.909841e+02 5.605905e+02
5 1.451433e+03 7.909841e+02
6 -3.962215e+01 1.451433e+03
7 -3.534710e+02 -3.962215e+01
8 3.053981e+01 -3.534710e+02
9 -2.090043e+02 3.053981e+01
10 2.902945e+02 -2.090043e+02
11 -1.329236e+02 2.902945e+02
12 4.012655e+02 -1.329236e+02
13 6.987458e+02 4.012655e+02
14 -2.585324e+02 6.987458e+02
15 -1.792418e+02 -2.585324e+02
16 -1.933071e+02 -1.792418e+02
17 4.517172e+02 -1.933071e+02
18 8.087419e+02 4.517172e+02
19 1.299893e+02 8.087419e+02
20 2.317925e+02 1.299893e+02
21 -1.564056e+02 2.317925e+02
22 -8.921811e+01 -1.564056e+02
23 4.610916e+02 -8.921811e+01
24 1.034341e+02 4.610916e+02
25 -1.368754e+02 1.034341e+02
26 -4.726898e+01 -1.368754e+02
27 -7.159900e+02 -4.726898e+01
28 -8.213319e+02 -7.159900e+02
29 3.659574e+01 -8.213319e+02
30 -1.363549e+02 3.659574e+01
31 -3.845533e+02 -1.363549e+02
32 5.001785e+02 -3.845533e+02
33 1.915020e+02 5.001785e+02
34 7.918998e+01 1.915020e+02
35 -1.077063e+01 7.918998e+01
36 -2.059486e+02 -1.077063e+01
37 3.108744e+02 -2.059486e+02
38 5.439874e+02 3.108744e+02
39 -5.125879e+02 5.439874e+02
40 -7.719553e+01 -5.125879e+02
41 1.682358e+02 -7.719553e+01
42 -2.484024e+02 1.682358e+02
43 9.210999e+01 -2.484024e+02
44 -2.304278e+02 9.210999e+01
45 -4.720609e+02 -2.304278e+02
46 -2.707273e+02 -4.720609e+02
47 -1.344997e+02 -2.707273e+02
48 -7.512675e+01 -1.344997e+02
49 5.053277e+02 -7.512675e+01
50 -5.685993e+01 5.053277e+02
51 6.365088e-03 -5.685993e+01
52 -4.092787e+02 6.365088e-03
53 -3.924559e+02 -4.092787e+02
54 -2.533745e+02 -3.924559e+02
55 1.840640e+02 -2.533745e+02
56 -3.489098e+02 1.840640e+02
57 -1.145412e+02 -3.489098e+02
58 -4.247742e+02 -1.145412e+02
59 6.782842e+02 -4.247742e+02
60 5.177100e+01 6.782842e+02
61 5.398194e+02 5.177100e+01
62 -9.725988e+01 5.398194e+02
63 -1.731323e+02 -9.725988e+01
64 -1.558545e+02 -1.731323e+02
65 8.584602e+00 -1.558545e+02
66 2.696060e+02 8.584602e+00
67 8.203734e+02 2.696060e+02
68 -2.357285e+02 8.203734e+02
69 -1.143143e+02 -2.357285e+02
70 3.057951e+02 -1.143143e+02
71 -1.989459e+02 3.057951e+02
72 -1.424872e+02 -1.989459e+02
73 2.898136e+02 -1.424872e+02
74 6.150016e+02 2.898136e+02
75 5.152862e+02 6.150016e+02
76 3.120126e+02 5.152862e+02
77 5.066584e+02 3.120126e+02
78 1.831761e+01 5.066584e+02
79 -7.277873e+00 1.831761e+01
80 -2.744013e+02 -7.277873e+00
81 -4.656551e+02 -2.744013e+02
82 -1.169432e+02 -4.656551e+02
83 5.430043e+01 -1.169432e+02
84 1.064241e+02 5.430043e+01
85 -1.129447e+02 1.064241e+02
86 1.756433e+02 -1.129447e+02
87 -2.503283e+01 1.756433e+02
88 -2.007207e+01 -2.503283e+01
89 -8.674494e+01 -2.007207e+01
90 -3.661573e+01 -8.674494e+01
91 1.569470e+02 -3.661573e+01
92 -4.184261e+02 1.569470e+02
93 -7.800980e+01 -4.184261e+02
94 -7.794719e+00 -7.800980e+01
95 -5.735223e+01 -7.794719e+00
96 -5.978851e+02 -5.735223e+01
97 -6.481625e+01 -5.978851e+02
98 1.900017e+02 -6.481625e+01
99 1.866887e+02 1.900017e+02
100 7.186367e+01 1.866887e+02
101 -8.985437e+01 7.186367e+01
102 -3.249220e+02 -8.985437e+01
103 -1.650641e+02 -3.249220e+02
104 -1.922499e+02 -1.650641e+02
105 1.655298e+02 -1.922499e+02
106 -2.817348e+02 1.655298e+02
107 1.155491e+02 -2.817348e+02
108 -1.177063e+01 1.155491e+02
109 -3.815634e+02 -1.177063e+01
110 3.832065e+01 -3.815634e+02
111 -2.549945e+02 3.832065e+01
112 -7.316888e+01 -2.549945e+02
113 -1.819287e+02 -7.316888e+01
114 3.594895e+01 -1.819287e+02
115 -1.177063e+01 3.594895e+01
116 -6.315239e+02 -1.177063e+01
117 -4.300217e+02 -6.315239e+02
118 2.931064e+02 -4.300217e+02
119 -2.041245e+02 2.931064e+02
120 3.446869e+02 -2.041245e+02
121 -3.585682e+02 3.446869e+02
122 -1.865775e+02 -3.585682e+02
123 1.340536e+02 -1.865775e+02
124 3.629702e+01 1.340536e+02
125 1.074443e+01 3.629702e+01
126 7.735852e+01 1.074443e+01
127 -1.330365e+02 7.735852e+01
128 -8.816078e+01 -1.330365e+02
129 1.145923e+02 -8.816078e+01
130 5.360788e+00 1.145923e+02
131 -3.590338e+02 5.360788e+00
132 -4.197056e+01 -3.590338e+02
133 -8.759624e+01 -4.197056e+01
134 -4.690854e+01 -8.759624e+01
135 8.060463e+01 -4.690854e+01
136 -1.177063e+01 8.060463e+01
137 -1.847972e+02 -1.177063e+01
138 6.475757e+01 -1.847972e+02
139 9.514298e+00 6.475757e+01
140 1.410877e+01 9.514298e+00
141 1.728540e+02 1.410877e+01
142 -3.312889e+02 1.728540e+02
143 -3.234801e-01 -3.312889e+02
> 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/7ebxi1323946263.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> acf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/wessaorg/rcomp/tmp/89n641323946263.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> pacf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Partial Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/wessaorg/rcomp/tmp/9x57x1323946263.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> opar <- par(mfrow = c(2,2), oma = c(0, 0, 1.1, 0))
> plot(mylm, las = 1, sub='Residual Diagnostics')
> par(opar)
> dev.off()
null device
1
> if (n > n25) {
+ postscript(file="/var/wessaorg/rcomp/tmp/106jmp1323946263.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
+ plot(kp3:nmkm3,gqarr[,2], main='Goldfeld-Quandt test',ylab='2-sided p-value',xlab='breakpoint')
+ grid()
+ dev.off()
+ }
null device
1
>
> #Note: the /var/wessaorg/rcomp/createtable file can be downloaded at http://www.wessa.net/cretab
> load(file="/var/wessaorg/rcomp/createtable")
>
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a, 'Multiple Linear Regression - Estimated Regression Equation', 1, TRUE)
> a<-table.row.end(a)
> myeq <- colnames(x)[1]
> myeq <- paste(myeq, '[t] = ', sep='')
> for (i in 1:k){
+ if (mysum$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/11xkky1323946263.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/12gaau1323946263.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/13l2mg1323946263.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/14u8791323946263.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/15j4rt1323946263.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/16sxxp1323946263.tab")
+ }
>
> try(system("convert tmp/1u9z21323946263.ps tmp/1u9z21323946263.png",intern=TRUE))
character(0)
> try(system("convert tmp/200co1323946263.ps tmp/200co1323946263.png",intern=TRUE))
character(0)
> try(system("convert tmp/3jdyu1323946263.ps tmp/3jdyu1323946263.png",intern=TRUE))
character(0)
> try(system("convert tmp/40wpc1323946263.ps tmp/40wpc1323946263.png",intern=TRUE))
character(0)
> try(system("convert tmp/5dbss1323946263.ps tmp/5dbss1323946263.png",intern=TRUE))
character(0)
> try(system("convert tmp/6usmr1323946263.ps tmp/6usmr1323946263.png",intern=TRUE))
character(0)
> try(system("convert tmp/7ebxi1323946263.ps tmp/7ebxi1323946263.png",intern=TRUE))
character(0)
> try(system("convert tmp/89n641323946263.ps tmp/89n641323946263.png",intern=TRUE))
character(0)
> try(system("convert tmp/9x57x1323946263.ps tmp/9x57x1323946263.png",intern=TRUE))
character(0)
> try(system("convert tmp/106jmp1323946263.ps tmp/106jmp1323946263.png",intern=TRUE))
character(0)
>
>
> proc.time()
user system elapsed
4.468 0.546 5.023