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(146455
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+ ,dim=c(6
+ ,164)
+ ,dimnames=list(c('Time_in_RFC'
+ ,'Shared_compendiums'
+ ,'Reviewed_compendiums'
+ ,'Long_feedback'
+ ,'Blogs'
+ ,'Characters')
+ ,1:164))
> y <- array(NA,dim=c(6,164),dimnames=list(c('Time_in_RFC','Shared_compendiums','Reviewed_compendiums','Long_feedback','Blogs','Characters'),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'
> library(lattice)
> library(lmtest)
Loading required package: zoo
> n25 <- 25 #minimum number of obs. for Goldfeld-Quandt test
> par1 <- as.numeric(par1)
> x <- t(y)
> k <- length(x[1,])
> n <- length(x[,1])
> x1 <- cbind(x[,par1], x[,1:k!=par1])
> mycolnames <- c(colnames(x)[par1], colnames(x)[1:k!=par1])
> colnames(x1) <- mycolnames #colnames(x)[par1]
> x <- x1
> if (par3 == 'First Differences'){
+ x2 <- array(0, dim=c(n-1,k), dimnames=list(1:(n-1), paste('(1-B)',colnames(x),sep='')))
+ for (i in 1:n-1) {
+ for (j in 1:k) {
+ x2[i,j] <- x[i+1,j] - x[i,j]
+ }
+ }
+ x <- x2
+ }
> if (par2 == 'Include Monthly Dummies'){
+ x2 <- array(0, dim=c(n,11), dimnames=list(1:n, paste('M', seq(1:11), sep ='')))
+ for (i in 1:11){
+ x2[seq(i,n,12),i] <- 1
+ }
+ x <- cbind(x, x2)
+ }
> if (par2 == 'Include Quarterly Dummies'){
+ x2 <- array(0, dim=c(n,3), dimnames=list(1:n, paste('Q', seq(1:3), sep ='')))
+ for (i in 1:3){
+ x2[seq(i,n,4),i] <- 1
+ }
+ x <- cbind(x, x2)
+ }
> k <- length(x[1,])
> if (par3 == 'Linear Trend'){
+ x <- cbind(x, c(1:n))
+ colnames(x)[k+1] <- 't'
+ }
> x
Time_in_RFC Shared_compendiums Reviewed_compendiums Long_feedback Blogs
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3 113337 9 24 37 68
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98 176789 0 23 66 149
99 181379 7 33 123 96
100 228548 7 19 65 198
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142 243551 9 21 57 93
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48 61704
49 117986
50 56733
51 55064
52 5950
53 84607
54 32551
55 31701
56 71170
57 101773
58 101653
59 81493
60 55901
61 109104
62 114425
63 36311
64 70027
65 73713
66 40671
67 89041
68 57231
69 78792
70 59155
71 55827
72 22618
73 58425
74 65724
75 56979
76 72369
77 79194
78 202316
79 44970
80 49319
81 36252
82 75741
83 38417
84 64102
85 56622
86 15430
87 72571
88 67271
89 43460
90 99501
91 28340
92 76013
93 37361
94 48204
95 76168
96 85168
97 125410
98 123328
99 83038
100 120087
101 91939
102 103646
103 29467
104 43750
105 34497
106 66477
107 71181
108 74482
109 174949
110 46765
111 90257
112 51370
113 1168
114 51360
115 25162
116 21067
117 58233
118 855
119 85903
120 14116
121 57637
122 94137
123 62147
124 62832
125 8773
126 63785
127 65196
128 73087
129 72631
130 86281
131 162365
132 56530
133 35606
134 70111
135 92046
136 63989
137 104911
138 43448
139 60029
140 38650
141 47261
142 73586
143 83042
144 37238
145 63958
146 78956
147 99518
148 111436
149 0
150 6023
151 0
152 0
153 0
154 0
155 42564
156 38885
157 0
158 0
159 1644
160 6179
161 3926
162 23238
163 0
164 49288
> k <- length(x[1,])
> df <- as.data.frame(x)
> (mylm <- lm(df))
Call:
lm(formula = df)
Coefficients:
(Intercept) Shared_compendiums Reviewed_compendiums
8265.6905 66.6081 2023.2066
Long_feedback Blogs Characters
261.8964 708.7474 0.1391
> (mysum <- summary(mylm))
Call:
lm(formula = df)
Residuals:
Min 1Q Median 3Q Max
-80876 -23464 -4364 19547 148669
Coefficients:
Estimate Std. Error t value Pr(>|t|)
(Intercept) 8265.6905 8519.6487 0.970 0.3334
Shared_compendiums 66.6081 1221.1335 0.055 0.9566
Reviewed_compendiums 2023.2066 858.5866 2.356 0.0197 *
Long_feedback 261.8964 235.4644 1.112 0.2677
Blogs 708.7474 107.2493 6.608 5.65e-10 ***
Characters 0.1391 0.1365 1.019 0.3099
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
Residual standard error: 38130 on 158 degrees of freedom
Multiple R-squared: 0.6554, Adjusted R-squared: 0.6445
F-statistic: 60.09 on 5 and 158 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,] 0.9895451 2.090976e-02 1.045488e-02
[2,] 0.9797638 4.047230e-02 2.023615e-02
[3,] 0.9629378 7.412447e-02 3.706223e-02
[4,] 0.9374259 1.251482e-01 6.257412e-02
[5,] 0.9151328 1.697344e-01 8.486719e-02
[6,] 0.8701897 2.596206e-01 1.298103e-01
[7,] 0.8188542 3.622917e-01 1.811458e-01
[8,] 0.7584936 4.830128e-01 2.415064e-01
[9,] 0.7049062 5.901876e-01 2.950938e-01
[10,] 0.7046154 5.907692e-01 2.953846e-01
[11,] 0.8289954 3.420093e-01 1.710046e-01
[12,] 0.7785273 4.429454e-01 2.214727e-01
[13,] 0.7583867 4.832266e-01 2.416133e-01
[14,] 0.9684782 6.304355e-02 3.152177e-02
[15,] 0.9584935 8.301301e-02 4.150650e-02
[16,] 0.9665532 6.689367e-02 3.344684e-02
[17,] 0.9653611 6.927787e-02 3.463894e-02
[18,] 0.9510036 9.799281e-02 4.899640e-02
[19,] 0.9450648 1.098703e-01 5.493517e-02
[20,] 0.9256592 1.486816e-01 7.434082e-02
[21,] 0.9027951 1.944098e-01 9.720491e-02
[22,] 0.8778105 2.443790e-01 1.221895e-01
[23,] 0.8602367 2.795266e-01 1.397633e-01
[24,] 0.8538699 2.922603e-01 1.461301e-01
[25,] 0.8254131 3.491738e-01 1.745869e-01
[26,] 0.7921841 4.156317e-01 2.078159e-01
[27,] 0.7696082 4.607837e-01 2.303918e-01
[28,] 0.7762872 4.474256e-01 2.237128e-01
[29,] 0.8768825 2.462350e-01 1.231175e-01
[30,] 0.8472554 3.054892e-01 1.527446e-01
[31,] 0.8269861 3.460277e-01 1.730139e-01
[32,] 0.8369499 3.261002e-01 1.630501e-01
[33,] 0.9295214 1.409572e-01 7.047862e-02
[34,] 0.9144836 1.710329e-01 8.551644e-02
[35,] 0.8926751 2.146498e-01 1.073249e-01
[36,] 0.8734682 2.530635e-01 1.265318e-01
[37,] 0.8445110 3.109781e-01 1.554890e-01
[38,] 0.9936679 1.266413e-02 6.332067e-03
[39,] 0.9916738 1.665241e-02 8.326207e-03
[40,] 0.9899345 2.013091e-02 1.006545e-02
[41,] 0.9872437 2.551261e-02 1.275630e-02
[42,] 0.9857808 2.843838e-02 1.421919e-02
[43,] 0.9825614 3.487728e-02 1.743864e-02
[44,] 0.9765746 4.685073e-02 2.342536e-02
[45,] 0.9807932 3.841356e-02 1.920678e-02
[46,] 0.9751412 4.971759e-02 2.485880e-02
[47,] 0.9708037 5.839266e-02 2.919633e-02
[48,] 0.9658607 6.827865e-02 3.413932e-02
[49,] 0.9588164 8.236730e-02 4.118365e-02
[50,] 0.9591350 8.172992e-02 4.086496e-02
[51,] 0.9493164 1.013672e-01 5.068360e-02
[52,] 0.9449315 1.101370e-01 5.506852e-02
[53,] 0.9471023 1.057954e-01 5.289770e-02
[54,] 0.9356724 1.286552e-01 6.432759e-02
[55,] 0.9229216 1.541568e-01 7.707841e-02
[56,] 0.9118163 1.763673e-01 8.818366e-02
[57,] 0.8958532 2.082936e-01 1.041468e-01
[58,] 0.8732778 2.534443e-01 1.267222e-01
[59,] 0.8814015 2.371970e-01 1.185985e-01
[60,] 0.8592559 2.814882e-01 1.407441e-01
[61,] 0.8503204 2.993592e-01 1.496796e-01
[62,] 0.8438036 3.123927e-01 1.561964e-01
[63,] 0.8256226 3.487549e-01 1.743774e-01
[64,] 0.8023128 3.953745e-01 1.976872e-01
[65,] 0.7752160 4.495680e-01 2.247840e-01
[66,] 0.7425204 5.149593e-01 2.574796e-01
[67,] 0.7809034 4.381932e-01 2.190966e-01
[68,] 0.7624219 4.751561e-01 2.375781e-01
[69,] 0.7602362 4.795276e-01 2.397638e-01
[70,] 0.8154662 3.690676e-01 1.845338e-01
[71,] 0.8317920 3.364159e-01 1.682080e-01
[72,] 0.8051438 3.897124e-01 1.948562e-01
[73,] 0.7720307 4.559385e-01 2.279693e-01
[74,] 0.9243657 1.512686e-01 7.563430e-02
[75,] 0.9167514 1.664972e-01 8.324861e-02
[76,] 0.9251220 1.497559e-01 7.487797e-02
[77,] 0.9083636 1.832728e-01 9.163639e-02
[78,] 0.8898351 2.203297e-01 1.101649e-01
[79,] 0.9214079 1.571843e-01 7.859213e-02
[80,] 0.9704219 5.915615e-02 2.957808e-02
[81,] 0.9750972 4.980557e-02 2.490279e-02
[82,] 0.9894868 2.102641e-02 1.051321e-02
[83,] 0.9867552 2.648968e-02 1.324484e-02
[84,] 0.9898240 2.035203e-02 1.017601e-02
[85,] 0.9865822 2.683560e-02 1.341780e-02
[86,] 0.9836574 3.268522e-02 1.634261e-02
[87,] 0.9819515 3.609695e-02 1.804848e-02
[88,] 0.9766141 4.677189e-02 2.338595e-02
[89,] 0.9788116 4.237677e-02 2.118838e-02
[90,] 0.9735611 5.287776e-02 2.643888e-02
[91,] 0.9667239 6.655227e-02 3.327613e-02
[92,] 0.9618007 7.639869e-02 3.819935e-02
[93,] 0.9506235 9.875305e-02 4.937653e-02
[94,] 0.9455599 1.088803e-01 5.444014e-02
[95,] 0.9483074 1.033852e-01 5.169258e-02
[96,] 0.9715657 5.686853e-02 2.843426e-02
[97,] 0.9671808 6.563844e-02 3.281922e-02
[98,] 0.9771602 4.567965e-02 2.283983e-02
[99,] 0.9701113 5.977739e-02 2.988869e-02
[100,] 0.9631068 7.378649e-02 3.689324e-02
[101,] 0.9626260 7.474792e-02 3.737396e-02
[102,] 0.9532179 9.356426e-02 4.678213e-02
[103,] 0.9411517 1.176966e-01 5.884830e-02
[104,] 0.9267023 1.465954e-01 7.329768e-02
[105,] 0.9073754 1.852492e-01 9.262459e-02
[106,] 0.8874684 2.250632e-01 1.125316e-01
[107,] 0.8612166 2.775669e-01 1.387834e-01
[108,] 0.8499203 3.001595e-01 1.500797e-01
[109,] 0.8294164 3.411671e-01 1.705836e-01
[110,] 0.7966924 4.066151e-01 2.033076e-01
[111,] 0.8296461 3.407077e-01 1.703539e-01
[112,] 0.8057739 3.884522e-01 1.942261e-01
[113,] 0.7984207 4.031585e-01 2.015793e-01
[114,] 0.7745999 4.508002e-01 2.254001e-01
[115,] 0.7470613 5.058774e-01 2.529387e-01
[116,] 0.7268652 5.462696e-01 2.731348e-01
[117,] 0.6782637 6.434726e-01 3.217363e-01
[118,] 0.6416829 7.166341e-01 3.583171e-01
[119,] 0.5880810 8.238380e-01 4.119190e-01
[120,] 0.6544438 6.911124e-01 3.455562e-01
[121,] 0.6836672 6.326655e-01 3.163328e-01
[122,] 0.6284012 7.431976e-01 3.715988e-01
[123,] 0.5711443 8.577115e-01 4.288557e-01
[124,] 0.5165403 9.669193e-01 4.834597e-01
[125,] 0.4566326 9.132653e-01 5.433674e-01
[126,] 0.4309903 8.619805e-01 5.690097e-01
[127,] 0.4700241 9.400482e-01 5.299759e-01
[128,] 0.5016417 9.967167e-01 4.983583e-01
[129,] 0.6485347 7.029306e-01 3.514653e-01
[130,] 0.6497618 7.004763e-01 3.502382e-01
[131,] 0.6140599 7.718802e-01 3.859401e-01
[132,] 0.5715098 8.569805e-01 4.284902e-01
[133,] 0.5072893 9.854215e-01 4.927107e-01
[134,] 0.8436918 3.126164e-01 1.563082e-01
[135,] 0.8312589 3.374821e-01 1.687411e-01
[136,] 0.9998832 2.335178e-04 1.167589e-04
[137,] 0.9999979 4.154530e-06 2.077265e-06
[138,] 0.9999946 1.081830e-05 5.409151e-06
[139,] 0.9999915 1.700628e-05 8.503140e-06
[140,] 0.9999995 9.173266e-07 4.586633e-07
[141,] 0.9999991 1.720362e-06 8.601808e-07
[142,] 0.9999947 1.061820e-05 5.309098e-06
[143,] 0.9999699 6.016695e-05 3.008347e-05
[144,] 0.9998360 3.280312e-04 1.640156e-04
[145,] 0.9999936 1.281108e-05 6.405540e-06
[146,] 0.9999084 1.831179e-04 9.155895e-05
[147,] 0.9997353 5.293953e-04 2.646976e-04
> postscript(file="/var/wessaorg/rcomp/tmp/13bvq1321542795.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/2uc5c1321542795.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> plot(mysum$resid, type='b', pch=19, main='Residuals', ylab='value of Residuals', xlab='time or index')
> grid()
> dev.off()
null device
1
> postscript(file="/var/wessaorg/rcomp/tmp/3zobm1321542795.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> hist(mysum$resid, main='Residual Histogram', xlab='values of Residuals')
> grid()
> dev.off()
null device
1
> postscript(file="/var/wessaorg/rcomp/tmp/4cwgb1321542795.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> densityplot(~mysum$resid,col='black',main='Residual Density Plot', xlab='values of Residuals')
> dev.off()
null device
1
> postscript(file="/var/wessaorg/rcomp/tmp/55af61321542795.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> qqnorm(mysum$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
-28205.978368 -53575.975092 -10734.103649 -28203.332368 -12632.633164
6 7 8 9 10
-49816.606099 128260.416678 -24410.766540 -13726.683262 15932.906438
11 12 13 14 15
-3370.045810 -48240.115407 -18597.640352 170.916427 -593.619167
16 17 18 19 20
28581.112889 -10862.818686 56745.205953 -43326.269719 -28314.272577
21 22 23 24 25
-10527.592703 112650.526785 3835.427347 -67833.840142 -30399.440127
26 27 28 29 30
2129.846585 27214.002113 -2323.270518 -378.591086 20926.110805
31 32 33 34 35
20499.372699 -40978.721163 17743.147738 -22915.103562 37187.677200
36 37 38 39 40
45371.965316 85466.190062 4922.152679 21691.737367 44977.994262
41 42 43 44 45
66997.897872 -23361.619032 3531.592198 -23771.303241 2125.131416
46 47 48 49 50
148668.697556 -18965.082577 -21764.157378 29919.607473 -36003.536771
51 52 53 54 55
-15211.264317 207.476348 46102.307462 -15373.876447 21286.844687
56 57 58 59 60
29228.805500 -12389.705781 -40668.409716 -4430.810792 20596.026237
61 62 63 64 65
49755.733250 19229.706589 10811.525455 23291.147701 -5366.322956
66 67 68 69 70
-3.805391 -32629.692444 -12502.946558 -31685.136258 -35310.308616
71 72 73 74 75
-19361.645667 -17022.240961 -15481.290038 -2988.376826 -55745.847568
76 77 78 79 80
27951.116888 38171.437780 -30073.951662 -47615.531952 -11612.614197
81 82 83 84 85
3218.025406 101842.902590 26171.548507 -43604.849328 448.362634
86 87 88 89 90
11495.278673 -59640.420440 81817.935057 43729.615884 -74050.868702
91 92 93 94 95
14335.294200 -46944.191320 -9615.056132 21970.602822 32397.973981
96 97 98 99 100
-5936.788519 -42154.706143 -18050.889492 -5920.334193 7318.700408
101 102 103 104 105
44.027528 -28349.885145 22066.435906 -61260.599183 27731.542051
106 107 108 109 110
-53561.106466 -1597.746573 15142.773113 -47923.039421 -21820.332913
111 112 113 114 115
17663.795659 -17911.805129 4690.441370 -16477.175962 -131.635895
116 117 118 119 120
-39408.410995 31845.058614 9834.410265 53462.989082 -24998.750866
121 122 123 124 125
33892.105202 -18094.488213 -24353.387373 -30618.842955 -4297.236256
126 127 128 129 130
-25909.325749 -10037.175447 -59422.205570 51539.526670 -792.426949
131 132 133 134 135
-1244.156816 7468.844470 -14060.266504 32263.317558 53907.471494
136 137 138 139 140
-30118.142164 54202.490534 -28578.956190 2426.764874 -31463.247861
141 142 143 144 145
7944.278771 101122.874736 -53265.065654 86069.118018 28256.206685
146 147 148 149 150
-80876.218257 -14505.983034 -39679.027927 -8865.163215 2040.919633
151 152 153 154 155
-8167.690543 -7810.690543 -8332.298618 -8265.690543 4012.527536
156 157 158 159 160
7221.684806 -8265.690543 -8062.690543 -5547.815200 14800.559027
161 162 163 164
3538.264049 -5340.524358 -7296.690543 11820.155527
> postscript(file="/var/wessaorg/rcomp/tmp/6fiq31321542795.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 -28205.978368 NA
1 -53575.975092 -28205.978368
2 -10734.103649 -53575.975092
3 -28203.332368 -10734.103649
4 -12632.633164 -28203.332368
5 -49816.606099 -12632.633164
6 128260.416678 -49816.606099
7 -24410.766540 128260.416678
8 -13726.683262 -24410.766540
9 15932.906438 -13726.683262
10 -3370.045810 15932.906438
11 -48240.115407 -3370.045810
12 -18597.640352 -48240.115407
13 170.916427 -18597.640352
14 -593.619167 170.916427
15 28581.112889 -593.619167
16 -10862.818686 28581.112889
17 56745.205953 -10862.818686
18 -43326.269719 56745.205953
19 -28314.272577 -43326.269719
20 -10527.592703 -28314.272577
21 112650.526785 -10527.592703
22 3835.427347 112650.526785
23 -67833.840142 3835.427347
24 -30399.440127 -67833.840142
25 2129.846585 -30399.440127
26 27214.002113 2129.846585
27 -2323.270518 27214.002113
28 -378.591086 -2323.270518
29 20926.110805 -378.591086
30 20499.372699 20926.110805
31 -40978.721163 20499.372699
32 17743.147738 -40978.721163
33 -22915.103562 17743.147738
34 37187.677200 -22915.103562
35 45371.965316 37187.677200
36 85466.190062 45371.965316
37 4922.152679 85466.190062
38 21691.737367 4922.152679
39 44977.994262 21691.737367
40 66997.897872 44977.994262
41 -23361.619032 66997.897872
42 3531.592198 -23361.619032
43 -23771.303241 3531.592198
44 2125.131416 -23771.303241
45 148668.697556 2125.131416
46 -18965.082577 148668.697556
47 -21764.157378 -18965.082577
48 29919.607473 -21764.157378
49 -36003.536771 29919.607473
50 -15211.264317 -36003.536771
51 207.476348 -15211.264317
52 46102.307462 207.476348
53 -15373.876447 46102.307462
54 21286.844687 -15373.876447
55 29228.805500 21286.844687
56 -12389.705781 29228.805500
57 -40668.409716 -12389.705781
58 -4430.810792 -40668.409716
59 20596.026237 -4430.810792
60 49755.733250 20596.026237
61 19229.706589 49755.733250
62 10811.525455 19229.706589
63 23291.147701 10811.525455
64 -5366.322956 23291.147701
65 -3.805391 -5366.322956
66 -32629.692444 -3.805391
67 -12502.946558 -32629.692444
68 -31685.136258 -12502.946558
69 -35310.308616 -31685.136258
70 -19361.645667 -35310.308616
71 -17022.240961 -19361.645667
72 -15481.290038 -17022.240961
73 -2988.376826 -15481.290038
74 -55745.847568 -2988.376826
75 27951.116888 -55745.847568
76 38171.437780 27951.116888
77 -30073.951662 38171.437780
78 -47615.531952 -30073.951662
79 -11612.614197 -47615.531952
80 3218.025406 -11612.614197
81 101842.902590 3218.025406
82 26171.548507 101842.902590
83 -43604.849328 26171.548507
84 448.362634 -43604.849328
85 11495.278673 448.362634
86 -59640.420440 11495.278673
87 81817.935057 -59640.420440
88 43729.615884 81817.935057
89 -74050.868702 43729.615884
90 14335.294200 -74050.868702
91 -46944.191320 14335.294200
92 -9615.056132 -46944.191320
93 21970.602822 -9615.056132
94 32397.973981 21970.602822
95 -5936.788519 32397.973981
96 -42154.706143 -5936.788519
97 -18050.889492 -42154.706143
98 -5920.334193 -18050.889492
99 7318.700408 -5920.334193
100 44.027528 7318.700408
101 -28349.885145 44.027528
102 22066.435906 -28349.885145
103 -61260.599183 22066.435906
104 27731.542051 -61260.599183
105 -53561.106466 27731.542051
106 -1597.746573 -53561.106466
107 15142.773113 -1597.746573
108 -47923.039421 15142.773113
109 -21820.332913 -47923.039421
110 17663.795659 -21820.332913
111 -17911.805129 17663.795659
112 4690.441370 -17911.805129
113 -16477.175962 4690.441370
114 -131.635895 -16477.175962
115 -39408.410995 -131.635895
116 31845.058614 -39408.410995
117 9834.410265 31845.058614
118 53462.989082 9834.410265
119 -24998.750866 53462.989082
120 33892.105202 -24998.750866
121 -18094.488213 33892.105202
122 -24353.387373 -18094.488213
123 -30618.842955 -24353.387373
124 -4297.236256 -30618.842955
125 -25909.325749 -4297.236256
126 -10037.175447 -25909.325749
127 -59422.205570 -10037.175447
128 51539.526670 -59422.205570
129 -792.426949 51539.526670
130 -1244.156816 -792.426949
131 7468.844470 -1244.156816
132 -14060.266504 7468.844470
133 32263.317558 -14060.266504
134 53907.471494 32263.317558
135 -30118.142164 53907.471494
136 54202.490534 -30118.142164
137 -28578.956190 54202.490534
138 2426.764874 -28578.956190
139 -31463.247861 2426.764874
140 7944.278771 -31463.247861
141 101122.874736 7944.278771
142 -53265.065654 101122.874736
143 86069.118018 -53265.065654
144 28256.206685 86069.118018
145 -80876.218257 28256.206685
146 -14505.983034 -80876.218257
147 -39679.027927 -14505.983034
148 -8865.163215 -39679.027927
149 2040.919633 -8865.163215
150 -8167.690543 2040.919633
151 -7810.690543 -8167.690543
152 -8332.298618 -7810.690543
153 -8265.690543 -8332.298618
154 4012.527536 -8265.690543
155 7221.684806 4012.527536
156 -8265.690543 7221.684806
157 -8062.690543 -8265.690543
158 -5547.815200 -8062.690543
159 14800.559027 -5547.815200
160 3538.264049 14800.559027
161 -5340.524358 3538.264049
162 -7296.690543 -5340.524358
163 11820.155527 -7296.690543
164 NA 11820.155527
> dum1 <- dum[2:length(myerror),]
> dum1
lag(myerror, k = 1) myerror
[1,] -53575.975092 -28205.978368
[2,] -10734.103649 -53575.975092
[3,] -28203.332368 -10734.103649
[4,] -12632.633164 -28203.332368
[5,] -49816.606099 -12632.633164
[6,] 128260.416678 -49816.606099
[7,] -24410.766540 128260.416678
[8,] -13726.683262 -24410.766540
[9,] 15932.906438 -13726.683262
[10,] -3370.045810 15932.906438
[11,] -48240.115407 -3370.045810
[12,] -18597.640352 -48240.115407
[13,] 170.916427 -18597.640352
[14,] -593.619167 170.916427
[15,] 28581.112889 -593.619167
[16,] -10862.818686 28581.112889
[17,] 56745.205953 -10862.818686
[18,] -43326.269719 56745.205953
[19,] -28314.272577 -43326.269719
[20,] -10527.592703 -28314.272577
[21,] 112650.526785 -10527.592703
[22,] 3835.427347 112650.526785
[23,] -67833.840142 3835.427347
[24,] -30399.440127 -67833.840142
[25,] 2129.846585 -30399.440127
[26,] 27214.002113 2129.846585
[27,] -2323.270518 27214.002113
[28,] -378.591086 -2323.270518
[29,] 20926.110805 -378.591086
[30,] 20499.372699 20926.110805
[31,] -40978.721163 20499.372699
[32,] 17743.147738 -40978.721163
[33,] -22915.103562 17743.147738
[34,] 37187.677200 -22915.103562
[35,] 45371.965316 37187.677200
[36,] 85466.190062 45371.965316
[37,] 4922.152679 85466.190062
[38,] 21691.737367 4922.152679
[39,] 44977.994262 21691.737367
[40,] 66997.897872 44977.994262
[41,] -23361.619032 66997.897872
[42,] 3531.592198 -23361.619032
[43,] -23771.303241 3531.592198
[44,] 2125.131416 -23771.303241
[45,] 148668.697556 2125.131416
[46,] -18965.082577 148668.697556
[47,] -21764.157378 -18965.082577
[48,] 29919.607473 -21764.157378
[49,] -36003.536771 29919.607473
[50,] -15211.264317 -36003.536771
[51,] 207.476348 -15211.264317
[52,] 46102.307462 207.476348
[53,] -15373.876447 46102.307462
[54,] 21286.844687 -15373.876447
[55,] 29228.805500 21286.844687
[56,] -12389.705781 29228.805500
[57,] -40668.409716 -12389.705781
[58,] -4430.810792 -40668.409716
[59,] 20596.026237 -4430.810792
[60,] 49755.733250 20596.026237
[61,] 19229.706589 49755.733250
[62,] 10811.525455 19229.706589
[63,] 23291.147701 10811.525455
[64,] -5366.322956 23291.147701
[65,] -3.805391 -5366.322956
[66,] -32629.692444 -3.805391
[67,] -12502.946558 -32629.692444
[68,] -31685.136258 -12502.946558
[69,] -35310.308616 -31685.136258
[70,] -19361.645667 -35310.308616
[71,] -17022.240961 -19361.645667
[72,] -15481.290038 -17022.240961
[73,] -2988.376826 -15481.290038
[74,] -55745.847568 -2988.376826
[75,] 27951.116888 -55745.847568
[76,] 38171.437780 27951.116888
[77,] -30073.951662 38171.437780
[78,] -47615.531952 -30073.951662
[79,] -11612.614197 -47615.531952
[80,] 3218.025406 -11612.614197
[81,] 101842.902590 3218.025406
[82,] 26171.548507 101842.902590
[83,] -43604.849328 26171.548507
[84,] 448.362634 -43604.849328
[85,] 11495.278673 448.362634
[86,] -59640.420440 11495.278673
[87,] 81817.935057 -59640.420440
[88,] 43729.615884 81817.935057
[89,] -74050.868702 43729.615884
[90,] 14335.294200 -74050.868702
[91,] -46944.191320 14335.294200
[92,] -9615.056132 -46944.191320
[93,] 21970.602822 -9615.056132
[94,] 32397.973981 21970.602822
[95,] -5936.788519 32397.973981
[96,] -42154.706143 -5936.788519
[97,] -18050.889492 -42154.706143
[98,] -5920.334193 -18050.889492
[99,] 7318.700408 -5920.334193
[100,] 44.027528 7318.700408
[101,] -28349.885145 44.027528
[102,] 22066.435906 -28349.885145
[103,] -61260.599183 22066.435906
[104,] 27731.542051 -61260.599183
[105,] -53561.106466 27731.542051
[106,] -1597.746573 -53561.106466
[107,] 15142.773113 -1597.746573
[108,] -47923.039421 15142.773113
[109,] -21820.332913 -47923.039421
[110,] 17663.795659 -21820.332913
[111,] -17911.805129 17663.795659
[112,] 4690.441370 -17911.805129
[113,] -16477.175962 4690.441370
[114,] -131.635895 -16477.175962
[115,] -39408.410995 -131.635895
[116,] 31845.058614 -39408.410995
[117,] 9834.410265 31845.058614
[118,] 53462.989082 9834.410265
[119,] -24998.750866 53462.989082
[120,] 33892.105202 -24998.750866
[121,] -18094.488213 33892.105202
[122,] -24353.387373 -18094.488213
[123,] -30618.842955 -24353.387373
[124,] -4297.236256 -30618.842955
[125,] -25909.325749 -4297.236256
[126,] -10037.175447 -25909.325749
[127,] -59422.205570 -10037.175447
[128,] 51539.526670 -59422.205570
[129,] -792.426949 51539.526670
[130,] -1244.156816 -792.426949
[131,] 7468.844470 -1244.156816
[132,] -14060.266504 7468.844470
[133,] 32263.317558 -14060.266504
[134,] 53907.471494 32263.317558
[135,] -30118.142164 53907.471494
[136,] 54202.490534 -30118.142164
[137,] -28578.956190 54202.490534
[138,] 2426.764874 -28578.956190
[139,] -31463.247861 2426.764874
[140,] 7944.278771 -31463.247861
[141,] 101122.874736 7944.278771
[142,] -53265.065654 101122.874736
[143,] 86069.118018 -53265.065654
[144,] 28256.206685 86069.118018
[145,] -80876.218257 28256.206685
[146,] -14505.983034 -80876.218257
[147,] -39679.027927 -14505.983034
[148,] -8865.163215 -39679.027927
[149,] 2040.919633 -8865.163215
[150,] -8167.690543 2040.919633
[151,] -7810.690543 -8167.690543
[152,] -8332.298618 -7810.690543
[153,] -8265.690543 -8332.298618
[154,] 4012.527536 -8265.690543
[155,] 7221.684806 4012.527536
[156,] -8265.690543 7221.684806
[157,] -8062.690543 -8265.690543
[158,] -5547.815200 -8062.690543
[159,] 14800.559027 -5547.815200
[160,] 3538.264049 14800.559027
[161,] -5340.524358 3538.264049
[162,] -7296.690543 -5340.524358
[163,] 11820.155527 -7296.690543
> z <- as.data.frame(dum1)
> z
lag(myerror, k = 1) myerror
1 -53575.975092 -28205.978368
2 -10734.103649 -53575.975092
3 -28203.332368 -10734.103649
4 -12632.633164 -28203.332368
5 -49816.606099 -12632.633164
6 128260.416678 -49816.606099
7 -24410.766540 128260.416678
8 -13726.683262 -24410.766540
9 15932.906438 -13726.683262
10 -3370.045810 15932.906438
11 -48240.115407 -3370.045810
12 -18597.640352 -48240.115407
13 170.916427 -18597.640352
14 -593.619167 170.916427
15 28581.112889 -593.619167
16 -10862.818686 28581.112889
17 56745.205953 -10862.818686
18 -43326.269719 56745.205953
19 -28314.272577 -43326.269719
20 -10527.592703 -28314.272577
21 112650.526785 -10527.592703
22 3835.427347 112650.526785
23 -67833.840142 3835.427347
24 -30399.440127 -67833.840142
25 2129.846585 -30399.440127
26 27214.002113 2129.846585
27 -2323.270518 27214.002113
28 -378.591086 -2323.270518
29 20926.110805 -378.591086
30 20499.372699 20926.110805
31 -40978.721163 20499.372699
32 17743.147738 -40978.721163
33 -22915.103562 17743.147738
34 37187.677200 -22915.103562
35 45371.965316 37187.677200
36 85466.190062 45371.965316
37 4922.152679 85466.190062
38 21691.737367 4922.152679
39 44977.994262 21691.737367
40 66997.897872 44977.994262
41 -23361.619032 66997.897872
42 3531.592198 -23361.619032
43 -23771.303241 3531.592198
44 2125.131416 -23771.303241
45 148668.697556 2125.131416
46 -18965.082577 148668.697556
47 -21764.157378 -18965.082577
48 29919.607473 -21764.157378
49 -36003.536771 29919.607473
50 -15211.264317 -36003.536771
51 207.476348 -15211.264317
52 46102.307462 207.476348
53 -15373.876447 46102.307462
54 21286.844687 -15373.876447
55 29228.805500 21286.844687
56 -12389.705781 29228.805500
57 -40668.409716 -12389.705781
58 -4430.810792 -40668.409716
59 20596.026237 -4430.810792
60 49755.733250 20596.026237
61 19229.706589 49755.733250
62 10811.525455 19229.706589
63 23291.147701 10811.525455
64 -5366.322956 23291.147701
65 -3.805391 -5366.322956
66 -32629.692444 -3.805391
67 -12502.946558 -32629.692444
68 -31685.136258 -12502.946558
69 -35310.308616 -31685.136258
70 -19361.645667 -35310.308616
71 -17022.240961 -19361.645667
72 -15481.290038 -17022.240961
73 -2988.376826 -15481.290038
74 -55745.847568 -2988.376826
75 27951.116888 -55745.847568
76 38171.437780 27951.116888
77 -30073.951662 38171.437780
78 -47615.531952 -30073.951662
79 -11612.614197 -47615.531952
80 3218.025406 -11612.614197
81 101842.902590 3218.025406
82 26171.548507 101842.902590
83 -43604.849328 26171.548507
84 448.362634 -43604.849328
85 11495.278673 448.362634
86 -59640.420440 11495.278673
87 81817.935057 -59640.420440
88 43729.615884 81817.935057
89 -74050.868702 43729.615884
90 14335.294200 -74050.868702
91 -46944.191320 14335.294200
92 -9615.056132 -46944.191320
93 21970.602822 -9615.056132
94 32397.973981 21970.602822
95 -5936.788519 32397.973981
96 -42154.706143 -5936.788519
97 -18050.889492 -42154.706143
98 -5920.334193 -18050.889492
99 7318.700408 -5920.334193
100 44.027528 7318.700408
101 -28349.885145 44.027528
102 22066.435906 -28349.885145
103 -61260.599183 22066.435906
104 27731.542051 -61260.599183
105 -53561.106466 27731.542051
106 -1597.746573 -53561.106466
107 15142.773113 -1597.746573
108 -47923.039421 15142.773113
109 -21820.332913 -47923.039421
110 17663.795659 -21820.332913
111 -17911.805129 17663.795659
112 4690.441370 -17911.805129
113 -16477.175962 4690.441370
114 -131.635895 -16477.175962
115 -39408.410995 -131.635895
116 31845.058614 -39408.410995
117 9834.410265 31845.058614
118 53462.989082 9834.410265
119 -24998.750866 53462.989082
120 33892.105202 -24998.750866
121 -18094.488213 33892.105202
122 -24353.387373 -18094.488213
123 -30618.842955 -24353.387373
124 -4297.236256 -30618.842955
125 -25909.325749 -4297.236256
126 -10037.175447 -25909.325749
127 -59422.205570 -10037.175447
128 51539.526670 -59422.205570
129 -792.426949 51539.526670
130 -1244.156816 -792.426949
131 7468.844470 -1244.156816
132 -14060.266504 7468.844470
133 32263.317558 -14060.266504
134 53907.471494 32263.317558
135 -30118.142164 53907.471494
136 54202.490534 -30118.142164
137 -28578.956190 54202.490534
138 2426.764874 -28578.956190
139 -31463.247861 2426.764874
140 7944.278771 -31463.247861
141 101122.874736 7944.278771
142 -53265.065654 101122.874736
143 86069.118018 -53265.065654
144 28256.206685 86069.118018
145 -80876.218257 28256.206685
146 -14505.983034 -80876.218257
147 -39679.027927 -14505.983034
148 -8865.163215 -39679.027927
149 2040.919633 -8865.163215
150 -8167.690543 2040.919633
151 -7810.690543 -8167.690543
152 -8332.298618 -7810.690543
153 -8265.690543 -8332.298618
154 4012.527536 -8265.690543
155 7221.684806 4012.527536
156 -8265.690543 7221.684806
157 -8062.690543 -8265.690543
158 -5547.815200 -8062.690543
159 14800.559027 -5547.815200
160 3538.264049 14800.559027
161 -5340.524358 3538.264049
162 -7296.690543 -5340.524358
163 11820.155527 -7296.690543
> 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/70fpy1321542795.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/80u931321542795.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/955tz1321542795.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/10hzbg1321542795.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$coefficients)[i] != 't') myeq <- paste(myeq, '[t]', sep='')
+ }
+ }
> myeq <- paste(myeq, ' + e[t]')
> a<-table.row.start(a)
> a<-table.element(a, myeq)
> a<-table.row.end(a)
> a<-table.end(a)
> table.save(a,file="/var/wessaorg/rcomp/tmp/11nn301321542795.tab")
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a,hyperlink('http://www.xycoon.com/ols1.htm','Multiple Linear Regression - Ordinary Least Squares',''), 6, TRUE)
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a,'Variable',header=TRUE)
> a<-table.element(a,'Parameter',header=TRUE)
> a<-table.element(a,'S.D.',header=TRUE)
> a<-table.element(a,'T-STAT
H0: parameter = 0',header=TRUE)
> a<-table.element(a,'2-tail p-value',header=TRUE)
> a<-table.element(a,'1-tail p-value',header=TRUE)
> a<-table.row.end(a)
> for (i in 1:k){
+ a<-table.row.start(a)
+ a<-table.element(a,rownames(mysum$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$coefficients[i,4]/2,6))
+ a<-table.row.end(a)
+ }
> a<-table.end(a)
> table.save(a,file="/var/wessaorg/rcomp/tmp/12jkbo1321542795.tab")
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a, 'Multiple Linear Regression - Regression Statistics', 2, TRUE)
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a, 'Multiple R',1,TRUE)
> a<-table.element(a, sqrt(mysum$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$sigma)
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a, 'Sum Squared Residuals',1,TRUE)
> a<-table.element(a, sum(myerror*myerror))
> a<-table.row.end(a)
> a<-table.end(a)
> table.save(a,file="/var/wessaorg/rcomp/tmp/13urua1321542795.tab")
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a, 'Multiple Linear Regression - Actuals, Interpolation, and Residuals', 4, TRUE)
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a, 'Time or Index', 1, TRUE)
> a<-table.element(a, 'Actuals', 1, TRUE)
> a<-table.element(a, 'Interpolation
Forecast', 1, TRUE)
> a<-table.element(a, 'Residuals
Prediction Error', 1, TRUE)
> a<-table.row.end(a)
> for (i in 1:n) {
+ a<-table.row.start(a)
+ a<-table.element(a,i, 1, TRUE)
+ a<-table.element(a,x[i])
+ a<-table.element(a,x[i]-mysum$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/149lda1321542795.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/1502901321542795.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/16wj311321542795.tab")
+ }
>
> try(system("convert tmp/13bvq1321542795.ps tmp/13bvq1321542795.png",intern=TRUE))
character(0)
> try(system("convert tmp/2uc5c1321542795.ps tmp/2uc5c1321542795.png",intern=TRUE))
character(0)
> try(system("convert tmp/3zobm1321542795.ps tmp/3zobm1321542795.png",intern=TRUE))
character(0)
> try(system("convert tmp/4cwgb1321542795.ps tmp/4cwgb1321542795.png",intern=TRUE))
character(0)
> try(system("convert tmp/55af61321542795.ps tmp/55af61321542795.png",intern=TRUE))
character(0)
> try(system("convert tmp/6fiq31321542795.ps tmp/6fiq31321542795.png",intern=TRUE))
character(0)
> try(system("convert tmp/70fpy1321542795.ps tmp/70fpy1321542795.png",intern=TRUE))
character(0)
> try(system("convert tmp/80u931321542795.ps tmp/80u931321542795.png",intern=TRUE))
character(0)
> try(system("convert tmp/955tz1321542795.ps tmp/955tz1321542795.png",intern=TRUE))
character(0)
> try(system("convert tmp/10hzbg1321542795.ps tmp/10hzbg1321542795.png",intern=TRUE))
character(0)
>
>
> proc.time()
user system elapsed
5.730 0.571 6.368