R version 2.15.2 (2012-10-26) -- "Trick or Treat"
Copyright (C) 2012 The R Foundation for Statistical Computing
ISBN 3-900051-07-0
Platform: i686-pc-linux-gnu (32-bit)
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Type 'q()' to quit R.
> x <- array(list(102
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+ ,dim=c(4
+ ,269)
+ ,dimnames=list(c('hours'
+ ,'lfm'
+ ,'blogs'
+ ,'uk')
+ ,1:269))
> y <- array(NA,dim=c(4,269),dimnames=list(c('hours','lfm','blogs','uk'),1:269))
> 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 = '2'
> library(lattice)
> library(lmtest)
Loading required package: zoo
Attaching package: 'zoo'
The following object(s) are masked from 'package:base':
as.Date, as.Date.numeric
> 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
lfm hours blogs uk
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253 2 15 24 0
254 83 14 23 0
255 11 13 43 0
256 16 13 28 0
257 9 12 19 0
258 46 11 16 0
259 41 11 40 0
260 14 10 14 0
261 63 10 19 0
262 9 10 22 0
263 0 10 8 0
264 58 9 31 0
265 18 8 9 0
266 42 8 18 0
267 26 7 9 0
268 38 7 5 0
269 1 4 11 0
> k <- length(x[1,])
> df <- as.data.frame(x)
> (mylm <- lm(df))
Call:
lm(formula = df)
Coefficients:
(Intercept) hours blogs uk
34.4159 0.5359 0.3717 38.2254
> (mysum <- summary(mylm))
Call:
lm(formula = df)
Residuals:
Min 1Q Median 3Q Max
-79.283 -15.776 2.832 16.852 106.391
Coefficients:
Estimate Std. Error t value Pr(>|t|)
(Intercept) 34.4159 4.0605 8.476 1.64e-15 ***
hours 0.5359 0.1167 4.592 6.80e-06 ***
blogs 0.3717 0.0922 4.031 7.25e-05 ***
uk 38.2254 3.5859 10.660 < 2e-16 ***
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
Residual standard error: 25.5 on 265 degrees of freedom
Multiple R-squared: 0.4998, Adjusted R-squared: 0.4941
F-statistic: 88.27 on 3 and 265 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,] 1.774652e-01 3.549304e-01 0.8225348
[2,] 8.651479e-02 1.730296e-01 0.9134852
[3,] 3.043645e-01 6.087290e-01 0.6956355
[4,] 1.977037e-01 3.954075e-01 0.8022963
[5,] 2.242277e-01 4.484555e-01 0.7757723
[6,] 2.617840e-01 5.235681e-01 0.7382160
[7,] 2.007956e-01 4.015912e-01 0.7992044
[8,] 1.634884e-01 3.269768e-01 0.8365116
[9,] 1.113624e-01 2.227247e-01 0.8886376
[10,] 1.025214e-01 2.050429e-01 0.8974786
[11,] 7.084650e-02 1.416930e-01 0.9291535
[12,] 9.228056e-02 1.845611e-01 0.9077194
[13,] 7.365499e-02 1.473100e-01 0.9263450
[14,] 4.884911e-02 9.769823e-02 0.9511509
[15,] 4.242735e-02 8.485471e-02 0.9575726
[16,] 2.817075e-02 5.634151e-02 0.9718292
[17,] 1.873452e-02 3.746904e-02 0.9812655
[18,] 1.191733e-02 2.383466e-02 0.9880827
[19,] 7.924985e-03 1.584997e-02 0.9920750
[20,] 4.905869e-03 9.811738e-03 0.9950941
[21,] 3.776304e-03 7.552608e-03 0.9962237
[22,] 2.659770e-03 5.319540e-03 0.9973402
[23,] 1.698483e-03 3.396967e-03 0.9983015
[24,] 1.105749e-03 2.211499e-03 0.9988943
[25,] 1.807309e-03 3.614618e-03 0.9981927
[26,] 1.057452e-03 2.114905e-03 0.9989425
[27,] 8.380729e-04 1.676146e-03 0.9991619
[28,] 6.049518e-04 1.209904e-03 0.9993950
[29,] 5.465188e-04 1.093038e-03 0.9994535
[30,] 5.167918e-04 1.033584e-03 0.9994832
[31,] 4.187020e-04 8.374039e-04 0.9995813
[32,] 3.425576e-04 6.851152e-04 0.9996574
[33,] 2.426915e-04 4.853830e-04 0.9997573
[34,] 3.295397e-04 6.590793e-04 0.9996705
[35,] 1.941591e-04 3.883182e-04 0.9998058
[36,] 2.852844e-04 5.705687e-04 0.9997147
[37,] 2.346290e-04 4.692580e-04 0.9997654
[38,] 1.744762e-04 3.489524e-04 0.9998255
[39,] 6.757467e-04 1.351493e-03 0.9993243
[40,] 4.738674e-04 9.477348e-04 0.9995261
[41,] 2.951499e-04 5.902997e-04 0.9997049
[42,] 1.878866e-04 3.757731e-04 0.9998121
[43,] 1.147291e-04 2.294582e-04 0.9998853
[44,] 6.928365e-05 1.385673e-04 0.9999307
[45,] 4.689887e-05 9.379775e-05 0.9999531
[46,] 7.361649e-05 1.472330e-04 0.9999264
[47,] 7.192979e-05 1.438596e-04 0.9999281
[48,] 4.873912e-05 9.747824e-05 0.9999513
[49,] 2.973923e-05 5.947845e-05 0.9999703
[50,] 1.376544e-04 2.753088e-04 0.9998623
[51,] 8.770933e-05 1.754187e-04 0.9999123
[52,] 5.535488e-05 1.107098e-04 0.9999446
[53,] 6.405375e-05 1.281075e-04 0.9999359
[54,] 7.316038e-05 1.463208e-04 0.9999268
[55,] 4.652460e-05 9.304921e-05 0.9999535
[56,] 3.119772e-05 6.239545e-05 0.9999688
[57,] 2.000460e-05 4.000920e-05 0.9999800
[58,] 1.241818e-05 2.483637e-05 0.9999876
[59,] 2.179788e-05 4.359576e-05 0.9999782
[60,] 2.233638e-05 4.467277e-05 0.9999777
[61,] 1.394045e-05 2.788089e-05 0.9999861
[62,] 8.815263e-06 1.763053e-05 0.9999912
[63,] 5.522700e-06 1.104540e-05 0.9999945
[64,] 1.768266e-05 3.536532e-05 0.9999823
[65,] 1.123971e-05 2.247942e-05 0.9999888
[66,] 7.361176e-06 1.472235e-05 0.9999926
[67,] 5.125806e-06 1.025161e-05 0.9999949
[68,] 3.362757e-06 6.725513e-06 0.9999966
[69,] 2.170991e-06 4.341983e-06 0.9999978
[70,] 1.594256e-06 3.188511e-06 0.9999984
[71,] 1.005385e-06 2.010770e-06 0.9999990
[72,] 7.333822e-07 1.466764e-06 0.9999993
[73,] 4.749682e-07 9.499364e-07 0.9999995
[74,] 2.984526e-07 5.969051e-07 0.9999997
[75,] 2.187484e-07 4.374968e-07 0.9999998
[76,] 2.472272e-07 4.944543e-07 0.9999998
[77,] 2.571256e-07 5.142512e-07 0.9999997
[78,] 1.886874e-07 3.773749e-07 0.9999998
[79,] 1.208995e-07 2.417990e-07 0.9999999
[80,] 1.253339e-07 2.506678e-07 0.9999999
[81,] 3.460115e-07 6.920229e-07 0.9999997
[82,] 6.569551e-07 1.313910e-06 0.9999993
[83,] 4.300573e-07 8.601145e-07 0.9999996
[84,] 4.119008e-07 8.238017e-07 0.9999996
[85,] 3.001070e-07 6.002140e-07 0.9999997
[86,] 2.341808e-07 4.683616e-07 0.9999998
[87,] 1.895175e-07 3.790351e-07 0.9999998
[88,] 3.139405e-07 6.278811e-07 0.9999997
[89,] 2.104821e-07 4.209641e-07 0.9999998
[90,] 2.149023e-07 4.298046e-07 0.9999998
[91,] 2.760198e-07 5.520396e-07 0.9999997
[92,] 1.821205e-07 3.642411e-07 0.9999998
[93,] 1.561514e-07 3.123028e-07 0.9999998
[94,] 1.079861e-07 2.159723e-07 0.9999999
[95,] 8.423426e-08 1.684685e-07 0.9999999
[96,] 1.010771e-07 2.021542e-07 0.9999999
[97,] 1.306738e-07 2.613477e-07 0.9999999
[98,] 2.384020e-07 4.768040e-07 0.9999998
[99,] 6.280154e-05 1.256031e-04 0.9999372
[100,] 6.895894e-05 1.379179e-04 0.9999310
[101,] 5.701012e-05 1.140202e-04 0.9999430
[102,] 8.454570e-05 1.690914e-04 0.9999155
[103,] 3.435521e-04 6.871043e-04 0.9996564
[104,] 4.478132e-03 8.956264e-03 0.9955219
[105,] 2.369665e-02 4.739330e-02 0.9763033
[106,] 6.514617e-02 1.302923e-01 0.9348538
[107,] 7.121323e-02 1.424265e-01 0.9287868
[108,] 1.272435e-01 2.544870e-01 0.8727565
[109,] 1.554367e-01 3.108734e-01 0.8445633
[110,] 1.721296e-01 3.442593e-01 0.8278704
[111,] 2.310247e-01 4.620494e-01 0.7689753
[112,] 2.404152e-01 4.808304e-01 0.7595848
[113,] 2.249283e-01 4.498565e-01 0.7750717
[114,] 2.093579e-01 4.187158e-01 0.7906421
[115,] 2.276387e-01 4.552775e-01 0.7723613
[116,] 2.174592e-01 4.349183e-01 0.7825408
[117,] 2.114292e-01 4.228584e-01 0.7885708
[118,] 1.966160e-01 3.932321e-01 0.8033840
[119,] 2.124167e-01 4.248333e-01 0.7875833
[120,] 1.923215e-01 3.846431e-01 0.8076785
[121,] 1.833363e-01 3.666727e-01 0.8166637
[122,] 1.669596e-01 3.339191e-01 0.8330404
[123,] 1.518077e-01 3.036153e-01 0.8481923
[124,] 1.844939e-01 3.689878e-01 0.8155061
[125,] 1.960322e-01 3.920644e-01 0.8039678
[126,] 2.158720e-01 4.317440e-01 0.7841280
[127,] 1.938718e-01 3.877436e-01 0.8061282
[128,] 1.730179e-01 3.460357e-01 0.8269821
[129,] 1.624859e-01 3.249719e-01 0.8375141
[130,] 1.430407e-01 2.860814e-01 0.8569593
[131,] 1.254805e-01 2.509611e-01 0.8745195
[132,] 1.109924e-01 2.219848e-01 0.8890076
[133,] 9.705053e-02 1.941011e-01 0.9029495
[134,] 8.609674e-02 1.721935e-01 0.9139033
[135,] 7.620513e-02 1.524103e-01 0.9237949
[136,] 6.513468e-02 1.302694e-01 0.9348653
[137,] 5.550916e-02 1.110183e-01 0.9444908
[138,] 5.386526e-02 1.077305e-01 0.9461347
[139,] 4.814572e-02 9.629145e-02 0.9518543
[140,] 4.007569e-02 8.015138e-02 0.9599243
[141,] 3.322262e-02 6.644525e-02 0.9667774
[142,] 2.752076e-02 5.504151e-02 0.9724792
[143,] 2.252589e-02 4.505178e-02 0.9774741
[144,] 2.084009e-02 4.168018e-02 0.9791599
[145,] 1.752041e-02 3.504081e-02 0.9824796
[146,] 1.486241e-02 2.972483e-02 0.9851376
[147,] 1.776778e-02 3.553555e-02 0.9822322
[148,] 1.457238e-02 2.914475e-02 0.9854276
[149,] 1.440311e-02 2.880621e-02 0.9855969
[150,] 1.519103e-02 3.038207e-02 0.9848090
[151,] 1.236052e-02 2.472103e-02 0.9876395
[152,] 1.513951e-02 3.027901e-02 0.9848605
[153,] 1.298333e-02 2.596665e-02 0.9870167
[154,] 1.141006e-02 2.282012e-02 0.9885899
[155,] 1.247377e-02 2.494754e-02 0.9875262
[156,] 1.022160e-02 2.044321e-02 0.9897784
[157,] 8.096069e-03 1.619214e-02 0.9919039
[158,] 6.352943e-03 1.270589e-02 0.9936471
[159,] 5.176806e-03 1.035361e-02 0.9948232
[160,] 4.799084e-03 9.598169e-03 0.9952009
[161,] 5.687563e-03 1.137513e-02 0.9943124
[162,] 5.506430e-03 1.101286e-02 0.9944936
[163,] 5.041016e-03 1.008203e-02 0.9949590
[164,] 1.973602e-02 3.947204e-02 0.9802640
[165,] 1.584429e-02 3.168858e-02 0.9841557
[166,] 1.424414e-02 2.848828e-02 0.9857559
[167,] 2.251110e-02 4.502219e-02 0.9774889
[168,] 2.447183e-02 4.894367e-02 0.9755282
[169,] 1.991161e-02 3.982321e-02 0.9800884
[170,] 2.116869e-02 4.233737e-02 0.9788313
[171,] 3.073110e-02 6.146220e-02 0.9692689
[172,] 3.973864e-02 7.947728e-02 0.9602614
[173,] 3.366983e-02 6.733965e-02 0.9663302
[174,] 3.229262e-02 6.458524e-02 0.9677074
[175,] 3.061673e-02 6.123346e-02 0.9693833
[176,] 2.495133e-02 4.990265e-02 0.9750487
[177,] 2.331143e-02 4.662286e-02 0.9766886
[178,] 1.865218e-02 3.730436e-02 0.9813478
[179,] 1.802222e-02 3.604443e-02 0.9819778
[180,] 1.429831e-02 2.859661e-02 0.9857017
[181,] 1.129133e-02 2.258266e-02 0.9887087
[182,] 1.952447e-02 3.904894e-02 0.9804755
[183,] 1.581300e-02 3.162599e-02 0.9841870
[184,] 1.881794e-02 3.763588e-02 0.9811821
[185,] 1.538016e-02 3.076032e-02 0.9846198
[186,] 1.818145e-02 3.636291e-02 0.9818185
[187,] 1.450389e-02 2.900779e-02 0.9854961
[188,] 1.277757e-02 2.555515e-02 0.9872224
[189,] 1.365975e-02 2.731950e-02 0.9863402
[190,] 1.291051e-02 2.582102e-02 0.9870895
[191,] 1.857079e-02 3.714157e-02 0.9814292
[192,] 1.478708e-02 2.957416e-02 0.9852129
[193,] 1.154551e-02 2.309102e-02 0.9884545
[194,] 1.194524e-02 2.389048e-02 0.9880548
[195,] 9.284685e-03 1.856937e-02 0.9907153
[196,] 7.570522e-03 1.514104e-02 0.9924295
[197,] 8.182043e-03 1.636409e-02 0.9918180
[198,] 6.245759e-03 1.249152e-02 0.9937542
[199,] 5.288049e-03 1.057610e-02 0.9947120
[200,] 5.217330e-03 1.043466e-02 0.9947827
[201,] 4.349997e-03 8.699995e-03 0.9956500
[202,] 5.017458e-03 1.003492e-02 0.9949825
[203,] 6.425156e-03 1.285031e-02 0.9935748
[204,] 7.267165e-03 1.453433e-02 0.9927328
[205,] 5.653017e-03 1.130603e-02 0.9943470
[206,] 4.254542e-03 8.509084e-03 0.9957455
[207,] 1.377308e-02 2.754617e-02 0.9862269
[208,] 1.317193e-02 2.634385e-02 0.9868281
[209,] 1.079916e-02 2.159833e-02 0.9892008
[210,] 9.169863e-03 1.833973e-02 0.9908301
[211,] 7.697135e-03 1.539427e-02 0.9923029
[212,] 6.028878e-03 1.205776e-02 0.9939711
[213,] 9.571940e-03 1.914388e-02 0.9904281
[214,] 2.791577e-02 5.583153e-02 0.9720842
[215,] 2.264169e-02 4.528338e-02 0.9773583
[216,] 3.318587e-01 6.637173e-01 0.6681413
[217,] 2.903373e-01 5.806746e-01 0.7096627
[218,] 3.980105e-01 7.960210e-01 0.6019895
[219,] 3.600232e-01 7.200463e-01 0.6399768
[220,] 3.241721e-01 6.483442e-01 0.6758279
[221,] 5.266373e-01 9.467255e-01 0.4733627
[222,] 4.871858e-01 9.743717e-01 0.5128142
[223,] 4.418201e-01 8.836402e-01 0.5581799
[224,] 4.481864e-01 8.963729e-01 0.5518136
[225,] 4.115536e-01 8.231073e-01 0.5884464
[226,] 4.052997e-01 8.105994e-01 0.5947003
[227,] 5.180264e-01 9.639471e-01 0.4819736
[228,] 5.168982e-01 9.662036e-01 0.4831018
[229,] 5.361728e-01 9.276544e-01 0.4638272
[230,] 4.857659e-01 9.715319e-01 0.5142341
[231,] 4.504181e-01 9.008362e-01 0.5495819
[232,] 4.626079e-01 9.252158e-01 0.5373921
[233,] 4.970186e-01 9.940371e-01 0.5029814
[234,] 4.397411e-01 8.794822e-01 0.5602589
[235,] 3.926355e-01 7.852710e-01 0.6073645
[236,] 3.418764e-01 6.837528e-01 0.6581236
[237,] 2.881064e-01 5.762128e-01 0.7118936
[238,] 2.670699e-01 5.341397e-01 0.7329301
[239,] 2.966278e-01 5.932556e-01 0.7033722
[240,] 3.097301e-01 6.194602e-01 0.6902699
[241,] 2.685302e-01 5.370605e-01 0.7314698
[242,] 2.154039e-01 4.308078e-01 0.7845961
[243,] 1.830084e-01 3.660167e-01 0.8169916
[244,] 1.603908e-01 3.207816e-01 0.8396092
[245,] 3.825956e-01 7.651913e-01 0.6174044
[246,] 3.142622e-01 6.285243e-01 0.6857378
[247,] 3.647567e-01 7.295135e-01 0.6352433
[248,] 6.497310e-01 7.005381e-01 0.3502690
[249,] 6.855050e-01 6.289901e-01 0.3144950
[250,] 6.510940e-01 6.978120e-01 0.3489060
[251,] 6.461033e-01 7.077935e-01 0.3538967
[252,] 5.854496e-01 8.291008e-01 0.4145504
[253,] 5.094012e-01 9.811975e-01 0.4905988
[254,] 4.206201e-01 8.412402e-01 0.5793799
[255,] 4.751859e-01 9.503718e-01 0.5248141
[256,] 5.104080e-01 9.791841e-01 0.4895920
> postscript(file="/var/wessaorg/rcomp/tmp/137kf1358279783.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/2snkd1358279783.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> plot(mysum$resid, type='b', pch=19, main='Residuals', ylab='value of Residuals', xlab='time or index')
> grid()
> dev.off()
null device
1
> postscript(file="/var/wessaorg/rcomp/tmp/3lcxf1358279783.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> hist(mysum$resid, main='Residual Histogram', xlab='values of Residuals')
> grid()
> dev.off()
null device
1
> postscript(file="/var/wessaorg/rcomp/tmp/4dg171358279783.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> densityplot(~mysum$resid,col='black',main='Residual Density Plot', xlab='values of Residuals')
> dev.off()
null device
1
> postscript(file="/var/wessaorg/rcomp/tmp/5h8do1358279783.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> qqnorm(mysum$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 = 269
Frequency = 1
1 2 3 4 5 6
-38.0083890 -51.0915954 -10.6383821 0.3993689 -12.7174589 0.9429941
7 8 9 10 11 12
-11.7777385 -14.2553385 32.4617486 3.6032050 -39.0648667 -14.0096924
13 14 15 16 17 18
12.1146685 -7.1455596 11.5544318 18.4919665 0.3468645 -18.7719072
19 20 21 22 23 24
21.6488168 -0.1570659 -11.0946006 -17.8612726 11.5827060 -10.5685551
25 26 27 28 29 30
10.7731777 -3.5985310 17.1448864 22.7432018 -1.3455939 -6.5268308
31 32 33 34 35 36
-24.4117047 2.1241453 15.8938931 -10.4551307 22.7751215 -12.3663350
37 38 39 40 41 42
-4.9982718 18.2448607 19.9846326 33.6129239 11.0997587 -13.4397369
43 44 45 46 47 48
-5.1831543 16.1787499 46.3165609 20.3790262 8.9448522 2.9185218
49 50 51 52 53 54
10.1751044 8.2639001 -2.9400217 38.9148762 -12.4041717 16.8524109
55 56 57 58 59 60
13.0563327 -35.4041717 13.8224350 2.5033871 33.0129068 -13.8719671
61 62 63 64 65 66
7.9431504 3.8016939 17.5677962 12.9658353 -21.7512517 29.5053309
67 68 69 70 71 72
9.5543461 14.6168114 13.8733940 -28.0775907 10.8336136 16.4092441
73 74 75 76 77 78
19.3431333 18.4055986 15.9450942 -2.4927254 13.7375268 -8.0193406
79 80 81 82 83 84
17.1319204 2.5562899 23.6187552 -13.4210252 27.5128639 24.6377945
85 86 87 88 89 90
9.8809271 -5.6585685 -23.8888207 -17.8924662 7.9526272 -14.6230033
91 92 93 94 95 96
-2.3039554 20.9489817 -2.6793096 -27.2947205 8.9092013 -13.8605465
97 98 99 100 101 102
-18.3737117 -1.9493422 18.6753035 1.5601774 12.2772644 -12.6339399
103 104 105 106 107 108
25.3226342 -22.5132245 -79.2829723 -22.7869026 -4.1586113 21.3245779
109 110 111 112 113 114
30.9791996 -75.6659452 -77.8735126 -75.3639929 -48.2682177 -74.7476908
115 116 117 118 119 120
-15.7757229 -11.0639832 25.9885919 16.5771028 4.1546771 4.2361817
121 122 123 124 125 126
-29.2585138 15.2700452 21.0226974 -10.0170830 -25.1431457 4.2450888
127 128 129 130 131 132
-7.8675238 -7.2851719 12.2660720 43.1473003 -24.4546606 39.3739070
133 134 135 136 137 138
0.1038744 10.9887483 23.8699766 0.8301962 3.7512050 -0.9695275
139 140 141 142 143 144
14.7965747 -9.2493647 17.6453137 11.0433528 5.8817249 30.2436291
145 146 147 148 149 150
-5.9241578 6.5492270 8.9834010 11.0226117 3.9663054 29.0287707
151 152 153 154 155 156
18.6172816 19.6662968 -26.4751597 15.0380055 -15.5278205 34.9228794
157 158 159 160 161 162
-0.8205380 -28.7942076 -6.4524748 23.4587295 -23.3998140 -1.5676009
163 164 165 166 167 168
10.2083059 9.2609667 -5.5810509 30.1948558 39.7606818 -15.8939399
169 170 171 172 173 174
29.4514384 -59.5846965 10.2836516 27.1287450 -36.4732159 -18.0690178
175 176 177 178 179 180
2.8323820 -17.2729396 48.6284602 -30.0524919 19.8024060 -8.5331677
181 182 183 184 185 186
28.7662711 12.7136103 28.7399407 6.8813972 31.7362952 9.1343343
187 188 189 190 191 192
12.7987605 -32.2539003 3.2231300 -19.0634285 3.2458149 50.6273281
193 194 195 196 197 198
13.9592564 24.8343257 33.1399236 -19.7186199 -34.5146981 0.1362781
199 200 201 202 203 204
11.3138695 -17.2880914 2.3928607 18.9060259 28.2415997 4.9550411
205 206 207 208 209 210
11.5208671 -28.4791329 19.5796869 42.7309479 -26.8710130 -30.1374001
211 212 213 214 215 216
7.1681978 18.4443894 -49.3124780 -12.0558954 10.4474652 24.1118915
217 218 219 220 221 222
5.7303782 10.8914438 -39.6051956 -42.0332106 22.1345763 106.3911589
223 224 225 226 227 228
4.6477415 -40.6088411 -19.2469369 -19.8752282 50.9796698 21.6802309
229 230 231 232 233 234
27.9858288 1.0550154 -3.0766365 -19.0503061 42.7421265 -40.5769214
235 236 237 238 239 240
-27.5144561 25.5480092 -27.2052127 -42.7844887 35.2516462 -1.4654408
241 242 243 244 245 246
-15.8144646 -17.1598429 2.0440789 -21.6993385 35.7611659 -40.4562060
247 248 249 250 251 252
-16.4200711 -1.6802992 10.6026138 9.9082117 41.7667552 -22.3747013
253 254 255 256 257 258
-49.3747013 32.5328574 -46.3654665 -35.7898360 -38.9086076 -0.2576315
259 260 261 262 263 264
-14.1786403 -30.9783640 16.1630925 -38.9520336 -42.7481118 7.2384382
265 266 267 268 269
-24.0481204 -3.3934987 -15.5122703 -2.0254355 -39.6481375
> postscript(file="/var/wessaorg/rcomp/tmp/6o3w81358279783.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 = 269
Frequency = 1
lag(myerror, k = 1) myerror
0 -38.0083890 NA
1 -51.0915954 -38.0083890
2 -10.6383821 -51.0915954
3 0.3993689 -10.6383821
4 -12.7174589 0.3993689
5 0.9429941 -12.7174589
6 -11.7777385 0.9429941
7 -14.2553385 -11.7777385
8 32.4617486 -14.2553385
9 3.6032050 32.4617486
10 -39.0648667 3.6032050
11 -14.0096924 -39.0648667
12 12.1146685 -14.0096924
13 -7.1455596 12.1146685
14 11.5544318 -7.1455596
15 18.4919665 11.5544318
16 0.3468645 18.4919665
17 -18.7719072 0.3468645
18 21.6488168 -18.7719072
19 -0.1570659 21.6488168
20 -11.0946006 -0.1570659
21 -17.8612726 -11.0946006
22 11.5827060 -17.8612726
23 -10.5685551 11.5827060
24 10.7731777 -10.5685551
25 -3.5985310 10.7731777
26 17.1448864 -3.5985310
27 22.7432018 17.1448864
28 -1.3455939 22.7432018
29 -6.5268308 -1.3455939
30 -24.4117047 -6.5268308
31 2.1241453 -24.4117047
32 15.8938931 2.1241453
33 -10.4551307 15.8938931
34 22.7751215 -10.4551307
35 -12.3663350 22.7751215
36 -4.9982718 -12.3663350
37 18.2448607 -4.9982718
38 19.9846326 18.2448607
39 33.6129239 19.9846326
40 11.0997587 33.6129239
41 -13.4397369 11.0997587
42 -5.1831543 -13.4397369
43 16.1787499 -5.1831543
44 46.3165609 16.1787499
45 20.3790262 46.3165609
46 8.9448522 20.3790262
47 2.9185218 8.9448522
48 10.1751044 2.9185218
49 8.2639001 10.1751044
50 -2.9400217 8.2639001
51 38.9148762 -2.9400217
52 -12.4041717 38.9148762
53 16.8524109 -12.4041717
54 13.0563327 16.8524109
55 -35.4041717 13.0563327
56 13.8224350 -35.4041717
57 2.5033871 13.8224350
58 33.0129068 2.5033871
59 -13.8719671 33.0129068
60 7.9431504 -13.8719671
61 3.8016939 7.9431504
62 17.5677962 3.8016939
63 12.9658353 17.5677962
64 -21.7512517 12.9658353
65 29.5053309 -21.7512517
66 9.5543461 29.5053309
67 14.6168114 9.5543461
68 13.8733940 14.6168114
69 -28.0775907 13.8733940
70 10.8336136 -28.0775907
71 16.4092441 10.8336136
72 19.3431333 16.4092441
73 18.4055986 19.3431333
74 15.9450942 18.4055986
75 -2.4927254 15.9450942
76 13.7375268 -2.4927254
77 -8.0193406 13.7375268
78 17.1319204 -8.0193406
79 2.5562899 17.1319204
80 23.6187552 2.5562899
81 -13.4210252 23.6187552
82 27.5128639 -13.4210252
83 24.6377945 27.5128639
84 9.8809271 24.6377945
85 -5.6585685 9.8809271
86 -23.8888207 -5.6585685
87 -17.8924662 -23.8888207
88 7.9526272 -17.8924662
89 -14.6230033 7.9526272
90 -2.3039554 -14.6230033
91 20.9489817 -2.3039554
92 -2.6793096 20.9489817
93 -27.2947205 -2.6793096
94 8.9092013 -27.2947205
95 -13.8605465 8.9092013
96 -18.3737117 -13.8605465
97 -1.9493422 -18.3737117
98 18.6753035 -1.9493422
99 1.5601774 18.6753035
100 12.2772644 1.5601774
101 -12.6339399 12.2772644
102 25.3226342 -12.6339399
103 -22.5132245 25.3226342
104 -79.2829723 -22.5132245
105 -22.7869026 -79.2829723
106 -4.1586113 -22.7869026
107 21.3245779 -4.1586113
108 30.9791996 21.3245779
109 -75.6659452 30.9791996
110 -77.8735126 -75.6659452
111 -75.3639929 -77.8735126
112 -48.2682177 -75.3639929
113 -74.7476908 -48.2682177
114 -15.7757229 -74.7476908
115 -11.0639832 -15.7757229
116 25.9885919 -11.0639832
117 16.5771028 25.9885919
118 4.1546771 16.5771028
119 4.2361817 4.1546771
120 -29.2585138 4.2361817
121 15.2700452 -29.2585138
122 21.0226974 15.2700452
123 -10.0170830 21.0226974
124 -25.1431457 -10.0170830
125 4.2450888 -25.1431457
126 -7.8675238 4.2450888
127 -7.2851719 -7.8675238
128 12.2660720 -7.2851719
129 43.1473003 12.2660720
130 -24.4546606 43.1473003
131 39.3739070 -24.4546606
132 0.1038744 39.3739070
133 10.9887483 0.1038744
134 23.8699766 10.9887483
135 0.8301962 23.8699766
136 3.7512050 0.8301962
137 -0.9695275 3.7512050
138 14.7965747 -0.9695275
139 -9.2493647 14.7965747
140 17.6453137 -9.2493647
141 11.0433528 17.6453137
142 5.8817249 11.0433528
143 30.2436291 5.8817249
144 -5.9241578 30.2436291
145 6.5492270 -5.9241578
146 8.9834010 6.5492270
147 11.0226117 8.9834010
148 3.9663054 11.0226117
149 29.0287707 3.9663054
150 18.6172816 29.0287707
151 19.6662968 18.6172816
152 -26.4751597 19.6662968
153 15.0380055 -26.4751597
154 -15.5278205 15.0380055
155 34.9228794 -15.5278205
156 -0.8205380 34.9228794
157 -28.7942076 -0.8205380
158 -6.4524748 -28.7942076
159 23.4587295 -6.4524748
160 -23.3998140 23.4587295
161 -1.5676009 -23.3998140
162 10.2083059 -1.5676009
163 9.2609667 10.2083059
164 -5.5810509 9.2609667
165 30.1948558 -5.5810509
166 39.7606818 30.1948558
167 -15.8939399 39.7606818
168 29.4514384 -15.8939399
169 -59.5846965 29.4514384
170 10.2836516 -59.5846965
171 27.1287450 10.2836516
172 -36.4732159 27.1287450
173 -18.0690178 -36.4732159
174 2.8323820 -18.0690178
175 -17.2729396 2.8323820
176 48.6284602 -17.2729396
177 -30.0524919 48.6284602
178 19.8024060 -30.0524919
179 -8.5331677 19.8024060
180 28.7662711 -8.5331677
181 12.7136103 28.7662711
182 28.7399407 12.7136103
183 6.8813972 28.7399407
184 31.7362952 6.8813972
185 9.1343343 31.7362952
186 12.7987605 9.1343343
187 -32.2539003 12.7987605
188 3.2231300 -32.2539003
189 -19.0634285 3.2231300
190 3.2458149 -19.0634285
191 50.6273281 3.2458149
192 13.9592564 50.6273281
193 24.8343257 13.9592564
194 33.1399236 24.8343257
195 -19.7186199 33.1399236
196 -34.5146981 -19.7186199
197 0.1362781 -34.5146981
198 11.3138695 0.1362781
199 -17.2880914 11.3138695
200 2.3928607 -17.2880914
201 18.9060259 2.3928607
202 28.2415997 18.9060259
203 4.9550411 28.2415997
204 11.5208671 4.9550411
205 -28.4791329 11.5208671
206 19.5796869 -28.4791329
207 42.7309479 19.5796869
208 -26.8710130 42.7309479
209 -30.1374001 -26.8710130
210 7.1681978 -30.1374001
211 18.4443894 7.1681978
212 -49.3124780 18.4443894
213 -12.0558954 -49.3124780
214 10.4474652 -12.0558954
215 24.1118915 10.4474652
216 5.7303782 24.1118915
217 10.8914438 5.7303782
218 -39.6051956 10.8914438
219 -42.0332106 -39.6051956
220 22.1345763 -42.0332106
221 106.3911589 22.1345763
222 4.6477415 106.3911589
223 -40.6088411 4.6477415
224 -19.2469369 -40.6088411
225 -19.8752282 -19.2469369
226 50.9796698 -19.8752282
227 21.6802309 50.9796698
228 27.9858288 21.6802309
229 1.0550154 27.9858288
230 -3.0766365 1.0550154
231 -19.0503061 -3.0766365
232 42.7421265 -19.0503061
233 -40.5769214 42.7421265
234 -27.5144561 -40.5769214
235 25.5480092 -27.5144561
236 -27.2052127 25.5480092
237 -42.7844887 -27.2052127
238 35.2516462 -42.7844887
239 -1.4654408 35.2516462
240 -15.8144646 -1.4654408
241 -17.1598429 -15.8144646
242 2.0440789 -17.1598429
243 -21.6993385 2.0440789
244 35.7611659 -21.6993385
245 -40.4562060 35.7611659
246 -16.4200711 -40.4562060
247 -1.6802992 -16.4200711
248 10.6026138 -1.6802992
249 9.9082117 10.6026138
250 41.7667552 9.9082117
251 -22.3747013 41.7667552
252 -49.3747013 -22.3747013
253 32.5328574 -49.3747013
254 -46.3654665 32.5328574
255 -35.7898360 -46.3654665
256 -38.9086076 -35.7898360
257 -0.2576315 -38.9086076
258 -14.1786403 -0.2576315
259 -30.9783640 -14.1786403
260 16.1630925 -30.9783640
261 -38.9520336 16.1630925
262 -42.7481118 -38.9520336
263 7.2384382 -42.7481118
264 -24.0481204 7.2384382
265 -3.3934987 -24.0481204
266 -15.5122703 -3.3934987
267 -2.0254355 -15.5122703
268 -39.6481375 -2.0254355
269 NA -39.6481375
> dum1 <- dum[2:length(myerror),]
> dum1
lag(myerror, k = 1) myerror
[1,] -51.0915954 -38.0083890
[2,] -10.6383821 -51.0915954
[3,] 0.3993689 -10.6383821
[4,] -12.7174589 0.3993689
[5,] 0.9429941 -12.7174589
[6,] -11.7777385 0.9429941
[7,] -14.2553385 -11.7777385
[8,] 32.4617486 -14.2553385
[9,] 3.6032050 32.4617486
[10,] -39.0648667 3.6032050
[11,] -14.0096924 -39.0648667
[12,] 12.1146685 -14.0096924
[13,] -7.1455596 12.1146685
[14,] 11.5544318 -7.1455596
[15,] 18.4919665 11.5544318
[16,] 0.3468645 18.4919665
[17,] -18.7719072 0.3468645
[18,] 21.6488168 -18.7719072
[19,] -0.1570659 21.6488168
[20,] -11.0946006 -0.1570659
[21,] -17.8612726 -11.0946006
[22,] 11.5827060 -17.8612726
[23,] -10.5685551 11.5827060
[24,] 10.7731777 -10.5685551
[25,] -3.5985310 10.7731777
[26,] 17.1448864 -3.5985310
[27,] 22.7432018 17.1448864
[28,] -1.3455939 22.7432018
[29,] -6.5268308 -1.3455939
[30,] -24.4117047 -6.5268308
[31,] 2.1241453 -24.4117047
[32,] 15.8938931 2.1241453
[33,] -10.4551307 15.8938931
[34,] 22.7751215 -10.4551307
[35,] -12.3663350 22.7751215
[36,] -4.9982718 -12.3663350
[37,] 18.2448607 -4.9982718
[38,] 19.9846326 18.2448607
[39,] 33.6129239 19.9846326
[40,] 11.0997587 33.6129239
[41,] -13.4397369 11.0997587
[42,] -5.1831543 -13.4397369
[43,] 16.1787499 -5.1831543
[44,] 46.3165609 16.1787499
[45,] 20.3790262 46.3165609
[46,] 8.9448522 20.3790262
[47,] 2.9185218 8.9448522
[48,] 10.1751044 2.9185218
[49,] 8.2639001 10.1751044
[50,] -2.9400217 8.2639001
[51,] 38.9148762 -2.9400217
[52,] -12.4041717 38.9148762
[53,] 16.8524109 -12.4041717
[54,] 13.0563327 16.8524109
[55,] -35.4041717 13.0563327
[56,] 13.8224350 -35.4041717
[57,] 2.5033871 13.8224350
[58,] 33.0129068 2.5033871
[59,] -13.8719671 33.0129068
[60,] 7.9431504 -13.8719671
[61,] 3.8016939 7.9431504
[62,] 17.5677962 3.8016939
[63,] 12.9658353 17.5677962
[64,] -21.7512517 12.9658353
[65,] 29.5053309 -21.7512517
[66,] 9.5543461 29.5053309
[67,] 14.6168114 9.5543461
[68,] 13.8733940 14.6168114
[69,] -28.0775907 13.8733940
[70,] 10.8336136 -28.0775907
[71,] 16.4092441 10.8336136
[72,] 19.3431333 16.4092441
[73,] 18.4055986 19.3431333
[74,] 15.9450942 18.4055986
[75,] -2.4927254 15.9450942
[76,] 13.7375268 -2.4927254
[77,] -8.0193406 13.7375268
[78,] 17.1319204 -8.0193406
[79,] 2.5562899 17.1319204
[80,] 23.6187552 2.5562899
[81,] -13.4210252 23.6187552
[82,] 27.5128639 -13.4210252
[83,] 24.6377945 27.5128639
[84,] 9.8809271 24.6377945
[85,] -5.6585685 9.8809271
[86,] -23.8888207 -5.6585685
[87,] -17.8924662 -23.8888207
[88,] 7.9526272 -17.8924662
[89,] -14.6230033 7.9526272
[90,] -2.3039554 -14.6230033
[91,] 20.9489817 -2.3039554
[92,] -2.6793096 20.9489817
[93,] -27.2947205 -2.6793096
[94,] 8.9092013 -27.2947205
[95,] -13.8605465 8.9092013
[96,] -18.3737117 -13.8605465
[97,] -1.9493422 -18.3737117
[98,] 18.6753035 -1.9493422
[99,] 1.5601774 18.6753035
[100,] 12.2772644 1.5601774
[101,] -12.6339399 12.2772644
[102,] 25.3226342 -12.6339399
[103,] -22.5132245 25.3226342
[104,] -79.2829723 -22.5132245
[105,] -22.7869026 -79.2829723
[106,] -4.1586113 -22.7869026
[107,] 21.3245779 -4.1586113
[108,] 30.9791996 21.3245779
[109,] -75.6659452 30.9791996
[110,] -77.8735126 -75.6659452
[111,] -75.3639929 -77.8735126
[112,] -48.2682177 -75.3639929
[113,] -74.7476908 -48.2682177
[114,] -15.7757229 -74.7476908
[115,] -11.0639832 -15.7757229
[116,] 25.9885919 -11.0639832
[117,] 16.5771028 25.9885919
[118,] 4.1546771 16.5771028
[119,] 4.2361817 4.1546771
[120,] -29.2585138 4.2361817
[121,] 15.2700452 -29.2585138
[122,] 21.0226974 15.2700452
[123,] -10.0170830 21.0226974
[124,] -25.1431457 -10.0170830
[125,] 4.2450888 -25.1431457
[126,] -7.8675238 4.2450888
[127,] -7.2851719 -7.8675238
[128,] 12.2660720 -7.2851719
[129,] 43.1473003 12.2660720
[130,] -24.4546606 43.1473003
[131,] 39.3739070 -24.4546606
[132,] 0.1038744 39.3739070
[133,] 10.9887483 0.1038744
[134,] 23.8699766 10.9887483
[135,] 0.8301962 23.8699766
[136,] 3.7512050 0.8301962
[137,] -0.9695275 3.7512050
[138,] 14.7965747 -0.9695275
[139,] -9.2493647 14.7965747
[140,] 17.6453137 -9.2493647
[141,] 11.0433528 17.6453137
[142,] 5.8817249 11.0433528
[143,] 30.2436291 5.8817249
[144,] -5.9241578 30.2436291
[145,] 6.5492270 -5.9241578
[146,] 8.9834010 6.5492270
[147,] 11.0226117 8.9834010
[148,] 3.9663054 11.0226117
[149,] 29.0287707 3.9663054
[150,] 18.6172816 29.0287707
[151,] 19.6662968 18.6172816
[152,] -26.4751597 19.6662968
[153,] 15.0380055 -26.4751597
[154,] -15.5278205 15.0380055
[155,] 34.9228794 -15.5278205
[156,] -0.8205380 34.9228794
[157,] -28.7942076 -0.8205380
[158,] -6.4524748 -28.7942076
[159,] 23.4587295 -6.4524748
[160,] -23.3998140 23.4587295
[161,] -1.5676009 -23.3998140
[162,] 10.2083059 -1.5676009
[163,] 9.2609667 10.2083059
[164,] -5.5810509 9.2609667
[165,] 30.1948558 -5.5810509
[166,] 39.7606818 30.1948558
[167,] -15.8939399 39.7606818
[168,] 29.4514384 -15.8939399
[169,] -59.5846965 29.4514384
[170,] 10.2836516 -59.5846965
[171,] 27.1287450 10.2836516
[172,] -36.4732159 27.1287450
[173,] -18.0690178 -36.4732159
[174,] 2.8323820 -18.0690178
[175,] -17.2729396 2.8323820
[176,] 48.6284602 -17.2729396
[177,] -30.0524919 48.6284602
[178,] 19.8024060 -30.0524919
[179,] -8.5331677 19.8024060
[180,] 28.7662711 -8.5331677
[181,] 12.7136103 28.7662711
[182,] 28.7399407 12.7136103
[183,] 6.8813972 28.7399407
[184,] 31.7362952 6.8813972
[185,] 9.1343343 31.7362952
[186,] 12.7987605 9.1343343
[187,] -32.2539003 12.7987605
[188,] 3.2231300 -32.2539003
[189,] -19.0634285 3.2231300
[190,] 3.2458149 -19.0634285
[191,] 50.6273281 3.2458149
[192,] 13.9592564 50.6273281
[193,] 24.8343257 13.9592564
[194,] 33.1399236 24.8343257
[195,] -19.7186199 33.1399236
[196,] -34.5146981 -19.7186199
[197,] 0.1362781 -34.5146981
[198,] 11.3138695 0.1362781
[199,] -17.2880914 11.3138695
[200,] 2.3928607 -17.2880914
[201,] 18.9060259 2.3928607
[202,] 28.2415997 18.9060259
[203,] 4.9550411 28.2415997
[204,] 11.5208671 4.9550411
[205,] -28.4791329 11.5208671
[206,] 19.5796869 -28.4791329
[207,] 42.7309479 19.5796869
[208,] -26.8710130 42.7309479
[209,] -30.1374001 -26.8710130
[210,] 7.1681978 -30.1374001
[211,] 18.4443894 7.1681978
[212,] -49.3124780 18.4443894
[213,] -12.0558954 -49.3124780
[214,] 10.4474652 -12.0558954
[215,] 24.1118915 10.4474652
[216,] 5.7303782 24.1118915
[217,] 10.8914438 5.7303782
[218,] -39.6051956 10.8914438
[219,] -42.0332106 -39.6051956
[220,] 22.1345763 -42.0332106
[221,] 106.3911589 22.1345763
[222,] 4.6477415 106.3911589
[223,] -40.6088411 4.6477415
[224,] -19.2469369 -40.6088411
[225,] -19.8752282 -19.2469369
[226,] 50.9796698 -19.8752282
[227,] 21.6802309 50.9796698
[228,] 27.9858288 21.6802309
[229,] 1.0550154 27.9858288
[230,] -3.0766365 1.0550154
[231,] -19.0503061 -3.0766365
[232,] 42.7421265 -19.0503061
[233,] -40.5769214 42.7421265
[234,] -27.5144561 -40.5769214
[235,] 25.5480092 -27.5144561
[236,] -27.2052127 25.5480092
[237,] -42.7844887 -27.2052127
[238,] 35.2516462 -42.7844887
[239,] -1.4654408 35.2516462
[240,] -15.8144646 -1.4654408
[241,] -17.1598429 -15.8144646
[242,] 2.0440789 -17.1598429
[243,] -21.6993385 2.0440789
[244,] 35.7611659 -21.6993385
[245,] -40.4562060 35.7611659
[246,] -16.4200711 -40.4562060
[247,] -1.6802992 -16.4200711
[248,] 10.6026138 -1.6802992
[249,] 9.9082117 10.6026138
[250,] 41.7667552 9.9082117
[251,] -22.3747013 41.7667552
[252,] -49.3747013 -22.3747013
[253,] 32.5328574 -49.3747013
[254,] -46.3654665 32.5328574
[255,] -35.7898360 -46.3654665
[256,] -38.9086076 -35.7898360
[257,] -0.2576315 -38.9086076
[258,] -14.1786403 -0.2576315
[259,] -30.9783640 -14.1786403
[260,] 16.1630925 -30.9783640
[261,] -38.9520336 16.1630925
[262,] -42.7481118 -38.9520336
[263,] 7.2384382 -42.7481118
[264,] -24.0481204 7.2384382
[265,] -3.3934987 -24.0481204
[266,] -15.5122703 -3.3934987
[267,] -2.0254355 -15.5122703
[268,] -39.6481375 -2.0254355
> z <- as.data.frame(dum1)
> z
lag(myerror, k = 1) myerror
1 -51.0915954 -38.0083890
2 -10.6383821 -51.0915954
3 0.3993689 -10.6383821
4 -12.7174589 0.3993689
5 0.9429941 -12.7174589
6 -11.7777385 0.9429941
7 -14.2553385 -11.7777385
8 32.4617486 -14.2553385
9 3.6032050 32.4617486
10 -39.0648667 3.6032050
11 -14.0096924 -39.0648667
12 12.1146685 -14.0096924
13 -7.1455596 12.1146685
14 11.5544318 -7.1455596
15 18.4919665 11.5544318
16 0.3468645 18.4919665
17 -18.7719072 0.3468645
18 21.6488168 -18.7719072
19 -0.1570659 21.6488168
20 -11.0946006 -0.1570659
21 -17.8612726 -11.0946006
22 11.5827060 -17.8612726
23 -10.5685551 11.5827060
24 10.7731777 -10.5685551
25 -3.5985310 10.7731777
26 17.1448864 -3.5985310
27 22.7432018 17.1448864
28 -1.3455939 22.7432018
29 -6.5268308 -1.3455939
30 -24.4117047 -6.5268308
31 2.1241453 -24.4117047
32 15.8938931 2.1241453
33 -10.4551307 15.8938931
34 22.7751215 -10.4551307
35 -12.3663350 22.7751215
36 -4.9982718 -12.3663350
37 18.2448607 -4.9982718
38 19.9846326 18.2448607
39 33.6129239 19.9846326
40 11.0997587 33.6129239
41 -13.4397369 11.0997587
42 -5.1831543 -13.4397369
43 16.1787499 -5.1831543
44 46.3165609 16.1787499
45 20.3790262 46.3165609
46 8.9448522 20.3790262
47 2.9185218 8.9448522
48 10.1751044 2.9185218
49 8.2639001 10.1751044
50 -2.9400217 8.2639001
51 38.9148762 -2.9400217
52 -12.4041717 38.9148762
53 16.8524109 -12.4041717
54 13.0563327 16.8524109
55 -35.4041717 13.0563327
56 13.8224350 -35.4041717
57 2.5033871 13.8224350
58 33.0129068 2.5033871
59 -13.8719671 33.0129068
60 7.9431504 -13.8719671
61 3.8016939 7.9431504
62 17.5677962 3.8016939
63 12.9658353 17.5677962
64 -21.7512517 12.9658353
65 29.5053309 -21.7512517
66 9.5543461 29.5053309
67 14.6168114 9.5543461
68 13.8733940 14.6168114
69 -28.0775907 13.8733940
70 10.8336136 -28.0775907
71 16.4092441 10.8336136
72 19.3431333 16.4092441
73 18.4055986 19.3431333
74 15.9450942 18.4055986
75 -2.4927254 15.9450942
76 13.7375268 -2.4927254
77 -8.0193406 13.7375268
78 17.1319204 -8.0193406
79 2.5562899 17.1319204
80 23.6187552 2.5562899
81 -13.4210252 23.6187552
82 27.5128639 -13.4210252
83 24.6377945 27.5128639
84 9.8809271 24.6377945
85 -5.6585685 9.8809271
86 -23.8888207 -5.6585685
87 -17.8924662 -23.8888207
88 7.9526272 -17.8924662
89 -14.6230033 7.9526272
90 -2.3039554 -14.6230033
91 20.9489817 -2.3039554
92 -2.6793096 20.9489817
93 -27.2947205 -2.6793096
94 8.9092013 -27.2947205
95 -13.8605465 8.9092013
96 -18.3737117 -13.8605465
97 -1.9493422 -18.3737117
98 18.6753035 -1.9493422
99 1.5601774 18.6753035
100 12.2772644 1.5601774
101 -12.6339399 12.2772644
102 25.3226342 -12.6339399
103 -22.5132245 25.3226342
104 -79.2829723 -22.5132245
105 -22.7869026 -79.2829723
106 -4.1586113 -22.7869026
107 21.3245779 -4.1586113
108 30.9791996 21.3245779
109 -75.6659452 30.9791996
110 -77.8735126 -75.6659452
111 -75.3639929 -77.8735126
112 -48.2682177 -75.3639929
113 -74.7476908 -48.2682177
114 -15.7757229 -74.7476908
115 -11.0639832 -15.7757229
116 25.9885919 -11.0639832
117 16.5771028 25.9885919
118 4.1546771 16.5771028
119 4.2361817 4.1546771
120 -29.2585138 4.2361817
121 15.2700452 -29.2585138
122 21.0226974 15.2700452
123 -10.0170830 21.0226974
124 -25.1431457 -10.0170830
125 4.2450888 -25.1431457
126 -7.8675238 4.2450888
127 -7.2851719 -7.8675238
128 12.2660720 -7.2851719
129 43.1473003 12.2660720
130 -24.4546606 43.1473003
131 39.3739070 -24.4546606
132 0.1038744 39.3739070
133 10.9887483 0.1038744
134 23.8699766 10.9887483
135 0.8301962 23.8699766
136 3.7512050 0.8301962
137 -0.9695275 3.7512050
138 14.7965747 -0.9695275
139 -9.2493647 14.7965747
140 17.6453137 -9.2493647
141 11.0433528 17.6453137
142 5.8817249 11.0433528
143 30.2436291 5.8817249
144 -5.9241578 30.2436291
145 6.5492270 -5.9241578
146 8.9834010 6.5492270
147 11.0226117 8.9834010
148 3.9663054 11.0226117
149 29.0287707 3.9663054
150 18.6172816 29.0287707
151 19.6662968 18.6172816
152 -26.4751597 19.6662968
153 15.0380055 -26.4751597
154 -15.5278205 15.0380055
155 34.9228794 -15.5278205
156 -0.8205380 34.9228794
157 -28.7942076 -0.8205380
158 -6.4524748 -28.7942076
159 23.4587295 -6.4524748
160 -23.3998140 23.4587295
161 -1.5676009 -23.3998140
162 10.2083059 -1.5676009
163 9.2609667 10.2083059
164 -5.5810509 9.2609667
165 30.1948558 -5.5810509
166 39.7606818 30.1948558
167 -15.8939399 39.7606818
168 29.4514384 -15.8939399
169 -59.5846965 29.4514384
170 10.2836516 -59.5846965
171 27.1287450 10.2836516
172 -36.4732159 27.1287450
173 -18.0690178 -36.4732159
174 2.8323820 -18.0690178
175 -17.2729396 2.8323820
176 48.6284602 -17.2729396
177 -30.0524919 48.6284602
178 19.8024060 -30.0524919
179 -8.5331677 19.8024060
180 28.7662711 -8.5331677
181 12.7136103 28.7662711
182 28.7399407 12.7136103
183 6.8813972 28.7399407
184 31.7362952 6.8813972
185 9.1343343 31.7362952
186 12.7987605 9.1343343
187 -32.2539003 12.7987605
188 3.2231300 -32.2539003
189 -19.0634285 3.2231300
190 3.2458149 -19.0634285
191 50.6273281 3.2458149
192 13.9592564 50.6273281
193 24.8343257 13.9592564
194 33.1399236 24.8343257
195 -19.7186199 33.1399236
196 -34.5146981 -19.7186199
197 0.1362781 -34.5146981
198 11.3138695 0.1362781
199 -17.2880914 11.3138695
200 2.3928607 -17.2880914
201 18.9060259 2.3928607
202 28.2415997 18.9060259
203 4.9550411 28.2415997
204 11.5208671 4.9550411
205 -28.4791329 11.5208671
206 19.5796869 -28.4791329
207 42.7309479 19.5796869
208 -26.8710130 42.7309479
209 -30.1374001 -26.8710130
210 7.1681978 -30.1374001
211 18.4443894 7.1681978
212 -49.3124780 18.4443894
213 -12.0558954 -49.3124780
214 10.4474652 -12.0558954
215 24.1118915 10.4474652
216 5.7303782 24.1118915
217 10.8914438 5.7303782
218 -39.6051956 10.8914438
219 -42.0332106 -39.6051956
220 22.1345763 -42.0332106
221 106.3911589 22.1345763
222 4.6477415 106.3911589
223 -40.6088411 4.6477415
224 -19.2469369 -40.6088411
225 -19.8752282 -19.2469369
226 50.9796698 -19.8752282
227 21.6802309 50.9796698
228 27.9858288 21.6802309
229 1.0550154 27.9858288
230 -3.0766365 1.0550154
231 -19.0503061 -3.0766365
232 42.7421265 -19.0503061
233 -40.5769214 42.7421265
234 -27.5144561 -40.5769214
235 25.5480092 -27.5144561
236 -27.2052127 25.5480092
237 -42.7844887 -27.2052127
238 35.2516462 -42.7844887
239 -1.4654408 35.2516462
240 -15.8144646 -1.4654408
241 -17.1598429 -15.8144646
242 2.0440789 -17.1598429
243 -21.6993385 2.0440789
244 35.7611659 -21.6993385
245 -40.4562060 35.7611659
246 -16.4200711 -40.4562060
247 -1.6802992 -16.4200711
248 10.6026138 -1.6802992
249 9.9082117 10.6026138
250 41.7667552 9.9082117
251 -22.3747013 41.7667552
252 -49.3747013 -22.3747013
253 32.5328574 -49.3747013
254 -46.3654665 32.5328574
255 -35.7898360 -46.3654665
256 -38.9086076 -35.7898360
257 -0.2576315 -38.9086076
258 -14.1786403 -0.2576315
259 -30.9783640 -14.1786403
260 16.1630925 -30.9783640
261 -38.9520336 16.1630925
262 -42.7481118 -38.9520336
263 7.2384382 -42.7481118
264 -24.0481204 7.2384382
265 -3.3934987 -24.0481204
266 -15.5122703 -3.3934987
267 -2.0254355 -15.5122703
268 -39.6481375 -2.0254355
> 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/7nqr31358279783.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/89xfy1358279783.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/95i5n1358279783.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/10tdk91358279783.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$coefficients)[i] != 't') myeq <- paste(myeq, '[t]', sep='')
+ }
+ }
> myeq <- paste(myeq, ' + e[t]')
> a<-table.row.start(a)
> a<-table.element(a, myeq)
> a<-table.row.end(a)
> a<-table.end(a)
> table.save(a,file="/var/wessaorg/rcomp/tmp/11dkuu1358279783.tab")
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a,hyperlink('http://www.xycoon.com/ols1.htm','Multiple Linear Regression - Ordinary Least Squares',''), 6, TRUE)
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a,'Variable',header=TRUE)
> a<-table.element(a,'Parameter',header=TRUE)
> a<-table.element(a,'S.D.',header=TRUE)
> a<-table.element(a,'T-STAT
H0: parameter = 0',header=TRUE)
> a<-table.element(a,'2-tail p-value',header=TRUE)
> a<-table.element(a,'1-tail p-value',header=TRUE)
> a<-table.row.end(a)
> for (i in 1:k){
+ a<-table.row.start(a)
+ a<-table.element(a,rownames(mysum$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$coefficients[i,4]/2,6))
+ a<-table.row.end(a)
+ }
> a<-table.end(a)
> table.save(a,file="/var/wessaorg/rcomp/tmp/12267u1358279783.tab")
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a, 'Multiple Linear Regression - Regression Statistics', 2, TRUE)
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a, 'Multiple R',1,TRUE)
> a<-table.element(a, sqrt(mysum$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$sigma)
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a, 'Sum Squared Residuals',1,TRUE)
> a<-table.element(a, sum(myerror*myerror))
> a<-table.row.end(a)
> a<-table.end(a)
> table.save(a,file="/var/wessaorg/rcomp/tmp/13obq61358279783.tab")
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a, 'Multiple Linear Regression - Actuals, Interpolation, and Residuals', 4, TRUE)
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a, 'Time or Index', 1, TRUE)
> a<-table.element(a, 'Actuals', 1, TRUE)
> a<-table.element(a, 'Interpolation
Forecast', 1, TRUE)
> a<-table.element(a, 'Residuals
Prediction Error', 1, TRUE)
> a<-table.row.end(a)
> for (i in 1:n) {
+ a<-table.row.start(a)
+ a<-table.element(a,i, 1, TRUE)
+ a<-table.element(a,x[i])
+ a<-table.element(a,x[i]-mysum$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/1413im1358279783.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/15qjix1358279783.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/16jr0q1358279783.tab")
+ }
>
> try(system("convert tmp/137kf1358279783.ps tmp/137kf1358279783.png",intern=TRUE))
character(0)
> try(system("convert tmp/2snkd1358279783.ps tmp/2snkd1358279783.png",intern=TRUE))
character(0)
> try(system("convert tmp/3lcxf1358279783.ps tmp/3lcxf1358279783.png",intern=TRUE))
character(0)
> try(system("convert tmp/4dg171358279783.ps tmp/4dg171358279783.png",intern=TRUE))
character(0)
> try(system("convert tmp/5h8do1358279783.ps tmp/5h8do1358279783.png",intern=TRUE))
character(0)
> try(system("convert tmp/6o3w81358279783.ps tmp/6o3w81358279783.png",intern=TRUE))
character(0)
> try(system("convert tmp/7nqr31358279783.ps tmp/7nqr31358279783.png",intern=TRUE))
character(0)
> try(system("convert tmp/89xfy1358279783.ps tmp/89xfy1358279783.png",intern=TRUE))
character(0)
> try(system("convert tmp/95i5n1358279783.ps tmp/95i5n1358279783.png",intern=TRUE))
character(0)
> try(system("convert tmp/10tdk91358279783.ps tmp/10tdk91358279783.png",intern=TRUE))
character(0)
>
>
> proc.time()
user system elapsed
10.726 0.837 11.720