R version 2.12.0 (2010-10-15)
Copyright (C) 2010 The R Foundation for Statistical Computing
ISBN 3-900051-07-0
Platform: i486-pc-linux-gnu (32-bit)
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> x <- array(list(1
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+ ,11
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+ ,805431
+ ,329118)
+ ,dim=c(9
+ ,100)
+ ,dimnames=list(c('Group'
+ ,'Costs'
+ ,'GrCosts'
+ ,'Trades'
+ ,'GrTrades'
+ ,'Dividends'
+ ,'GrDiv'
+ ,'TrDiv'
+ ,'Wealth
')
+ ,1:100))
> y <- array(NA,dim=c(9,100),dimnames=list(c('Group','Costs','GrCosts','Trades','GrTrades','Dividends','GrDiv','TrDiv','Wealth
'),1:100))
> 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'
> #'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
Costs Group GrCosts Trades GrTrades Dividends GrDiv TrDiv Wealth\r
1 162556 1 162556 1081 1081 213118 213118 230380558 6282929
2 29790 1 29790 309 309 81767 81767 25266003 4324047
3 87550 1 87550 458 458 153198 153198 70164684 4108272
4 84738 0 0 588 0 -26007 0 -15292116 -1212617
5 54660 1 54660 299 299 126942 126942 37955658 1485329
6 42634 1 42634 156 156 157214 157214 24525384 1779876
7 40949 0 0 481 0 129352 0 62218312 1367203
8 42312 1 42312 323 323 234817 234817 75845891 2519076
9 37704 1 37704 452 452 60448 60448 27322496 912684
10 16275 1 16275 109 109 47818 47818 5212162 1443586
11 25830 0 0 115 0 245546 0 28237790 1220017
12 12679 0 0 110 0 48020 0 5282200 984885
13 18014 1 18014 239 239 -1710 -1710 -408690 1457425
14 43556 0 0 247 0 32648 0 8064056 -572920
15 24524 1 24524 497 497 95350 95350 47388950 929144
16 6532 0 0 103 0 151352 0 15589256 1151176
17 7123 0 0 109 0 288170 0 31410530 790090
18 20813 1 20813 502 502 114337 114337 57397174 774497
19 37597 1 37597 248 248 37884 37884 9395232 990576
20 17821 0 0 373 0 122844 0 45820812 454195
21 12988 1 12988 119 119 82340 82340 9798460 876607
22 22330 1 22330 84 84 79801 79801 6703284 711969
23 13326 0 0 102 0 165548 0 16885896 702380
24 16189 0 0 295 0 116384 0 34333280 264449
25 7146 0 0 105 0 134028 0 14072940 450033
26 15824 0 0 64 0 63838 0 4085632 541063
27 26088 1 26088 267 267 74996 74996 20023932 588864
28 11326 0 0 129 0 31080 0 4009320 -37216
29 8568 0 0 37 0 32168 0 1190216 783310
30 14416 0 0 361 0 49857 0 17998377 467359
31 3369 1 3369 28 28 87161 87161 2440508 688779
32 11819 1 11819 85 85 106113 106113 9019605 608419
33 6620 1 6620 44 44 80570 80570 3545080 696348
34 4519 1 4519 49 49 102129 102129 5004321 597793
35 2220 0 0 22 0 301670 0 6636740 821730
36 18562 0 0 155 0 102313 0 15858515 377934
37 10327 0 0 91 0 88577 0 8060507 651939
38 5336 1 5336 81 81 112477 112477 9110637 697458
39 2365 1 2365 79 79 191778 191778 15150462 700368
40 4069 0 0 145 0 79804 0 11571580 225986
41 7710 0 0 816 0 128294 0 104687904 348695
42 13718 0 0 61 0 96448 0 5883328 373683
43 4525 0 0 226 0 93811 0 21201286 501709
44 6869 0 0 105 0 117520 0 12339600 413743
45 4628 0 0 62 0 69159 0 4287858 379825
46 3653 1 3653 24 24 101792 101792 2443008 336260
47 1265 1 1265 26 26 210568 210568 5474768 636765
48 7489 1 7489 322 322 136996 136996 44112712 481231
49 4901 0 0 84 0 121920 0 10241280 469107
50 2284 0 0 33 0 76403 0 2521299 211928
51 3160 1 3160 108 108 108094 108094 11674152 563925
52 4150 1 4150 150 150 134759 134759 20213850 511939
53 7285 1 7285 115 115 188873 188873 21720395 521016
54 1134 1 1134 162 162 146216 146216 23686992 543856
55 4658 1 4658 158 158 156608 156608 24744064 329304
56 2384 0 0 97 0 61348 0 5950756 423262
57 3748 0 0 9 0 50350 0 453150 509665
58 5371 0 0 66 0 87720 0 5789520 455881
59 1285 0 0 107 0 99489 0 10645323 367772
60 9327 1 9327 101 101 87419 87419 8829319 406339
61 5565 1 5565 47 47 94355 94355 4434685 493408
62 1528 0 0 38 0 60326 0 2292388 232942
63 3122 1 3122 34 34 94670 94670 3218780 416002
64 7317 1 7317 84 84 82425 82425 6923700 337430
65 2675 0 0 79 0 59017 0 4662343 361517
66 13253 0 0 947 0 90829 0 86015063 360962
67 880 0 0 74 0 80791 0 5978534 235561
68 2053 1 2053 53 53 100423 100423 5322419 408247
69 1424 0 0 94 0 131116 0 12324904 450296
70 4036 1 4036 63 63 100269 100269 6316947 418799
71 3045 1 3045 58 58 27330 27330 1585140 247405
72 5119 0 0 49 0 39039 0 1912911 378519
73 1431 0 0 34 0 106885 0 3634090 326638
74 554 0 0 11 0 79285 0 872135 328233
75 1975 0 0 35 0 118881 0 4160835 386225
76 1286 1 1286 17 17 77623 77623 1319591 283662
77 1012 0 0 47 0 114768 0 5394096 370225
78 810 0 0 43 0 74015 0 3182645 269236
79 1280 0 0 117 0 69465 0 8127405 365732
80 666 1 666 171 171 117869 117869 20155599 420383
81 1380 0 0 26 0 60982 0 1585532 345811
82 4608 1 4608 73 73 90131 90131 6579563 431809
83 876 0 0 59 0 138971 0 8199289 418876
84 814 0 0 18 0 39625 0 713250 297476
85 514 0 0 15 0 102725 0 1540875 416776
86 5692 1 5692 72 72 64239 64239 4625208 357257
87 3642 0 0 86 0 90262 0 7762532 458343
88 540 0 0 14 0 103960 0 1455440 388386
89 2099 0 0 64 0 106611 0 6823104 358934
90 567 0 0 11 0 103345 0 1136795 407560
91 2001 0 0 52 0 95551 0 4968652 392558
92 2949 1 2949 41 41 82903 82903 3399023 373177
93 2253 0 0 99 0 63593 0 6295707 428370
94 6533 1 6533 75 75 126910 126910 9518250 369419
95 1889 0 0 45 0 37527 0 1688715 358649
96 3055 1 3055 43 43 60247 60247 2590621 376641
97 272 0 0 8 0 112995 0 903960 467427
98 1414 1 1414 198 198 70184 70184 13896432 364885
99 2564 0 0 22 0 130140 0 2863080 436230
100 1383 1 1383 11 11 73221 73221 805431 329118
> k <- length(x[1,])
> df <- as.data.frame(x)
> (mylm <- lm(df))
Call:
lm(formula = df)
Coefficients:
(Intercept) Group GrCosts Trades GrTrades Dividends
2.064e+03 -1.191e+04 1.219e+00 7.526e+01 -3.277e+01 2.021e-02
GrDiv TrDiv `Wealth\r`
6.061e-02 -4.116e-04 -1.129e-03
> (mysum <- summary(mylm))
Call:
lm(formula = df)
Residuals:
Min 1Q Median 3Q Max
-26106.7 -3736.2 -529.6 1887.8 31281.0
Coefficients:
Estimate Std. Error t value Pr(>|t|)
(Intercept) 2.064e+03 2.550e+03 0.809 0.42042
Group -1.191e+04 3.855e+03 -3.090 0.00265 **
GrCosts 1.219e+00 1.106e-01 11.021 < 2e-16 ***
Trades 7.526e+01 9.707e+00 7.754 1.24e-11 ***
GrTrades -3.277e+01 1.345e+01 -2.437 0.01677 *
Dividends 2.021e-02 2.208e-02 0.915 0.36239
GrDiv 6.061e-02 3.248e-02 1.866 0.06524 .
TrDiv -4.116e-04 8.560e-05 -4.809 5.97e-06 ***
`Wealth\r` -1.129e-03 1.909e-03 -0.591 0.55575
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
Residual standard error: 7801 on 91 degrees of freedom
Multiple R-squared: 0.8827, Adjusted R-squared: 0.8723
F-statistic: 85.56 on 8 and 91 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,] 0.9824120 3.517590e-02 1.758795e-02
[2,] 0.9650577 6.988458e-02 3.494229e-02
[3,] 0.9997172 5.655983e-04 2.827991e-04
[4,] 0.9994049 1.190124e-03 5.950621e-04
[5,] 0.9999224 1.551078e-04 7.755392e-05
[6,] 0.9999142 1.716411e-04 8.582054e-05
[7,] 0.9997995 4.010429e-04 2.005214e-04
[8,] 0.9995851 8.298922e-04 4.149461e-04
[9,] 0.9999997 5.615008e-07 2.807504e-07
[10,] 0.9999995 9.029213e-07 4.514606e-07
[11,] 0.9999990 1.997388e-06 9.986940e-07
[12,] 0.9999994 1.204480e-06 6.022398e-07
[13,] 1.0000000 1.276981e-08 6.384906e-09
[14,] 1.0000000 1.250621e-08 6.253105e-09
[15,] 1.0000000 6.667993e-10 3.333996e-10
[16,] 1.0000000 1.807156e-09 9.035780e-10
[17,] 1.0000000 2.927443e-10 1.463721e-10
[18,] 1.0000000 6.312813e-10 3.156406e-10
[19,] 1.0000000 2.352007e-13 1.176004e-13
[20,] 1.0000000 4.737396e-13 2.368698e-13
[21,] 1.0000000 1.469198e-12 7.345990e-13
[22,] 1.0000000 3.438214e-12 1.719107e-12
[23,] 1.0000000 9.562464e-12 4.781232e-12
[24,] 1.0000000 2.112782e-11 1.056391e-11
[25,] 1.0000000 5.807655e-17 2.903827e-17
[26,] 1.0000000 6.600830e-18 3.300415e-18
[27,] 1.0000000 2.438058e-17 1.219029e-17
[28,] 1.0000000 9.427599e-17 4.713800e-17
[29,] 1.0000000 6.589168e-17 3.294584e-17
[30,] 1.0000000 7.638395e-21 3.819198e-21
[31,] 1.0000000 3.570160e-31 1.785080e-31
[32,] 1.0000000 6.750693e-31 3.375346e-31
[33,] 1.0000000 3.837637e-33 1.918819e-33
[34,] 1.0000000 2.085987e-33 1.042993e-33
[35,] 1.0000000 1.780774e-32 8.903868e-33
[36,] 1.0000000 1.416503e-31 7.082516e-32
[37,] 1.0000000 9.923014e-31 4.961507e-31
[38,] 1.0000000 2.604958e-31 1.302479e-31
[39,] 1.0000000 6.648118e-31 3.324059e-31
[40,] 1.0000000 4.191627e-30 2.095814e-30
[41,] 1.0000000 3.558324e-29 1.779162e-29
[42,] 1.0000000 3.480722e-28 1.740361e-28
[43,] 1.0000000 1.722359e-27 8.611796e-28
[44,] 1.0000000 1.466102e-26 7.330508e-27
[45,] 1.0000000 6.231919e-26 3.115960e-26
[46,] 1.0000000 4.592221e-25 2.296111e-25
[47,] 1.0000000 1.308366e-26 6.541831e-27
[48,] 1.0000000 5.421719e-26 2.710859e-26
[49,] 1.0000000 5.736040e-25 2.868020e-25
[50,] 1.0000000 4.685356e-24 2.342678e-24
[51,] 1.0000000 3.842190e-23 1.921095e-23
[52,] 1.0000000 3.607127e-22 1.803563e-22
[53,] 1.0000000 3.419119e-21 1.709559e-21
[54,] 1.0000000 2.724283e-20 1.362142e-20
[55,] 1.0000000 2.036846e-20 1.018423e-20
[56,] 1.0000000 1.669042e-19 8.345209e-20
[57,] 1.0000000 1.646164e-18 8.230820e-19
[58,] 1.0000000 1.145166e-17 5.725829e-18
[59,] 1.0000000 1.096722e-16 5.483609e-17
[60,] 1.0000000 8.860304e-16 4.430152e-16
[61,] 1.0000000 7.145459e-18 3.572729e-18
[62,] 1.0000000 7.369305e-17 3.684652e-17
[63,] 1.0000000 8.680714e-16 4.340357e-16
[64,] 1.0000000 5.693829e-15 2.846915e-15
[65,] 1.0000000 6.017806e-14 3.008903e-14
[66,] 1.0000000 6.613191e-13 3.306595e-13
[67,] 1.0000000 7.451589e-12 3.725794e-12
[68,] 1.0000000 1.064350e-11 5.321751e-12
[69,] 1.0000000 1.379150e-10 6.895751e-11
[70,] 1.0000000 1.572623e-09 7.863117e-10
[71,] 1.0000000 1.836378e-08 9.181889e-09
[72,] 1.0000000 3.029581e-08 1.514791e-08
[73,] 0.9999998 4.031531e-07 2.015765e-07
[74,] 0.9999980 4.061463e-06 2.030731e-06
[75,] 0.9999774 4.521410e-05 2.260705e-05
[76,] 0.9998091 3.817863e-04 1.908931e-04
[77,] 0.9988151 2.369816e-03 1.184908e-03
> postscript(file="/var/www/rcomp/tmp/12rra1293220729.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$resid)
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/rcomp/tmp/22rra1293220729.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> plot(mysum$resid, type='b', pch=19, main='Residuals', ylab='value of Residuals', xlab='time or index')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/rcomp/tmp/3v08v1293220729.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> hist(mysum$resid, main='Residual Histogram', xlab='values of Residuals')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/rcomp/tmp/4v08v1293220729.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> densityplot(~mysum$resid,col='black',main='Residual Density Plot', xlab='values of Residuals')
> dev.off()
null device
1
> postscript(file="/var/www/rcomp/tmp/5v08v1293220729.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 = 100
Frequency = 1
1 2 3 4 5 6
13051.52696 -1124.21050 -7627.46946 31281.04033 -7772.98108 -6707.49428
7 8 9 10 11 12
27224.07641 1954.41958 -10214.67691 1568.22664 23149.24307 4652.19458
13 14 15 16 17 18
-2631.91642 24914.97468 -3785.53264 1373.96976 4852.88201 -775.49395
19 20 21 22 23 24
-6990.17926 4575.42871 320.06890 -1491.21784 7983.31250 4001.64656
25 26 27 28 29 30
771.77925 9945.94392 -4357.42987 533.57528 4443.85320 -7889.03681
31 32 33 34 35 36
2661.08257 -524.07378 2265.81325 1260.00347 -3937.11627 9719.22910
37 38 39 40 41 42
3678.17907 687.92898 -2496.66209 -5502.39391 -14874.84913 7957.61861
43 44 45 46 47 48
-7150.62075 73.96513 -1305.88705 1189.46245 -5577.03763 2157.90663
49 50 51 52 53 54
-1203.66476 -2530.40680 1275.32003 575.42536 -2366.18971 1265.08244
55 56 57 58 59 60
17.08619 -5292.68663 751.36439 -535.09226 -6045.44397 545.54886
61 62 63 64 65 66
1392.09888 -3408.27182 1865.65092 1249.10402 -4199.89664 -26106.72872
67 68 69 70 71 72
-5659.10609 1684.33946 -4782.71933 1259.28948 5442.17621 -206.74883
73 74 75 76 77 78
-3487.20313 -3210.39347 -2976.82891 3436.28512 -4270.27049 -4371.83741
79 80 81 82 83 84
-7234.99469 1682.94444 -2829.89449 1651.33511 -4588.98604 -2775.74455
85 86 87 88 89 90
-3649.97775 2660.59444 -3005.80419 -3640.89931 -3722.39842 -3485.19414
91 92 93 94 95 96
-3419.07939 2582.87873 -5471.82927 -688.04505 -3219.85467 3976.89022
97 98 99 100
-3777.70127 1586.64096 -2114.71519 3865.48014
> postscript(file="/var/www/rcomp/tmp/6osqy1293220729.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 = 100
Frequency = 1
lag(myerror, k = 1) myerror
0 13051.52696 NA
1 -1124.21050 13051.52696
2 -7627.46946 -1124.21050
3 31281.04033 -7627.46946
4 -7772.98108 31281.04033
5 -6707.49428 -7772.98108
6 27224.07641 -6707.49428
7 1954.41958 27224.07641
8 -10214.67691 1954.41958
9 1568.22664 -10214.67691
10 23149.24307 1568.22664
11 4652.19458 23149.24307
12 -2631.91642 4652.19458
13 24914.97468 -2631.91642
14 -3785.53264 24914.97468
15 1373.96976 -3785.53264
16 4852.88201 1373.96976
17 -775.49395 4852.88201
18 -6990.17926 -775.49395
19 4575.42871 -6990.17926
20 320.06890 4575.42871
21 -1491.21784 320.06890
22 7983.31250 -1491.21784
23 4001.64656 7983.31250
24 771.77925 4001.64656
25 9945.94392 771.77925
26 -4357.42987 9945.94392
27 533.57528 -4357.42987
28 4443.85320 533.57528
29 -7889.03681 4443.85320
30 2661.08257 -7889.03681
31 -524.07378 2661.08257
32 2265.81325 -524.07378
33 1260.00347 2265.81325
34 -3937.11627 1260.00347
35 9719.22910 -3937.11627
36 3678.17907 9719.22910
37 687.92898 3678.17907
38 -2496.66209 687.92898
39 -5502.39391 -2496.66209
40 -14874.84913 -5502.39391
41 7957.61861 -14874.84913
42 -7150.62075 7957.61861
43 73.96513 -7150.62075
44 -1305.88705 73.96513
45 1189.46245 -1305.88705
46 -5577.03763 1189.46245
47 2157.90663 -5577.03763
48 -1203.66476 2157.90663
49 -2530.40680 -1203.66476
50 1275.32003 -2530.40680
51 575.42536 1275.32003
52 -2366.18971 575.42536
53 1265.08244 -2366.18971
54 17.08619 1265.08244
55 -5292.68663 17.08619
56 751.36439 -5292.68663
57 -535.09226 751.36439
58 -6045.44397 -535.09226
59 545.54886 -6045.44397
60 1392.09888 545.54886
61 -3408.27182 1392.09888
62 1865.65092 -3408.27182
63 1249.10402 1865.65092
64 -4199.89664 1249.10402
65 -26106.72872 -4199.89664
66 -5659.10609 -26106.72872
67 1684.33946 -5659.10609
68 -4782.71933 1684.33946
69 1259.28948 -4782.71933
70 5442.17621 1259.28948
71 -206.74883 5442.17621
72 -3487.20313 -206.74883
73 -3210.39347 -3487.20313
74 -2976.82891 -3210.39347
75 3436.28512 -2976.82891
76 -4270.27049 3436.28512
77 -4371.83741 -4270.27049
78 -7234.99469 -4371.83741
79 1682.94444 -7234.99469
80 -2829.89449 1682.94444
81 1651.33511 -2829.89449
82 -4588.98604 1651.33511
83 -2775.74455 -4588.98604
84 -3649.97775 -2775.74455
85 2660.59444 -3649.97775
86 -3005.80419 2660.59444
87 -3640.89931 -3005.80419
88 -3722.39842 -3640.89931
89 -3485.19414 -3722.39842
90 -3419.07939 -3485.19414
91 2582.87873 -3419.07939
92 -5471.82927 2582.87873
93 -688.04505 -5471.82927
94 -3219.85467 -688.04505
95 3976.89022 -3219.85467
96 -3777.70127 3976.89022
97 1586.64096 -3777.70127
98 -2114.71519 1586.64096
99 3865.48014 -2114.71519
100 NA 3865.48014
> dum1 <- dum[2:length(myerror),]
> dum1
lag(myerror, k = 1) myerror
[1,] -1124.21050 13051.52696
[2,] -7627.46946 -1124.21050
[3,] 31281.04033 -7627.46946
[4,] -7772.98108 31281.04033
[5,] -6707.49428 -7772.98108
[6,] 27224.07641 -6707.49428
[7,] 1954.41958 27224.07641
[8,] -10214.67691 1954.41958
[9,] 1568.22664 -10214.67691
[10,] 23149.24307 1568.22664
[11,] 4652.19458 23149.24307
[12,] -2631.91642 4652.19458
[13,] 24914.97468 -2631.91642
[14,] -3785.53264 24914.97468
[15,] 1373.96976 -3785.53264
[16,] 4852.88201 1373.96976
[17,] -775.49395 4852.88201
[18,] -6990.17926 -775.49395
[19,] 4575.42871 -6990.17926
[20,] 320.06890 4575.42871
[21,] -1491.21784 320.06890
[22,] 7983.31250 -1491.21784
[23,] 4001.64656 7983.31250
[24,] 771.77925 4001.64656
[25,] 9945.94392 771.77925
[26,] -4357.42987 9945.94392
[27,] 533.57528 -4357.42987
[28,] 4443.85320 533.57528
[29,] -7889.03681 4443.85320
[30,] 2661.08257 -7889.03681
[31,] -524.07378 2661.08257
[32,] 2265.81325 -524.07378
[33,] 1260.00347 2265.81325
[34,] -3937.11627 1260.00347
[35,] 9719.22910 -3937.11627
[36,] 3678.17907 9719.22910
[37,] 687.92898 3678.17907
[38,] -2496.66209 687.92898
[39,] -5502.39391 -2496.66209
[40,] -14874.84913 -5502.39391
[41,] 7957.61861 -14874.84913
[42,] -7150.62075 7957.61861
[43,] 73.96513 -7150.62075
[44,] -1305.88705 73.96513
[45,] 1189.46245 -1305.88705
[46,] -5577.03763 1189.46245
[47,] 2157.90663 -5577.03763
[48,] -1203.66476 2157.90663
[49,] -2530.40680 -1203.66476
[50,] 1275.32003 -2530.40680
[51,] 575.42536 1275.32003
[52,] -2366.18971 575.42536
[53,] 1265.08244 -2366.18971
[54,] 17.08619 1265.08244
[55,] -5292.68663 17.08619
[56,] 751.36439 -5292.68663
[57,] -535.09226 751.36439
[58,] -6045.44397 -535.09226
[59,] 545.54886 -6045.44397
[60,] 1392.09888 545.54886
[61,] -3408.27182 1392.09888
[62,] 1865.65092 -3408.27182
[63,] 1249.10402 1865.65092
[64,] -4199.89664 1249.10402
[65,] -26106.72872 -4199.89664
[66,] -5659.10609 -26106.72872
[67,] 1684.33946 -5659.10609
[68,] -4782.71933 1684.33946
[69,] 1259.28948 -4782.71933
[70,] 5442.17621 1259.28948
[71,] -206.74883 5442.17621
[72,] -3487.20313 -206.74883
[73,] -3210.39347 -3487.20313
[74,] -2976.82891 -3210.39347
[75,] 3436.28512 -2976.82891
[76,] -4270.27049 3436.28512
[77,] -4371.83741 -4270.27049
[78,] -7234.99469 -4371.83741
[79,] 1682.94444 -7234.99469
[80,] -2829.89449 1682.94444
[81,] 1651.33511 -2829.89449
[82,] -4588.98604 1651.33511
[83,] -2775.74455 -4588.98604
[84,] -3649.97775 -2775.74455
[85,] 2660.59444 -3649.97775
[86,] -3005.80419 2660.59444
[87,] -3640.89931 -3005.80419
[88,] -3722.39842 -3640.89931
[89,] -3485.19414 -3722.39842
[90,] -3419.07939 -3485.19414
[91,] 2582.87873 -3419.07939
[92,] -5471.82927 2582.87873
[93,] -688.04505 -5471.82927
[94,] -3219.85467 -688.04505
[95,] 3976.89022 -3219.85467
[96,] -3777.70127 3976.89022
[97,] 1586.64096 -3777.70127
[98,] -2114.71519 1586.64096
[99,] 3865.48014 -2114.71519
> z <- as.data.frame(dum1)
> z
lag(myerror, k = 1) myerror
1 -1124.21050 13051.52696
2 -7627.46946 -1124.21050
3 31281.04033 -7627.46946
4 -7772.98108 31281.04033
5 -6707.49428 -7772.98108
6 27224.07641 -6707.49428
7 1954.41958 27224.07641
8 -10214.67691 1954.41958
9 1568.22664 -10214.67691
10 23149.24307 1568.22664
11 4652.19458 23149.24307
12 -2631.91642 4652.19458
13 24914.97468 -2631.91642
14 -3785.53264 24914.97468
15 1373.96976 -3785.53264
16 4852.88201 1373.96976
17 -775.49395 4852.88201
18 -6990.17926 -775.49395
19 4575.42871 -6990.17926
20 320.06890 4575.42871
21 -1491.21784 320.06890
22 7983.31250 -1491.21784
23 4001.64656 7983.31250
24 771.77925 4001.64656
25 9945.94392 771.77925
26 -4357.42987 9945.94392
27 533.57528 -4357.42987
28 4443.85320 533.57528
29 -7889.03681 4443.85320
30 2661.08257 -7889.03681
31 -524.07378 2661.08257
32 2265.81325 -524.07378
33 1260.00347 2265.81325
34 -3937.11627 1260.00347
35 9719.22910 -3937.11627
36 3678.17907 9719.22910
37 687.92898 3678.17907
38 -2496.66209 687.92898
39 -5502.39391 -2496.66209
40 -14874.84913 -5502.39391
41 7957.61861 -14874.84913
42 -7150.62075 7957.61861
43 73.96513 -7150.62075
44 -1305.88705 73.96513
45 1189.46245 -1305.88705
46 -5577.03763 1189.46245
47 2157.90663 -5577.03763
48 -1203.66476 2157.90663
49 -2530.40680 -1203.66476
50 1275.32003 -2530.40680
51 575.42536 1275.32003
52 -2366.18971 575.42536
53 1265.08244 -2366.18971
54 17.08619 1265.08244
55 -5292.68663 17.08619
56 751.36439 -5292.68663
57 -535.09226 751.36439
58 -6045.44397 -535.09226
59 545.54886 -6045.44397
60 1392.09888 545.54886
61 -3408.27182 1392.09888
62 1865.65092 -3408.27182
63 1249.10402 1865.65092
64 -4199.89664 1249.10402
65 -26106.72872 -4199.89664
66 -5659.10609 -26106.72872
67 1684.33946 -5659.10609
68 -4782.71933 1684.33946
69 1259.28948 -4782.71933
70 5442.17621 1259.28948
71 -206.74883 5442.17621
72 -3487.20313 -206.74883
73 -3210.39347 -3487.20313
74 -2976.82891 -3210.39347
75 3436.28512 -2976.82891
76 -4270.27049 3436.28512
77 -4371.83741 -4270.27049
78 -7234.99469 -4371.83741
79 1682.94444 -7234.99469
80 -2829.89449 1682.94444
81 1651.33511 -2829.89449
82 -4588.98604 1651.33511
83 -2775.74455 -4588.98604
84 -3649.97775 -2775.74455
85 2660.59444 -3649.97775
86 -3005.80419 2660.59444
87 -3640.89931 -3005.80419
88 -3722.39842 -3640.89931
89 -3485.19414 -3722.39842
90 -3419.07939 -3485.19414
91 2582.87873 -3419.07939
92 -5471.82927 2582.87873
93 -688.04505 -5471.82927
94 -3219.85467 -688.04505
95 3976.89022 -3219.85467
96 -3777.70127 3976.89022
97 1586.64096 -3777.70127
98 -2114.71519 1586.64096
99 3865.48014 -2114.71519
> 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/www/rcomp/tmp/7osqy1293220729.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> acf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/rcomp/tmp/8yjo01293220729.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> pacf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Partial Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/rcomp/tmp/9yjo01293220729.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> opar <- par(mfrow = c(2,2), oma = c(0, 0, 1.1, 0))
> plot(mylm, las = 1, sub='Residual Diagnostics')
> par(opar)
> dev.off()
null device
1
> if (n > n25) {
+ postscript(file="/var/www/rcomp/tmp/10yjo01293220729.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
+ plot(kp3:nmkm3,gqarr[,2], main='Goldfeld-Quandt test',ylab='2-sided p-value',xlab='breakpoint')
+ grid()
+ dev.off()
+ }
null device
1
>
> #Note: the /var/www/rcomp/createtable file can be downloaded at http://www.wessa.net/cretab
> load(file="/var/www/rcomp/createtable")
>
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a, 'Multiple Linear Regression - Estimated Regression Equation', 1, TRUE)
> a<-table.row.end(a)
> myeq <- colnames(x)[1]
> myeq <- paste(myeq, '[t] = ', sep='')
> for (i in 1:k){
+ if (mysum$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/www/rcomp/tmp/11k15o1293220729.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/www/rcomp/tmp/12524c1293220729.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/www/rcomp/tmp/13u31o1293220729.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/www/rcomp/tmp/145ui91293220729.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/www/rcomp/tmp/158vyx1293220729.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/www/rcomp/tmp/164n0g1293220730.tab")
+ }
>
> try(system("convert tmp/12rra1293220729.ps tmp/12rra1293220729.png",intern=TRUE))
character(0)
> try(system("convert tmp/22rra1293220729.ps tmp/22rra1293220729.png",intern=TRUE))
character(0)
> try(system("convert tmp/3v08v1293220729.ps tmp/3v08v1293220729.png",intern=TRUE))
character(0)
> try(system("convert tmp/4v08v1293220729.ps tmp/4v08v1293220729.png",intern=TRUE))
character(0)
> try(system("convert tmp/5v08v1293220729.ps tmp/5v08v1293220729.png",intern=TRUE))
character(0)
> try(system("convert tmp/6osqy1293220729.ps tmp/6osqy1293220729.png",intern=TRUE))
character(0)
> try(system("convert tmp/7osqy1293220729.ps tmp/7osqy1293220729.png",intern=TRUE))
character(0)
> try(system("convert tmp/8yjo01293220729.ps tmp/8yjo01293220729.png",intern=TRUE))
character(0)
> try(system("convert tmp/9yjo01293220729.ps tmp/9yjo01293220729.png",intern=TRUE))
character(0)
> try(system("convert tmp/10yjo01293220729.ps tmp/10yjo01293220729.png",intern=TRUE))
character(0)
>
>
> proc.time()
user system elapsed
3.840 0.830 4.645