R : Copyright 2005, The R Foundation for Statistical Computing
Version 2.1.1  (2005-06-20), ISBN 3-900051-07-0

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.

R is a collaborative project with many contributors.
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 a HTML browser interface to help.
Type 'q()' to quit R.

> ### * <HEADER>
> ###
> attach(NULL, name = "CheckExEnv")
> assign(".CheckExEnv", as.environment(2), pos = length(search())) # base
> ## add some hooks to label plot pages for base and grid graphics
> setHook("plot.new", ".newplot.hook")
> setHook("persp", ".newplot.hook")
> setHook("grid.newpage", ".gridplot.hook")
> 
> assign("cleanEx",
+        function(env = .GlobalEnv) {
+ 	   rm(list = ls(envir = env, all.names = TRUE), envir = env)
+            RNGkind("default", "default")
+ 	   set.seed(1)
+    	   options(warn = 1)
+ 	   delayedAssign("T", stop("T used instead of TRUE"),
+ 		  assign.env = .CheckExEnv)
+ 	   delayedAssign("F", stop("F used instead of FALSE"),
+ 		  assign.env = .CheckExEnv)
+ 	   sch <- search()
+ 	   newitems <- sch[! sch %in% .oldSearch]
+ 	   for(item in rev(newitems))
+                eval(substitute(detach(item), list(item=item)))
+ 	   missitems <- .oldSearch[! .oldSearch %in% sch]
+ 	   if(length(missitems))
+ 	       warning("items ", paste(missitems, collapse=", "),
+ 		       " have been removed from the search path")
+        },
+        env = .CheckExEnv)
> assign("..nameEx", "__{must remake R-ex/*.R}__", env = .CheckExEnv) # for now
> assign("ptime", proc.time(), env = .CheckExEnv)
> grDevices::postscript("fracdiff-Examples.ps")
> assign("par.postscript", graphics::par(no.readonly = TRUE), env = .CheckExEnv)
> options(contrasts = c(unordered = "contr.treatment", ordered = "contr.poly"))
> options(warn = 1)    
> library('fracdiff')
> 
> assign(".oldSearch", search(), env = .CheckExEnv)
> assign(".oldNS", loadedNamespaces(), env = .CheckExEnv)
> cleanEx(); ..nameEx <- "fracdiff"
> 
> ### * fracdiff
> 
> flush(stderr()); flush(stdout())
> 
> ### Name: fracdiff
> ### Title: ML Estimates for Fractionally-Differenced ARIMA (p,d,q) models
> ### Aliases: fracdiff
> ### Keywords: ts
> 
> ### ** Examples
> 
> ts.test <- fracdiff.sim( 5000, ar = .2, ma = -.4, d = .3)
> fracdiff( ts.test$series, nar = length(ts.test$ar), nma = length(ts.test$ma))
$log.likelihood
[1] -7228.933

$d
[1] 0.2901102

$ar
[1] 0.2095184

$ma
[1] -0.4063822

$covariance.dpq
                d           ar1           ma1
d    0.0002766653 -0.0003901960 -0.0001066595
ar1 -0.0003901960  0.0011602590  0.0006301288
ma1 -0.0001066595  0.0006301288  0.0005909529

$stderror.dpq
[1] 0.01663326 0.03406257 0.02430952

$correlation.dpq
           [,1]       [,2]       [,3]
[1,]  1.0000000 -0.6886966 -0.2637824
[2,] -0.6886966  1.0000000  0.7609838
[3,] -0.2637824  0.7609838  1.0000000

$h
[1] 7.617972e-05

$d.tol
[1] 0.0001220703

$M
[1] 100

$hessian.dpq
            d       ar1       ma1
d   -9910.447 -5610.440  4193.661
ar1 -5610.440 -5223.828  4557.517
ma1  4193.661  4557.517 -5794.926

$length.w
[1] 25014

> 
> 
> 
> cleanEx(); ..nameEx <- "fracdiff.sim"
> 
> ### * fracdiff.sim
> 
> flush(stderr()); flush(stdout())
> 
> ### Name: fracdiff.sim
> ### Title: Simulate fractional ARIMA Time Series
> ### Aliases: fracdiff.sim
> ### Keywords: ts
> 
> ### ** Examples
> 
> ## Pretty (too) short to "see" the long memory
> fracdiff.sim(100, ar = .2, ma = .4, d = .3)
$series
  [1]  0.23881111 -0.77058664  1.56944453  0.46955593 -0.65866704  0.56022603
  [7]  0.85633192  0.75999222 -0.07255621  1.70478585  0.72601126 -0.26854347
 [13] -1.95074069  1.14336954  0.07771185  0.09074226  1.05358810  1.02797912
 [19]  0.87902437  1.25612190  1.19750080  0.54560747 -1.54212813  0.83600496
 [25]  0.20241969  0.07599861 -1.26409645 -0.42760580  0.42172169  1.41041045
 [31]  0.09498683  0.57956243  0.17870265 -1.16027485 -0.34690184 -0.37167933
 [37] -0.07708237  1.08597823  0.87228625  0.02794560 -0.07612007  0.84521057
 [43]  0.76814146 -0.43174739 -0.53052875  0.46220226  0.89671644  0.08873311
 [49]  1.06826642  0.67098987 -0.31114482  0.56790988 -0.88135265  1.55332601
 [55]  2.24205552  0.08227386 -0.64678862  0.84516271  0.17664792  2.68040789
 [61]  0.46998021  1.17262546  0.56067850 -0.24056761  0.58644768 -1.41504901
 [67]  1.65153451  0.47986235  2.50314512  1.02168014 -0.13577999  1.09144770
 [73] -0.41997327 -0.86549643  0.53439485 -0.18334757  0.20916555  0.28550067
 [79] -0.36913337 -0.40530841 -0.02448992  1.28144130 -1.29475686  0.67357076
 [85]  0.48351171  1.24807387 -0.00811021  0.63228443  0.56244719 -0.23205392
 [91]  1.45339503  1.51957061  1.16184551  2.10370810  1.21237933 -0.60158236
 [97] -0.06402830 -0.80757723 -0.20958069 -0.41743316

$ar
[1] 0.2

$ma
[1] 0.4

$d
[1] 0.3

$mu
[1] 0

$n.start
[1] 6

> 
> ## longer with "extreme" ar:
> r <- fracdiff.sim(n=1500, ar=-0.9, d= 0.3)
> plot(as.ts(r$series))
> 
> 
> 
> cleanEx(); ..nameEx <- "fracdiff.var"
> 
> ### * fracdiff.var
> 
> flush(stderr()); flush(stdout())
> 
> ### Name: fracdiff.var
> ### Title: Recompute Covariance Estimate for fracdiff
> ### Aliases: fracdiff.var
> ### Keywords: ts
> 
> ### ** Examples
> 
> ## Generate a fractionally-differenced ARIMA(1,d,1) model :
> ts.test <- fracdiff.sim(10000, ar = .2, ma = .4, d = .3)
> ## estimate the parameters in an ARIMA(1,d,1) model for the simulated series
> fd.out <- fracdiff(ts.test$ser, nar= 1, nma = 1)
> 
> ## Modify the covariance estimate by changing the finite-difference interval
> fracdiff.var(ts.test$series, fd.out, h = .0001)
$log.likelihood
[1] -14310.08

$d
[1] 0.2575488

$ar
[1] 0.1330638

$ma
[1] 0.2784551

$covariance.dpq
               d         ar1          ma1
d   0.0002518780 0.000668328 0.0009272233
ar1 0.0006683280 0.005961131 0.0065198777
ma1 0.0009272233 0.006519878 0.0074432007

$stderror.dpq
[1] 0.01587066 0.07720836 0.08627399

$correlation.dpq
          [,1]     [,2]      [,3]
[1,] 1.0000000 0.545419 0.6771882
[2,] 0.5454190 1.000000 0.9788029
[3,] 0.6771882 0.978803 1.0000000

$h
[1] 1e-04

$d.tol
[1] 0.0001220703

$M
[1] 100

$hessian.dpq
            d       ar1       ma1
d   -18662.02 -10738.25  11730.97
ar1 -10738.25 -10178.24  10253.33
ma1  11730.97  10253.33 -10577.13

$length.w
[1] 50014

> 
> 
> 
> ### * <FOOTER>
> ###
> cat("Time elapsed: ", proc.time() - get("ptime", env = .CheckExEnv),"\n")
Time elapsed:  3.36 0.02 3.41 0 0 
> grDevices::dev.off()
null device 
          1 
> ###
> ### Local variables: ***
> ### mode: outline-minor ***
> ### outline-regexp: "\\(> \\)?### [*]+" ***
> ### End: ***
> quit('no')