#
#
#  ARFIMA generation
#    For n=40k and ittMax=1000, it takes about 90min
#
#####################################################
library(fracdiff)
library(fGarch)     #- for rstdt() distribution
library(stabledist) #- for rstable() distribution

#- fracdiff has ARMA sign convention as \Phi = 1-p1-p2...  \Th= 1-t1-t2    \Ph(B) X_t = \Th(B) e_t

d      <-     .2
oFile  <- "temp2.Rdata"
n      <- 20000
ittMax <- 1000


ST <- date()
X  <- matrix(0, ittMax, n) 
for (i in 1:ittMax) {
  if (i %% 100==0) { print(i) } 
  #fds.sim  <- fracdiff.sim(n, ar=NULL,  ma=NULL,   d=d, n.start=5000, rand.gen=function(x) rnorm(x, 0, 1) )
  #fds.sim  <- fracdiff.sim(n, ar=c(.5), ma=NULL,   d=d, n.start=5000, rand.gen=function(x) rnorm(x, 0, 1) )
  #fds.sim  <- fracdiff.sim(n, ar=NULL,  ma=NULL,   d=d, n.start=5000, rand.gen=function(x) rstd(x, 0, 1, 40) )
  #fds.sim  <- fracdiff.sim(n, ar=NULL,  ma=NULL,   d=d, n.start=5000, rand.gen=function(x) rstable(x, alpha=1.9,beta=0) )
  fds.sim   <- fracdiff.sim(n, ar=NULL,  ma=NULL,   d=d, n.start=5000, rand.gen=function(x) (rexp(x,1)-1)  )

  X[i,]  <- fds.sim$series
}
                 X_d2 <- X
save(file=oFile, X_d2)



note <- "Std Gaussian ARFIMA(0,d,0) n=80k and ittMax=1000 made by TS-8.txt"
save(file="ARFIMA1d0_n40k.Rdata", X_d1, X_d2, X_d3, X_d4, note)