https://github.com/cran/tseries
Tip revision: b205accc3a9288787565b1430963919f333d4bc9 authored by Kurt Hornik on 07 February 2011, 00:00:00 UTC
version 0.10-25
version 0.10-25
Tip revision: b205acc
boot.c
/* Copyright (C) 1997-1999 Adrian Trapletti
This library is free software; you can redistribute it and/or
modify it under the terms of the GNU Library General Public
License as published by the Free Software Foundation; either
version 2 of the License, or (at your option) any later version.
This library is distributed in the hope that it will be useful,
but WITHOUT ANY WARRANTY; without even the implied warranty of
MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU
Library General Public License for more details.
You should have received a copy of the GNU Library General Public
License along with this library; if not, write to the Free
Foundation, Inc., 59 Temple Place, Suite 330, Boston, MA 02111-1307 USA
time series bootstrap functions */
#include <math.h>
#include <R.h>
static int geodev (double p)
/* Return geometric distributed random deviate with p(i) = p*(1-p)^i,
where 0<p<1 and i=0,1,..
See Fishman, G. S., 1996, Monte Carlo (Springer, NY, Berlin, Heidelberg), 221. */
{
double b, y, z;
b = (-1.0)/log(1.0-p);
y = exp_rand();
z = b*y;
return (int)z;
}
static int disuni (int n)
/* Return discrete uniform distributed random deviate on {1,..,n} */
{
double temp;
temp = unif_rand()*(double)n+1.0;
return (int)temp;
}
static int WRAP (int i, int n)
/* WRAP (i=..,-n+1,..,-1,0,1,..,n,n+1,.., n) = ..,1,..,n-1,n,1,..,n,1,.. */
{
if (i < 1)
return i%n+n;
else if (i > n)
return (i-1)%n+1;
else
return i;
}
static void StatBoot (double x[], double xBoot[], int n, double p)
/* Generates a bootstrap sample xBoot[1..n] from x[1..n]
according to the stationary bootstrap resampling scheme
(Politis, D. N. and Romano, J. P., 1994, The Stationary Bootstrap,
J. Amer. Statist. Assoc. 89, 1303-1313).
Input is n, x[1..n], xBoot[1..n] and p, the parameter for
the geometric distribution, output xBoot[1..n]. */
{
int i, j, I, L;
i = 1;
while (i <= n)
{
I = disuni(n);
L = geodev(p);
j = 0;
while ((j < L) && (i <= n))
{
xBoot[i] = x[WRAP(I+j,n)];
i++;
j++;
}
}
}
static void BlockBoot (double x[], double xBoot[], int n, int L)
/* Generates a bootstrap sample xBoot[1..n] from x[1..n]
according to the blockwise bootstrap resampling scheme
(Kuensch, H. R., 1989, The Jackknife and the Bootstrap
for General Stationary Observations, Ann. Stat. 17, 1217-1241).
Input is n, x[1..n], xBoot[1..n] and L, the blocklength,
output xBoot[1..n]. */
{
int i, j, I;
i = 1;
while (i <= n)
{
I = disuni(n-L+1);
j = 0;
while ((j < L) && (i <= n))
{
xBoot[i] = x[I+j];
i++;
j++;
}
}
}
void boot (double *x, double *xb, int *n, double *b, int *type)
{
GetRNGstate();
if (*type == 0) StatBoot (x-1, xb-1, *n, *b);
else if (*type == 1) BlockBoot (x-1, xb-1, *n, (int)*b);
else error ("this type of bootstrap is not yet implemented\n");
PutRNGstate();
}