dcKessler {sde}R Documentation

Approximated conditional law of a diffusion process by Kessler's method

Description

Approximated conditional densities for X(t) | X(t0) = x0 of a diffusion process.

Usage

dcKessler(x, t, x0, t0, theta, d, dx, dxx, s, sx, sxx, 
          log=FALSE) 

Arguments

x vector of quantiles.
t lag or time.
x0 the value of the process at time t0; see details.
t0 initial time.
theta parameter of the process; see details.
log logical; if TRUE, probabilities p are given as log(p).
d drift coefficient as a function; see details.
dx partial derivative w.r.t. x of the drift coefficient; see details.
dxx second partial derivative wrt x^2 of the drift coefficient; see details.
s diffusion coefficient as a function; see details.
sx partial derivative w.r.t. x of the diffusion coefficient; see details.
sxx second partial derivative w.r.t. x^2 of the diffusion coefficient; see details.

Details

This function returns the value of the conditional density of X(t) | X(t0) = x0 at point x.

All the functions d, dx, dxx, dt, s, sx, and sxx must be functions of t, x, and theta.

Value

x a numeric vector

Author(s)

Stefano Maria Iacus

References

Kessler, M. (1997) Estimation of an ergodic diffusion from discrete observations, Scand. J. Statist., 24, 211-229.


[Package sde version 2.0.4 Index]