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 intial 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 wrt 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 wrt x of the diffusion coefficient. See details.
sxx second partial derivative wrt 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 1.9.33 Index]