dcShoji {sde}R Documentation

Approximated conditional law of a diffusion process by Shoji-Ozaki method

Description

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

Usage

dcShoji(x, t, x0, t0, theta, d, dx, dxx, dt, s, 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.
dt partial derivative wrt t of the drift coefficient. See details.
s diffusion coefficient as a function. 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 and s must be functions of t0, x0 and theta.

Value

x a numeric vector

Note

This package is a companion to the book Simulation and Inference for Stochastic Differential Equation, Springer, NY.

Author(s)

Stefano Maria Iacus

References

Shoji, L., Ozaki, T. (1998) Estimation for nonlinear stochastic differential equations by a local linearization method, Stochastic Analysis and Applications, 16, 733-752.


[Package sde version 1.9.14 Index]