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sde (version 2.0.20)

Simulation and Inference for Stochastic Differential Equations

Description

Description: Provides functions for simulation and inference for stochastic differential equations (SDEs). It accompanies the book "Simulation and Inference for Stochastic Differential Equations: With R Examples" (Iacus, 2008, Springer; ISBN: 978-0-387-75838-1).

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Version

Install

install.packages('sde')

Monthly Downloads

6,064

Version

2.0.20

License

GPL (>= 2)

Maintainer

Stefano M. Iacus

Last Published

December 22nd, 2025

Functions in sde (2.0.20)

Nonparametric invariant density, drift, and diffusion coefficient estimation

Akaike's information criterion for diffusion processes

Simple estimating functions of types I and II

Simple estimating function based on the infinitesimal generator a the diffusion process

Conditional law of the Cox-Ingersoll-Ross process

Cox-Ingersoll-Ross process stationary law

Ornstein-Uhlenbeck or Vasicek process conditional law

Phi-Divergences test for diffusion processes

Ornstein-Uhlenbeck or Vasicek process stationary law

Simulation of stochastic differential equation

Pedersen's approximation of the likelihood

Ait-Sahalia Hermite polynomial expansion approximation of the likelihood

Simulation of diffusion bridge

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

Approximated conditional law of a diffusion process

Brownian motion, Brownian bridge, and geometric Brownian motion simulators

Linear martingale estimating function

Daily closings of 20 financial time series from 2006-01-03 to 2007-12-31

Black-Scholes-Merton or geometric Brownian motion process conditional law

Euler approximation of the likelihood

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

Volatility change-point estimator for diffusion processes

Weekly closings of the Dow-Jones industrial average

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

Pedersen's simulated transition density

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

Generalized method of moments estimator

Markov Operator distance for clustering diffusion processes.