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msde (version 1.0.5)

Bayesian Inference for Multivariate Stochastic Differential Equations

Description

Implements an MCMC sampler for the posterior distribution of arbitrary time-homogeneous multivariate stochastic differential equation (SDE) models with possibly latent components. The package provides a simple entry point to integrate user-defined models directly with the sampler's C++ code, and parallelizes large portions of the calculations when compiled with 'OpenMP'.

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Version

Install

install.packages('msde')

Monthly Downloads

202

Version

1.0.5

License

GPL-3

Maintainer

Martin Lysy

Last Published

December 17th, 2021

Functions in msde (1.0.5)

sde.loglik

SDE loglikelihood function.
sde.make.model

Create an SDE model object.
sde.post

MCMC sampler for the SDE posterior.
sde.examples

Example SDE models.
sde.drift

SDE drift function.
sde.prior

SDE prior function.
sde.sim

Simulation of multivariate SDE trajectories.
sde.valid

SDE data and parameter validators.
msde-package

msde: Bayesian Inference for Multivariate Stochastic Differential Equations
mou.loglik

Loglikelihood for multivariate Ornstein-Uhlenbeck process.
mvn.hyper.check

Argument checking for the default multivariate normal prior.
sde.init

MCMC initialization.
sde.diff

SDE diffusion function.