Package: msde 1.0.5

msde: Bayesian Inference for Multivariate Stochastic Differential Equations

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'.

Authors:Martin Lysy [aut, cre], Feiyu Zhu [aut], JunYong Tong [aut], Trevor Kitt [ctb], Nigel Delaney [ctb]

msde_1.0.5.tar.gz
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msde_1.0.5.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
DESCRIPTION
card.svg |card.png
msde/json (API)

# Install 'msde' in R:
install.packages('msde', repos = c('https://mlysy.r-universe.dev', 'https://cloud.r-project.org'))

Bug tracker:https://github.com/mlysy/msde/issues

Uses libs:
  • c++– GNU Standard C++ Library v3

On CRAN:

Conda:

cpp

5.02 score 35 scripts 342 downloads 13 exports 3 dependencies

Last updated from:2774ebd9f2. Checks:13 OK. Indexed: yes.

TargetResultTimeFilesSyslog
linux-devel-arm64OK204
linux-devel-x86_64OK167
source / vignettesOK203
linux-release-arm64OK171
linux-release-x86_64OK213
macos-release-arm64OK160
macos-release-x86_64OK252
macos-oldrel-arm64OK146
macos-oldrel-x86_64OK208
windows-develOK155
windows-releaseOK146
windows-oldrelOK138
wasm-releaseOK137

Exports:mou.loglikmvn.hyper.checksde.diffsde.driftsde.examplessde.initsde.logliksde.make.modelsde.postsde.priorsde.simsde.valid.datasde.valid.params

Dependencies:RcppRcppProgresswhisker

Example SDE models provided by msde
Heston's stochastic volatility model | Bivariate Ornstein-Uhlenbeck process | Lotka-Volterra predator-prey model | Prokaryotic autoregulatory gene network model | References
Rendered frommsde-exmodels.Rmdusingknitr::rmarkdown

Last update: 2021-12-17
Started: 2017-07-04

Inference for Multivariate Stochastic Differential Equations with msde
Introduction | Creating an sde.model object | The sdeModel class definition | Compiling and checking the sde.model object | Simulating trajectories from the Lotka-Volterra model | Inference for multivariate SDE models | Missing data specification with sde.init() | Default prior specification | Default prior | Custom prior specification | The sdePrior class definition | Formatting the R input to the C++ code | Compiling and checking the prior | Installation | Enable C++ compiling for R | Optimize settings for the C++ compiler (optional) | Enable OpenMP support (optional) | References
Rendered frommsde-quicktut.Rmdusingknitr::rmarkdown

Last update: 2021-12-17
Started: 2017-06-14