R package for statistical inference using partially observed Markov processes
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Updated
May 28, 2024 - R
R package for statistical inference using partially observed Markov processes
R Code to accompany "A Note on Efficient Fitting of Stochastic Volatility Models"
Source code and data for the tutorial: "Getting started with particle Metropolis-Hastings for inference in nonlinear models"
R package for Bayesian inference with interacting particle systems
R and C++ codes that can be used to replicate the empirical results obtained in the paper "Time-varying state correlations in state space models and their estimation via indirect inference" by Caterina Schiavoni, Siem Jan Koopman, Franz Palm, Stephan Smeekes and Jan van den Brakel.
a helper package for pomp
R package pmhtutorial available from CRAN.
State-space models for statistical mortality projections
This repository contains code for the paper `Sequential Monte Carlo algorithms for agent-based models of disease transmission' by Nianqiao (Phyllis) Ju, Jeremy Heng and Pierre Jacob.
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