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npfseir

Nested Particle Filter for Stochastic SEIR Epidemic Models

Implements the online Bayesian inference framework for joint state and parameter estimation in a stochastic Susceptible-Exposed-Infectious-Recovered (SEIR) epidemic model with a time-varying transmission rate. The log-transmission rate is modelled as a latent Ornstein-Uhlenbeck (OU) process with exact Gaussian discrete-time transitions. Inference is performed via the nested particle filter (NPF) of Crisan and Miguez (2018) <doi:10.3150/17-BEJ954>, which maintains an outer particle layer over the OU hyperparameters and, for each outer particle, an inner bootstrap filter over epidemic states. The Cori-style renewal-equation estimator follows Cori et al. (2013) <doi:10.1093/aje/kwt133>. The package also provides utilities for simulation, posterior summarisation, and forecasting.

Versions across snapshots

VersionRepositoryFileSize
0.2.1 rolling linux/jammy R-4.5 npfseir_0.2.1.tar.gz 174.3 KiB
0.2.1 rolling linux/noble R-4.5 npfseir_0.2.1.tar.gz 174.2 KiB
0.2.1 rolling source/ R- npfseir_0.2.1.tar.gz 123.1 KiB
0.2.1 latest linux/jammy R-4.5 npfseir_0.2.1.tar.gz 174.3 KiB
0.2.1 latest linux/noble R-4.5 npfseir_0.2.1.tar.gz 174.2 KiB
0.2.1 latest source/ R- npfseir_0.2.1.tar.gz 123.1 KiB
0.2.1 2026-04-26 source/ R- npfseir_0.2.1.tar.gz 123.1 KiB
0.2.1 2026-04-23 source/ R- npfseir_0.2.1.tar.gz 0 B

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