jarad/tlpl: Tau-leaped particle learning
Tau-leaped particle learning is a sequential Monte Carlo (SMC) approach to Bayesian inference in a Poisson-binomial state-space model, ie. Poisson transitions and binomial observations on those transitions. Tau-leaping provides a discrete approximation to a continuous-time process and particle utilizes analytical tractabilities of the model to provide an efficient algorithm.
Getting started
Browse package contents
Package details |
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| Author | Jarad Niemi |
| Maintainer | Jarad Niemi <niemi@iastate.edu> |
| License | GPL-3 |
| Version | 0.1.1 |
| URL | https://github.com/jarad/tlpl |
| Package repository | View on GitHub |
| Installation |
Install the latest version of this package by entering the following in R:
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