Universal Resampling Routines with Algorithmic Implementation Details

These algorithms are implemented with modular code architecture for straightforward adaptation to diverse problems. The package includes multiple universal resampling methods with full theoretical derivation documented in: Rudolph van der Merwe, Arnaud Doucet, Nando de Freitas, and Eric Wan. The implementation features object-oriented design patterns and parameterized function interfaces for seamless integration.

Implementation of a Generic SIR Filter for Nonlinear Non-Gaussian State Estimation

This demonstration illustrates the implementation of a generic Sequential Importance Resampling (SIR) filter - also known as particle, bootstrap, or Monte Carlo filter - for estimating hidden states in nonlinear, non-Gaussian state space models, complete with algorithm explanations and code implementation details.