bssm: ekpf_filter – R documentation

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ekpf_filter

Extended Kalman Particle Filtering

Description

Function ekpf_filter performs a extended Kalman particle filtering with stratification resampling, based on Van Der Merwe et al (2001).

Usage

ekpf_filter(object, particles, ...)

## S3 method for class 'ssm_nlg'
ekpf_filter(
  object,
  particles,
  seed = sample(.Machine$integer.max, size = 1),
  ...
)

Arguments

`object`	of class `ssm_nlg`.
`particles`	Number of particles.
`...`	Ignored.
`seed`	Seed for RNG.

Value

A list containing samples, filtered estimates and the corresponding covariances, weights, and an estimate of log-likelihood.

References

Van Der Merwe, R., Doucet, A., De Freitas, N., & Wan, E. A. (2001). The unscented particle filter. In Advances in neural information processing systems (pp. 584-590).

bssm

Bayesian Inference of Non-Linear and Non-Gaussian State Space Models

v1.1.4

GPL (>= 2)

Authors

Jouni Helske [aut, cre] (<https://orcid.org/0000-0001-7130-793X>), Matti Vihola [aut] (<https://orcid.org/0000-0002-8041-7222>)

Initial release

2021-04-13