KFAS: Exponential Family State Space Models in R

TL;DR

KFAS is an R package that enables flexible state space modeling for various distributions, including Gaussian, Poisson, binomial, negative binomial, and gamma, facilitating advanced time series analysis.

Contribution

This paper introduces KFAS, an R package that extends state space modeling to exponential family distributions, offering a unified framework for non-Gaussian time series analysis.

Findings

Demonstrates Poisson time series forecasting using KFAS.

Provides a comparison with other R packages for non-Gaussian models.

Shows KFAS's versatility across multiple exponential family distributions.

Abstract

State space modelling is an efficient and flexible method for statistical inference of a broad class of time series and other data. This paper describes an R package KFAS for state space modelling with the observations from an exponential family, namely Gaussian, Poisson, binomial, negative binomial and gamma distributions. After introducing the basic theory behind Gaussian and non-Gaussian state space models, an illustrative example of Poisson time series forecasting is provided. Finally, a comparison to alternative R packages suitable for non-Gaussian time series modelling is presented.