EconPapers    
Economics at your fingertips  
 

KFAS: Exponential Family State Space Models in R

Jouni Helske

Journal of Statistical Software, 2017, vol. 078, issue i10

Abstract: State space modeling is an efficient and flexible method for statistical inference of a broad class of time series and other data. This paper describes the R package KFAS for state space modeling 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 modeling is presented.

Date: 2017-06-09
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (13)

Downloads: (external link)
https://www.jstatsoft.org/index.php/jss/article/view/v078i10/v78i10.pdf
https://www.jstatsoft.org/index.php/jss/article/do ... 10/KFAS_1.2.8.tar.gz
https://www.jstatsoft.org/index.php/jss/article/do ... ile/v078i10/v78i10.R

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:jss:jstsof:v:078:i10

DOI: 10.18637/jss.v078.i10

Access Statistics for this article

Journal of Statistical Software is currently edited by Bettina Grün, Edzer Pebesma and Achim Zeileis

More articles in Journal of Statistical Software from Foundation for Open Access Statistics
Bibliographic data for series maintained by Christopher F. Baum ().

 
Page updated 2025-03-19
Handle: RePEc:jss:jstsof:v:078:i10