Sequential Solution for General State-Space Model

Junichiro Hagiwara ()
Additional contact information
Junichiro Hagiwara: Hokkaido University, Graduate School / Faculty of Information Science and Technology

Chapter Chapter 11 in Time Series Analysis for the State-Space Model with R/Stan, 2021, pp 219-275 from Springer

Abstract: Abstract This chapter describes the sequential estimation method for the case wherein the observations are obtained sequentially in the general state-space model. While various methods have been proposed as solutions, this book introduces the particle filter. Regarding the implementation of the particle filter, this book mentions both the scratching and library-based approaches.

Date: 2021
References: Add references at CitEc
Citations:

There are no downloads for this item, see the EconPapers FAQ for hints about obtaining it.

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:spr:sprchp:978-981-16-0711-0_11

Ordering information: This item can be ordered from
http://www.springer.com/9789811607110

DOI: 10.1007/978-981-16-0711-0_11

Access Statistics for this chapter

More chapters in Springer Books from Springer
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().