A skew-normal dynamic linear model and Bayesian forecasting

Reinaldo B. Arellano-Valle, Javier E. Contreras-Reyes (), Freddy O. López Quintero and Abel Valdebenito
Additional contact information
Reinaldo B. Arellano-Valle: Pontificia Universidad Católica de Chile
Javier E. Contreras-Reyes: Universidad de Valparaíso
Freddy O. López Quintero: Compañía de Telecomunicaciones de Chile S.A.
Abel Valdebenito: Pontificia Universidad Católica de Chile

Computational Statistics, 2019, vol. 34, issue 3, No 7, 1055-1085

Abstract: Abstract Dynamic linear models are typically developed assuming that both the observational and system distributions are normal. In this work, we relax this assumption by considering a skew-normal distribution for the observational random errors, providing thus an extension of the standard normal dynamic linear model. Full Bayesian inference is carried out using the hierarchical representation of the model. The inference scheme is led by means of the adaptation of the Forward Filtering Backward sampling and the usual MCMC algorithms to perform the inference. The proposed methodology is illustrated by a simulation study and applied to the condition factor index of male and female anchovies off northern Chile. These indexes have not been studied in a dynamic linear model framework.

Keywords: Bayesian sequential inference; Kalman filter and smoothing; FFBS algorithm; MCMC; Skew-normal; Condition factor (search for similar items in EconPapers)
Date: 2019
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (3)

Downloads: (external link)
http://link.springer.com/10.1007/s00180-018-0848-1 Abstract (text/html)
Access to the full text of the articles in this series is restricted.

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:compst:v:34:y:2019:i:3:d:10.1007_s00180-018-0848-1

Ordering information: This journal article can be ordered from
http://www.springer.com/statistics/journal/180/PS2

DOI: 10.1007/s00180-018-0848-1

Access Statistics for this article

Computational Statistics is currently edited by Wataru Sakamoto, Ricardo Cao and Jürgen Symanzik

More articles in Computational Statistics from Springer
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().