Modified Recursive Bayesian Algorithm for Estimating Time-Varying Parameters in Dynamic Linear Models

• Autorzy: O. Olawale Awe , A. Adedayo Adepoju
• Języki publikacji: EN

Abstrakty

EN

Estimation in Dynamic Linear Models (DLMs) with Fixed Parameters (FPs) has been faced with considerable limitations due to its inability to capture the dynamics of most time-varying phenomena in econometric studies. An attempt to address this limitation resulted in the use of Recursive Bayesian Algorithms (RBAs) which is also affected by increased computational problems in estimating the Evolution Variance (EV) of the time-varying parameters. In this paper, we propose a modified RBA for estimating TVPs in DLMs with reduced computational challenges. (original abstract)

Słowa kluczowe

EN

Stochastic models; Stochastic Volatility Processes; Bayesian statistics; Estimation

PL

Modele stochastyczne; Procesy zmienności stochastycznej; Statystyka bayesowska; Estymacja

• Czasopismo: Statistics in Transition
• Rocznik: 2018
• Tom: 19
• Numer: nr 2
• Strony: 239--258

Twórcy

autor

O. Olawale Awe

• Anchor University, Lagos, Nigeria

autor

A. Adedayo Adepoju

• University of Ibadan, Ibadan, Nigeria

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Identyfikatory

DOI

10.21307/stattrans-2018-014