Regression modelEconometrics / time series

Bayesian NARDL: Nelinearna ARDL s Bayesijanskom procjenom

Bayesian NARDL kombinira okvir Nelinearnog Autoregresivnog Distribuiranog Proširenja (Nonlinear Autoregressive Distributed Lag – NARDL) Shin, Yu i Greenwood-Nimmo (2014.) s Bayesijanskim zaključivanjem o aposteriornoj distribuciji. Modelira dugoročnu ko-integraciju sa značajkama asimetrije — dopuštajući pozitivnim i negativnim šokovima na regresor da imaju različite ravnotežne učinke — istovremeno uključujući prethodno znanje i proizvodeći potpune aposteriorne distribucije za sve parametre, uključujući jaz asimetrije.

Primijenite uz EconMindUskoroVideoUskoroDownload slides

Pročitajte cijelu metodu

Samo za članove

Prijavite se besplatnim računom kako biste pročitali ovaj odjeljak.

Prijavite se

Method map

The neighbourhood of related methods — select a node to explore.

Izvori

  1. Shin, Y., Yu, B., & Greenwood-Nimmo, M. (2014). Modelling asymmetric cointegration and dynamic multipliers in a nonlinear ARDL framework. In W. C. Horrace & R. C. Sickles (Eds.), Festschrift in Honor of Peter Schmidt: Econometric Methods and Applications (pp. 281–314). Springer. link
  2. Koop, G. (2003). Bayesian Econometrics. Wiley. ISBN: 978-0470845677

Kako citirati ovu stranicu

ScholarGate. (2026, June 3). Bayesian Nonlinear Autoregressive Distributed Lag Model. ScholarGate. https://scholargate.app/hr/econometrics/bayesian-nardl

Which method?

Set this method beside its closest kin and read them side by side — the library lays the books on the table; the choice is yours.

Compare side by side
ScholarGateBayesian NARDL (Bayesian Nonlinear Autoregressive Distributed Lag Model). Preuzeto 2026-06-15 s https://scholargate.app/hr/econometrics/bayesian-nardl · Skup podataka: https://doi.org/10.5281/zenodo.20539026