Bayesian Inference in Dynamic Econometric Models
Book Details
Format
Paperback / Softback
Book Series
Advanced Texts in Econometrics
ISBN-10
0198773137
ISBN-13
9780198773139
Publisher
Oxford University Press
Imprint
Oxford University Press
Country of Manufacture
GB
Country of Publication
GB
Publication Date
Jan 6th, 2000
Print length
366 Pages
Weight
514 grams
Dimensions
23.40 x 15.70 x 2.10 cms
Product Classification:
EconometricsProbability & statisticsMathematical modelling3D graphics & modelling
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This work contains an up-to-date coverage of the last 20 years' advances in Bayesian inference in econometrics, with an emphasis on dynamic models. Several examples illustrate the methods.
This book contains an up-to-date coverage of the last twenty years advances in Bayesian inference in econometrics, with an emphasis on dynamic models. It shows how to treat Bayesian inference in non linear models, by integrating the useful developments of numerical integration techniques based on simulations (such as Markov Chain Monte Carlo methods), and the long available analytical results of Bayesian inference for linear regression models. It thus covers a broad range of rather recent models for economic time series, such as non linear models, autoregressive conditional heteroskedastic regressions, and cointegrated vector autoregressive models. It contains also an extensive chapter on unit root inference from the Bayesian viewpoint. Several examples illustrate the methods.
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