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Chapman and Hall/CRC Bayesian Econometric Modelling for Big Data - Chapman and Hall/CRC

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Description

Master the complexities of large-scale data analysis with Bayesian Econometric Modelling for Big Data. This text provides a deep look into scalable Bayesian statistical methods specifically built to address the challenges of big data environments. By exploring various divide-and-conquer and subsampling techniques, the book shows how to integrate these scalable approaches into a wide range of econometric models. Beyond large-scale data applications, this book introduces new concepts to traditional statistics. You will learn about the summation, subtraction, and multiplication of conjugate distributions. These arithmetic operators help conceptualize pseudo data within the conjugate prior and sufficient statistics that determine the likelihood. This resource is an essential addition for researchers and professionals working at the intersection of statistics, business, and economics.

Key Features

Scalable Bayesian statistical methods designed to handle the specific challenges presented by big data sets.

Comprehensive exploration of divide-and-conquer and subsampling techniques for efficient data processing.

Seamless integration of scalable methods into a broad spectrum of various econometric models.

Introduction of novel concepts in traditional statistics, including arithmetic operators for conjugate distributions.

Practical application of pseudo data concepts within the conjugate prior and sufficient statistics.

Product Specifications

Format
hardcover
Domain
Amazon UK
Release Date
20 June 2025
Listed Since
26 November 2024

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