Articles liés à Bayesian Econometric Modelling for Big Data
Synopsis
This book delves into scalable Bayesian statistical methods designed to tackle the challenges posed by big data. It explores a variety of divide-and-conquer and subsampling techniques. The book is an essential resource for graduate students, early-career statisticians, data analysts, and statistical software users and developers.
Les informations fournies dans la section « Synopsis » peuvent faire référence à une autre édition de ce titre.
À propos de l?auteur
Hang Qian is the principal engineer of the Econometrics Toolbox for MATLAB and has been dedicated to statistical software development at MathWorks since 2012. He earned his PhD in economics, specializing in Bayesian statistics, big data analysis, and computational finance. His research has been published in journals such as Bayesian Analysis, Journal of Business & Economic Statistics, and Journal of Econometrics.
Les informations fournies dans la section « A propos du livre » peuvent faire référence à une autre édition de ce titre.
Acheter neuf
Afficher cet article
EUR 128,04
Gratuit expédition vers Etats-Unis
Destinations, frais et délaisRésultats de recherche pour Bayesian Econometric Modelling for Big Data
Image d'archives
Bayesian Econometric Modelling for Big Data (Hardcover)
Edité par
Taylor & Francis Ltd, 2025
ISBN 10 : 1032915250
ISBN 13 : 9781032915258
Neuf
Couverture rigide
Vendeur : Grand Eagle Retail, Bensenville, IL, Etats-Unis
Évaluation du vendeur 5 sur 5 étoiles
Hardcover. Etat : new. Hardcover. This book delves into scalable Bayesian statistical methods designed to tackle the challenges posed by big data. It explores a variety of divide-and-conquer and subsampling techniques, seamlessly integrating these scalable methods into a broad spectrum of econometric models.In addition to its focus on big data, the book introduces novel concepts within traditional statistics, such as the summation, subtraction, and multiplication of conjugate distributions. These arithmetic operators conceptualize pseudo data in the conjugate prior, sufficient statistics that determine the likelihood, and the posterior as a balance between data and prior information, adding an intriguing dimension to Bayesian analysis. This book also offers a deep dive into Bayesian computation. Given the intricacies of floating-point representation of real numbers, computer programs can sometimes yield unexpected or theoretically impossible results. Drawing from his experience as a senior statistical software developer, the author shares valuable strategies for designing numerically stable algorithms.The book is an essential resource for a diverse audience: graduate students seeking foundational knowledge in Bayesian econometric models, early-career statisticians eager to explore cutting-edge advancements in scalable Bayesian methods, data analysts struggling with out-of-memory challenges in large datasets, and statistical software users and developers striving to program with efficiency and numerical stability. This book delves into scalable Bayesian statistical methods designed to tackle the challenges posed by big data. It explores a variety of divide-and-conquer and subsampling techniques. The book is an essential resource for graduate students, early-career statisticians, data analysts, and statistical software users and developers. Shipping may be from multiple locations in the US or from the UK, depending on stock availability. N° de réf. du vendeur 9781032915258
Quantité disponible : 1 disponible(s)
Image d'archives
Bayesian Econometric Modelling for Big Data (Chapman and Hall/CRC Series on Statistics in Business and Economics)
Edité par
Chapman and Hall/CRC, 2025
ISBN 10 : 1032915250
ISBN 13 : 9781032915258
Neuf
Couverture rigide
Vendeur : California Books, Miami, FL, Etats-Unis
Évaluation du vendeur 5 sur 5 étoiles
Etat : New. N° de réf. du vendeur I-9781032915258
Quantité disponible : Plus de 20 disponibles
Image d'archives
Bayesian Econometric Modelling for Big Data
Edité par
Chapman and Hall/CRC, 2025
ISBN 10 : 1032915250
ISBN 13 : 9781032915258
Neuf
Couverture rigide
Vendeur : Majestic Books, Hounslow, Royaume-Uni
Évaluation du vendeur 4 sur 5 étoiles
Etat : New. N° de réf. du vendeur 410656754
Quantité disponible : 3 disponible(s)
Image d'archives
Bayesian Econometric Modelling for Big Data
Edité par
Chapman and Hall/CRC, 2025
ISBN 10 : 1032915250
ISBN 13 : 9781032915258
Neuf
Couverture rigide
Vendeur : Books Puddle, New York, NY, Etats-Unis
Évaluation du vendeur 4 sur 5 étoiles
Etat : New. N° de réf. du vendeur 26403546157
Quantité disponible : 3 disponible(s)
Image d'archives
Bayesian Econometric Modelling for Big Data
Edité par
Chapman and Hall/CRC, 2025
ISBN 10 : 1032915250
ISBN 13 : 9781032915258
Neuf
Couverture rigide
Vendeur : Biblios, Frankfurt am main, HESSE, Allemagne
Évaluation du vendeur 5 sur 5 étoiles
Etat : New. N° de réf. du vendeur 18403546151
Quantité disponible : 1 disponible(s)
Image d'archives
Bayesian Econometric Modelling for Big Data (Chapman and Hall/CRC Series on Statistics in Business and Economics)
Edité par
Chapman and Hall/CRC, 2025
ISBN 10 : 1032915250
ISBN 13 : 9781032915258
Neuf
Couverture rigide
Vendeur : Ria Christie Collections, Uxbridge, Royaume-Uni
Évaluation du vendeur 5 sur 5 étoiles
Etat : New. In. N° de réf. du vendeur ria9781032915258_new
Quantité disponible : Plus de 20 disponibles
Image d'archives
Bayesian Econometric Modelling for Big Data
impression à la demandeVendeur : PBShop.store UK, Fairford, GLOS, Royaume-Uni
Évaluation du vendeur 5 sur 5 étoiles
HRD. Etat : New. New Book. Delivered from our UK warehouse in 4 to 14 business days. THIS BOOK IS PRINTED ON DEMAND. Established seller since 2000. N° de réf. du vendeur L1-9781032915258
Quantité disponible : Plus de 20 disponibles
Image d'archives
Bayesian Econometric Modelling for Big Data
impression à la demandeVendeur : PBShop.store US, Wood Dale, IL, Etats-Unis
Évaluation du vendeur 5 sur 5 étoiles
HRD. Etat : New. New Book. Shipped from UK. THIS BOOK IS PRINTED ON DEMAND. Established seller since 2000. N° de réf. du vendeur L1-9781032915258
Quantité disponible : Plus de 20 disponibles
Image d'archives
Bayesian Econometric Modelling for Big Data (Hardcover)
Edité par
Taylor & Francis Ltd, 2025
ISBN 10 : 1032915250
ISBN 13 : 9781032915258
Neuf
Couverture rigide
Vendeur : AussieBookSeller, Truganina, VIC, Australie
Évaluation du vendeur 5 sur 5 étoiles
Hardcover. Etat : new. Hardcover. This book delves into scalable Bayesian statistical methods designed to tackle the challenges posed by big data. It explores a variety of divide-and-conquer and subsampling techniques, seamlessly integrating these scalable methods into a broad spectrum of econometric models.In addition to its focus on big data, the book introduces novel concepts within traditional statistics, such as the summation, subtraction, and multiplication of conjugate distributions. These arithmetic operators conceptualize pseudo data in the conjugate prior, sufficient statistics that determine the likelihood, and the posterior as a balance between data and prior information, adding an intriguing dimension to Bayesian analysis. This book also offers a deep dive into Bayesian computation. Given the intricacies of floating-point representation of real numbers, computer programs can sometimes yield unexpected or theoretically impossible results. Drawing from his experience as a senior statistical software developer, the author shares valuable strategies for designing numerically stable algorithms.The book is an essential resource for a diverse audience: graduate students seeking foundational knowledge in Bayesian econometric models, early-career statisticians eager to explore cutting-edge advancements in scalable Bayesian methods, data analysts struggling with out-of-memory challenges in large datasets, and statistical software users and developers striving to program with efficiency and numerical stability. This book delves into scalable Bayesian statistical methods designed to tackle the challenges posed by big data. It explores a variety of divide-and-conquer and subsampling techniques. The book is an essential resource for graduate students, early-career statisticians, data analysts, and statistical software users and developers. Shipping may be from our Sydney, NSW warehouse or from our UK or US warehouse, depending on stock availability. N° de réf. du vendeur 9781032915258
Quantité disponible : 1 disponible(s)
Image d'archives
Bayesian Econometric Modelling for Big Data
Edité par
Taylor & Francis Ltd, 2025
ISBN 10 : 1032915250
ISBN 13 : 9781032915258
Neuf
Couverture rigide
Vendeur : THE SAINT BOOKSTORE, Southport, Royaume-Uni
Évaluation du vendeur 5 sur 5 étoiles
Hardback. Etat : New. New copy - Usually dispatched within 4 working days. 1060. N° de réf. du vendeur B9781032915258
Quantité disponible : 1 disponible(s)