Bayesian Econometric Modelling For Big Data
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Bayesian Econometric Modelling For Big Data
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Author : Hang Qian
language : en
Publisher: CRC Press
Release Date : 2025-06-20
Bayesian Econometric Modelling For Big Data written by Hang Qian and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-06-20 with Mathematics categories.
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.
Bayesian Econometric Modelling For Big Data
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Author : Hang Qian
language : en
Publisher: CRC Press
Release Date : 2025
Bayesian Econometric Modelling For Big Data written by Hang Qian and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025 with Mathematics categories.
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.
Bayesian Econometric Modelling For Big Data
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Author : Hang Qian (Economist)
language : en
Publisher:
Release Date : 2025
Bayesian Econometric Modelling For Big Data written by Hang Qian (Economist) and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025 with Mathematics categories.
"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"--
Predictive Econometrics And Big Data
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Author : Vladik Kreinovich
language : en
Publisher: Springer
Release Date : 2017-11-30
Predictive Econometrics And Big Data written by Vladik Kreinovich and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2017-11-30 with Technology & Engineering categories.
This book presents recent research on predictive econometrics and big data. Gathering edited papers presented at the 11th International Conference of the Thailand Econometric Society (TES2018), held in Chiang Mai, Thailand, on January 10-12, 2018, its main focus is on predictive techniques – which directly aim at predicting economic phenomena; and big data techniques – which enable us to handle the enormous amounts of data generated by modern computers in a reasonable time. The book also discusses the applications of more traditional statistical techniques to econometric problems. Econometrics is a branch of economics that employs mathematical (especially statistical) methods to analyze economic systems, to forecast economic and financial dynamics, and to develop strategies for achieving desirable economic performance. It is therefore important to develop data processing techniques that explicitly focus on prediction. The more data we have, the better our predictions will be. As such, these techniques are essential to our ability to process huge amounts of available data.
Bayesian Data Analysis Third Edition
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Author : Andrew Gelman
language : en
Publisher: CRC Press
Release Date : 2013-11-01
Bayesian Data Analysis Third Edition written by Andrew Gelman and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2013-11-01 with Mathematics categories.
Now in its third edition, this classic book is widely considered the leading text on Bayesian methods, lauded for its accessible, practical approach to analyzing data and solving research problems. Bayesian Data Analysis, Third Edition continues to take an applied approach to analysis using up-to-date Bayesian methods. The authors—all leaders in the statistics community—introduce basic concepts from a data-analytic perspective before presenting advanced methods. Throughout the text, numerous worked examples drawn from real applications and research emphasize the use of Bayesian inference in practice. New to the Third Edition Four new chapters on nonparametric modeling Coverage of weakly informative priors and boundary-avoiding priors Updated discussion of cross-validation and predictive information criteria Improved convergence monitoring and effective sample size calculations for iterative simulation Presentations of Hamiltonian Monte Carlo, variational Bayes, and expectation propagation New and revised software code The book can be used in three different ways. For undergraduate students, it introduces Bayesian inference starting from first principles. For graduate students, the text presents effective current approaches to Bayesian modeling and computation in statistics and related fields. For researchers, it provides an assortment of Bayesian methods in applied statistics. Additional materials, including data sets used in the examples, solutions to selected exercises, and software instructions, are available on the book’s web page.
Macroeconomic Forecasting In The Era Of Big Data
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Author : Peter Fuleky
language : en
Publisher: Springer Nature
Release Date : 2019-11-28
Macroeconomic Forecasting In The Era Of Big Data written by Peter Fuleky and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-11-28 with Business & Economics categories.
This book surveys big data tools used in macroeconomic forecasting and addresses related econometric issues, including how to capture dynamic relationships among variables; how to select parsimonious models; how to deal with model uncertainty, instability, non-stationarity, and mixed frequency data; and how to evaluate forecasts, among others. Each chapter is self-contained with references, and provides solid background information, while also reviewing the latest advances in the field. Accordingly, the book offers a valuable resource for researchers, professional forecasters, and students of quantitative economics.
Spatial Analysis Using Big Data
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Author : Yoshiki Yamagata
language : en
Publisher: Academic Press
Release Date : 2019-11-03
Spatial Analysis Using Big Data written by Yoshiki Yamagata and has been published by Academic Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-11-03 with Business & Economics categories.
Spatial Analysis Using Big Data: Methods and Urban Applications helps readers understand the most powerful, state-of-the-art spatial econometric methods, focusing particularly on urban research problems. The methods represent a cluster of potentially transformational socio-economic modeling tools that allow researchers to capture real-time and high-resolution information to potentially reveal new socioeconomic dynamics within urban populations. Each method, written by leading exponents of the discipline, uses real-time urban big data to solve research problems in spatial science. Urban applications of these methods are provided in unsurpassed depth, with chapters on surface temperature mapping, view value analysis, community clustering and spatial-social networks, among many others. - Reviews some of the most powerful and challenging modern methods to study big data problems in spatial science - Provides computer codes written in R, MATLAB and Python to help implement methods - Applies these methods to common problems observed in urban and regional economics
Bayesian Modeling Of Spatio Temporal Data With R
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Author : Sujit Sahu
language : en
Publisher: CRC Press
Release Date : 2022-03-01
Bayesian Modeling Of Spatio Temporal Data With R written by Sujit Sahu and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-03-01 with Mathematics categories.
Applied sciences, both physical and social, such as atmospheric, biological, climate, demographic, economic, ecological, environmental, oceanic and political, routinely gather large volumes of spatial and spatio-temporal data in order to make wide ranging inference and prediction. Ideally such inferential tasks should be approached through modelling, which aids in estimation of uncertainties in all conclusions drawn from such data. Unified Bayesian modelling, implemented through user friendly software packages, provides a crucial key to unlocking the full power of these methods for solving challenging practical problems. Key features of the book: • Accessible detailed discussion of a majority of all aspects of Bayesian methods and computations with worked examples, numerical illustrations and exercises • A spatial statistics jargon buster chapter that enables the reader to build up a vocabulary without getting clouded in modeling and technicalities • Computation and modeling illustrations are provided with the help of the dedicated R package bmstdr, allowing the reader to use well-known packages and platforms, such as rstan, INLA, spBayes, spTimer, spTDyn, CARBayes, CARBayesST, etc • Included are R code notes detailing the algorithms used to produce all the tables and figures, with data and code available via an online supplement • Two dedicated chapters discuss practical examples of spatio-temporal modeling of point referenced and areal unit data • Throughout, the emphasis has been on validating models by splitting data into test and training sets following on the philosophy of machine learning and data science This book is designed to make spatio-temporal modeling and analysis accessible and understandable to a wide audience of students and researchers, from mathematicians and statisticians to practitioners in the applied sciences. It presents most of the modeling with the help of R commands written in a purposefully developed R package to facilitate spatio-temporal modeling. It does not compromise on rigour, as it presents the underlying theories of Bayesian inference and computation in standalone chapters, which would be appeal those interested in the theoretical details. By avoiding hard core mathematics and calculus, this book aims to be a bridge that removes the statistical knowledge gap from among the applied scientists.
Econometrics
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Author : Samir Ganaka
language : en
Publisher: Educohack Press
Release Date : 2025-02-20
Econometrics written by Samir Ganaka and has been published by Educohack Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-02-20 with Business & Economics categories.
"Econometrics: The Essentials" takes you on an engaging journey through the world of econometrics, designed to demystify this complex field. In a world where economic decisions shape our daily lives, understanding the interplay between economic theories and statistical methods is crucial. This book, crafted for a diverse global audience with a focus on the United States, serves as your guide through the landscape of econometrics. We present the subject in everyday language, making it accessible to both newcomers and seasoned practitioners. Econometrics is more than numbers—it's about uncovering the stories behind economic phenomena, understanding the drivers of our economies, and helping readers make sense of the complex web of data. The book emphasizes the global relevance of econometric principles while offering insights into the U.S. economic landscape. We explore the impact of fiscal policies, financial markets, and other economic intricacies. Practical concepts such as regression analyses, instrumental variables, and Two-Stage Least Squares Estimation are grounded in relatable scenarios and real-world applications. Our human-centric approach recognizes that behind every data point is a story involving individuals and communities. We illustrate how econometric techniques address pressing issues, from unemployment dynamics to the effectiveness of social programs. "Econometrics: The Essentials" equips readers with the skills to navigate econometrics, fostering a deeper understanding of the empirical realities shaping our world. Whether you're a policymaker, economist, researcher, or curious mind, this book empowers you with the knowledge and tools to unravel the mysteries of econometrics.
Handbook On Big Data Artificial Intelligence And Cities
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Author : Dani Broitman
language : en
Publisher: Edward Elgar Publishing
Release Date : 2025-04-09
Handbook On Big Data Artificial Intelligence And Cities written by Dani Broitman and has been published by Edward Elgar Publishing this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-04-09 with Business & Economics categories.
This pioneering Handbook outlines the ways in which big data and artificial intelligence (AI) are reshaping cities. Leading scholars analyze how innovative computational methods can make use of the vast amounts of data available to gain new insights into urban life, inform policy, and drive innovation.