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Showing 1 - 12 of 12 results for “david lunn”
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  • The BUGS Book

    A Practical Introduction to Bayesian Analysis

    by David Lunn, Chris Jackson, Nicky Best, Andrew Thomas, David Spiegelhalter ...
    Series series Chapman & Hall/CRC Texts in Statistical Science
    Bayesian statistical methods have become widely used for data analysis and modelling in recent years, and the BUGS software has become the most popular software for Bayesian analysis worldwide. Authored by the team that originally developed this software, The BUGS Book provides a practical introduction to this program and its use. The text presents ... Read more

    $85.99 USD

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  • Statistical Rethinking

    A Bayesian Course with Examples in R and STAN

    by Richard McElreath ...
    Series series Chapman & Hall/CRC Texts in Statistical Science
    Winner of the 2024 De Groot Prize awarded by the International Society for Bayesian Analysis (ISBA)Statistical Rethinking: A Bayesian Course with Examples in R and Stan builds your knowledge of and confidence in making inferences from data. Reflecting the need for scripting in today's model-based statistics, the book pushes you to perform step-by-step calculations that are usually automated. This ... Read more

    $115.99 USD

  • Bayesian Analysis with Python

    Introduction to statistical modeling and probabilistic programming using PyMC3 and ArviZ

    by Osvaldo Martin, Eric Ma, Austin Rochford ...
    Bayesian modeling with PyMC3 and exploratory analysis of Bayesian models with ArviZ Key FeaturesA step-by-step guide to conduct Bayesian data analyses using PyMC3 and ArviZA modern, practical and computational approach to Bayesian statistical modelingA tutorial for Bayesian analysis and best practices with the help of sample problems and practice exercises.Book DescriptionThe second edition of ... Read more

    $37.79 USD or Free with Kobo Plus

  • Bayesian Analysis with Python

    A practical guide to probabilistic modeling

    by Osvaldo Martin ...
    Learn the fundamentals of Bayesian modeling using state-of-the-art Python libraries, such as PyMC, ArviZ, Bambi, and more, guided by an experienced Bayesian modeler who contributes to these libraries. Free with your book: DRM-free PDF version + access to Packt's next-gen Reader\*Key FeaturesConduct Bayesian data analysis with step-by-step guidanceGain insight into a modern, practical, and ... Read more

    $35.99 USD or Free with Kobo Plus

  • Fundamentals of Machine Learning for Predictive Data Analytics, second edition

    Algorithms, Worked Examples, and Case Studies

    by John D. Kelleher, Brian Mac Namee, Aoife D'Arcy ...
    The second edition of a comprehensive introduction to machine learning approaches used in predictive data analytics, covering both theory and practice.Machine learning is often used to build predictive models by extracting patterns from large datasets. These models are used in predictive data analytics applications including price prediction, risk assessment, predicting customer behavior, and ... Read more

    $49.99 USD

  • Introduction to Machine Learning, fourth edition

    by Ethem Alpaydin ...
    Series series Adaptive Computation and Machine Learning series
    A substantially revised fourth edition of a comprehensive textbook, including new coverage of recent advances in deep learning and neural networks.The goal of machine learning is to program computers to use example data or past experience to solve a given problem. Machine learning underlies such exciting new technologies as self-driving cars, speech recognition, and translation applications. This ... Read more

    $52.99 USD

  • Computer Age Statistical Inference

    Algorithms, Evidence, and Data Science

    by Bradley Efron, Trevor Hastie ...
    Series Book 5 - Institute of Mathematical Statistics Monographs
    The twenty-first century has seen a breathtaking expansion of statistical methodology, both in scope and in influence. 'Big data', 'data science', and 'machine learning' have become familiar terms in the news, as statistical methods are brought to bear upon the enormous data sets of modern science and commerce. How did we get here? And where are we going? This book takes us on an exhilarating ... Read more

    $72.99 USD

  • Bayesian Statistics

    An Introduction

    by Peter M. Lee ...
    Bayesian Statistics is the school of thought that combines prior beliefs with the likelihood of a hypothesis to arrive at posterior beliefs. The first edition of Peter Lee’s book appeared in 1989, but the subject has moved ever onwards, with increasing emphasis on Monte Carlo based techniques.This new fourth edition looks at recent techniques such as variational methods, Bayesian importance ... Read more

    $58.00 USD

  • Generalized Additive Models

    An Introduction with R, Second Edition

    by Simon N. Wood ...
    Series series Chapman & Hall/CRC Texts in Statistical Science
    The first edition of this book has established itself as one of the leading references on generalized additive models (GAMs), and the only book on the topic to be introductory in nature with a wealth of practical examples and software implementation. It is self-contained, providing the necessary background in linear models, linear mixed models, and generalized linear models (GLMs), before ... Read more

    $125.99 USD

  • Bayesian Cognitive Modeling

    A Practical Course

    by Michael D. Lee, Eric-Jan Wagenmakers ...
    Bayesian inference has become a standard method of analysis in many fields of science. Students and researchers in experimental psychology and cognitive science, however, have failed to take full advantage of the new and exciting possibilities that the Bayesian approach affords. Ideal for teaching and self study, this book demonstrates how to do Bayesian modeling. Short, to-the-point chapters ... Read more

    $50.89 USD

  • Introduction to Bayesian Econometrics

    by Edward Greenberg ...
    This textbook explains the basic ideas of subjective probability and shows how subjective probabilities must obey the usual rules of probability to ensure coherency. It defines the likelihood function, prior distributions and posterior distributions. It explains how posterior distributions are the basis for inference and explores their basic properties. Various methods of specifying prior ... Read more

    $50.09 USD

  • Bayesian Biostatistics

    by Emmanuel Lesaffre, Andrew B. Lawson ...
    Series series Statistics in Practice
    The growth of biostatistics has been phenomenal in recent years and has been marked by considerable technical innovation in both methodology and computational practicality. One area that has experienced significant growth is Bayesian methods. The growing use of Bayesian methodology has taken place partly due to an increasing number of practitioners valuing the Bayesian paradigm as matching that of ... Read more

    $69.00 USD