General

Highly praised for its broad, practical coverage, the second edition of this popular text incorporated the major statistical models and issues relevant to epidemiological studies. Epidemiology: Study Design and Data Analysis, Third Edition continues to...

Apologies but we at Booksplease don't have a full description for this book.Book InformationISBN 9780143038344Author Michael KaplanFormat PaperbackPage Count 336Imprint The Penguin PressPublisher Penguin Putnam IncWeight(grams) 295gDimensions(mm) 203mm *...

Statistics is central in the biosciences, social sciences and other disciplines, yet many students often struggle to learn how to perform statistical tests, and to understand how and why statistical tests work. Although there are many approaches to...

This is an introduction to Bayesian statistics and decision theory, including advanced topics such as Monte Carlo methods. This new edition contains several revised chapters and a new chapter on model choice.2nd editionReviewsFrom the reviews of the...

* A self-contained introduction to probability, exchangeability and Bayes' rule provides a theoretical understanding of the applied material. * Numerous examples with R-code that can be run "as-is" allow the reader to perform the data analyses...

Praise for the First Edition"The main strength of this book is that it provides a unified framework of graphical tools for data analysis, especially for univariate and low-dimensional multivariate data. In addition, it is clearly written in plain...

Machine learning (ML) is progressively reshaping the fields of quantitative finance and algorithmic trading. ML tools are increasingly adopted by hedge funds and asset managers, notably for alpha signal generation and stocks selection. The technicality...

A fascinating account of the breakthrough ideas that transformed probability and statistics In the sixteenth and seventeenth centuries, gamblers and mathematicians transformed the idea of chance from a mystery into the discipline of probability, setting...

Introduction to Time Series Using Stata, Revised Edition provides a step-by-step guide to essential time-series techniques-from the incredibly simple to the quite complex- and, at the same time, demonstrates how these techniques can be applied in the...

An Introduction to Stata for Health Researchers, Fifth Edition updates this classic book that has become a standard reference for health researchers. As with previous editions, readers will learn to work effectively in Stata to perform data management,...

Implement the Snowflake Data Cloud using best practices and reap the benefits of scalability and low-cost from the industry-leading, cloud-based, data warehousing platform. This book provides a detailed how-to explanation, and assumes familiarity with...

Starting with the fundamentals of classical smooth optimization and building on established convex programming techniques, this research monograph presents a foundation and methodology for modern nonconvex nondifferentiable optimization. It provides...

This book provides an introduction to double generalized linear models (DGLMs) under frequentist and Bayesian frameworks. These models include the class of generalized linear models and compose a unified class of models, where appropriate functions of...

From the Ising model to large language models, Gibbs Measures in Machine Learning offers a complete journey through one of the most powerful concepts connecting statistical physics and modern AI.Starting with the mathematical foundations - measure...

ELEMENTARY SURVEY SAMPLING is an engaging and practical introduction to survey sampling. The book begins with real-world scenarios and uses easy-to-understand formulas, methodologies, and concepts to show how sample surveys are used in a wide variety of...

Theory, experiments, computation, and data are considered as the four pillars of science and engineering. Experimental Design for Data Science and Engineering describes efficient statistical methods for making the experiments cheaper and computations...

This thoroughly revised and updated new edition reflects the progress that has been made in dose-exposure-response (DER) modeling. As the title suggests, the new edition covers more topics on dose and dose adjustment. A large part of the book has been...

Hidden Semi-Markov Models (HSMMs) have been extensively used for diverse applications where the objective is to analyze time series whose dynamics can be explained by a hidden process. A Comprehensive Guide to HSMM offers an accessible introduction to...

The presented ideas create and shape the vision of a "Manifesto of Higher Education Governance".Fractals are typically understood as self-similar structures, but this concept is expanded to include "self-different fractals". These fractals align with a...

This book offers a comprehensive exploration of popular continuous distribution families, including Exponentiated, Beta, Kumaraswamy, T-X, and Transmuted. It details methods for developing new distribution families, their properties, and inference...

Predicting the future is a difficult task but, as with the weather, it is possible with good models. But how does one predict the far future before the near future is known? Time parallel time integration, also known as PinT (Parallel-in-Time) methods,...

Statistics in Environmental Monitoring and Assessment details how statistics plays an essential role in every step of an environmental monitoring and assessment program, from the sampling design to the data management and data analysis methods that are...

Applied Statistics with Python, Volume II focuses on ANOVA, multivariate models such as multiple regression, model selection, and reduction techniques, regularization methods like lasso and ridge, logistic regression, K-nearest neighbors (KNN), support...

The primary purpose of this book is to introduce the reader to elementary statistical methods as related to tests of differences, such as one-sample tests, tests of two independent samples, tests of two matched samples, and one-way analysis of variance...

Mathematical Foundations of Artificial Intelligence: Basics of Manifold Theory is the first volume in a two-part series. Together, they establish a unifying mathematical framework based on smooth manifold theory and Riemannian geometry essential tools...

This book delves into the cutting-edge field of person re-identification (ReID), a critical area within deep learning and computer vision. Addressing key challenges in current ReID models, it presents novel research combining automated machine learning...

The purpose of these notes is to explore some simple relations between Markovian path and loop measures, the Poissonian ensembles of loops they determine, their occupation fields, uniform spanning trees, determinants, and Gaussian Markov fields such as...

Apologies but we at Booksplease don't have a full description for this book.Book InformationISBN 9780486801445Author David S. KahnFormat PaperbackPage Count 112Imprint Dover Publications Inc.Publisher Dover Publications Inc.Weight(grams)...

Advanced Forecasting with Python, Second Edition, is a comprehensive and practical guide to mastering modern forecasting techniques using Python. Designed for data scientists, analysts, and machine learning practitioners, this updated edition bridges the...

This book provides fundamental concepts and algorithms of the Hidden Markov Model (HMM) and its applications in finance, such as stock price predictions, and other areas such as speech recognition. Their wide range uses make HMMs very attractive to...

An accessible and authoritative introduction to data handling and analysis for biology students—requiring no previous experience of statistics.

An accessible and authoritative introduction to data handling and analysis for biology students—requiring no previous experience of statistics.

Most data arrive with more than two numeric variables which means that plotting it on a computer screen or printed page presents a challenge: how do you visually explore for associations between more than two variables? Visualising data provides the...

Queuing theory methods are employed in managing traffic flows, shipping facilities, communication systems, vertical transportation, and others. The study of such systems is outside the framework of the methods of classical queuing theory; thus, new...

This volume constitutes the proceedings of First International Conference on Modeling, Simulation and Computer Technology, ICMSCT 2024, held in Skikda, Algeria, during November 5-6, 2024. The 45 full papers presented in this volume were carefully...

This volume provides a comprehensive introduction to the principles and practices of experimental design, a cornerstone of empirical research across disciplines. Covering foundational topics such as sampling, randomization, and analysis of variance,...

This volume addresses the complexities of real-world data analysis, offering clear guidance through common challenges such as missing data, model specification, variable selection, and hypothesis testing. It also introduces tools for deeper...

The book provides a description of the process of health economic evaluation and modelling for cost-effectiveness analysis, particularly from the perspective of a Bayesian statistical approach. Some relevant theory and introductory concepts are presented...

The description for this book, Stationary Processes and Prediction Theory. (AM-44), will be forthcoming.Book InformationISBN 9780691080413Author Harry FurstenbergFormat PaperbackPage Count 296Imprint Princeton University PressPublisher Princeton...

An Introduction to Stochastic Modeling, Fifth Edition bridges the gap between basic probability and an intermediate level course in stochastic processes, serving as the foundation for either a one-semester or two-semester course in stochastic processes...