General

When a doctor tells you there s a one percent chance that an operation will result in your death, or a scientist claims that his theory is probably true, what exactly does that mean? Understanding probability is clearly very important, if we are to make...

Apologies but we at Booksplease don't have a full description for this book.Book InformationISBN 9781602068513Author Marquis De Laplace Pierre-SimonFormat HardbackPage Count 208Imprint Cosimo ClassicsPublisher Cosimo ClassicsWeight(grams)...

This book is about discrete-time, time-homogeneous, Markov chains (Mes) and their ergodic behavior. To this end, most of the material is in fact about stable Mes, by which we mean Mes that admit an invariant probability measure. To state this more...

Up-to-Date Guidance from One of the Foremost Members of the R Core TeamWritten by John M. Chambers, the leading developer of the original S software, Extending R covers key concepts and techniques in R to support analysis and research projects. It...

This is the revised and expanded second edition of the hugely popular Numerical Recipes: the Art of Scientific Computing. The product of a unique collaboration among four leading scientists in academic research and industry, Numerical Recipes is a...

Most textbooks on regression focus on theory and the simplest of examples. Real statistical problems, however, are complex and subtle. This is not a book about the theory of regression. It is about using regression to solve real problems of comparison,...

This book provides a coherent description of foundational matters concerning statistical inference and shows how statistics can help us make inductive inferences about a broader context, based only on a limited dataset such as a random sample drawn from...

In statistics, the Kalman filter is a mathematical method whose purpose is to use a series of measurements observed over time, containing random variations and other inaccuracies, and produce estimates that tend to be closer to the true unknown...

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...

This new, thoroughly revised and expanded 3rd edition of a classic gives a comprehensive coverage of modern probability in a single book. It is a truly modern text, providing not only classical results but also material that will be important for future...

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...

Simulation has now become an integral part of research and development across many fields of study. Despite the large amounts of literature in the field of simulation and modeling, one recurring problem is the issue of accuracy and confidence level of...

This is an introductory course on the methods of computing asymptotics of probabilities of rare events: the theory of large deviations. The book combines large deviation theory with basic statistical mechanics, namely Gibbs measures with their...

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...

Implementing R for Statistics provides comprehensive coverage of basic statistical concepts using this important open-source programming language tool, from installing R and RStudio, to exploring its basic structure and uses, to extending some core...

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)...