General

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...

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...

An Introduction to Statistical Learning provides an accessible overview of the field of statistical learning, an essential toolset for making sense of the vast and complex data sets that have emerged in fields ranging from biology to finance, marketing,...

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 Memoirs of the AMS is devoted to the publication of new research in all areas of pure and applied mathematics. The Memoirs is designed particularly to publish long papers of groups of cognate papers in book form, and is under the supervision of the...

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...

This book covers probability and statistics from the machine learning perspective. The chapters of this book belong to three categories: 1. The basics of probability and statistics: These chapters focus on the basics of probability and statistics, and...

Predictive Modelling for Football Analytics discusses the most well-known models and the main computational tools for the football analytics domain. It further introduces the footBayes R package that accompanies the reader through all the examples...

This textbook is the second edition of the linear algebra and optimization book that was published in 2020. The exposition in this edition is greatly simplified as compared to the first edition. The second edition is enhanced with a large number of...

This CCIS 2538 volume constitutes the proceedings of First and Second International Conference on Advancements in Machine Learning, ICCAML 2024, in Pune, India, during February 28-29, 2024. The 19 full papers are carefully reviewed and selected from 173...

This book provides a self-contained lecture on a Malliavin calculus approach to asymptotic expansion and weak approximation of stochastic differential equations (SDEs), along with numerical methods for computing parabolic partial differential equations...

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...

Exploratory and Robust Data Analysis: A Modern Applied Statistics Guide Using SPSS and R is an essential resource for students, researchers, and professionals seeking a comprehensive yet practical approach to modern statistical analysis. This book...

This textbook introduces the major ideas of stochastic analysis with a view to modeling or simulating systems involving randomness. Suitable for students and researchers in applied mathematics and related disciplines, this book prepares readers to solve...

Apologies but we at Booksplease don't have a full description for this book.Book InformationISBN 9781260373622Author William NavidiImprint McGraw-Hill EducationPublisher McGraw-Hill EducationWeight(grams) 5g

Apologies but we at Booksplease don't have a full description for this book.Book InformationISBN 9781260389692Author David SobeckiImprint McGraw-Hill EducationPublisher McGraw-Hill EducationWeight(grams) 5g

Fisheries science is an applied field. A biologist working on a depleted population might need to forecast the population trajectory or examine which factors are limiting recovery. For an exploited population, a biologist might investigate whether the...

This textbook is designed for teaching quantitative research in the scientific, health and engineering disciplines at first-year undergraduate level, with an emphasis on statistics. It covers the research process, including asking research questions,...

"This is an important book on an important topic. I particularly like the examples showing different visualizations of the same data and the parallel presentation of graphics and code. And I absolutely love the chapter on visual storytelling. I can't...

The book contains hundreds of engaging, class-tested statistics exercises (and detailed solutions) that test students' understanding of the material. Many are educational in their own right-for example, baseball managers who played professional ball were...

The book contains hundreds of engaging, class-tested statistics exercises (and detailed solutions) that test students' understanding of the material. Many are educational in their own right-for example, baseball managers who played professional ball were...

Focusing on the exploration of data with visual methods, "Displaying Time Series, Spatial, and Space-Time Data with R" presents methods and R code for producing high-quality static graphics, interactive visualizations, and animations, of time series,...

The objective of this book is to assist readers in acquiring proficiency in the introductory stages of R statistics. It aims to provide guidance on how to navigate the computer and input commands, as practice is essential for mastery. Furthermore, the...

Learn how to think like a statistician with Peck/Case's STATISTICS: LEARNING FROM DATA, 3rd Edition. This updated edition addresses common obstacles to learning based on the latest research for mastering statistics and probability. The authors use proven...

We set the foundation for a series of works aimed at proving strong relations between uniform random planar maps and Liouville quantum gravity (LQG). Our method relies on a bijective encoding of site-percolated planar triangulations by certain 2D lattice...

This advanced text focuses on the uses of distance sampling to estimate the density and abundance of biological populations. It addresses new methodologies, new technologies and recent developments in statistical theory and is the follow up companion to...