Probability and statistics

This book highlights the need for studying multi-state models analytically for understanding the physics of molecular processes.

RicochetConfessions Of A Gun Lobbyist"e;Ricochet tells the truth.

This book examines how to develop the main traits that are necessary to become an "e;informed intuitant"e;.

Quantum-like structure is present practically everywhere.

Since its introduction in 1972, Stein's method has offered a completely novel way of evaluating the quality of normal approximations.

This volume showcases a collection of thirty-two peer-reviewed articles presented at the XXVI Congress of the Portuguese Statistical Society (2023).

The aim of this book is to provide a strong theoretical support for understanding and analyzing the behavior of evolutionary algorithms, as well as for creating a bridge between probability, set-oriented numerics and evolutionary computation.

In recent years, many pharmaceutical companies and clinical research organizations have been focusing on the development of traditional Chinese (herbal) medicines (TCMs) as alternatives to treating critical or life-threatening diseases and as pathways to personalized medicine.

Written by an experienced statistics educator and two data scientists, this book unifies conventional statistical thinking and contemporary machine learning framework into a single overarching umbrella over data science.

This is a new, completely revised, updated and enlarged edition of the author's Ergebnisse vol.

This book introduces the reader to the optical switching technology for its application to data centers.

The purpose of this edited book is to bring together the ideas and findings of data mining researchers and bioinformaticians by discussing cutting-edge research topics such as, gene expressions, protein/RNA structure prediction, phylogenetics, sequence and structural motifs, genomics and proteomics, gene findings, drug design, RNAi and microRNA analysis, text mining in bioinformatics, modelling of biochemical pathways, biomedical ontologies, system biology and pathways, and biological database management.

The theory of time series models has been well developed over the last thirt,y years.

In the 2nd edition some sections of Part I are omitted for better readability, and a brand new chapter is devoted to volatility risk.

This book focuses on economic inequality, its measurement, and its relationship with economic growth and development.

An introductory 2002 student text giving insights into economics as seen from the perspective of physics.

Encyclopedic in breadth, yet practical and concise, Medical Biostatistics, Fourth Edition focuses on the statistical aspects ofmedicine with a medical perspective, showing the utility of biostatistics as a tool to manage many medical uncertainties.

Ranking of Multivariate Populations: A Permutation Approach with Applications presents a novel permutation-based nonparametric approach for ranking several multivariate populations.

Learn how to program by diving into the R language, and then use your newfound skills to solve practical data science problems.

geschlossene Darstellung, welche die Plankostenrechnung in den Rahmen der kosten­ rechnerischen Entwicklung stellt und ihren Aufbau als ein in sich geschlossenes Sy­ stem wiedergibt.

This book uses asymptotic methods to obtain simple approximate analytic solutions to various problems within mechanics, notably wave processes in heterogeneous materials.

Jean-Jacques Rousseau wrote in the Preface to his famous Discourse on Inequality that "e;I consider the subject of the following discourse as one of the most interesting questions philosophy can propose, and unhappily for us, one of the most thorny that philosophers can have to solve.

The long-awaited revision of Fundamentals of Applied Probability and Random Processes expands on the central components that made the first edition a classic.

This proceedings volume presents new methods and applications in applied economics with special interest in advanced cross-section data estimation methodology.

This book provides the necessary prerequisites in probability and statistics as well as the key ideas in decision theory.

A mathematician who has taken the romantic decision to devote himself to biology will doubtlessly look upon cell kinetics as the most simple and natural field of application for his knowledge and skills.

This two-part volume gathers extended conference abstracts corresponding to selected talks from the "e;Biostatnet workshop on Biomedical (Big) Data"e; and from the "e;DoReMi LD-RadStats: Workshop for statisticians interested in contributing to EU low dose radiation research"e;, which were held at the Centre de Recerca Matematica (CRM) in Barcelona from November 26th to 27th, 2015, and at the Institut de Salut Global ISGlobal (former CREAL) from October 26th to 28th, 2015, respectively.

This book presents innovations in the mathematical foundations of financial analysis and numerical methods for finance and applications to the modeling of risk.

An Introduction to Quantum Stochastic Calculus aims to deepen our understanding of the dynamics of systems subject to the laws of chance both from the classical and the quantum points of view and stimulate further research in their unification.

This selection of Donald B.

This book includes speeches given during five seminar sessions held in honor of Prof.

Our time is characterized by an explosive growth in the use of ever more complicated and sophisticated (computer) models.

"e;Decision Systems and Non-stochastic Randomness"e; is the first systematic presentation and mathematical formalization (including existence theorems) of the statistical regularities of non-stochastic randomness.

Mathematical Theory of Bayesian Statistics introduces the mathematical foundation of Bayesian inference which is well-known to be more accurate in many real-world problems than the maximum likelihood method.

This book is a concise hands-on guide that provides students a useful tool for a systematic approach to scientific inquiry.

Simplifies the treatment of statistical inference focusing on how to specify and interpret models in the context of testing causal theories.

Covers everything readers need to know about clustering methodology for symbolic data including new methods and headings while providing a focus on multi-valued list data, interval data and histogram data This book presents all of the latest developments in the field of clustering methodology for symbolic data paying special attention to the classification methodology for multi-valued list, interval-valued and histogram-valued data methodology, along with numerous worked examples.

This book provides a general framework for learning sparse graphical models with conditional independence tests.

At the intersection of computer science and healthcare, data analytics has emerged as a promising tool for solving problems across many healthcare-related disciplines.

During the past few decades we have witnessed an era of remarkable growth in the field of molecular biology.

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.

Teaches students how to use R to conduct the statistical analyses most commonly used in political science.

This book highlights the tribological behavior of elastomers by investigating the effect of operating variables such as, the applied load and the abrasive particle size, and the materials' mechanical properties such as, tensile strength, elongation at break, hardness, and tear strength by the experimental, statistical and analytical methods.

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