Probability and statistics

Focuses on a few of the important clustering algorithms in the context of information retrieval.

This book presents a coherent and unified account of classical and more advanced techniques for analyzing the performance of randomized algorithms.

An advanced textbook; with many examples and exercises, often with hints or solutions; code is provided for computational examples and simulations.

The book presents contributions on statistical models and methods applied, for both data science and SDGs, in one place.

Many conventional survival analysis methods, such as the Kaplan-Meier method for survival function estimation and the partial likelihood method for Cox model regression coefficients estimation, were developed under the assumption that survival times are subject to right censoring only.

This book introduces readers to the fundamentals of creating presentation graphics using R, based on 100 detailed and complete scripts.

Modern computer-intensive statistical methods play a key role in solving many problems across a wide range of scientific disciplines.

This textbook is aimed at computer science undergraduates late in sophomore or early in junior year, supplying a comprehensive background in qualitative and quantitative data analysis, probability, random variables, and statistical methods, including machine learning.

Do you find statistics overwhelming and confusing?

Item Response Theory clearly describes the most recently developed IRT models and furnishes detailed explanations of algorithms that can be used to estimate the item or ability parameters under various IRT models.

This book is the first volume of a two-volume monograph devoted to the study of limit and ergodic theorems for regularly and singularly perturbed Markov chains, semi-Markov processes, and multi-alternating regenerative processes with semi-Markov modulation.

This book introduces readers to statistical methodologies used to analyze doubly truncated data.

This book builds bridges between two yet separated branches of theoretical and mathematical chemistry: Chemical Graph Theory and Electronic Structure Calculations.

Great interest is now being shown in computational and mathematical neuroscience, fuelled in part by the rise in computing power, the ability to record large amounts of neurophysiological data, and advances in stochastic analysis.

This book gives a necessary and sufficient condition in terms of the scattering amplitude for a scatterer to be spherically symmetric.

This handbook provides a thorough overview of the current state of knowledge in this area.

This book provides an undergraduate introduction to discrete and continuous-time Markov chains and their applications.

This book constitutes the refereed proceedings of the Second International Symposium on Dependable Software Engineering: Theories, Tools, and Applications, SETTA 2016, held in Beijing, China, in November 2016.

These proceedings of the workshop on quantum probability held in Heidelberg, September 26-30, 1988 contains a representative selection of research articles on quantum stochastic processes, quantum stochastic calculus, quantum noise, geometry, quantum probability, quantum central limit theorems and quantum statistical mechanics.

This book discusses recent developments in mathematical programming and game theory, and the application of several mathematical models to problems in finance, games, economics and graph theory.

This book shows the reader how to transform cold numbers into captivating narratives that drive business success.

This book explores all relevant aspects of net scoring, also known as uplift modeling: a data mining approach used to analyze and predict the effects of a given treatment on a desired target variable for an individual observation.

Focusing on shocks modeling, burn-in and heterogeneous populations, Stochastic Modeling for Reliability naturally combines these three topics in the unified stochastic framework and presents numerous practical examples that illustrate recent theoretical findings of the authors.

Das vorliegende Buch gibt eine umfassende Darstellung der in der ökonometrischen Literatur gebräuchlichen Ungleichgewichtsmodelle zusammen mit einer eingehenden theoretisch-statistischen Analyse der Identifizierbarkeits- und Schätzproblematik.

From the author of the bestselling "e;Analysis of Time Series,"e; Time-Series Forecasting offers a comprehensive, up-to-date review of forecasting methods.

The theory of the measure of noncompactness has proved its significance in various contexts, particularly in the study of fixed point theory, differential equations, functional equations, integral and integrodifferential equations, optimization, and others.

A valuable resource for students and teachers alike, this second edition contains more than 200 worked examples and exam questions.

This book reports on cutting-edge theories and methods for analyzing complex systems, such as transportation and communication networks and discusses multi-disciplinary approaches to dependability problems encountered when dealing with complex systems in practice.

Elementary Probability with Applications, Second Edition shows students how probability has practical uses in many different fields, such as business, politics, and sports.

A properly structured financial model can provide decision makers with a powerful planning tool that helps them identify the consequences of their decisions before they are put into practice.

Taking readers with a basic knowledge of probability and real analysis to the frontiers of a very active research discipline, this textbook provides all the necessary background from functional analysis and the theory of PDEs.

This book offers an overview on the main modern important topics in random variables, random processes, and decision theory for solving real-world problems.

Drawing on a comprehensive theoretical foundation encompassing socio-constructivism, social learning, and motivation, this book offers a new theoretical contribution and sheds light on the transformative power of acumenous game-based learning to reengage learners with Mathematics and Statistics Education.

Image analysis is one of the most challenging areas in today's computer sci- ence, and image technologies are used in a host of applications.

An introductory text for students taking a first course in statistics-in fields as diverse as engineering, business, chemistry, and biology-Essential Statistics: Fourth Edition thoroughly updates and enhances the hugely successful third edition.

This book discusses chemometric methods for spectroscopy analysis including NIR, MIR, Raman, NMR, and LIBS, from the perspective of practical applied spectroscopy.

This is a self-contained exposition by one of the leading experts in lattice theory, George Gratzer, presenting the major results of the last 70 years on congruence lattices of finite lattices, featuring the author's signature Proof-by-Picture method.

"e;Overall, this textbook is a perfect guide for interested researchers and students who wish to understand the rationale and methods of causal inference.

This volume contains the proceedings of the Tenth International Congress on Medical Informatics, MIE 91, that will be held in Vienna, Austria, August 19-22, 1991.

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.

A beginner s guide to stochastic growth modeling The chief advantage of stochastic growth models over deterministic models is that they combine both deterministic and stochastic elements of dynamic behaviors, such as weather, natural disasters, market fluctuations, and epidemics.

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

Aggregation plays a central role in many of the technological tasks we are faced with.

A guide to the implementation and interpretation of Quantile Regression models This book explores the theory and numerous applications of quantile regression, offering empirical data analysis as well as the software tools to implement the methods.

The aim of this book is to equip biostatisticians and other quantitative scientists with the necessary skills, knowledge, and habits to collaborate effectively with clinicians in the healthcare field.

Practice your way to a higher statistics score The adage that "e;practice makes perfect"e; is never truer than with math problems.