Probability and statistics

This book provides a concise yet rigorous introduction to probability theory.

This book is among the first to present the mathematical models most commonly used to solve optimal execution problems and market making problems in finance.

Find the right algorithm for your image processing applicationExploring the recent achievements that have occurred since the mid-1990s, Circular and Linear Regression: Fitting Circles and Lines by Least Squares explains how to use modern algorithms to fit geometric contours (circles and circular arcs) to observed data in image processing and comput

Mathematical Statistics: Basic Ideas and Selected Topics, Volume I, Second Edition presents fundamental, classical statistical concepts at the doctorate level.

Contains Nearly 100 Pages of New MaterialThe recent financial crisis has shown that credit risk in particular and finance in general remain important fields for the application of mathematical concepts to real-life situations.

This book is an essential guide for product managers seeking to harness the power of data to drive their product decisions.

This book is an essential guide for product managers seeking to harness the power of data to drive their product decisions.

An Integrated Approach to Modeling and Optimization in Engineering and Science examines the effects of experimental design, mathematical modeling, and optimization processes for solving many different problems.

As multicriteria decision-making (MCDM) continues to grow and evolve, machine learning (ML) techniques have become increasingly important in finding efficient and effective solutions to complex problems.

The new book highlights the application of artificial intelligence, machine learning, and deep learning techniques to diagnose medical problems.

Intermediate Poker Mathematics provides a fascinating collection of mathematical questions set in the diverse world of poker.

Oftentimes, small groups (called clusters) of individuals (called subunits) are randomized between treatment arms.

To make the best decisions, you need the best information.

An Integrated Approach to Modeling and Optimization in Engineering and Science examines the effects of experimental design, mathematical modeling, and optimization processes for solving many different problems.

Statistical methods provide a logical, coherent framework in which data from experimental science can be analyzed.

As sensors become ubiquitous, a set of broad requirements is beginning to emerge across high-priority applications including disaster preparedness and management, adaptability to climate change, national or homeland security, and the management of critical infrastructures.

In real-life scenarios, service management involves complex decision-making processes usually affected by random or stochastic variables.

This book shows how statistical reasoning affects all aspects of our lives.

An Introductory Econometrics TextMathematical Statistics for Applied Econometrics covers the basics of statistical inference in support of a subsequent course on classical econometrics.

El libro Análisis exploratorio de datos es una introducción a la estadística descriptiva y probabilidad, con aplicaciones en áreas económico-administrativas.

Unlock the power of data with this comprehensive guide to statistics and probability!

In the past, disease pattern mapping depended on census tracts based on political units, such as states and counties.

In a VUCA world, which is becoming increasingly volatile, uncertain, and complex, companies, organizations, and states must respond promptly and adequately to the respective situations.

In a VUCA world, which is becoming increasingly volatile, uncertain, and complex, companies, organizations, and states must respond promptly and adequately to the respective situations.

Drawing from the authors' own work and from the most recent developments in the field, Missing Data in Longitudinal Studies: Strategies for Bayesian Modeling and Sensitivity Analysis describes a comprehensive Bayesian approach for drawing inference from incomplete data in longitudinal studies.

Although the popularity of the Bayesian approach to statistics has been growing for years, many still think of it as somewhat esoteric, not focused on practical issues, or generally too difficult to understand.

Is adaptive randomization always better than traditional fixed-schedule randomization?

This classic text, originally from the noted logician Elliot Mendelson, is intended to be an easy-to-read introduction to the basic ideas and techniques of game theory.

Geographic information, spatial analysis and geospatial technologies play an important role in understanding changes in planetary health and in defining the drivers contributing to different health outcomes both locally and globally.

It's been over a decade since the first edition of Measurement Error in Nonlinear Models splashed onto the scene, and research in the field has certainly not cooled in the interim.

In answer to the intense development of new financial products and the increasing complexity of portfolio management theory, Portfolio Optimization and Performance Analysis offers a solid grounding in modern portfolio theory.

Nonpharmacological treatments include a wide variety of treatments such as surgery, technical procedures, implantable and non-implantable devices, rehabilitation, psychotherapy, and behavioral interventions.

The book introduces a series of state-of-art Bayesian models that can be used to understand and predict spatially structured population dynamics in our changing world.

The book introduces a series of state-of-art Bayesian models that can be used to understand and predict spatially structured population dynamics in our changing world.

This monograph is a compilation of research on the inverse Gaussian distribution.

Bayesian Modeling in Bioinformatics discusses the development and application of Bayesian statistical methods for the analysis of high-throughput bioinformatics data arising from problems in molecular and structural biology and disease-related medical research, such as cancer.

Lucidly Integrates Current ActivitiesFocusing on both fundamentals and recent advances, Introduction to Machine Learning and Bioinformatics presents an informative and accessible account of the ways in which these two increasingly intertwined areas relate to each other.

¿Por qué algunas personas tienen la vida de sus sueños y otras se quedan esperando algo que nunca llega?

With today's consumers spending more time on their mobiles than on their PCs, new methods of empirical stochastic modeling have emerged that can provide marketers with detailed information about the products, content, and services their customers desire.

Handbook of Cluster Analysis provides a comprehensive and unified account of the main research developments in cluster analysis.

This is the fourth book in the Neural Network series.

This is the fourth book in the Neural Network series.

This book describes how Bayesian methods work.

This book describes how Bayesian methods work.