Probability and statistics

The Monte Carlo Method: The Method of Statistical Trials is a systematic account of the fundamental concepts and techniques of the Monte Carlo method, together with its range of applications.

An engaging, sophisticated, and fun introduction to the field of Bayesian statistics, Bayes Rules!

This textbook provides an introduction to financial option valuation for undergraduates.

Linear regression is an important area of statistics, theoretical or applied.

This monograph develops adaptive stochastic methods in computational mathematics.

Conveniently grouping methods by techniques, such as chi-squared and empirical distributionfunction , and also collecting methods of testing for specific famous distributions, this usefulreference is the fust comprehensive.

"e;This textbook is a well-rounded, rigorous, and informative work presenting the mathematics behind modern machine learning techniques.

In this revised and extended version of his course notes from a 1-year course at Scuola Normale Superiore, Pisa, the author provides an introduction - for an audience knowing basic functional analysis and measure theory but not necessarily probability theory - to analysis in a separable Hilbert space of infinite dimension.

A look at Statistical Physics by renowned Russia-Soviet physicist Yuri Klimontovich of the Moscow State University, MSU Faculty of Physics.

This book provides a thorough conversation on the underpinnings of Covid-19 spread modelling by using stochastics nonlocal differential and integral operators with singular and non-singular kernels.

The book presents hands-on protocols for conventional and advanced forensic DNA fingerprinting experiments.

This contributed volume offers a much-needed overview of the statistical methods in early clinical drug and biomarker development.

Coefficient of Variation (CV) is a unit free index indicating the consistency of the data associated with a real-world process and is simple to mold into computational paradigms.

This book provides quantitative and applied methodologies in the Covid-19 era exploring important issues in demography, population studies, and health.

This book introduces readers to various signal processing models that have been used in analyzing periodic data, and discusses the statistical and computational methods involved.

This symposium on 'Computerized Basin Analysis for Prognosis of Energy - and Mineral Resources' was organized by Dr.

A road map for implementing quantitative financial models Financial Derivative and Energy Market Valuation brings the application of financial models to a higher level by helping readers capture the true behavior of energy markets and related financial derivatives.

 Deep Learning with R introduces deep learning and neural networks using the R programming language.

This book is the first exclusively devoted to the systematic synthesis of diagnostic test accuracy studies.

Mit der Version 6.

This book constitutes the refereed proceedings of the Third European Conference on Principles and Practice of Knowledge Discovery in Databases, PKDD'99, held in Prague, Czech Republic in September 1999.

This book presents fundamental concepts of optimization problems and its real-world applications in various fields.

One of the central problems synergetics is concerned with consists in the study of macroscopic qualitative changes of systems belonging to various disciplines such as physics, chemistry, or electrical engineering.

This volume brings together the main results in the field of Bayesian Optimization (BO), focusing on the last ten years and showing how, on the basic framework, new methods have been specialized to solve emerging problems from machine learning, artificial intelligence, and system optimization.

This volume describes how to conceptualize, perform, and critique traditional generalized linear models (GLMs) from a Bayesian perspective and how to use modern computational methods to summarize inferences using simulation.

Introduction to WinBUGS for Ecologists introduces applied Bayesian modeling to ecologists using the highly acclaimed, free WinBUGS software.

The purpose of these notes is to highlight the far-reaching connections between Information Theory and Statistics.

This book represents the refereed proceedings of the Tenth International Conference on Monte Carlo and Quasi-Monte Carlo Methods in Scientific Computing that was held at the University of New South Wales (Australia) in February 2012.

Statistical science s first coordinated manual of methods for analyzing ordered categorical data, now fully revised and updated, continues to present applications and case studies in fields as diverse as sociology, public health, ecology, marketing, and pharmacy.

This textbook is the result of the enhancement of several courses on non-equilibrium statistics, stochastic processes, stochastic differential equations, anomalous diffusion and disorder.

A practical guide to analysing partially observed data.

Effectively Access, Transform, Manipulate, Visualize, and Reason about Data and ComputationData Science in R: A Case Studies Approach to Computational Reasoning and Problem Solving illustrates the details involved in solving real computational problems encountered in data analysis.

Applied Stochastic Models and Control for Finance and Insurance presents at an introductory level some essential stochastic models applied in economics, finance and insurance.

Bayesian Networks: An Introduction provides a self-contained introduction to the theory and applications of Bayesian networks, a topic of interest and importance for statisticians, computer scientists and those involved in modelling complex data sets.

This 3-volume reference covers the entire field of epidemiology, from statistical methods and study design, to specialized areas such as molecular epidemiology, and applications in clinical medicine and health services research.

Nonlinearity and stochastic structural dynamics is of common interest to engineers and applied scientists belonging to many disciplines.

From the Preface.

This book is a practical guide on how to design, create and validate a spatial microsimulation model.

This unique book explores the definition, sources and role of randomness.

Students of statistics, operations research, and engineering will be informed of simulation methodology for problems in both mathematical statistics and systems simulation.

Statistical Decision Theory and Related Topics III, Volume 2 is a collection of papers presented at the Third Purdue Symposium on Statistical Decision Theory and Related Topics, held at Purdue University in June 1981.

This book constitutes the thoroughly refereed proceedings of the 14th International Conference on Web and Internet Economics, WINE 2018, held in Oxford, UK, in December 2018.

Data analysis is changing fast.

This book brings together expert researchers engaged in Monte-Carlo simulation-based statistical modeling, offering them a forum to present and discuss recent issues in methodological development as well as public health applications.