Probability and statistics

Asymptotic methods provide important tools for approximating and analysing functions that arise in probability and statistics.

The contents of this monograph approximate the lectures I gave In a graduate course at Stanford University in the first half of 1981.

A bibliography on stochastic orderings.

Multiple Imputation in Practice: With Examples Using IVEware provides practical guidance on multiple imputation analysis, from simple to complex problems using real and simulated data sets.

Discrete stochastic models are tools that allow us to understand, control, and optimize engineering systems and processes.

Designed as a self-contained text, this book covers a wide spectrum of topics on portfolio theory.

Newly revised to specifically address Microsoft Excel 2019, this book is a step-by-step, exercise-driven guide for students and practitioners who need to master Excel to solve practical biological and life science problems.

This book presents the theory of matrix algebra for statistical applications, explores various types of matrices encountered in statistics, and covers numerical linear algebra.

This book explains how to employ MASEM, the combination of meta-analysis (MA) and structural equation modelling (SEM).

Testing for economic convergence across countries has been a central issue in the literature of economic growth and development.

An Introductory Handbook of Bayesian Thinking brings Bayesian thinking and methods to a wide audience beyond the mathematical sciences.

This book includes a review of mathematical tools like modelling, analysis of stochastic processes, calculus of variations and stochastic differential equations which are applied to solve financial problems like modern portfolio theory and option pricing.

This monograph is written for advanced Master's students, Ph.

The goal of this guide and manual is to provide a practical and brief overview of the theory on computerized adaptive testing (CAT) and multistage testing (MST) and to illustrate the methodologies and applications using R open source language and several data examples.

This book provides insights into important new developments in the area of statistical quality control and critically discusses methods used in on-line and off-line statistical quality control.

This book discusses the systems of interacting particles evolving in the random media.

This volume is representative of the work of Chinese probabilitists on probability theory and its applications in physics.

This is a masterly introduction to the modern, and rigorous, theory of probability.

Multivariate Bonferroni-Type Inequalities: Theory and Applications presents a systematic account of research discoveries on multivariate Bonferroni-type inequalities published in the past decade.

Methods for estimating sparse and large covariance matrices Covariance and correlation matrices play fundamental roles in every aspect of the analysis of multivariate data collected from a variety of fields including business and economics, health care, engineering, and environmental and physical sciences.

This volume of Methods of Experimental Physics provides an extensive introduction to probability and statistics in many areas of the physical sciences, with an emphasis on the emerging area of spatial statistics.

An in-depth guide to understanding probability distributions and financial modeling for the purposes of investment management In Financial Models with L vy Processes and Volatility Clustering, the expert author team provides a framework to model the behavior of stock returns in both a univariate and a multivariate setting, providing you with practical applications to option pricing and portfolio management.

This book presents a step by step Asset Health Management Optimization Approach Using Internet of Things (IoT).

The book provides necessary knowledge for readers interested in developing the theory of uniform experimental design.

This compact, entry-level Handbook equips applied practitioners to choose and use core models for real-world data - with R and SAS.

This thesis explores several interdisciplinary topics at the border of theoretical physics and biology, presenting results that demonstrate the power of methods from statistical physics when applied to neighbouring disciplines.

Biostatistics, Second Edition, is a user-friendly guide on biostatistics, which focuses on the proper use and interpretation of statistical methods.

The 39 self-contained sections in this book present worked-out examples as well as many sample problems categorized by the level of difficulty as Bronze, Silver, and Gold in order to help the readers gauge their progress and learning.

This book presents a systematic explanation of the SIML (Separating Information Maximum Likelihood) method, a new approach to financial econometrics.

Addressed to both pure and applied probabilitists, including graduate students, this text is a pedagogically-oriented introduction to the Schwartz-Meyer second-order geometry and its use in stochastic calculus.

This monograph contains a comprehensive account of the recent work of the authors and other workers on large sample optimal inference for non-ergodic models.

This book introduces the basic principles underlying the design and analysis of the digital communication systems that have heralded the information revolution.

This two-volume set constitutes the refereed post-conference proceedings of the 25th International Conference on Enterprise Information Systems, ICEIS 2023, which was held in Prague, Czech Republic, during April 2023.

Presenting tools to aid understanding of asymptotic theory and weakly dependent processes, this book is devoted to inequalities and limit theorems for sequences of random variables that are strongly mixing in the sense of Rosenblatt, or absolutely regular.

Rolf Steyer, Autor des erfolgreichen Lehrbuchs "Messen und Testen", schließt mit diesem Buch die Kluft zwischen Regressionstheorie und deren empirischer Anwendung, der Regressionsanalyse.

Probability Models is designed to aid students studying probability as part of an undergraduate course on mathematics or mathematics and statistics.

The book is a comprehensive treatment of classical and modern ruin probability theory.

This book covers numerical methods for stochastic partial differential equations with white noise using the framework of Wong-Zakai approximation.

This book is concerned with continuous-time Markov chains.

This book provides the tools, the methods, and the theory to meet the challenges of contemporary data science applied to geographic problems and data.

This book presents a treatise on the theory and modeling of second-order stationary processes, including an exposition on selected application areas that are important in the engineering and applied sciences.

This book constitutes the thoroughly refereed proceedings of the 22st International Conference on Computer Networks, CN 2015, held in Brunow, Poland, in June 2015.

This book explains the primary path to success, using software designed to sample and analyze cashflow and then link that analysis, with forecasting and market research.

This textbook presents some basic stochastic processes, mainly Markov processes.

Markov processes are used to model systems with limited memory.

Collecting Bayesian material scattered throughout the literature, Current Trends in Bayesian Methodology with Applications examines the latest methodological and applied aspects of Bayesian statistics.

The seminar on Stochastic Analysis and Mathematical Physics of the Ca- tholic University of Chile, started in Santiago in 1984, has being followed and enlarged since 1995 by a series of international workshops aimed at pro- moting a wide-spectrum dialogue between experts on the fields of classical and quantum stochastic analysis, mathematical physics, and physics.

Explore Important Tools for High-Quality Work in Pharmaceutical SafetyStatistical Methods for Drug Safety presents a wide variety of statistical approaches for analyzing pharmacoepidemiologic data.