Probability and statistics

This book presents the first comprehensive and modern mathematical treatment of these mean field particle models, including refined convergence analysis on nonlinear Markov chain models.

This focuses on the developing field of building probability models with the power of symbolic algebra systems.

This book is devoted to the study of multivariate discrete q-distributions, which is greatly facilitated by existing multivariate q-sequences and q-functions.

The general topic of this book is the ergodic behavior of Markov processes.

The second edition of Robust Statistical Methods with R provides a systematic treatment of robust procedures with an emphasis on new developments and on the computational aspects.

Learn how to easily transform your data into engaging, interactive visual reports!

This book constitutes the refereed joint proceedings of the First International Workshop on Computational Pathology, COMPAY 2018, and the 5th International Workshop on Ophthalmic Medical Image Analysis, OMIA 2018, held in conjunction with the 21st International Conference on Medical Imaging and Computer-Assisted Intervention, MICCAI 2018, in Granada, Spain, in September 2018.

As a stand-alone text, a self-study manual, or a supplement to a lab manual or comprehensive text, The Joy of Stats is a unique and versatile resource.

Functional analysis and operator theory are widely used in the description, understanding and control of dynamical systems and natural processes in physics, chemistry, medicine and the engineering sciences.

This book reflects general trends in the study of geometric aspects of functional analysis, understood in a broad sense.

This volume discusses an important area of statistics and highlights the most important statistical advances.

Fundamental Statistics for the Social and Behavioral Sciences, Second Edition, places statistics within the research process, illustrating how they are used to answer questions and test ideas.

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Clarifies modern data analysis through nonparametric density estimation for a complete working knowledge of the theory and methods Featuring a thoroughly revised presentation, Multivariate Density Estimation: Theory, Practice, and Visualization, Second Edition maintains an intuitive approach to the underlying methodology and supporting theory of density estimation.

A valuable teaching aid.

A Primer on Linear Models presents a unified, thorough, and rigorous development of the theory behind the statistical methodology of regression and analysis of variance (ANOVA).

This coherent mathematical and statistical approach aimed at graduate students incorporates regression and topology as well as graph theory.

A versatile manual that can be used to stimulate product innovation, benchmarking analysis, and engineering design, this book goes beyond theory to provide relevant advanced methods and techniques that readers can apply in their work for both short- and long-term results.

Dieser Buchtitel ist Teil des Digitalisierungsprojekts Springer Book Archives mit Publikationen, die seit den Anfängen des Verlags von 1842 erschienen sind.

Stochastic elasticity is a fast developing field that combines nonlinear elasticity and stochastic theories in order to significantly improve model predictions by accounting for uncertainties in the mechanical responses of materials.

Using real data sets throughout, this text introduces the latest methods for analyzing high-dimensional survival data.

This book includes discussions related to solutions of such tasks as: probabilistic description of the investment function; recovering the income function from GDP estimates; development of models for the economic cycles; selecting the time interval of pseudo-stationarity of cycles; estimating characteristics/parameters of cycle models; analysis of accuracy of model factors.

This book provides a coherent framework for understanding shrinkage estimation in statistics.

The aim of this book is an applied and unified introduction into parametric, non- and semiparametric regression that closes the gap between theory and application.

This book is the third edition of a successful textbook for upper-undergraduate and early graduate students, which offers a solid foundation in probability theory and statistics and their application to physical sciences, engineering, biomedical sciences and related disciplines.

Of the three lecture courses making up the CIME summer school on Fluid Dynamics at Cetraro in 2005 reflected in this volume, the first, due to Sergio Albeverio describes deterministic and stochastic models of hydrodynamics.

This book continues the mission of the previous text by the author, Lectures on Categorical Data Analysis, by expanding on the introductory concepts from that volume and providing a mathematically rigorous presentation of advanced topics and current research in statistical techniques which can be applied in the social, political, behavioral, and life sciences.

Introductory Statistics, Third Edition, presents statistical concepts and techniques in a manner that will teach students not only how and when to utilize the statistical procedures developed, but also to understand why these procedures should be used.

Linear models courses are often presented as either theoretical or applied.

Matrix algebra plays a very important role in statistics and in many other dis- plines.

Since their introduction, hierarchical generalized linear models (HGLMs) have proven useful in various fields by allowing random effects in regression models.

Analyzing Event Statistics in Corporate Finance provides new alternative methodologies to increase accuracy when performing statistical tests for event studies within corporate finance.

All techniques illustrated on data sets relevant to insurance; SAS code and output, data sets, exercise solutions on website

Mathematical programming has know a spectacular diversification in the last few decades.

A Technical Guide to Mathematical Finance covers those foundational mathematical topics most important to an aspiring or professional quant.

What are your chances of dying on your next flight, being called for jury duty, or winning the lottery?

This book provides in a concise, yet detailed way, the bulk of the probabilistic tools that a student working toward an advanced degree in statistics,probability and other related areas, should be equipped with.

This book provides an overview of state-of-the-art uncertainty quantification (UQ) methodologies and applications, and covers a wide range of current research, future challenges and applications in various domains, such as aerospace and mechanical applications, structure health and seismic hazard, electromagnetic energy (its impact on systems and humans) and global environmental state change.

A New Way of Analyzing Object Data from a Nonparametric ViewpointNonparametric Statistics on Manifolds and Their Applications to Object Data Analysis provides one of the first thorough treatments of the theory and methodology for analyzing data on manifolds.

This volume contains a collection of research articles on multivariate statistical methods, encompassing both theoretical advances and emerging applications in a variety of scientific disciplines.

The R Companion for Sampling: Design and Analysis, designed to be read alongside Sampling: Design and Analysis, Third Edition by Sharon L.

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 book introduces a new representation of probability measures, the lift zonoid representation, and demonstrates its usefulness in statistical applica- tions.

All data are the result of human actions whether by experimentations, observations, or declarations.