Statistics

Statistics for Engineering and Physical Science

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Multivariate Kernel Smoothing and Its Applications

José E. Chacón, Tarn Duong
May 08, 2018

Kernel smoothing has greatly evolved since its inception to become an essential methodology in the Data Science tool kit for the 21st century. Its widespread adoption is due to its fundamental role for multivariate exploratory data analysis, as well as the crucial role it plays in composite...

Missing and Modified Data in Nonparametric Estimation: With R Examples

Sam Efromovich
March 12, 2018

This book presents a systematic and unified approach for modern nonparametric treatment of missing and modified data via examples of density and hazard rate estimation, nonparametric regression, filtering signals, and time series analysis. All basic types of missing at random and not at random,...

Theory of Stochastic Objects: Probability, Stochastic Processes and Inference

Athanasios Christou Micheas
January 29, 2018

This book defines and investigates the concept of a random object. To accomplish this task in a natural way, it brings together three major areas; statistical inference, measure-theoretic probability theory and stochastic processes. This point of view has not been explored by existing textbooks;...

Process Capability Analysis: Estimating Quality

Neil W. Polhemus
December 07, 2017

Process Capability Analysis: Estimating Quality presents a systematic exploration of process capability analysis and how it may be used to estimate quality. The book is designed for practitioners who are tasked with insuring a high level of quality for the products and services offered by their...

Statistics for Engineering and the Sciences, Sixth Edition, Textbook and Student Solutions Manual

William M. Mendenhall, Terry L. Sincich
November 28, 2017

This text is designed for a two-semester introductory course in statistics for students majoring in engineering or any of the physical sciences. Inevitably, once these students graduate and are employed, they will be involved in the collection and analysis of data and will be required to think...

Chemometric Monitoring: Product Quality Assessment, Process Fault Detection, and Applications

Madhusree Kundu, Palash Kumar Kundu, Seshu K. Damarla
October 03, 2017

Data collection, compression, storage, and interpretation have become mature technologies over the years. Extraction of meaningful information from the process historical database seems to be a natural and logical choice. In view of this, the proposed book aims to apply the data driven knowledge...

Simulation Methodology for Statisticians, Operations Analysts, and Engineers (1988)

P. W. A. Lewis, Ed McKenzie
October 02, 2017

Students of statistics, operations research, and engineering will be informed of simulation methodology for problems in both mathematical statistics and systems simulation. This discussion presents many of the necessary statistical and graphical techniques. A discussion of statistical methods based...

Random Signal Processing

Shaila Dinkar Apte
August 22, 2017

This book covers random signals and random processes along with estimation of probability density function, estimation of energy spectral density and power spectral density. The properties of random processes and signal modelling are discussed with basic communication theory estimation and...

Generalized Linear Models with Random Effects: Unified Analysis via H-likelihood, Second Edition

Youngjo Lee, John A. Nelder, Yudi Pawitan
August 04, 2017

This is the second edition of a monograph on generalized linear models with random effects that extends the classic work of McCullagh and Nelder. It has been thoroughly updated, with around 80 pages added, including new material on the extended likelihood approach that strengthens the theoretical...

Exploratory Data Analysis with MATLAB, Third Edition

Wendy L. Martinez, Angel R. Martinez, Jeffrey Solka
July 27, 2017

Praise for the Second Edition:"The authors present an intuitive and easy-to-read book. … accompanied by many examples, proposed exercises, good references, and comprehensive appendices that initiate the reader unfamiliar with MATLAB."—Adolfo Alvarez Pinto, International Statistical Review "...

Uncertainty Analysis of Experimental Data with R

Benjamin David Shaw
July 11, 2017

"This would be an excellent book for undergraduate, graduate and beyond….The style of writing is easy to read and the author does a good job of adding humor in places. The integration of basic programming in R with the data that is collected for any experiment provides a powerful platform for...

Computational Methods for Numerical Analysis with R

James P Howard, II
June 08, 2017

Computational Methods for Numerical Analysis with R is an overview of traditional numerical analysis topics presented using R. This guide shows how common functions from linear algebra, interpolation, numerical integration, optimization, and differential equations can be implemented in pure R code....

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