Numerical Methods Of Statistics

Author : John F. Monahan
Publisher : Cambridge University Press
Page : 465 pages
File Size : 43,8 Mb
Release : 2011-04-18
Category : Computers
ISBN : 9781139498005

Get Book

Numerical Methods of Statistics by John F. Monahan Pdf

This book explains how computer software is designed to perform the tasks required for sophisticated statistical analysis. For statisticians, it examines the nitty-gritty computational problems behind statistical methods. For mathematicians and computer scientists, it looks at the application of mathematical tools to statistical problems. The first half of the book offers a basic background in numerical analysis that emphasizes issues important to statisticians. The next several chapters cover a broad array of statistical tools, such as maximum likelihood and nonlinear regression. The author also treats the application of numerical tools; numerical integration and random number generation are explained in a unified manner reflecting complementary views of Monte Carlo methods. Each chapter contains exercises that range from simple questions to research problems. Most of the examples are accompanied by demonstration and source code available from the author's website. New in this second edition are demonstrations coded in R, as well as new sections on linear programming and the Nelder–Mead search algorithm.

Author : John F. Monahan
Publisher : Cambridge University Press
Page : 446 pages
File Size : 44,6 Mb
Release : 2001-02-05
Category : Computers
ISBN : 0521791685

Get Book

Numerical Methods of Statistics by John F. Monahan Pdf

This 2001 book provides a basic background in numerical analysis and its applications in statistics.

Author : Kenneth Lange
Publisher : Springer Science & Business Media
Page : 606 pages
File Size : 44,7 Mb
Release : 2010-05-17
Category : Business & Economics
ISBN : 9781441959454

Get Book

Numerical Analysis for Statisticians by Kenneth Lange Pdf

Numerical analysis is the study of computation and its accuracy, stability and often its implementation on a computer. This book focuses on the principles of numerical analysis and is intended to equip those readers who use statistics to craft their own software and to understand the advantages and disadvantages of different numerical methods.

Author : James P Howard, II
Publisher : CRC Press
Page : 257 pages
File Size : 52,7 Mb
Release : 2017-07-12
Category : Mathematics
ISBN : 9781498723640

Get Book

Computational Methods for Numerical Analysis with R by James P Howard, II Pdf

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. Every algorithm described is given with a complete function implementation in R, along with examples to demonstrate the function and its use. Computational Methods for Numerical Analysis with R is intended for those who already know R, but are interested in learning more about how the underlying algorithms work. As such, it is suitable for statisticians, economists, and engineers, and others with a computational and numerical background.

Author : John Monahan
Publisher : Unknown
Page : 128 pages
File Size : 42,5 Mb
Release : 2024-07-02
Category : Electronic
ISBN : 1107665930

Get Book

Numerical Methods of Statistics by John Monahan Pdf

Author : Paolo Brandimarte
Publisher : John Wiley & Sons
Page : 501 pages
File Size : 44,6 Mb
Release : 2013-06-06
Category : Mathematics
ISBN : 9781118625576

Get Book

Numerical Methods in Finance and Economics by Paolo Brandimarte Pdf

A state-of-the-art introduction to the powerful mathematical and statistical tools used in the field of finance The use of mathematical models and numerical techniques is a practice employed by a growing number of applied mathematicians working on applications in finance. Reflecting this development, Numerical Methods in Finance and Economics: A MATLAB?-Based Introduction, Second Edition bridges the gap between financial theory and computational practice while showing readers how to utilize MATLAB?--the powerful numerical computing environment--for financial applications. The author provides an essential foundation in finance and numerical analysis in addition to background material for students from both engineering and economics perspectives. A wide range of topics is covered, including standard numerical analysis methods, Monte Carlo methods to simulate systems affected by significant uncertainty, and optimization methods to find an optimal set of decisions. Among this book's most outstanding features is the integration of MATLAB?, which helps students and practitioners solve relevant problems in finance, such as portfolio management and derivatives pricing. This tutorial is useful in connecting theory with practice in the application of classical numerical methods and advanced methods, while illustrating underlying algorithmic concepts in concrete terms. Newly featured in the Second Edition: * In-depth treatment of Monte Carlo methods with due attention paid to variance reduction strategies * New appendix on AMPL in order to better illustrate the optimization models in Chapters 11 and 12 * New chapter on binomial and trinomial lattices * Additional treatment of partial differential equations with two space dimensions * Expanded treatment within the chapter on financial theory to provide a more thorough background for engineers not familiar with finance * New coverage of advanced optimization methods and applications later in the text Numerical Methods in Finance and Economics: A MATLAB?-Based Introduction, Second Edition presents basic treatments and more specialized literature, and it also uses algebraic languages, such as AMPL, to connect the pencil-and-paper statement of an optimization model with its solution by a software library. Offering computational practice in both financial engineering and economics fields, this book equips practitioners with the necessary techniques to measure and manage risk.

Author : Anonim
Publisher : Academic Publishers
Page : 491 pages
File Size : 53,8 Mb
Release : 2024-07-02
Category : Electronic
ISBN : 9789380599298

Get Book

Numerical Analysis & Statistical Methods by Anonim Pdf

Author : R.A. Thisted
Publisher : Routledge
Page : 448 pages
File Size : 45,5 Mb
Release : 2017-10-19
Category : Mathematics
ISBN : 9781351452755

Get Book

Elements of Statistical Computing by R.A. Thisted Pdf

Statistics and computing share many close relationships. Computing now permeates every aspect of statistics, from pure description to the development of statistical theory. At the same time, the computational methods used in statistical work span much of computer science. Elements of Statistical Computing covers the broad usage of computing in statistics. It provides a comprehensive account of the most important computational statistics. Included are discussions of numerical analysis, numerical integration, and smoothing. The author give special attention to floating point standards and numerical analysis; iterative methods for both linear and nonlinear equation, such as Gauss-Seidel method and successive over-relaxation; and computational methods for missing data, such as the EM algorithm. Also covered are new areas of interest, such as the Kalman filter, projection-pursuit methods, density estimation, and other computer-intensive techniques.

Author : J. H. Pollard
Publisher : CUP Archive
Page : 372 pages
File Size : 40,7 Mb
Release : 1977
Category : Mathematics
ISBN : 0521297508

Get Book

A Handbook of Numerical and Statistical Techniques by J. H. Pollard Pdf

This handbook is designed for experimental scientists, particularly those in the life sciences. It is for the non-specialist, and although it assumes only a little knowledge of statistics and mathematics, those with a deeper understanding will also find it useful. The book is directed at the scientist who wishes to solve his numerical and statistical problems on a programmable calculator, mini-computer or interactive terminal. The volume is also useful for the user of full-scale computer systems in that it describes how the large computer solves numerical and statistical problems. The book is divided into three parts. Part I deals with numerical techniques and Part II with statistical techniques. Part III is devoted to the method of least squares which can be regarded as both a statistical and numerical method. The handbook shows clearly how each calculation is performed. Each technique is illustrated by at least one example and there are worked examples and exercises throughout the volume.

Author : Manish Goyal
Publisher : Laxmi Publications
Page : 814 pages
File Size : 48,5 Mb
Release : 2009
Category : C (Computer program language)
ISBN : 8131805220

Get Book

Numerical Methods and Statistical Techniques Using 'C' by Manish Goyal Pdf

Author : Christopher G. Small,Jinfang Wang
Publisher : Oxford University Press
Page : 330 pages
File Size : 54,6 Mb
Release : 2003
Category : Mathematics
ISBN : 0198506880

Get Book

Numerical Methods for Nonlinear Estimating Equations by Christopher G. Small,Jinfang Wang Pdf

Non linearity arises in statistical inference in various ways, with varying degrees of severity, as an obstacle to statistical analysis. More entrenched forms of nonlinearity often require intensive numerical methods to construct estimators, and the use of root search algorithms, or one-step estimators, is a standard method of solution. This book provides a comprehensive study of nonlinear estimating equations and artificial likelihood's for statistical inference. It provides extensive coverage and comparison of hill climbing algorithms, which when started at points of nonconcavity often have very poor convergence properties, and for additional flexibility proposes a number of modification to the standard methods for solving these algorithms. The book also extends beyond simple root search algorithms to include a discussion of the testing of roots for consistency, and the modification of available estimating functions to provide greater stability in inference. A variety of examples from practical applications are included to illustrate the problems and possibilities thus making this text ideal for the research statistician and graduate student.

Author : Marcos von Sperling ,Matthew E. Verbyla ,Silvia M.A.C Oliveira
Publisher : IWA Publishing
Page : 668 pages
File Size : 49,5 Mb
Release : 2020-01-15
Category : Science
ISBN : 9781780409313

Get Book

Assessment of Treatment Plant Performance and Water Quality Data: A Guide for Students, Researchers and Practitioners by Marcos von Sperling ,Matthew E. Verbyla ,Silvia M.A.C Oliveira Pdf

This book presents the basic principles for evaluating water quality and treatment plant performance in a clear, innovative and didactic way, using a combined approach that involves the interpretation of monitoring data associated with (i) the basic processes that take place in water bodies and in water and wastewater treatment plants and (ii) data management and statistical calculations to allow a deep interpretation of the data. This book is problem-oriented and works from practice to theory, covering most of the information you will need, such as (a) obtaining flow data and working with the concept of loading, (b) organizing sampling programmes and measurements, (c) connecting laboratory analysis to data management, (e) using numerical and graphical methods for describing monitoring data (descriptive statistics), (f) understanding and reporting removal efficiencies, (g) recognizing symmetry and asymmetry in monitoring data (normal and log-normal distributions), (h) evaluating compliance with targets and regulatory standards for effluents and water bodies, (i) making comparisons with the monitoring data (tests of hypothesis), (j) understanding the relationship between monitoring variables (correlation and regression analysis), (k) making water and mass balances, (l) understanding the different loading rates applied to treatment units, (m) learning the principles of reaction kinetics and reactor hydraulics and (n) performing calibration and verification of models. The major concepts are illustrated by 92 fully worked-out examples, which are supported by 75 freely-downloadable Excel spreadsheets. Each chapter concludes with a checklist for your report. If you are a student, researcher or practitioner planning to use or already using treatment plant and water quality monitoring data, then this book is for you! 75 Excel spreadsheets are available to download.

Author : James E. Gentle
Publisher : Springer Science & Business Media
Page : 732 pages
File Size : 42,6 Mb
Release : 2009-07-28
Category : Mathematics
ISBN : 9780387981444

Get Book

Computational Statistics by James E. Gentle Pdf

Computational inference is based on an approach to statistical methods that uses modern computational power to simulate distributional properties of estimators and test statistics. This book describes computationally intensive statistical methods in a unified presentation, emphasizing techniques, such as the PDF decomposition, that arise in a wide range of methods.

Author : John David Lee,Timothy D. Lee
Publisher : Van Nostrand Reinhold Company
Page : 288 pages
File Size : 46,7 Mb
Release : 1982
Category : Computers
ISBN : UVA:X001448956

Get Book

Statistics and Numerical Methods in BASIC for Biologists by John David Lee,Timothy D. Lee Pdf

Author : Rudolf Frühwirth,Are Strandlie
Publisher : Springer Nature
Page : 208 pages
File Size : 51,9 Mb
Release : 2021
Category : Electronic books
ISBN : 9783030657710

Get Book

Pattern Recognition, Tracking and Vertex Reconstruction in Particle Detectors by Rudolf Frühwirth,Are Strandlie Pdf

This open access book is a comprehensive review of the methods and algorithms that are used in the reconstruction of events recorded by past, running and planned experiments at particle accelerators such as the LHC, SuperKEKB and FAIR. The main topics are pattern recognition for track and vertex finding, solving the equations of motion by analytical or numerical methods, treatment of material effects such as multiple Coulomb scattering and energy loss, and the estimation of track and vertex parameters by statistical algorithms. The material covers both established methods and recent developments in these fields and illustrates them by outlining exemplary solutions developed by selected experiments. The clear presentation enables readers to easily implement the material in a high-level programming language. It also highlights software solutions that are in the public domain whenever possible. It is a valuable resource for PhD students and researchers working on online or offline reconstruction for their experiments.