Parameter Redundancy and Identifiability

Author:   Diana Cole
Publisher:   Taylor & Francis Inc
ISBN:  

9781498720878


Pages:   272
Publication Date:   18 May 2020
Format:   Hardback
Availability:   In Print   Availability explained
This item will be ordered in for you from one of our suppliers. Upon receipt, we will promptly dispatch it out to you. For in store availability, please contact us.

Our Price $315.00 Quantity:  
Add to Cart

Share |

Parameter Redundancy and Identifiability


Add your own review!

Overview

Statistical and mathematical models are defined by parameters that describe different characteristics of those models. Ideally it would be possible to find parameter estimates for every parameter in that model, but, in some cases, this is not possible. For example, two parameters that only ever appear in the model as a product could not be estimated individually; only the product can be estimated. Such a model is said to be parameter redundant, or the parameters are described as non-identifiable. This book explains why parameter redundancy and non-identifiability is a problem and the different methods that can be used for detection, including in a Bayesian context. Key features of this book: Detailed discussion of the problems caused by parameter redundancy and non-identifiability Explanation of the different general methods for detecting parameter redundancy and non-identifiability, including symbolic algebra and numerical methods Chapter on Bayesian identifiability Throughout illustrative examples are used to clearly demonstrate each problem and method. Maple and R code are available for these examples More in-depth focus on the areas of discrete and continuous state-space models and ecological statistics, including methods that have been specifically developed for each of these areas This book is designed to make parameter redundancy and non-identifiability accessible and understandable to a wide audience from masters and PhD students to researchers, from mathematicians and statisticians to practitioners using mathematical or statistical models.

Full Product Details

Author:   Diana Cole
Publisher:   Taylor & Francis Inc
Imprint:   Chapman & Hall/CRC
Weight:   0.530kg
ISBN:  

9781498720878


ISBN 10:   1498720870
Pages:   272
Publication Date:   18 May 2020
Audience:   College/higher education ,  General/trade ,  Tertiary & Higher Education ,  General
Format:   Hardback
Publisher's Status:   Active
Availability:   In Print   Availability explained
This item will be ordered in for you from one of our suppliers. Upon receipt, we will promptly dispatch it out to you. For in store availability, please contact us.

Table of Contents

Reviews

This is an interesting book which concentrates on a relatively narrow, but certainly important and unfortunately often neglected topic of identifiability in statistical (and generic mathematical) models...In principle, it is certainly accessible to a wide audience, from students to practicing statisticians, or even to quantitatively oriented non-statistical scientists...Very nicely, the book reads somewhat as a story, going from simpler things to the more complicated, ultimately leading to fascinating and far-reaching things like design considerations with respect to extrinsic parameter redundancy, as well as practical implications for what the author calls integrated population models. - Marek Brabec, ISCB News, December 2020


Author Information

Diana Cole is a Senior Lecturer in Statistics at the University of Kent. She has written and co-authored 15 papers on parameter redundancy and identifiability, including general theory and ecological applications.

Tab Content 6

Author Website:  

Customer Reviews

Recent Reviews

No review item found!

Add your own review!

Countries Available

All regions
Latest Reading Guide

ls

Shopping Cart
Your cart is empty
Shopping cart
Mailing List