Parameter Redundancy and Identifiability by Diana Cole
Statistical and mathematical models are defined by parameters that describe different characteristics of those models. 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.-
Statistical and Econometric Methods for Transportation Data Analysis
- Bayesian Computational Methods in Statistical Signal Processing
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Age-Period-Cohort Analysis
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Measurement Error
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Clinical Trials in Oncology
- Compositional Data Analysis in Practice
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Bayesian Analysis of Capture-Recapture Data with Hidden Markov Models
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Survival Analysis with Interval-Censored Data
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Statistics for Fission Track Analysis
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Analysis of Capture-Recapture Data
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Missing Data Analysis in Practice
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Power Analysis of Trials with Multilevel Data
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Bayesian Analysis for Population Ecology
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Statistical Methods in Epilepsy
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Applied Directional Statistics
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An Invariant Approach to Statistical Analysis of Shapes
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Bayesian Disease Mapping
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Modern Directional Statistics
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Statistical Methods in Psychiatry and Related Fields
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Statistics of Medical Imaging
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Capture-Recapture Methods for the Social and Medical Sciences
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Multiple Imputation of Missing Data in Practice
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Bayesian Modeling of Spatio-Temporal Data with R
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Clinical Trials in Oncology, Third Edition
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Correspondence Analysis in Practice
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Introduction to Computational Biology
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Model-based Geostatistics for Global Public Health
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Design of Experiments for Generalized Linear Models
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Statistics for Biological Networks
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Model-Based Monitoring and Statistical Control
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Flexible Imputation of Missing Data, Second Edition
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The Data Book
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Mendelian Randomization
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Statistical Analysis of Questionnaires
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Design and Analysis of Quality of Life Studies in Clinical Trials
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Statistical Detection and Surveillance of Geographic Clusters
"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
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.
| SKU | Unavailable |
| ISBN 13 | 9780367493219 |
| ISBN 10 | 0367493217 |
| Title | Parameter Redundancy and Identifiability |
| Author | Diana Cole |
| Series | Chapman And Hall Crc Interdisciplinary Statistics |
| Condition | Unavailable |
| Binding Type | Paperback |
| Publisher | Taylor & Francis Ltd |
| Year published | 2021-12-13 |
| Number of pages | 252 |
| Cover note | Book picture is for illustrative purposes only, actual binding, cover or edition may vary. |
| Note | Unavailable |