Shrinkage Estimation by Dominique Fourdrinier
The book focuses primarily on point and loss estimation of the mean vector of multivariate normal and spherically symmetric distributions. In particular, Chapter 5 extends many of the results from Chapters 2 and 3 to spherically and elliptically symmetric distributions.-
The Elements of Statistical Learning
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Dragons of Winter Night
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Functional Data Analysis
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Time Series: Theory and Methods
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Modeling Discrete Time-to-Event Data
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Targeted Learning
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Models for Discrete Longitudinal Data
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Regression Modeling Strategies
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Targeted Learning in Data Science
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An Introduction to Sequential Monte Carlo
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Sampling Algorithms
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Modern Multidimensional Scaling
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Correlation Theory of Stationary and Related Random Functions
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Mathematical Statistics
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Breakthroughs in Statistics
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Statistical Models Based on Counting Processes
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Hidden Markov Processes and Adaptive Filtering
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Design of Observational Studies
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Chaos: A Statistical Perspective
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A Comparison of the Bayesian and Frequentist Approaches to Estimation
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Smoothing Spline ANOVA Models
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Analysis of Neural Data
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Finite Mixture and Markov Switching Models
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The Gini Methodology
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Ten Projects in Applied Statistics
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Growth Curve Models and Statistical Diagnostics
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Statistical Methods in Software Engineering
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Gaussian and Non-Gaussian Linear Time Series and Random Fields
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Markov Bases in Algebraic Statistics
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Data
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A Course on Point Processes
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Theory of Statistics
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Bayesian and Frequentist Regression Methods
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A Statistical Model
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Prediction Theory for Finite Populations
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Tools for Statistical Inference
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Parameter Estimation and Hypothesis Testing in Spectral Analysis of Stationary Time Series
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ARMA Model Identification
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Statistical Design and Analysis for Intercropping Experiments
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Approximate Distributions of Order Statistics
“This book a timely and well-written exposition of shrinkage, or Stein, estimation intended for graduate students and researchers who wish to learn more about the topic” (Éric Marchand, Mathematical Reviews, August, 2019)
“The well-written volume, presenting the actual knowledge in this field, is suitable for readers having good background in analysis, linear algebra, probability theory and mathematical statistics.” (Kurt Marti, zbMATH 1411.62011, 2019)
“The well-written volume, presenting the actual knowledge in this field, is suitable for readers having good background in analysis, linear algebra, probability theory and mathematical statistics.” (Kurt Marti, zbMATH 1411.62011, 2019)
Dominique Fourdrinier is a Professor of Mathematical Statistics at the University of Rouen in France and an Adjunct Professor of Statistical Science at Cornell University. He earned his M.S. and Ph.D. degrees, both in Mathematical Statistics, at the University of Rouen. He is noted for his deep insights on the connections between shrinkage estimation and the properties of differential operators and has made important contributions to Bayesian statistics, decision theory, estimation theory, spherical and elliptical symmetry, the Stein phenomena as well as to statistical methods for signal and image processing. William E. Strawderman is a Professor of Statistics at Rutgers University. He earned an M.S. in Mathematics from Cornell University and a second M.S. in Statistics from Rutgers, and then completed his Ph.D. in Statistics, also at Rutgers. He is a fellow of both the Institute of Mathematical Statistics and American Statistical Society and an Elected Member, International Statistical Institute. In 2015 he was named a Distinguished Alumni at Cornell. He is noted for path-breaking work in shrinkage estimation and has made fundamental contributions to a number of additional areas in statistics, including Bayesian statistics, decision theory, spherical symmetry, and biostatistics.
Martin T. Wells is the Charles A. Alexander Professor of Statistical Sciences at Cornell University. He is also a Professor of Social Statistics, Professor of Biostatistics and Epidemiology at Weill Cornell Medicine as well as an Elected Member of the Cornell Law School Faculty. He is a fellow of both the Institute of Mathematical Statistics and American Statistical Society and an Elected Member, International Statistical Institute. His research interests include Bayesian statistics, biostatistics, decision theory, empirical legal studies, machine learning, and statistical genomics.
Martin T. Wells is the Charles A. Alexander Professor of Statistical Sciences at Cornell University. He is also a Professor of Social Statistics, Professor of Biostatistics and Epidemiology at Weill Cornell Medicine as well as an Elected Member of the Cornell Law School Faculty. He is a fellow of both the Institute of Mathematical Statistics and American Statistical Society and an Elected Member, International Statistical Institute. His research interests include Bayesian statistics, biostatistics, decision theory, empirical legal studies, machine learning, and statistical genomics.
| SKU | Unavailable |
| ISBN 13 | 9783030021849 |
| ISBN 10 | 303002184X |
| Title | Shrinkage Estimation |
| Author | Dominique Fourdrinier |
| Series | Springer Series In Statistics |
| Condition | Unavailable |
| Binding Type | Hardback |
| Publisher | Springer Nature Switzerland AG |
| Year published | 2018-12-06 |
| Number of pages | 333 |
| Cover note | Book picture is for illustrative purposes only, actual binding, cover or edition may vary. |
| Note | Unavailable |