Applied Asymptotics by A R Brazzale
In fields such as biology, medical sciences, sociology, and economics researchers often face the situation where the number of available observations, or the amount of available information, is sufficiently small that approximations based on the normal distribution may be unreliable. Theoretical work over the last quarter-century has led to new likelihood-based methods that lead to very accurate approximations in finite samples, but this work has had limited impact on statistical practice. This book illustrates by means of realistic examples and case studies how to use the new theory, and investigates how and when it makes a difference to the resulting inference. The treatment is oriented towards practice and comes with code in the R language (available from the web) which enables the methods to be applied in a range of situations of interest to practitioners. The analysis includes some comparisons of higher order likelihood inference with bootstrap or Bayesian methods.-
Data Analysis and Graphics Using R
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Measure Theory and Filtering
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Essentials of Statistical Inference
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Markov Chains
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A User's Guide to Measure Theoretic Probability
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Probability
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High-Dimensional Probability
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Asymptotic Statistics
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Statistical Models
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Model Selection and Model Averaging
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Bootstrap Methods and their Application
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Random Graph Dynamics
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Modern Statistical Methods and Theory
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A Course in Interacting Particle Systems
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Networks
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The Coordinate-Free Approach to Linear Models
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The Estimation and Tracking of Frequency
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Semiparametric Regression
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Statistical Mechanics of Disordered Systems
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Random Networks for Communication
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Statistical Analysis of Stochastic Processes in Time
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Regression for Categorical Data
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Numerical Methods of Statistics
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Symmetry Studies
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Nonparametric Estimation under Shape Constraints
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Elements of Distribution Theory
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From Finite Sample to Asymptotic Methods in Statistics
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Bayesian Methods
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Design of Comparative Experiments
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Analysis of Multivariate and High-Dimensional Data
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Mathematical Foundations of Infinite-Dimensional Statistical Models
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Probability on Trees and Networks
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Spectral Analysis for Univariate Time Series
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Predictive Statistics
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Long-Range Dependence and Self-Similarity
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Statistical Hypothesis Testing in Context: Volume 52
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Saddlepoint Approximations with Applications
'…I welcome this book and wish it well in achieving some inroads into practical use of a large area of theoretical developments' Journal of Applied Statistics
'This is a very welcome book, on a very important topic.' Andrew Robinson, University of Melbourne
'This is an excellent book for applied statisticians. It presents application of higher order asymptotic theory in likelihood in many different contexts. … I highly recommend the book to researchers looking for ways to improve accuracy in statistical testing. The book is well written, the examples are clear and because all examples can be verified by the reader through the provided packages and code in R, the analyses can be explored in great detail.' Biometrics
'This is a very welcome book, on a very important topic.' Andrew Robinson, University of Melbourne
'This is an excellent book for applied statisticians. It presents application of higher order asymptotic theory in likelihood in many different contexts. … I highly recommend the book to researchers looking for ways to improve accuracy in statistical testing. The book is well written, the examples are clear and because all examples can be verified by the reader through the provided packages and code in R, the analyses can be explored in great detail.' Biometrics
Alessandra Brazzale is a Researcher in Statistics at the Institute of Biomedical Engineering, Italian National Research Council, Padova. Anthony Davison is a Professor of Statistics at the Ecole Polytechnique Fédérale de Lausanne. Nancy Reid is a University Professor of Statistics at the University of Toronto.
| SKU | Unavailable |
| ISBN 13 | 9780521847032 |
| ISBN 10 | 0521847036 |
| Title | Applied Asymptotics |
| Author | A R Brazzale |
| Series | Cambridge Series In Statistical And Probabilistic Mathematics |
| Condition | Unavailable |
| Binding Type | Hardback |
| Publisher | Cambridge University Press |
| Year published | 2007-05-31 |
| Number of pages | 248 |
| Cover note | Book picture is for illustrative purposes only, actual binding, cover or edition may vary. |
| Note | Unavailable |