The objective of this book is to compare the statistical
properties of penalty and non-penalty estimation strategies for
some popular models. Specifically, it considers the full model,
submodel, penalty, pretest and shrinkage estimation techniques for
three regression models before presenting the asymptotic properties
of the non-penalty estimators and their asymptotic distributional
efficiency comparisons. Further, the risk properties of the
non-penalty estimators and penalty estimators are explored through
a Monte Carlo simulation study. Showcasing examples based on real
datasets, the book will be useful for students and applied
researchers in a host of applied fields.
The book's level of presentation and style make it accessible to
a broad audience. It offers clear, succinct expositions of each
estimation strategy. More importantly, it clearly describes how to
use each estimation strategy for the problem at hand. The book is
largely self-contained, as are the individual chapters, so that
anyone interested in a particular topic or area of application may
read only that specific chapter. The book is specially designed for
graduate students who want to understand the foundations and
concepts underlying penalty and non-penalty estimation and its
applications. It is well-suited as a textbook for senior
undergraduate and graduate courses surveying penalty and
non-penalty estimation strategies, and can also be used as a
reference book for a host of related subjects, including courses on
meta-analysis. Professional statisticians will find this book to be
a valuable reference work, since nearly all chapters are
self-contained.
General
| Imprint: |
Springer International Publishing AG
|
| Country of origin: |
Switzerland |
| Series: |
SpringerBriefs in Statistics |
| Release date: |
December 2013 |
| First published: |
2014 |
| Authors: |
S. Ejaz Ahmed
|
| Dimensions: |
235 x 155 x 6mm (L x W x T) |
| Format: |
Paperback
|
| Pages: |
115 |
| Edition: |
2014 ed. |
| ISBN-13: |
978-3-319-03148-4 |
| Categories: |
Books >
Science & Mathematics >
Mathematics >
Probability & statistics
Promotions
|
| LSN: |
3-319-03148-1 |
| Barcode: |
9783319031484 |
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