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Multivariate Statistical Analysis - A High-Dimensional Approach (Hardcover, 2000 ed.)
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Multivariate Statistical Analysis - A High-Dimensional Approach (Hardcover, 2000 ed.)
Series: Theory and Decision Library B, 41
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This book presents a new branch of mathematical statistics aimed at
constructing unimprovable methods of multivariate analysis,
multi-parametric estimation, and discriminant and regression
analysis. In contrast to the traditional consistent Fisher method
of statistics, the essentially multivariate technique is based on
the decision function approach by A. Wald. Developing this new
method for high dimensions, comparable in magnitude with sample
size, provides stable approximately unimprovable procedures in some
wide classes, depending on an arbitrary function. A remarkable fact
is established: for high-dimensional problems, under some weak
restrictions on the variable dependence, the standard quality
functions of regularized multivariate procedures prove to be
independent of distributions. For the first time in the history of
statistics, this opens the possibility to construct unimprovable
procedures free from distributions. Audience: This work will be of
interest to researchers and graduate students whose work involves
statistics and probability, reliability and risk analysis,
econometrics, machine learning, medical statistics, and various
applications of multivariate analysis.
General
Imprint: |
Springer
|
Country of origin: |
Netherlands |
Series: |
Theory and Decision Library B, 41 |
Release date: |
2001 |
First published: |
2000 |
Authors: |
V.I. Serdobolskii
|
Dimensions: |
234 x 156 x 25mm (L x W x T) |
Format: |
Hardcover
|
Pages: |
244 |
Edition: |
2000 ed. |
ISBN-13: |
978-0-7923-6643-0 |
Categories: |
Books >
Science & Mathematics >
Mathematics >
Probability & statistics
|
LSN: |
0-7923-6643-3 |
Barcode: |
9780792366430 |
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