Because estimation involves inferring information about an unknown
quantity on the basis of available data, the selection of an
estimator is influenced by its ability to perform well under the
conditions that are assumed to underlie the data. Since these
conditions are never known exactly, the estimators chosen must be
robust; i.e., they must be able to perform well under a variety of
underlying conditions. The theory of robust estimation is based on
specified properties of specified estimators under specified
conditions. This book was written as the result of a study
undertaken to establish the interaction of these three components
over as large a range as possible. Originally published in 1972.
The Princeton Legacy Library uses the latest print-on-demand
technology to again make available previously out-of-print books
from the distinguished backlist of Princeton University Press.
These editions preserve the original texts of these important books
while presenting them in durable paperback and hardcover editions.
The goal of the Princeton Legacy Library is to vastly increase
access to the rich scholarly heritage found in the thousands of
books published by Princeton University Press since its founding in
1905.
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