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Intended as a textbook for students taking a first graduate course in the subject, as well as for the general reference of interested research workers, this text discusses, in a readable form, developments from recently published work on certain broad topics not otherwise easily accessible, such as robust inference and the use of the bootstrap in a multivariate setting. A minimum background expected of the reader would include at least two courses in mathematical statistics, and certainly some exposure to the calculus of several variables together with the descriptive geometry of linear algebra.
Intended as a textbook for students taking a first graduate course
in the subject, as well as for the general reference of interested
research workers, this text discusses, in a readable form,
developments from recently published work on certain broad topics
not otherwise easily accessible, such as robust inference and the
use of the bootstrap in a multivariate setting. A minimum
background expected of the reader would include at least two
courses in mathematical statistics, and certainly some exposure to
the calculus of several variables together with the descriptive
geometry of linear algebra.
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