A Course in Large Sample Theory is presented in four parts. The
first treats basic probabilistic notions, the second features the
basic statistical tools for expanding the theory, the third
contains special topics as applications of the general theory, and
the fourth covers more standard statistical topics. Nearly all
topics are covered in their multivariate setting. The book is
intended as a first year graduate course in large sample theory for
statisticians. It has been used by graduate students in statistics,
biostatistics, mathematics, and related fields. Throughout the book
there are many examples and exercises with solutions. It is an
ideal text for self study.
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