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​The complexity of today’s statistical data calls for modern
mathematical tools. Â Many fields of science make use of
mathematical statistics and require continuous updating on
statistical technologies. Practice makes perfect, Â since
mastering the tools makes them applicable. Â Our book of
exercises and solutions offers a wide range of applications and
numerical solutions based on R. In modern mathematical statistics,
the purpose is to provide statistics students with a number of
basic exercises and also an understanding of how the theory can be
applied to real-world problems. The application aspect is also
quite important, as most previous exercise books are mostly on
theoretical derivations. Also we add some problems from topics
often encountered in recent research papers. The book was written
for statistics students with one or two years of coursework in
mathematical statistics and probability, professors who hold
courses in mathematical statistics, and researchers in other fields
who would like to do some exercises on math statistics.
This textbook provides a unified and self-contained presentation of
the main approaches to and ideas of mathematical statistics. It
collects the basic mathematical ideas and tools needed as a basis
for more serious study or even independent research in statistics.
The majority of existing textbooks in mathematical statistics
follow the classical asymptotic framework. Yet, as modern
statistics has changed rapidly in recent years, new methods and
approaches have appeared. The emphasis is on finite sample
behavior, large parameter dimensions, and model misspecifications.
The present book provides a fully self-contained introduction to
the world of modern mathematical statistics, collecting the basic
knowledge, concepts and findings needed for doing further research
in the modern theoretical and applied statistics. This textbook is
primarily intended for graduate and postdoc students and young
researchers who are interested in modern statistical methods.
This textbook provides a unified and self-contained presentation of
the main approaches to and ideas of mathematical statistics. It
collects the basic mathematical ideas and tools needed as a basis
for more serious study or even independent research in statistics.
The majority of existing textbooks in mathematical statistics
follow the classical asymptotic framework. Yet, as modern
statistics has changed rapidly in recent years, new methods and
approaches have appeared. The emphasis is on finite sample
behavior, large parameter dimensions, and model misspecifications.
The present book provides a fully self-contained introduction to
the world of modern mathematical statistics, collecting the basic
knowledge, concepts and findings needed for doing further research
in the modern theoretical and applied statistics. This textbook is
primarily intended for graduate and postdoc students and young
researchers who are interested in modern statistical methods.
The complexity of today's statistical data calls for modern
mathematical tools. Many fields of science make use of mathematical
statistics and require continuous updating on statistical
technologies. Practice makes perfect, since mastering the tools
makes them applicable. Our book of exercises and solutions offers a
wide range of applications and numerical solutions based on R. In
modern mathematical statistics, the purpose is to provide
statistics students with a number of basic exercises and also an
understanding of how the theory can be applied to real-world
problems. The application aspect is also quite important, as most
previous exercise books are mostly on theoretical derivations. Also
we add some problems from topics often encountered in recent
research papers. The book was written for statistics students with
one or two years of coursework in mathematical statistics and
probability, professors who hold courses in mathematical
statistics, and researchers in other fields who would like to do
some exercises on math statistics.
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