For graduate-level courses in Statistical Inference or Theoretical Statistics in departments of Statistics, Bio-Statistics, Economics, Computer Science, and Mathematics.
A classic, time-honored introduction to the theory and practice of statistics modeling and inference―revised to reflect the changing focus of Statistics and the mathematics background of today's students. Coverage begins with the more general nonparametric point of view and then looks at parametric models as submodels of the nonparametric ones which can be described smoothly by Euclidean parameters. Although some computational issues are discussed, this is very much a book on theory. A second volume treating more advanced topics is in preparation.
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