By Ulhas Jayram Dixit
This e-book discusses examples in parametric inference with R.
Combining uncomplicated concept with sleek methods, it offers the latest
developments and tendencies in statistical inference for college kids who don't have
an complicated mathematical and statistical history. the themes mentioned in
the publication are primary and customary to many fields of statistical inference and
thus function some extent of departure for in-depth learn. The ebook is split into
eight chapters: bankruptcy 1 presents an outline of subject matters on sufficiency and
completeness, whereas bankruptcy 2 in short discusses impartial estimation. bankruptcy 3
focuses at the learn of moments and greatest chance estimators, and bankruptcy 4
presents bounds for the variance. In bankruptcy five, issues on constant estimator
are mentioned. bankruptcy 6 discusses Bayes, whereas bankruptcy 7 experiences a few more
powerful exams. finally, bankruptcy eight examines impartial and different tests.
Senior undergraduate and graduate scholars in information and
mathematics, and those that have taken an introductory path in probability,
will significantly make the most of this ebook. scholars are anticipated to grasp matrix
algebra, calculus, chance and distribution concept earlier than starting this
course. providing a wealth of appropriate solved and unsolved difficulties, the book
offers an outstanding software for academics and teachers who can assign homework
problems from the routines, and scholars will locate the solved examples hugely
beneficial in fixing the workout problems.
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