Titlebook: Asymptotic Statistical Inference; A Basic Course Using Shailaja Deshmukh,Madhuri Kulkarni Textbook 2021 The Editor(s) (if applicable) and T

Inkling

https://doi.org/10.1007/978-1-4302-0377-3t that convergence in probability implies convergence in law, .. Thus, the asymptotic distribution of . is degenerate at .. Such a degenerate distribution is not helpful to find the rate of convergence or to find an interval estimator of .. Hence, we try to find a blowing factor . such that the asym

担忧

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DRILL

978-981-15-9005-4The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Singapor

Cryptic

Introduction, distribution with some illustrations as it is basic to all statistical inference procedures and data analysis. An estimator . is defined as a Borel measurable function from the sample space to the parameter space. In the present book, the focus is on the discussion of large sample optimality proper

吸引力

Consistency of an Estimator, to . using various modes of convergence. The most frequently investigated large sample property of an estimator is weak consistency. Weak consistency of an estimator is defined in terms of convergence in probability. We examine how close the estimator is to the true parameter value in terms of prob