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A course in large sample theory by Thomas S. Ferguson

A course in large sample theory Thomas S. Ferguson ebook
Page: 247
Publisher: Chapman & Hall
ISBN: 0412043718, 9780412043710
Format: djvu

The Generalized Likelihood Ratio Procedure and its large sample behavior, goodness of fit tests. Ferguson, A Course in Large Sample Theory, Chapman & Hall, New York, NY, USA, 1996. Ferguson, A Course in Large Sample Theory, Chapman and Hall, 1996. Description: A first course in the theory of statistics, to follow STAT 516. For large samples, since no such procedure is im- Now usually, a first course on statistical inference more theoretical details see e.g. The central limit theorem is one of the most remarkable results of the theory of probability [1], which is critical to understand inferential statistics and hypothesis testing [2, 3]. Not mathematically advanced, but covers a large volume of material. A Course in Large Sample Theory. Hence, the dependence condition (2.3) allows a stronger dependence within a larger class of random variables and demands more independence within a smaller class. Www.maths.lth.se/matstat/staff/nader/stint/course-plan_heping.pdf. Foss, Ergodicity of queueing networks, Siberian Math.