Algebraic Methods in Statistics and Probability
Marlos A. G. Viana, Donald St. P. Richards
Algebraic methods and arguments in statistics and probability are well known, from Gauss' least squares principle through Fisher's method of variance decomposition. The relevance of group-theoretic arguments, for example, became evident in the 1980s. Such techniques continue to be of interest today, along with other developments, such as the use of graph theory in modelling complex stochastic systems.
This volume is based on lectures presented at the AMS Special Session on Algebraic Methods and Statistics held at the University of Notre Dame (Indiana) and on contributed articles solicited for this volume. The articles are intended to foster communication between representatives of the diverse scientific areas in which these functions are utilized and to further the trend of utilizing algebraic methods in the areas of statistics and probability. This is one of few volumes devoted to the subject of algebraic methods in statistics and probability. The wide range of topics covered in this volume demonstrates the vigorous level of research and opportunities ongoing in these areas
ক্যাটাগোরিগুলো:
সাল:
2001
প্রকাশক:
American Mathematical Society
ভাষা:
english
পৃষ্ঠা:
354
ISBN 10:
2319734074
ISBN 13:
9782519763355
বইয়ের সিরিজ:
Contemporary Mathematics 287
ফাইল:
DJVU, 3.31 MB
IPFS:
,
english, 2001
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