Divide-and-Conquer Information-Based Optimal Subdata Selection Algorithm

The information-based optimal subdata selection (IBOSS) is a computationally efficient method to select informative data points from large data sets through processing full data by columns. However, when the volume of a data set is too large to be processed in the available memory of a machine, it i...

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Vydáno v:	Journal of statistical theory and practice Ročník 13; číslo 3
Hlavní autor:	Wang, HaiYing
Médium:	Journal Article
Jazyk:	angličtina
Vydáno:	Cham Springer International Publishing 01.09.2019
Témata:	Algorithms Analysis and Advanced Methodologies in the Design of Experiments Mathematics and Statistics Original Article Probability Theory and Stochastic Processes Statistical Theory and Methods Statistics D-optimality Big data Subdata Linear regression Information matrix
ISSN:	1559-8608, 1559-8616
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