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Document type:
Zeitschriftenaufsatz 
Author(s):
Drton, Mathias 
Title:
Algebraic Techniques for Gaussian Models 
Abstract:
Many statistical models are algebraic in that they are defined by polynomial constraints or by parameterizations that are polynomial or rational maps. This opens the door for tools from computational algebraic geometry. These tools can be employed to solve equation systems arising in maximum likelihood estimation and parameter identification, but they also permit to study model singularities at which standard asymptotic approximations to the distribution of estimators and test statistics may no...    »
 
Keywords:
Algebraic statistics, multivariate normal distribution, parameter identification, singularities 
Dewey Decimal Classification:
510 Mathematik 
Congress title:
Prague Stochastics 2006, A joint session of "7th Prague Symposium on Asymptotic Statistics" and "15th Prague Conference on Information Theory, Statistical Decision Functions and Random Processes" 
Congress / additional information:
August 21-25, 2006 
Journal title:
Proceedings of Prague Stochastics 2006 
Year:
2006 
Year / month:
2006-11 
Quarter:
4. Quartal 
Month:
Nov 
Pages contribution:
91-90 
Language:
en 
WWW:
Publisher:
Matfyzpress 
Publisher address:
Prague 
Print-ISSN:
8086732754 9788086732756 
Date of publication:
01.11.2006 
Format:
Text