On bagging and estimation in multivariate mixtures

Pakyari, Reza (author)

Two bagging approaches, say 1 2 n-out-of-n without replacement (subagging) and n-out-of-n with replacement (bagging) have been applied in the problem of estimation of the parameters in a multivariate mixture model. It has been observed by Monte Carlo simulations and a real data example, that both bagging methods have improved the standard deviation of the maximum likelihood estimator of the mixing proportion, whilst the absolute bias increased slightly. In estimating the component distributions, bagging could increase the root mean integrated squared error when estimating the most probable component.

• Language: English
• Work type: Not categorized
• Typology: 1.01 - Original Scientific Article
• Organization: FDV - Faculty of Social Sciences
• Publisher: Fakulteta za družbene vede
• Year: 2008
• Number of pages: Str. 9-18
• Numbering: Vol. 5, No. 1
• PID: 20.500.12556/RUL-58694
• UDC: 519.2
• ISSN on article: 1854-0023
• COBISS.SI-ID: 29128797
• Publication date in RUL: 10.07.2015

Record is a part of a journal

• Title: Advances in methodology and statistics
• Shortened title: Metodol. zv.
• Publisher: Fakulteta za družbene vede
• ISSN: 1854-0023
• COBISS.SI-ID: 215795712