Mixture models for studying stellar populations. II - Multivariate finite mixture models

Details Mixture models for studying stellar populations. II - Multivariate finite mixture models Mixture models for studying stellar populations. II - Multivariate finite mixture models

Apr 1993

adsabs.harvard.edu/cgi-bin/nph-data_query?bibcode=1993aj....105.1455n&link_type=abstract

Astronomical Journal (ISSN 0004-6256), vol. 105, no. 4, p. 1455-1471.

Astronomy and Astrophysics

Astronomy

10

Astronomical Models, Multivariate Statistical Analysis, Star Distribution, Kinematics, Metallicity, Mixing, Solar Neighborhood

Scientific paper

Multivariate finite mixture models provide a framework for analyzing and interpreting observational data that arise from the overlapping spatial, kinematical, chemical, and age distributions of stellar populations. The basic properties of multivariate finite mixture distributions are summarized; emphasis is placed on (1) the interpretation of observed overall gradients and (2) the distinction between models in which a gradient exists in at least one component and those in which there are no gradients within individual stellar population components. Central to this discussion are posterior mixing proportions, which describe how the mixing proportions for an observed sample of stars vary as functions of metal abundance, age, etc., and conditional mixture distributions, which describe the relationships that exist among the variables. General expressions for overall gradients in the mean and overall gradients in the variance are derived and certain types of selection effects are discussed briefly in the context of conditional mixture models. Illustrative examples of the methods are concerned primarily with the analysis of samples of solar neighborhood stars.

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