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A. Mahabal, S. G. Djorgovski, M. Graham, R. Williams (Caltech), E. Feigelson, G. J. Babu (Penn State), R. Nichol, D. Vanden Berk, L. Wasserman (CMU)
VOStat (Virtual Observatory Statistics) project aims to provide a rich suite of web-based statistical services for exploration and analysis of astronomical data sets, especially in the context of a Virtual Observatory environment. We demonstrate here a few exploratory science applications covering a range of functionalities. We start by showing how to rediscover basic relationships like the HR diagram using stellar catalogues, move on to discoveries of more complex, multivariate correlations for parameters of globular clusters, and go on to show how KDE trees can be used to identify quasar candidates using multicolor Palomar-QUEST survey data, as outliers in the color space. Some other planned applications are also briefly outlined.
This work is supported in part by the NSF grant DMS-0101360.
If you would like more information about this abstract, please follow the link to http://www.astro.caltech.edu/~aam/science/vostat. This link was provided by the author. When you follow it, you will leave the Web site for this meeting; to return, you should use the Back comand on your browser.
The author(s) of this abstract have provided an email address for comments about the abstract: aam@astro.caltech.edu
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Bulletin of the American Astronomical Society, 36 #2
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