JSM 2004 - Toronto

Abstract #300869

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Activity Number: 27
Type: Contributed
Date/Time: Sunday, August 8, 2004 : 2:00 PM to 3:50 PM
Sponsor: Biometrics Section
Abstract - #300869
Title: Classic Poisson Mixture Modeling with Application to Neuroscience
Author(s): Zhuoxin Sun*+ and Ori Rosen and Allan R. Sampson
Companies: University of Pittsburgh and University of Pittsburgh and University of Pittsburgh
Address: 27th Fl. CL, Dept. of Statistics, Pittsburgh, PA, 15260,
Keywords: mixture models ; EM algorithm ; mixtures of Poissons
Abstract:

In some neurological post-mortem tissue studies, each observation can be viewed as coming from one of a pre-specified number of populations where each population corresponds to a possible type of neurons. We employ standard mixture models with pre-specified number of components to model such data. The EM algorithm is implemented to estimate the parameters in the model. Also we provide a discussion of the statistical and computational issues concerning estimation of Poisson mixtures. An application is given to compare schizophrenic and control subjects with regard to the parvalbumin mRNA expression level of the neurons in the prefrontal cortex. Our approach is compared to a more standard approach to analyze such data.

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