[Solomonov Seminar] 243. Solomonov seminar

[Marko Grobelnik]

Zacenjamo po poletno sezono Solomonovih seminarjev. V dveh tednih se 
bodo zvrstili trije.

V cetrtek, 13. septembra bo ob 13h v Oranzni predavalnici IJS (drugo 
nadstropje glavne stavbe) 243 Solomonov seminar. Posnetki preteklih 
seminarjev so na http://videolectures.net/solomon/

Predavala bo gostja Galit Shmueli na temo ucinkovitega prestevanja podatkov.

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Galit Shmueli, SRITNE Chaired Professor of Data AnalyticsAssociate 
Professor of Statistics & IS
Indian School of Business || Gachibowli, Hyderabad

A Flexible Model for Count Data: The COM-Poisson Distribution

Count data arise in many contexts, from word lengths to traffic volume 
to number of bids in online auctions, and generally in many 
event-counting applications. Yet, there is a scarcity of statistical 
models for such data. The Poisson distribution is the most popular 
distribution for modeling count data, yet it is constrained by its 
equi-dispersion assumption, making it less than ideal for modeling real 
data that often exhibit over-dispersion or under-dispersion. The 
COM-Poisson distribution is a two-parameter generalization of the 
Poisson distribution that allows for a wide range of over-dispersion and 
under-dispersion. It also contains the Bernoulli and geometric 
distributions as special cases, and as a member of the exponential 
family has useful statistical properties. This distribution's 
flexibility and special properties have prompted a fast growth of 
methodological and applied research in various fields. In this talk, I 
will introduce the COM-Poisson distribution and regression model and 
mention several other COM-Poisson models that have been published thus 
far. I will also describe applications of the COM-Poisson in various 
areas including disclosure limitation, marketing, transportation and 
linguistics.