Prof. Kazuhiko Kakamu (Kobe University) gave a lecture on February 3, 2017.

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Day & Time 3rd February 2017
Venue Room C816, Building of the Faculty of Science Graduate school of Science
Lecturer Prof. Kazuhiko Kakamu (Kobe University)
Presentation Title Baysian estimation of beta-type distribution parameters based on grouped data
Abstract This study considers the estimation method of generalized beta (GB) distribution parameters based on
grouped data from a Bayesian point of view. Because the GB distribution, which was proposed by McDonald
and Xu (1995), includes several kinds of familiar distributions as special or limiting cases, it performs at least
as well as those special or limiting distributions. Therefore, it is reasonable to estimate the parameters of the GB distribution. However, when the number of groups is small or when the number of parameters increases, it may become difficult to estimate the distribution parameters for grouped data using the existing estimation
methods. This study uses a Tailored randomized block Metropolis–Hastings (TaRBMH) algorithm proposed by Chib and Ramamurthy (2010) to estimate the GB distribution parameters, and this method is applied to one simulated and two real datasets. Moreover, the Gini coefficients from the estimated parameters for the GB distribution are examined.