منابع مشابه
Bayesian Robust Estimation of Systematic Risk Using Product Partition Models
We consider Bayesian estimation of the systematic risk of a share using product partition models (PPM). The cluster structure of the PPM is used to derive a robust Bayes estimator of beta and also to identify outliers or clusters of observations. The procedure is implemented considering independent scale mixture of normals for the error terms. The results are illustrated with an application to ...
متن کاملBayesian Analysis of Value-at-Risk with Product Partition Models
Extended Abstract Value-at-Risk (VaR) measures the maximum potential loss of single assets or portfolio of assets, once a given confidence level and a time horizon have been fixed. VaR has become the standard measure for financial analysts to quantify market risk and it is also important for regulatory pourposes. In particular Basel accords impose that all financial institutions have to meet ca...
متن کاملProduct Representation of Dyon Partition Function in CHL Models
A formula for the exact partition function of 1/4 BPS dyons in a class of CHL models has been proposed earlier. The formula involves inverse of Siegel modular forms of subgroups of Sp(2, ZZ). In this paper we propose product formulae for these modular forms. This generalizes the result of Borcherds and Gritsenko and Nikulin for the weight 10 cusp form of the full Sp(2, ZZ) group.
متن کاملModal Clustering in a Univariate Class of Product Partition Models
This paper presents an algorithm for finding the maximum a posteriori (MAP) clustering in a class of univariate product partition models. While the number of possible clusterings of n observations grows according to the Bell exponential number, the dynamic programming algorithm presented here exploits properties of the model to provide an O(n2) search. Hence, the algorithm can be used to find t...
متن کاملBayesian Generalized Product Partition Model
Starting with a carefully formulated Dirichlet process (DP) mixture model, we derive a generalized product partition model (GPPM) in which the partition process is predictor-dependent. The GPPM generalizes DP clustering to relax the exchangeability assumption through the incorporation of predictors, resulting in a generalized Pólya urn scheme. In addition, the GPPM can be used for formulating f...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: Bayesian Analysis
سال: 2016
ISSN: 1936-0975
DOI: 10.1214/15-ba971