Zobrazeno 1 - 10
of 804
pro vyhledávání: '"Karabatsos, A."'
Autor:
Karabatsos, George
This short communication introduces a sensitivity analysis method for Multiple Testing Procedures (MTPs), based on marginal $p$-values and the Dirichlet process prior distribution. The method measures each $p$-value's insensitivity towards a signific
Externí odkaz:
http://arxiv.org/abs/2410.08080
Autor:
Karabatsos, George
This invited feature article introduces and provides an extensive simulation study of a new Approximate Bayesian Computation (ABC) framework for estimating the posterior distribution and the maximum likelihood estimate (MLE) of the parameters of mode
Externí odkaz:
http://arxiv.org/abs/2402.18450
Autor:
George Karabatsos
Publikováno v:
Stats, Vol 7, Iss 3, Pp 1002-1050 (2024)
Ongoing modern computational advancements continue to make it easier to collect increasingly large and complex datasets, which can often only be realistically analyzed using models defined by intractable likelihood functions. This Stats invited featu
Externí odkaz:
https://doaj.org/article/7b49f693ec2543828a02b046e0ce9f8a
Autor:
Ding, Dawei, Karabatsos, George
We propose Dirichlet Process Mixture (DPM) models for prediction and cluster-wise variable selection, based on two choices of shrinkage baseline prior distributions for the linear regression coefficients, namely the Horseshoe prior and Normal-Gamma p
Externí odkaz:
http://arxiv.org/abs/2010.11385
Autor:
Karabatsos, George, Leisen, Fabrizio
In statistical practice, a realistic Bayesian model for a given data set can be defined by a likelihood function that is analytically or computationally intractable, due to large data sample size, high parameter dimensionality, or complex likelihood
Externí odkaz:
http://arxiv.org/abs/1802.00796
Autor:
Karabatsos, George, Leisen, Fabrizio
We are living in the big data era, as current technologies and networks allow for the easy and routine collection of data sets in different disciplines. Bayesian Statistics offers a flexible modeling approach which is attractive for describing the co
Externí odkaz:
http://arxiv.org/abs/1708.05341
Publikováno v:
Journal of Pharmacy Practice; Aug2024, Vol. 37 Issue 4, p814-821, 8p
Autor:
Karabatsos, George
The mixture of Dirichlet process (MDP) defines a flexible prior distribution on the space of probability measures. This study shows that ordinary least-squares (OLS) estimator, as a functional of the MDP posterior distribution, has posterior mean giv
Externí odkaz:
http://arxiv.org/abs/1602.05155
Autor:
Karabatsos, George
Most of applied statistics involves regression analysis of data. This paper presents a stand-alone and menu-driven software package, Bayesian Regression: Nonparametric and Parametric Models. Currently, this package gives the user a choice from 83 Bay
Externí odkaz:
http://arxiv.org/abs/1506.05435
Autor:
Karabatsos, George
This paper introduces a flexible Bayesian nonparametric Item Response Theory (IRT) model, which applies to dichotomous or polytomous item responses, and which can apply to either unidimensional or multidimensional scaling. This is an infinite-mixture
Externí odkaz:
http://arxiv.org/abs/1502.03339