Browsing Centro de Bioestadística y Bioinformática by Title
Now showing items 7-14 of 14
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Limiting the Shrinkage for the Exceptional by Objective Robust Bayesian Analysis
Modern Statistics is made of the sensible combination of direct evidence (the data directly relevant or the “individual data”) and indirect evidence (the data and knowledge indirectly relevant or the “group data”). The ... -
Modelling outliers and structural breaks in dynamic linear models with a novel use of a heavy tailed prior for the variances: An alternative to the Inverted Gamma
In this paper we propose a new wider class of hypergeometric heavy tailed priors that are given as the convolution of a Student-t density for the location parameter and a Scaled Beta2 prior for the variance. These priors ... -
New Criteria for the Choice of Training Sample Size for Model Selection and Prediction: The Cubic Root Rule
(2012)The size of a training sample in Objective Bayesian Testing and Model Selection is a central problem in the theory and in the practice. We concentrate here in simulated training samples and in simple hypothesis. The striking ... -
Quick Anomaly Detection by the Newcomb–Benford Law, with Applications to Electoral Processes Data from the USA, Puerto Rico and Venezuela
A simple and quick general test to screen for numerical anomalies is presented. It can be applied, for example, to electoral processes, both electronic and manual. It uses vote counts in officially published voting units, ... -
Skeptical and Optimistic Robust Priors for Clinical Trials
A useful technique from the subjective Bayesian viewpoint, suggested by Spiegelhalter et al. (1994), is to ask the subject matter researchers and other parties involved, such as pharmaceutical companies and regulatory ... -
The case for a fully robust hierarchical Bayesian statistical analysis of clinical trials
(International Workshop on Objective Bayes Methodology (OBayes 09),, 2009-06)Two clinical trials (past and present), conjugate priors are compared with (Robust) Cauchy- Student-t and what we call Berger's prior. The behavior of the latter Robust Bayesian methods is qualitatively di erent from ... -
The Scaled Beta2 Distribution as a robust prior for scales, and a Explicit Horseshoe Prior for locations
In the tradition of ”Conjugate Priors” analysis (and extensions to Conditional Conjugate Priors), priors for locations are assumed Normal and for precisions are assumed Gamma or equivalently for variances Inverted Gamma. ... -
Towards a General Theory of Optimal Testing
In Pericchi and Pereira (2012)it is argued against the traditional way on which testing is based on xed signi cance level, either using p-values (with xed levels of evidence, like the 5% rule) or values. We instead, ...