On a Class of Bayesian Nonparametric Estimates: I. Density Estimates

Comparison of Estimates Using Record Statistics from Lomax Model: Bayesian and Non Bayesian Approaches

This paper address the problem of Bayesian estimation of the parameters, reliability and hazard function in the context of record statistics values from the two-parameter Lomax distribution. The ML and the Bayes estimates based on records are derived for the two unknown parameters and the survival time parameters, reliability and hazard functions. The Bayes estimates are obtained based on conju...

Rosenblatt, M. (1956) \remarks on Some Nonparametric Estimates of a Density Function,"

Bayesian sperm competition estimates.

We introduce a Bayesian method for estimating parameters for a model of multiple mating and sperm displacement from genotype counts of brood-structured data. The model is initially targeted for Drosophila melanogaster, but is easily adapted to other organisms. The method is appropriate for use with field studies where the number of mates and the genotypes of the mates cannot be controlled, but ...

On Class-probability Estimates and Cost-sensitive Evaluation of Classiiers 1. Class-probability Estimates

This paper addresses two cost-sensitive learning methodology issues. First, we ask the question of whether Bagging is always an appropriate procedure to compute accurate class-probability estimates for cost-sensitive classiication. Second, we will point the reader to a potential source of erroneous results in the most common procedure of evaluating cost-sensitive classiiers when the real miscla...

Non-crossing nonparametric estimates of quantile curves

In this paper a new nonparametric estimate of conditional quantiles is proposed, that avoids the problem of crossing quantile curves [calculated for various p ∈ (0, 1)]. The method uses an initial estimate of the conditional distribution function in a first step and solves the problem of inversion and monotonization with respect to p ∈ (0, 1) simultaneously. It is demonstrated that the new esti...