English (United Kingdom)

https://curated-unify.zendy.io/wp-json/zendy-region/v1/featured_content/oa?rat=en

https://curated-unify.zendy.io/wp-json/zendy-region/v1/highlighted_journal/

Global: Zendy Plus annual

Presents the access of premium content as premium feature

Premium Content

Presents the keyphrase highlighting as premium feature

Keyphrase Highlighting

Presents the summarisation as premium feature

Summarisation

Insights

Presents the pdf analysis as premium feature

PDF Analysis

Presents the zaia usage as premium feature

ZAIA

Global: Zendy Plus monthly

Global: Zendy Tools annual

Global: Zendy Tools monthly

Global: Zendy Free Plan

In this paper several related estimation problems are addressed from aBayesian point of view and optimal estimators are obtained for each of themwhen some natural loss functions are considered. Namely, we are interested inestimating a regression curve. Simultaneously, the estimation problems of aconditional distribution function, or a conditional density, or even theconditional distribution itself, are considered. All these problems are posedin a sufficiently general framework to cover continuous and discrete,univariate and multivariate, parametric and non-parametric cases, without theneed to use a specific prior distribution. The loss functions considered comenaturally from the quadratic error loss function comonly used in estimating areal function of the unknown parameter. The cornerstone of the mentioned Bayesestimators is the posterior predictive distribution. Some examples are providedto illustrate these results.

Optimal Bayesian Estimation of a Regression Curve, a Conditional Density and a Conditional Distribution