On Probabilistic Parametric Inference

TL;DR

This paper develops an objective operational framework for probabilistic parametric inference that does not rely on non-informative prior distributions, aiming to improve inference methods.

Contribution

It introduces a novel approach to probabilistic inference that avoids the use of non-informative priors, providing a new theoretical foundation.

Findings

Provides a new operational theory for inference

Eliminates the need for non-informative priors

Lays groundwork for more objective inference methods

Abstract

An objective operational theory of probabilistic parametric inference is formulated without invoking the so-called non-informative prior probability distributions.