activity
20182023
most citedThrowing Stones and Collecting Bones: Looking for Poisson-like Random Measures

11 citations · 14 across the 8 of their papers we have counts for

collaborators

8 papers

stat.ME2023

Random Measures, ANOVA Models and Quantifying Uncertainty in Randomized Controlled Trials

Caleb Deen Bastian, Herschel Rabitz, Grzegorz A Rempala

The paper introduces a novel approach to global sensitivity analysis, grounded in the variance-covariance structure of random variables derived from random measures. The proposed m…

math.DS2022

A field equation for induction-transduction of activation-deactivation probability on measurable space

Caleb Deen Bastian, Herschel Rabitz

Induction-transduction of activating-deactivating points are fundamental mechanisms of action that underlie innumerable systems and phenomena, mathematical, natural, and anthropoge…

math.PR2022

Random Graphs by Product Random Measures

Caleb Bastian, Herschel Rabitz

A natural representation of random graphs is the random measure. The collection of product random measures, their transformations, and non-negative test functions forms a general r…

math.PR2021

The Jacobi Theta Distribution

Caleb Deen Bastian, Grzegorz Rempala, Herschel Rabitz

We form the Jacobi theta distribution through discrete integration of exponential random variables over an infinite inverse square law surface. It is continuous, supported on the p…

math.PR2020

Uncertainty Quantification by Random Measures and Fields

Caleb Deen Bastian, Herschel Rabitz

We present a general framework for uncertainty quantification that is a mosaic of interconnected models. We define global first and second order structural and correlative sensitiv…

math.PR2020★ 1 cited

Orthogonal Dice

Caleb Deen Bastian, Herschel Rabitz, Grzegorz A Rempala

In this paper, we introduce a family of discrete rectangular uniform distributions on the natural numbers-referred to as orthogonal dice-characterized by the property that their me…

stat.ME2018★ 2 cited

High Dimensional Model Representation as a Glass Box in Supervised Machine Learning

Caleb Deen Bastian, Herschel Rabitz

Prediction and explanation are key objects in supervised machine learning, where predictive models are known as black boxes and explanatory models are known as glass boxes. Explana…

math.PR2018★ 11 cited

Throwing Stones and Collecting Bones: Looking for Poisson-like Random Measures

Caleb Deen Bastian, Grzegorz A. Rempala

We show that in a broad class of random counting measures one may identify only three that are rescaled versions of themselves when restricted to a subspace. These are Poisson, bin…