most citedOn approximating the shape of one dimensional functions

1 citations · 1 across the 3 of their papers we have counts for

collaborators

5 papers

stat.AP2020

Considerations for developing predictive models of crime and new methods for measuring their accuracy

Chaitanya Joshi, Clayton D'Ath, Sophie Curtis-Ham +1

Developing spatio-temporal crime prediction models, and to a lesser extent, developing measures of accuracy and operational efficiency for them, has been an active area of research…

stat.ME2020

Duality between Approximate Bayesian Methods and Prior Robustness

Chaitanya Joshi, Fabrizio Ruggeri

In this paper we show that there is a link between approximate Bayesian methods and prior robustness. We show that what is typically recognized as an approximation to the likelihoo…

stat.CO2019

A Novel Method of Marginalisation using Low Discrepancy Sequences for Integrated Nested Laplace Approximations

Paul T. Brown, Chaitanya Joshi, Stephen Joe +1

Recently, it has been shown that approximations to marginal posterior distributions obtained using a low discrepancy sequence (LDS) can outperform standard grid-based methods with…

cs.CR2019

Insider threat modeling: An adversarial risk analysis approach

Chaitanya Joshi, David Rios Insua, Jesus Rios

Insider threats entail major security issues in geopolitics, cyber risk management and business organization. The game theoretic models proposed so far do not take into account som…

math.NA20191 cited

On approximating the shape of one dimensional functions

Chaitanya Joshi, Paul T. Brown, Stephen Joe

Consider an -dimensional function being evaluated at points of a low discrepancy sequence (LDS), where the objective is to approximate the one-dimensional functions that res…