activity
20092026
most citedGPfit: An R package for Gaussian Process Model Fitting using a New Optimization Algorithm

112 citations · 227 across the 26 of their papers we have counts for

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Showing stat.MEShow all

18 papers · 1 filter

stat.ME2026

smartcor: Intelligent Correlation Method Selection for Mixed Variable Types

M Harshvardhan, Pritam Ranjan

Pearson correlation is the default measure of association in most statistical software, yet it is only appropriate for pairs of continuous variables with a linear relationship. Whe…

stat.ME2022★ 1 cited

Solving an Inverse Problem for Time Series Valued Computer Simulators via Multiple Contour Estimation

Pritam Ranjan, Joseph Resch, Abhyuday Mandal

Computer simulators are often used as a substitute of complex real-life phenomena which are either expensive or infeasible to experiment with. This paper focuses on how to efficien…

stat.ME2020★ 1 cited

Statistical Modelling and Analysis of the Computer-Simulated Datasets

M. Harshvardhan, Pritam Ranjan

Over the last two decades, the science has come a long way from relying on only physical experiments and observations to experimentation using computer simulators. This chapter foc…

stat.ME2020

IsoCheck: An R Package to check Isomorphism for Two-level Factorial Designs with Randomization Restrictions

Pratishtha Batra, Neil A. Spencer, Pritam Ranjan

Factorial designs are often used in various industrial and sociological experiments to identify significant factors and factor combinations that may affect the process response. In…

stat.ME2020

Inverse Problem for Dynamic Computer Simulators via Multiple Scalar-valued Contour Estimation

Joseph Resch, Abhyuday Mandal, Pritam Ranjan

In this paper we consider a dynamic computer simulator that produces a time-series response over time points, for every given input parameter . We propose a method…

stat.ME2019

Global Fitting of the Response Surface via Estimating Multiple Contours of a Simulator

Feng Yang, C. Devon Lin, Pritam Ranjan

Computer simulators are nowadays widely used to understand complex physical systems in many areas such as aerospace, renewable energy, climate modeling, and manufacturing. One fund…