activity
20162021
most citedThe Effect of Heteroscedasticity on Regression Trees

1 citations · 3 across the 5 of their papers we have counts for

collaborators

5 papers

stat.ME2021★ 1 cited

Improving the Hosmer-Lemeshow Goodness-of-Fit Test in Large Models with Replicated Trials

Nikola Surjanovic, Thomas M. Loughin

The Hosmer-Lemeshow (HL) test is a commonly used global goodness-of-fit (GOF) test that assesses the quality of the overall fit of a logistic regression model. In this paper, we gi…

stat.ME2020

A Generalized Hosmer-Lemeshow Goodness-of-Fit Test for a Family of Generalized Linear Models

Nikola Surjanovic, Richard Lockhart, Thomas M. Loughin

Generalized linear models (GLMs) are used within a vast number of application domains. However, formal goodness of fit (GOF) tests for the overall fit of the modelso-called "glo…

stat.ME2019★ 1 cited

A Comparison of Methods for Identifying Location Effects in Unreplicated Fractional Factorials in the Presence of Dispersion Effects

Thomas M. Loughin, Yan Zhang

Most methods for identifying location effects in unreplicated fractional factorial designs assume homoscedasticity of the response values. However, dispersion effects in the underl…

stat.ML2017

Display advertising: Estimating conversion probability efficiently

Abdollah Safari, Rachel MacKay Altman, Thomas M. Loughin

The goal of online display advertising is to entice users to "convert" (i.e., take a pre-defined action such as making a purchase) after clicking on the ad. An important measure of…

stat.ML2016★ 1 cited

The Effect of Heteroscedasticity on Regression Trees

Will Ruth, Thomas Loughin

Regression trees are becoming increasingly popular as omnibus predicting tools and as the basis of numerous modern statistical learning ensembles. Part of their popularity is their…