85 citations · 114 across the 4 of their papers we have counts for
4 papers
A Note on Using Discretized Simulated Data to Estimate Implicit Likelihoods in Bayesian Analyses
M. S. Hamada, T. L. Graves, N. W. Hengartner +9
This article presents a Bayesian inferential method where the likelihood for a model is unknown but where data can easily be simulated from the model. We discretize simulated (cont…
Nonparametric Density Estimation for High-Dimensional Data - Algorithms and Applications
Zhipeng Wang, David W. Scott
Density Estimation is one of the central areas of statistics whose purpose is to estimate the probability density function underlying the observed data. It serves as a building blo…
The Hybrid Bootstrap: A Drop-in Replacement for Dropout
Robert Kosar, David W. Scott
Regularization is an important component of predictive model building. The hybrid bootstrap is a regularization technique that functions similarly to dropout except that features a…
Robust Parametric Classification and Variable Selection by a Minimum Distance Criterion
Eric C. Chi, David W. Scott
We investigate a robust penalized logistic regression algorithm based on a minimum distance criterion. Influential outliers are often associated with the explosion of parameter vec…