11 citations · 23 across the 9 of their papers we have counts for
10 papers
Scale Reliant Inference
Michelle Pistner Nixon, Kyle C. McGovern, Jeffrey Letourneau +4
Many scientific fields, including human gut microbiome science, collect multivariate count data where the sum of the counts is unrelated to the scale of the underlying system being…
Improving COVID-19 Forecasting using eXogenous Variables
Mohammadhossein Toutiaee, Xiaochuan Li, Yogesh Chaudhari +7
In this work, we study the pandemic course in the United States by considering national and state levels data. We propose and compare multiple time-series prediction techniques whi…
Hypothesis Testing for Shapes using Vectorized Persistence Diagrams
Chul Moon, Nicole A. Lazar
Topological data analysis involves the statistical characterization of the shape of data. Persistent homology is a primary tool of topological data analysis, which can be used to a…
Method of Moments Histograms
James S. Weber, Nicole A. Lazar
Uniform bin width histograms are widely used so this data graphic should represent data as correctly as possible. Method of moments based on familiar mean, variance and Fisher-Pear…
Persistence Terrace for Topological Inference of Point Cloud Data
Chul Moon, Noah Giansiracusa, Nicole A. Lazar
Topological data analysis (TDA) is a rapidly developing collection of methods for studying the shape of point cloud and other data types. One popular approach, designed to be robus…
Split Sample Empirical Likelihood
Adam Jaeger, Nicole Lazar
We propose a new approach that combines multiple non-parametric likelihood-type components to build a data-driven approximation of the true likelihood function. Our approach is bui…
Piecewise Empirical Likelihood
Adam Jaeger, Nicole Lazar
Non-parametric methods avoid the problem of having to specify a particular data generating mechanism, but can be computationally intensive, reducing their accessibility for large d…
A Bayesian Generalized CAR Model for Correlated Signal Detection
D. Andrew Brown, Gauri S. Datta, Nicole A. Lazar
Over the last decade, large-scale multiple testing has found itself at the forefront of modern data analysis. In many applications data are correlated, so that the observed test st…
Composite Empirical Likelihood
Adam Jaeger, Nicole Lazar
The likelihood function plays a pivotal role in statistical inference; it is adaptable to a wide range of models and the resultant estimators are known to have good properties. How…
Regression shrinkage and grouping of highly correlated predictors with HORSES
Woncheol Jang, Johan Lim, Nicole A. Lazar +2
Identifying homogeneous subgroups of variables can be challenging in high dimensional data analysis with highly correlated predictors. We propose a new method called Hexagonal Oper…