65 citations · 123 across the 9 of their papers we have counts for
11 papers
Sample Selection Bias in Evaluation of Prediction Performance of Causal Models
James P. Long, Min Jin Ha
Causal models are notoriously difficult to validate because they make untestable assumptions regarding confounding. New scientific experiments offer the possibility of evaluating c…
A Framework for Mediation Analysis with Multiple Exposures, Multivariate Mediators, and Non-Linear Response Models
James P. Long, Ehsan Irajizad, James D. Doecke +2
Mediation analysis seeks to identify and quantify the paths by which an exposure affects an outcome. Intermediate variables which are effected by the exposure and which effect the…
Identification of RR Lyrae stars in multiband, sparsely-sampled data from the Dark Energy Survey using template fitting and Random Forest classification
K. M. Stringer, J. P. Long, L. M. Macri +75
Many studies have shown that RR Lyrae variable stars (RRL) are powerful stellar tracers of Galactic halo structure and satellite galaxies. The Dark Energy Survey (DES), with its de…
A Flexible Procedure for Mixture Proportion Estimation in Positive-Unlabeled Learning
Zhenfeng Lin, James P. Long
Positive--unlabeled (PU) learning considers two samples, a positive set P with observations from only one class and an unlabeled set U with observations from two classes. The goal…
Statistical methods in astronomy
James P. Long, Rafael S. de Souza
We present a review of data types and statistical methods often encountered in astronomy. The aim is to provide an introduction to statistical applications in astronomy for statist…
A Note on Parameter Estimation for Misspecified Regression Models with Heteroskedastic Errors
James P. Long
Misspecified models often provide useful information about the true data generating distribution. For example, if is a non-linear function of the least squares estimator $\…
A Study of Functional Depths
James P. Long, Jianhua Z. Huang
Functional depth is used for ranking functional observations from most outlying to most typical. The ranks produced by functional depth have been proposed as the basis for function…
Estimating a Common Period for a Set of Irregularly Sampled Functions with Applications to Periodic Variable Star Data
James P. Long, Eric C. Chi, Richard G. Baraniuk
We consider the estimation of a common period for a set of functions sampled at irregular intervals. The problem arises in astronomy, where the functions represent a star's brightn…
Kernel Density Estimation with Berkson Error
James P. Long, Noureddine El Karoui, John A. Rice
Given a sample from , we construct kernel density estimators for , the convolution of with a known error density . This problem is known as d…
Optimizing Automated Classification of Periodic Variable Stars in New Synoptic Surveys
James P. Long, Noureddine El Karoui, John A. Rice +2
Efficient and automated classification of periodic variable stars is becoming increasingly important as the scale of astronomical surveys grows. Several recent papers have used met…
Active Learning to Overcome Sample Selection Bias: Application to Photometric Variable Star Classification
Joseph W. Richards, Dan L. Starr, Henrik Brink +6
Despite the great promise of machine-learning algorithms to classify and predict astrophysical parameters for the vast numbers of astrophysical sources and transients observed in l…