115 citations · 282 across the 12 of their papers we have counts for
6 papers · 1 filter
Incorporating Measurement Error in Astronomical Object Classification
Sarah Shy, Hyungsuk Tak, Eric D. Feigelson +2
Most general-purpose classification methods, such as support-vector machine (SVM) and random forest (RF), fail to account for an unusual characteristic of astronomical data: known…
21st Century Statistical and Computational Challenges in Astrophysics
Eric D. Feigelson, Rafael S. de Souza, Emille E. O. Ishida +1
Modern astronomy has been rapidly increasing our ability to see deeper into the universe, acquiring enormous samples of cosmic populations. Gaining astrophysical insights from thes…
Algorithms and Statistical Models for Scientific Discovery in the Petabyte Era
Brian Nord, Andrew J. Connolly, Jamie Kinney +35
The field of astronomy has arrived at a turning point in terms of size and complexity of both datasets and scientific collaboration. Commensurately, algorithms and statistical mode…
Autoregressive Times Series Methods for Time Domain Astronomy
Eric D. Feigelson, G. Jogesh Babu, Gabriel A. Caceres
Celestial objects exhibit a wide range of variability in brightness at different wavebands. Surprisingly, the most common methods for characterizing time series in statistics -- pa…
VOStat: A Statistical Web Service for Astronomers
Arnab Chakraborty, Eric D. Feigelson, G. Jogesh Babu
VOStat is a Web service providing interactive statistical analysis of astronomical tabular datasets. It is integrated into the suite of analysis and visualization tools associated…
Statistical Methods for Astronomy
Eric D. Feigelson, G. Jogesh Babu
This review outlines concepts of mathematical statistics, elements of probability theory, hypothesis tests and point estimation for use in the analysis of modern astronomical data.…