Results 31 to 40 of about 357 (112)

Statistical Issues Often Overlooked when Analyzing Astronomical Data

The Astrophysical Journal Supplement Series
The main topics covered in this paper are (1) controlling significance levels when applying the same hypothesis test to many (possibly millions) of datasets; (2) dealing with the fact that for very large datasets hypotheses are rejected for trivially ...
C. Koen
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Classification of Chandra X-Ray Sources in Cygnus OB2

The Astrophysical Journal Supplement Series, 2023
We have devised a predominantly Naive Bayes−based method to classify X-ray sources detected by Chandra in the Cygnus OB2 association into members, foreground objects, and background objects.
Vinay L. Kashyap, Mario G. Guarcello, Nicholas J. Wright, Jeremy J. Drake, Ettore Flaccomio, Tom L. Aldcroft, Juan F. Albacete Colombo, Kevin Briggs, Francesco Damiani, Janet E. Drew, Eduardo L. Martin, Giusi Micela, Tim Naylor, Salvatore Sciortino   +13 more
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Rigorous Analytic Solution to the Gravitational-wave Overlapping Event Rates

The Astrophysical Journal
In the era of the next-generation gravitational-wave detectors, signal overlaps will become prevalent due to the high detection rate and long signal duration, posing significant challenges to data analysis. While effective algorithms are being developed,
Ziming Wang, Zexin Hu, Lijing Shao
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Robust Estimates of Orientation between Astrometric Catalogs

The Astronomical Journal, 2023
Accurately comparing two celestial reference frames based on the observed position of a number of common objects requires to detect and appropriately process outliers, lest they spuriously influence the results.
Julien Frouard
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Multistage analysis in astrostatistics

, 2020
A sequence of statistical analyses often needs to be conducted by different groups of researchers where the output of each analysis feeds into subsequent analyses. The statistical and systematic uncertainties of estimated quantities, especially high dimensional quantities, are hard to quantify and difficult to carry forward into subsequent analyses. In
openaire   +2 more sources

Maximum-likelihood Regression with Systematic Errors for Astronomy and the Physical Sciences. II. Hypothesis Testing of Nested Model Components for Poisson Data

The Astrophysical Journal
A novel model of systematic errors for the regression of Poisson data is applied to hypothesis testing of nested model components with the introduction of a generalization of the Δ C statistic that applies in the presence of systematic errors. This paper
Massimiliano Bonamente, Dale Zimmerman, Yang Chen   +2 more
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Realizing the potential of astrostatistics and astroinformatics

, 2019
This Astro2020 State of the Profession Consideration White Paper highlights the growth of astrostatistics and astroinformatics in astronomy, identifies key issues hampering the maturation of these new subfields, and makes recommendations for structural improvements at different levels that, if acted upon, will make significant positive impacts across ...
Eadie, Gwendolyn, Loredo, Thomas J., Mahabal, Ashish A., Siemiginowska, Aneta, Feigelson, Eric, Ford, Eric B., Djorgovski, S. G., Graham, Matthew, Ivezic, Zeljko, Borne, Kirk, Cisewski-Kehe, Jessi, Peek, J. E. G., Schafer, Chad, Yanamandra-Fisher, Padma A., Young, C. Alex   +14 more
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Photometric Redshift Estimation of Quasars by a Cross-modal Contrast Learning Method

The Astronomical Journal
Estimating photometric redshifts (photo- z ) of quasars is crucial for measuring cosmic distances and monitoring cosmic evolution. While numerous point estimation methods have successfully determined photo- z , they often struggle with the inherently ill-
Chen Zhang, Wenyu Wang, Meixia Qu, Bin Jiang, YanXia Zhang   +4 more
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The Role of Statistics and Statisticians in the Future of Astrostatistics [PDF]

Proceedings of the International Astronomical Union, 2014
AbstractGiven the generic definition of statistics, it is clear that astronomers have engaged in statistical analysis of some variety since astronomy first emerged as a science. However, from the early nineteenth century until the beginning of the twenty-first the two disciplines have been somewhat estranged – there was no formal relationship between ...
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Multifidelity Emulator for Large-scale 21 cm Lightcone Images: A Few-shot Transfer Learning Approach with Generative Adversarial Network

The Astrophysical Journal
Emulators using machine learning techniques have emerged to efficiently generate mock data matching the large survey volume for upcoming experiments, as an alternative approach to large-scale numerical simulations.
Kangning Diao, Yi Mao
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