Results 21 to 30 of about 502 (78)
The Overlooked Potential of Generalized Linear Models in Astronomy - I: Binomial Regression [PDF]
, 2015 Revealing hidden patterns in astronomical data is often the path to fundamental scientific breakthroughs; meanwhile the complexity of scientific inquiry increases as more subtle relationships are sought.
Biffi, V. +8 more
core +2 more sources
Introduction to papers on astrostatistics
, 2009 We are pleased to present a Special Section on Statistics and Astronomy in this issue of the The Annals of Applied Statistics. Astronomy is an observational rather than experimental science; as a result, astronomical data sets both small and large ...
Loredo, Thomas J. +2 more
core +1 more source
An analysis of feature relevance in the classification of astronomical transients with machine learning methods [PDF]
, 2016 The exploitation of present and future synoptic (multi-band and multi-epoch) surveys requires an extensive use of automatic methods for data processing and data interpretation.
Brescia, Massimo +6 more
core +4 more sources
Bayesian astrostatistics: a backward look to the future
, 2012 This perspective chapter briefly surveys: (1) past growth in the use of Bayesian methods in astrophysics; (2) current misconceptions about both frequentist and Bayesian statistical inference that hinder wider adoption of Bayesian methods by astronomers ...
A Gelman +41 more
core +1 more source
Pluto’s Surface Mapping Using Unsupervised Learning from Near-infrared Observations of LEISA/Ralph
The Planetary Science Journal, 2023 We map the surface of Pluto using an unsupervised machine-learning technique using the near-infrared observations of the LEISA/Ralph instrument on board NASA’s New Horizons spacecraft.
A. Emran +5 more
doaj +1 more source
Model fitting of kink waves in the solar atmosphere: Gaussian damping and time-dependence [PDF]
, 2016 {Observations of the solar atmosphere have shown that magnetohydrodynamic waves are ubiquitous throughout. Improvements in instrumentation and the techniques used for measurement of the waves now enables subtleties of competing theoretical models to be ...
Mooroogen, K., Morton, R. J.
core +2 more sources
Statistical Analysis and Data Mining: The ASA Data Science Journal, Volume 17, Issue 1, February 2024.Abstract We propose a simple, statistically principled, and theoretically justified method to improve supervised learning when the training set is not representative, a situation known as covariate shift. We build upon a well‐established methodology in causal inference and show that the effects of covariate shift can be reduced or eliminated by ...
Maximilian Autenrieth +3 more
wiley +1 more source
Statistical Issues Often Overlooked when Analyzing Astronomical Data
The Astrophysical Journal Supplement SeriesThe 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
doaj +1 more source
Bayesian Analysis of Two Stellar Populations in Galactic Globular Clusters II: NGC 5024, NGC 5272, and NGC 6352 [PDF]
, 2016 We use Cycle 21 Hubble Space Telescope (HST) observations and HST archival ACS Treasury observations of Galactic Globular Clusters to find and characterize two stellar populations in NGC 5024 (M53), NGC 5272 (M3), and NGC 6352.
Jefferys, W. H. +7 more
core +4 more sources
A Geometric Approach to Estimate Background in Astronomical Images
The Astrophysical Journal Supplement SeriesEstimating the true background in an astronomical image is fundamental to detecting faint sources. In a typical low-photon-count astronomical image, such as in the far- and near-ultraviolet wavelength ranges, conventional methods relying on 3 σ clipping ...
Pushpak Pandey, Kanak Saha
doaj +1 more source