Results 11 to 20 of about 78 (56)
A New Approach to Astronomical Data Analysis Based on Multiple Variables
Advances in Astronomy, Volume 2023, Issue 1, 2023., 2023 Data analysis for a sample of celestial bodies generally is preceded by the completeness test in order to verify whether the sample objects are proper representatives of the corresponding part of the universe. A data set following a multivariate, continuous, uniform distribution is said to be “complete in space.” This paper introduces a new approach to
Prasenjit Banerjee +3 more
wiley +1 more source
Advances in Astronomy, Volume 2010, Issue 1, 2010., 2010 Recent and forthcoming advances in instrumentation, and giant new surveys, are creating astronomical data sets that are not amenable to the methods of analysis familiar to astronomers. Traditional methods are often inadequate not merely because of the size in bytes of the data sets, but also because of the complexity of modern data sets.
Meyer Z. Pesenson +3 more
wiley +1 more source
The Astrophysical Journal Supplement Series, 2023 By applying our previously developed two-step scheme for galaxy morphology classification, we present a catalog of galaxy morphology for H -band-selected massive galaxies in the COSMOS-DASH field, which includes 17,292 galaxies with stellar mass M _ ...
Yao Dai +8 more
doaj +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
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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
The Astrophysical JournalEmulators 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
doaj +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
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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
Photometric Redshift Estimation of Quasars by a Cross-modal Contrast Learning Method
The Astronomical JournalEstimating 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 +4 more
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The Astrophysical JournalMolecular emission from the galactic and extragalactic interstellar medium (ISM) is often used to determine the physical conditions of the dense gas. However, even from spatially resolved regions, the observed molecules do not necessarily arise from a ...
Damien de Mijolla +3 more
doaj +1 more source