Results 21 to 30 of about 357 (112)

Robust joint modelling of sparsely observed paired functional data

Canadian Journal of Statistics, Volume 52, Issue 3, Page 734-754, September 2024.
Abstract A reduced‐rank mixed‐effects model is developed for robust modelling of sparsely observed paired functional data. In this model, the curves for each functional variable are summarized using a few functional principal components, and the association of the two functional variables is modelled through the association of the principal component ...
Huiya Zhou, Xiaomeng Yan, Lan Zhou
wiley   +1 more source

Listening to stars: audio-inspired multimodal learning for star classification

Frontiers in Astronomy and Space Sciences
Stellar spectral classification plays a crucial role in understanding the intrinsic properties of stars, such as their temperature, composition, and luminosity.
Shengwen Zhang, Shengwen Zhang, Yanxia Zhang, Chao Liu   +3 more
doaj   +1 more source

Stratified learning: A general‐purpose statistical method for improved learning under covariate shift

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, David A. van Dyk, Roberto Trotta, David C. Stenning   +3 more
wiley   +1 more source

Bayesian inference: more than Bayes’s theorem

Frontiers in Astronomy and Space Sciences
Bayesian inference gets its name from Bayes’s theorem, expressing posterior probabilities for hypotheses about a data generating process as the (normalized) product of prior probabilities and a likelihood function.
Thomas J. Loredo, Robert L. Wolpert
doaj   +1 more source

Astrostatistics in Canada

, 2019
This state-of-the-profession white paper focuses on the interdisciplinary fields of astrostatistics and astroinformatics, in which modern statistical and computational methods are applied to and developed for astronomical data. Astrostatistics and astroinformatics have grown dramatically in the past ten years, with international organizations ...
Eadie, Gwendolyn, Bahramian, Arash, Barmby, Pauline, Craiu, Radu, Bingham, Derek, Hložek, Renée, Kavelaars, JJ, Stenning, David, Thomas, Guillaume, Thanjavur, Karun, Bovy, Jo, Cami, Jan, Carlberg, Ray, Lawler, Sam, Liu, Adrian, Ngo, Henry, Rahman, Mubdi, Rupen, Michael   +17 more
openaire   +1 more source

Bayesian Functional Data Analysis in Astronomy

Physical Sciences Forum
Cosmic demographics—the statistical study of populations of astrophysical objects—has long relied on tools from multivariate statistics for analyzing data comprising fixed-length vectors of properties of objects, as might be compiled in a tabular ...
Thomas Loredo, Tamás Budavári, David Kent, David Ruppert   +3 more
doaj   +1 more source

LRP2020: Astrostatistics in Canada

, 2019
White paper E017 submitted to the Canadian Long Range Plan ...
Eadie, Gwendolyn, Bahramian, Arash, Barmby, Pauline, Craiu, Radu, Bingham, Derek, Hložek, Renée, Kavelaars, JJ, Stenning, David, Benincasa, Samantha, Thomas, Guillaume, Thanjavur, Karun, Bovy, Jo, Cami, Jan, Carlberg, Ray, Lawler, Sam, Liu, Adrian, Ngo, Henry, Rahman, Mubdi, Rupen, Michael   +18 more
openaire   +2 more sources

SBI++: Flexible, Ultra-fast Likelihood-free Inference Customized for Astronomical Applications

The Astrophysical Journal Letters, 2023
Flagship near-future surveys targeting 10 ^8 –10 ^9 galaxies across cosmic time will soon reveal the processes of galaxy assembly in unprecedented resolution.
Bingjie Wang, Joel Leja, V. Ashley Villar, Joshua S. Speagle   +3 more
doaj   +1 more source

Big data and paradigm shift for astronomy in the 21^stcentury

大数据, 2016
With the development of large space-based and ground-based observational technologies,the volume,output rate and complexity of astronomical data rapidly increase.The astronomy steps into a new data-intensive era.The characteristics of astronomical data ...
Yanxia ZHANG, Chenzhou CUI, Yongheng ZHAO   +2 more
doaj  

Bayesian Astrostatistics: A Backward Look to the Future [PDF]

, 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; and (3) multilevel (hierarchical) Bayesian modeling as a major future direction for research in ...
openaire   +2 more sources