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pro vyhledávání: '"generalised linear models"'
Developing an efficient computational scheme for high-dimensional Bayesian variable selection in generalised linear models and survival models has always been a challenging problem due to the absence of closed-form solutions for the marginal likeliho
Externí odkaz:
http://arxiv.org/abs/2308.00869
Akademický článek
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Autor:
Hosack, Geoffrey R.
A statistical method for the elicitation of priors in Bayesian generalised linear models (GLMs) and extensions is proposed. Probabilistic predictions are elicited from the expert to parametrise a multivariate t prior distribution for the unknown line
Externí odkaz:
http://arxiv.org/abs/2303.15069
Autor:
Altmeyer, Randolf
The problem of computing posterior functionals in general high-dimensional statistical models with possibly non-log-concave likelihood functions is considered. Based on the proof strategy of [49], but using only local likelihood conditions and withou
Externí odkaz:
http://arxiv.org/abs/2208.13296
In today's modern era of Big data, computationally efficient and scalable methods are needed to support timely insights and informed decision making. One such method is sub-sampling, where a subset of the Big data is analysed and used as the basis fo
Externí odkaz:
http://arxiv.org/abs/2207.14440
Autor:
Mahendran, Amalan1,2 (AUTHOR) mahendr3@qut.edu.au, Thompson, Helen1,2 (AUTHOR), McGree, James M.1,2 (AUTHOR)
Publikováno v:
Statistical Papers. Aug2023, Vol. 64 Issue 4, p1137-1157. 21p.
Autor:
Loureiro, Bruno, Sicuro, Gabriele, Gerbelot, Cédric, Pacco, Alessandro, Krzakala, Florent, Zdeborová, Lenka
Publikováno v:
Advances in Neural Information Processing Systems 34 (2021): 10144-10157
Generalised linear models for multi-class classification problems are one of the fundamental building blocks of modern machine learning tasks. In this manuscript, we characterise the learning of a mixture of $K$ Gaussians with generic means and covar
Externí odkaz:
http://arxiv.org/abs/2106.03791
Akademický článek
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Publikováno v:
Entropy, Vol 25, Iss 9, p 1310 (2023)
Developing an efficient computational scheme for high-dimensional Bayesian variable selection in generalised linear models and survival models has always been a challenging problem due to the absence of closed-form solutions to the marginal likelihoo
Externí odkaz:
https://doaj.org/article/30b27be9635940b689898d99495cc847
Autor:
Li, Guilin1 (AUTHOR) graceleemtan@gmail.com, Ng, Szu Hui2 (AUTHOR), Tan, Matthias Hwai-yong1 (AUTHOR)
Publikováno v:
Quality Technology & Quantitative Management. Jan2020, Vol. 17 Issue 1, p89-107. 19p.