Results 11 to 20 of about 4,929,720 (302)
Covariance regression with random forests
BMC Bioinformatics, 2023 Capturing the conditional covariances or correlations among the elements of a multivariate response vector based on covariates is important to various fields including neuroscience, epidemiology and biomedicine.
Cansu Alakus +2 more
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Exploring nonlinearity with random field regression [PDF]
Applied Economics Letters, 2007 Random field regression models provide an extremely flexible way to investigate nonlinearity in economic data. This paper introduces a new approach to interpreting such models, which may allow for improved inference about the possible parametric specification of nonlinearity.
Bond, D. (Derek) +2 more
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Regression models and random effects [PDF]
Revista do Colégio Brasileiro de Cirurgiões, 2021 ÁLIDA ROSÁRIA SILVA FERREIRA
doaj +4 more sources
Impact of the Order of Legendre Polynomials in Random Regression Model on Genetic Evaluation for Milk Yield in Dairy Cattle Population [PDF]
Frontiers in Genetics, 2020 The random regression test-day model has become the most commonly adopted model for routine genetic evaluations in dairy populations, which allows accurately accounting for genetic and environmental effects over lactation. The objective of this study was
Jianbin Li +9 more
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Prior elicitation and variable selection for bayesian quantile regression [PDF]
, 2013 This thesis was submitted for the degree of Doctor of Philosophy and awarded by Brunel University.Bayesian subset selection suffers from three important difficulties: assigning priors over model space, assigning priors to all components of the regression
Al-Hamzawi, Rahim Jabbar Thaher
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Modeling genetic components of hatch of fertile in broiler breeders
Poultry Science, 2021 Reproductive efficiency such as fertility and hatch of fertile (HoF) are of economic importance and concern to breeding companies becaue of their effects on chick output.
Bayode O. Makanjuola +2 more
doaj +1 more source
Ridgeless Regression with Random Features
Proceedings of the Thirty-First International Joint Conference on Artificial Intelligence, 2022 Recent theoretical studies illustrated that kernel ridgeless regression can guarantee good generalization ability without an explicit regularization. In this paper, we investigate the statistical properties of ridgeless regression with random features and stochastic gradient descent.
Jian Li 0040 +2 more
openaire +3 more sources
Journal of Dairy Science, 2023 : Residual feed intake is viewed as an important trait in breeding programs that could be used to enhance genetic progress in feed efficiency. In particular, improving feed efficiency could improve both economic and environmental sustainability in the ...
R.B. Stephansen +20 more
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Random projections for Bayesian regression [PDF]
Statistics and Computing, 2015 This article deals with random projections applied as a data reduction technique for Bayesian regression analysis. We show sufficient conditions under which the entire $d$-dimensional distribution is approximately preserved under random projections by reducing the number of data points from $n$ to $k\in O(\operatorname{poly}(d/\varepsilon))$ in the ...
Leo N. Geppert +4 more
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Panel Regression with Random Noise [PDF]
, 2009 The paper explores the effect of measurement errors on the estimation of a linear panel data model. The conventional fixed effects estimator, which ignores measurement errors, is biased. By correcting for the bias one can construct consistent and asymptotically normal estimators.
Gerd Ronning, Hans Schneeweiss
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