Results 1 to 10 of about 2,173,075 (279)
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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Quantile Regression Under Random Censoring [PDF]
Journal of Econometrics, 2002 No abstract.
Bo Honore, James L. Powell, Shakeeb Khan
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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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Nonlinear regression of stable random variables [PDF]
The Annals of Applied Probability, 1991 Let (X1,X2) be an α-stable random vector, not necessarily symmetric, with ...
Hardin, Clyde D., Jr +2 more
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Random design analysis of ridge regression [PDF]
Foundations of Computational Mathematics, 2014 This work gives a simultaneous analysis of both the ordinary least squares estimator and the ridge regression estimator in the random design setting under mild assumptions on the covariate/response distributions.
Hsu, Daniel +2 more
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Random Projections For Large-Scale Regression [PDF]
, 2017 Fitting linear regression models can be computationally very expensive in large-scale data analysis tasks if the sample size and the number of variables are very large.
B. McWilliams +8 more
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Panel regression with random noise [PDF]
SSRN Electronic Journal, 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.
Ronning, Gerd, Schneeweiss, Hans
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Regression models and random effects [PDF]
Revista do Colégio Brasileiro de Cirurgiões, 2021 ÁLIDA ROSÁRIA SILVA FERREIRA
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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 ...
Geppert, Leo N. +4 more
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Random kernel k-nearest neighbors regression
Frontiers in Big DataThe k-nearest neighbors (KNN) regression method, known for its nonparametric nature, is highly valued for its simplicity and its effectiveness in handling complex structured data, particularly in big data contexts.
Patchanok Srisuradetchai +1 more
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