Results 11 to 20 of about 2,148,018 (281)

Quantile Regression Under Random Censoring [PDF]

Journal of Econometrics, 2002
No abstract.
Bo Honore, James L. Powell, Shakeeb Khan
core   +4 more sources

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, Samorodnitsky, Gennady, Taqqu, Murad S.   +2 more
core   +4 more sources

Regression models and random effects [PDF]

Revista do Colégio Brasileiro de Cirurgiões, 2021
ÁLIDA ROSÁRIA SILVA FERREIRA
doaj   +4 more sources

Random kernel k-nearest neighbors regression

Frontiers in Big Data
The 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, Korn Suksrikran   +1 more
doaj   +3 more sources

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
core   +5 more sources

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, Kakade, Sham M., Zhang, Tong   +2 more
core   +3 more sources

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, D. Achlioptas, M.W. Mahoney, O.-A. Maillard, P. Dhillon, P.S. Dhillon, R.D. Cook, S. Dasgupta, T. Marzetta   +8 more
core   +2 more sources

Heatmap Regression via Randomized Rounding [PDF]

IEEE Transactions on Pattern Analysis and Machine Intelligence, 2022
To appear in ...
Baosheng Yu, Dacheng Tao
openaire   +3 more sources

Linear regression with random projections [PDF]

, 2010
We consider ordinary (non penalized) least-squares regression where the regression function is chosen in a randomly generated sub-space GP \subset S of finite dimension P, where S is a function space of infinite dimension, e.g. L2([0, 1]^d).
Maillard, Odalric-Ambrym, Munos, Rémi
core   +4 more sources

Linear Regression with Random Projections [PDF]

, 2012
International audienceWe investigate a method for regression that makes use of a randomly generated subspace $G_P$ (of finite dimension $P$) of a given large (possibly infinite) dimensional function space $F$, for example, $L_{2}([0,1]^d)$.
Maillard, Odalric, Munos, Rémi
core   +4 more sources