Results 61 to 70 of about 233 (155)
Regularization, linear regression, nonparametric regression, boosting, covariance matrix, principal component, bootstrap, subsampling, model selection, Primary 62G08, 62H12, Secondary 62F12, 62G20, 62H25,
Peter Bickel +8 more
core +1 more source
, 2013 International audienceAMS 2000 subject classifications: 62G08 62G20 62M20 68Q32 62H12 Keywords: Conditional quantile regression Functional covariate Iterative reweighted least squares Reproducing kernel Hilbert space Support vector machine a b s t r a c ...
Henchiri, Yousri +2 more
core +1 more source
Statistical inferences for single-index models with measurement errors. [PDF]
J Appl Stat, 2021 Huang Z, Lou W.
europepmc +1 more source
Nonparametric Regression Estimation for Random Fields in a Fixed-Design
60G60, 62G08, nonparametric regression estimation, kernel estimators, strong consistency, fixed-design, exponential inequalities, martingale difference random fields, mixing, Orlicz spaces,
Mohamed Machkouri
core +1 more source
Convexification for data fitting
Convexification, Global optimization, Local minima, Data fitting, Neural network, Nonlinear regression, Minimax, Robustifying error crition, Degree of robustness, 90C30, 90C31, 62M45, 62G08,
James Lo
core +1 more source
Application of MARS for the Construction of Nonparametric Models [PDF]
, 2010 2000 Mathematics Subject Classification: 62G08, 62P30.This paper presents the main features of the relatively new statistical technique called Multivariate Adaptive Regression Splines (MARS) and the corresponding software product.
Gocheva-Ilieva, Snezhana
core
Accelerating the Pool-Adjacent-Violators Algorithm for Isotonic Distributional Regression. [PDF]
Methodol Comput Appl Probab, 2022 Henzi A, Mösching A, Dümbgen L.
europepmc +1 more source
A SIEVE STOCHASTIC GRADIENT DESCENT ESTIMATOR FOR ONLINE NONPARAMETRIC REGRESSION IN SOBOLEV ELLIPSOIDS. [PDF]
Ann Stat, 2022 Zhang T, Simon N.
europepmc +1 more source
A Data-Dependent Weighted LASSO Under Poisson Noise
, 2019 International audienceSparse linear inverse problems appear in a variety of settings, but often the noise contaminating observations cannot accurately be described as bounded by or arising from a Gaussian distribution.
Rivoirard, Vincent +4 more
core +1 more source
, 2014 International audienceWe consider Grenander type estimators for monotone functions f in a very general setting, which includes estimation of monotone regression curves, monotone densities, and monotone failure rates.
Lopuhaä, Hendrik, P., Durot, Cécile
core +1 more source