Results 31 to 40 of about 1,005 (119)
Nonparametric expectile shortfall regression for functional data
Demonstratio MathematicaThis work addresses the issue of financial risk analysis by introducing a novel expected shortfall (ES) regression model, which employs expectile regression to define the shortfall threshold in financial risk management.
Almanjahie Ibrahim M. +4 more
doaj +1 more source
Dependence Modeling, 2019 We study nonparametric estimators of conditional Kendall’s tau, a measure of concordance between two random variables given some covariates. We prove non-asymptotic pointwise and uniform bounds, that hold with high probabilities.
Derumigny Alexis, Fermanian Jean-David
doaj +1 more source
, 2014 We consider an adaptive smoothing spline with a piecewiseconstant penalty function λ(x), in which a univariate smoothing parameter λ in the classic smoothing spline is converted into an adaptive multivariate parameter λ.
Heeyoung Kim, X. Huo
semanticscholar +1 more source
Parameter Estimation of the Partially Linear Quantile Regression Model Under Monotonic Constraints
Journal of Mathematics, Volume 2025, Issue 1, 2025.The paper brings forward the partially linear quantile regression model by incorporating monotonic constraints, which are common in real‐world relationships between variables. It introduces two novel parameter estimation methods, that is, the coordinate descent method and the profile likelihood method, which eliminate the extensive tuning and simplify ...
Shujin Wu +4 more
wiley +1 more source
Estimation of the tail-index in a conditional location-scale family of heavy-tailed distributions
Dependence Modeling, 2019 We introduce a location-scale model for conditional heavy-tailed distributions when the covariate is deterministic. First, nonparametric estimators of the location and scale functions are introduced.
Ahmad Aboubacrène Ag +3 more
doaj +1 more source
Optimal learning with $Q$-aggregation
, 2014 We consider a general supervised learning problem with strongly convex and Lipschitz loss and study the problem of model selection aggregation. In particular, given a finite dictionary functions (learners) together with the prior, we generalize the ...
Lecué, Guillaume, Rigollet, Philippe
core +1 more source
About tests of the “simplifying” assumption for conditional copulas
Dependence Modeling, 2017 We discuss the so-called “simplifying assumption” of conditional copulas in a general framework. We introduce several tests of the latter assumption for non- and semiparametric copula models.
Derumigny Alexis, Fermanian Jean-David
doaj +1 more source
Lasso type classifiers with a reject option
, 2007 We consider the problem of binary classification where one can, for a particular cost, choose not to classify an observation. We present a simple proof for the oracle inequality for the excess risk of structural risk minimizers using a lasso type penalty.
Wegkamp, Marten
core +2 more sources
Local linear regression for functional predictor and scalar response [PDF]
, 2007 The aim of this work is to introduce a new nonparametric regression technique in the context of functional covariate and scalar response. We propose a local linear regression estimator and study its asymptotic behaviour.
Baíllo, Amparo, Grané, Aurea
core +1 more source
SiZer for time series: A new approach to the analysis of trends [PDF]
, 2007 Smoothing methods and SiZer are a useful statistical tool for discovering statistically significant structure in data. Based on scale space ideas originally developed in the computer vision literature, SiZer (SIgnificant ZERo crossing of the derivatives)
Marron, J. S. +2 more
core +4 more sources