Results 21 to 30 of about 149 (141)

Bias-variance decomposition in Genetic Programming

Open Mathematics, 2016
We study properties of Linear Genetic Programming (LGP) through several regression and classification benchmarks. In each problem, we decompose the results into bias and variance components, and explore the effect of varying certain key parameters on the
Kowaliw Taras, Doursat René
doaj   +1 more source

Bootstrap tests for nonparametric comparison of regression curves with dependent errors [PDF]

, 2007
Hypothesis testing, Regression models, Nonparametric estimators, Dependent data, 62G08, 62G09, 62G10, 62M10,
W. González-Manteiga, Vilar, Juan M., J. Vilar-Fernández, Vilar, José   +3 more
core   +1 more source

Nonparametric regression on the hyper-sphere with uniform design [PDF]

, 2011
Nonparametric regression, Uniform design, Minimax rate, Needlets, Needlet-shrinkage, Stochastic thresholding, 62G08, 62G05, 62C20,
Monnier, Jean-Baptiste, Jean-Baptiste Monnier   +1 more
core   +1 more source

Nonparametric expectile shortfall regression for functional data

Demonstratio Mathematica
This 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., Abood Hanan, Bouzebda Salim, Alshahrani Fatimah, Laksaci Ali   +4 more
doaj   +1 more source

Mixed Inverse Gaussian Analysis of Covariance for Censored Data: A Bayesian Approach

Journal of Mathematics, Volume 2025, Issue 1, 2025.
This paper proposes a model for analysis of covariance (ANCOVA) of censored data obtained from a positively skewed population by using the mixed inverse Gaussian (MIG) distribution. A hierarchical fully Bayesian approach is employed to fit and infer about the proposed model.
Ehsan Mesdaghi, Afshin Fallah, Rahman Farnoosh, Gholamhossein Yari, Barbara Martinucci   +4 more
wiley   +1 more source

Projection Estimates of Constrained Functional Parameters [PDF]

, 2005
AMS classifications: 62G05; 62G07; 62G08; 62G20 ...
Segers, J., Guillou, A., Fils-Villetard, A.   +2 more
core  

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, Zhilin Yu, Shanshan Liang, Yanke Ren, Pramita Mishra   +4 more
wiley   +1 more source

On internally corrected and symmetrized kernel estimators for nonparametric regression

, 2010
Multivariate regression, Smoothing matrix, Symmetry, 62G08, 62G20,
Jacho-Chávez, David, Linton, Oliver, David Jacho-Chávez, Oliver Linton   +3 more
core   +1 more source

Goodness-of-fit Tests in Nonparametric Regression [PDF]

, 2004
AMS classifications: 62G08, 62G10, 62G20, 62G30 ...
Einmahl, J.H.J., van Keilegom, I.
core  

On kernel-based estimation of conditional Kendall’s tau: finite-distance bounds and asymptotic behavior

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