Imagen de Portada

Totally Concave Regression

Fuente: arXiv

Guardado en:

Detalles Bibliográficos
Autores principales:	Ki, Dohyeong, Guntuboyina, Adityanand
Formato:	Preprint
Publicado:	2025
Materias:	Statistics Theory Methodology 62G08
Acceso en línea:	Acceder al recurso
Etiquetas:	Agregar Etiqueta Sin Etiquetas, Sea el primero en etiquetar este registro!

Ejemplares similares

What Functions Does XGBoost Learn?
por: Ki, Dohyeong, et al.
Publicado: (2026)

MARS via LASSO
por: Ki, Dohyeong, et al.
Publicado: (2021)

Least Squares-Based Permutation Tests in Time Series
por: Romano, Joseph P., et al.
Publicado: (2024)

Adaptation using spatially distributed Gaussian Processes
por: Szabo, Botond, et al.
Publicado: (2023)

Automatic and location-adaptive estimation in functional single-index regression
por: Novo, Silvia, et al.
Publicado: (2024)

A Nonparametric Maximum Likelihood Approach to Mixture of Regression
por: Jiang, Hansheng, et al.
Publicado: (2021)

Variable Selection for Additive Global Fréchet Regression
por: Yang, Haoyi, et al.
Publicado: (2025)

A Note on Local Linear Regression for Time Series in Banach Spaces
por: Heinrichs, Florian
Publicado: (2025)

Sparse semiparametric regression when predictors are mixture of functional and high-dimensional variables
por: Novo, Silvia, et al.
Publicado: (2024)

Asymptotic confidence bands for the histogram regression estimator
por: Neumeyer, Natalie, et al.
Publicado: (2025)

Distributional Conformal Prediction for Markov Processes
por: Dai, Dehao, et al.
Publicado: (2026)

Factor Informed Double Deep Learning For Average Treatment Effect Estimation
por: Fan, Jianqing, et al.
Publicado: (2025)

Minimax And Adaptive Transfer Learning for Nonparametric Classification under Distributed Differential Privacy Constraints
por: Auddy, Arnab, et al.
Publicado: (2024)

CINDES: Classification induced neural density estimator and simulator
por: Dai, Dehao, et al.
Publicado: (2025)

Causality Pursuit from Heterogeneous Environments via Neural Adversarial Invariance Learning
por: Gu, Yihong, et al.
Publicado: (2024)

On the Dirichlet-kernel Gasser--Müller estimator and its competitors for fixed design regression on the simplex
por: Daayeb, Hanen, et al.
Publicado: (2025)

Estimation of a Likelihood Ratio Ordered Family of Distributions
por: Mösching, Alexandre, et al.
Publicado: (2020)

Local linear smoothing for regression surfaces on the simplex using Dirichlet kernels
por: Genest, Christian, et al.
Publicado: (2024)

Mean and Covariance Estimation for Discretely Observed High-Dimensional Functional Data: Rates of Convergence and Division of Observational Regimes
por: Petersen, Alexander
Publicado: (2024)

A Bernstein polynomial approach for the estimation of cumulative distribution functions in the presence of missing data
por: Gharbi, Rihab, et al.
Publicado: (2025)

Adaptive Geometric Regression for High-Dimensional Structured Data
por: Gajer, Pawel, et al.
Publicado: (2025)

Vecchia Gaussian Processes: on probabilistic and statistical properties
por: Szabo, Botond, et al.
Publicado: (2024)

Adaptive functional principal components analysis
por: Wang, Sunny G. W., et al.
Publicado: (2023)

Structure-Preserving Nonlinear Sufficient Dimension Reduction for Tensors
por: Lin, Dianjun, et al.
Publicado: (2025)

Symmetry: a General Structure in Nonparametric Regression
por: Christie, Louis G., et al.
Publicado: (2024)

Functional Partial Least-Squares: Adaptive Estimation and Inference
por: Babii, Andrii, et al.
Publicado: (2024)

Inference with Mondrian Random Forests
por: Cattaneo, Matias D., et al.
Publicado: (2023)

Nonparametric Regression for Random Unbiased Perturbations
por: Lyubarskaja, Anna, et al.
Publicado: (2025)

A Minimax Theory of Nonparametric Regression Under Covariate Shift
por: Zamolodtchikov, Petr
Publicado: (2026)

Deep Regression for Repeated Measurements under Covariate Shift
por: Wang, Yingxuan, et al.
Publicado: (2026)

Deep learning with missing data
por: Ma, Tianyi, et al.
Publicado: (2025)

Local Fréchet regression with toroidal predictors
por: Im, Chang Jun, et al.
Publicado: (2026)

Dirichlet kernel density estimation on the simplex with missing data
por: Daayeb, Hanen, et al.
Publicado: (2026)

Average Marginal Effects in One-Step Partially Linear Instrumental Regressions
por: Girard, Lucas, et al.
Publicado: (2026)

Conditionality principle under unconstrained randomness
por: Vovk, Vladimir
Publicado: (2024)

Factor Augmented Quantile Regression Model
por: Wei, Xiaoyang, et al.
Publicado: (2025)

Noise-resilient penalty operators based on statistical differentiation schemes
por: Vidal, Marc, et al.
Publicado: (2026)

On Regression in Extreme Regions
por: Clémençon, Stephan, et al.
Publicado: (2023)

Harmonic Map Regression: Rate-Optimal Nonparametric Estimation on Manifolds with Topological Recovery
por: Chen, Xiaoyu
Publicado: (2026)

From Global to Local Correlation: Geometric Decomposition of Statistical Inference
por: Gajer, Pawel, et al.
Publicado: (2025)