Space partitioning and regression maxima seeking via a mean-shift-inspired algorithm
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Publication:2106775
DOI10.1214/22-EJS2073MaRDI QIDQ2106775
Publication date: 19 December 2022
Published in: Electronic Journal of Statistics (Search for Journal in Brave)
Full work available at URL: https://arxiv.org/abs/2104.10103
Uses Software
Cites Work
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- Nonparametric modal regression
- Theoretical analysis of nonparametric filament estimation
- Nonparametric ridge estimation
- Gaussian approximation of suprema of empirical processes
- U-processes: Rates of convergence
- Recursive estimation of the mode of a multivariate distribution
- Multivariate adaptive regression splines
- A population background for nonparametric density-based clustering
- Adaptive nonparametric peak estimation
- Rates of strong uniform consistency for multivariate kernel density estimators. (Vitesse de convergence uniforme presque sûre pour des estimateurs à noyaux de densités multivariées)
- A sufficient condition for the convergence of the mean shift algorithm with Gaussian kernel
- Gradient-based smoothing parameter selection for nonparametric regression estimation
- Uniform in bandwidth consistency of kernel-type function estimators
- Morse Theory. (AM-51)
- The estimation of the gradient of a density function, with applications in pattern recognition
- Matrices
- On nonparametric kernel estimation of the mode of the regression function in the random design model
- Bandwidth selection for nonparametric modal regression
- Applied Nonparametric Econometrics
- Comparison of Smoothing Parameterizations in Bivariate Kernel Density Estimation
- Modelling Beyond Regression Functions: An Application of Multimodal Regression to Speed–Flow Data
- A comprehensive approach to mode clustering
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