Automatic bandwidth selection for recursive kernel density estimators with length-biased data

Yousri Slaoui

doi:10.1007/s42081-019-00053-z

ScienceGate Book Chapters

JOURNAL ARTICLE

Automatic bandwidth selection for recursive kernel density estimators with length-biased data

Yousri Slaoui

Year: 2019 Journal: Japanese Journal of Statistics and Data Science Vol: 3 (2)Pages: 429-452 Publisher: Springer Science+Business Media

DOI: 10.1007/s42081-019-00053-z

Get Full-Text PDF Get Analytical Report

Keywords:

Estimator Bandwidth (computing) Kernel density estimation Algorithm Computer science Kernel (algebra) Probability density function Variable kernel density estimation Stochastic approximation Kernel method Mathematics Mathematical optimization Statistics Artificial intelligence Support vector machine Discrete mathematics

Metrics

Cited By

1.07

FWCI (Field Weighted Citation Impact)

Refs

0.77

Citation Normalized Percentile

Is in top 1%

Is in top 10%

Citation History

Topics

Statistical Methods and Inference

Physical Sciences → Mathematics → Statistics and Probability

Stochastic Gradient Optimization Techniques

Physical Sciences → Computer Science → Artificial Intelligence

Gaussian Processes and Bayesian Inference

Physical Sciences → Computer Science → Artificial Intelligence

Automatic bandwidth selection for recursive kernel density estimators with length-biased data

Metrics

Citation History

Topics

Related Documents

Bandwidth selection for kernel density estimation with length-biased data

Optimal bandwidth selection for recursive Gumbel kernel density estimators

Data-Driven Bandwidth Selection for Recursive Kernel Density Estimators Under Double Truncation

Bandwidth Selection for Recursive Kernel Density Estimators Defined by Stochastic Approximation Method

Optimal bandwidth selection for semi-recursive kernel regression estimators