Central limit theorem for the total squared error of local polynomial estimators of cell probabilities

DOI10.1016/S0378-3758(00)00177-4zbMath0970.62039OpenAlexW2053459437MaRDI QIDQ5928930

Paul Janssen, Ilse Augustyns, Marc Aerts

Publication date: 3 October 2001

Published in: Journal of Statistical Planning and Inference (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/s0378-3758(00)00177-4

zbMATH Keywords

characterizationcell probabilitiesfrequency estimatorslocal polynomial smootherssquared errors

Mathematics Subject Classification ID

Density estimation (62G07) Nonparametric estimation (62G05) Central limit and other weak theorems (60F05) Contingency tables (62H17)

Related Items (2)

\(L_2\)-tests for sparse multinomials ⋮ Relative smoothing of discrete distributions with sparse observations

Uses Software

• KernSmooth

Cites Work

• Unnamed Item
• Unnamed Item
• Central limit theorem for integrated square error of multivariate nonparametric density estimators
• Central limit theorem for quadratic forms for sparse tables
• Sparse consistency and smoothing for multinomial data
• Dependent central limit theorems and invariance principles
• Smoothing methods in statistics
• On Smoothing Sparse Multinomial Data
• Three Sides of Smoothing: Categorical Data Smoothing, Nonparametric Regression, and Density Estimation
• Smoothing sparse multinomial data using local polynomial fitting
• Local Polynomial Estimation of Contingency Table Cell Probabilities
• Simultaneous Estimation of Multinomial Cell Probabilities
• Convergence of stochastic processes

This page was built for publication: Central limit theorem for the total squared error of local polynomial estimators of cell probabilities