Least squares estimation of a completely monotone pmf: from analysis to statistics

DOI10.1016/j.jspi.2019.04.006zbMath1421.62034OpenAlexW2954907195MaRDI QIDQ2317336

Gabriella De Fournas-Labrosse, Fadoua Balabdaoui

Publication date: 9 August 2019

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

Full work available at URL: https://doi.org/10.1016/j.jspi.2019.04.006

zbMATH Keywords

least squaresasymptotic theorycompletely monotonenonparametric estimationmixture modelsshape constraintprobability mass functions

Mathematics Subject Classification ID

Density estimation (62G07) Classification and discrimination; cluster analysis (statistical aspects) (62H30) Order statistics; empirical distribution functions (62G30)

Related Items (4)

Stacked grenander and rearrangement estimators of a discrete distribution ⋮ Completely monotone distributions: mixing, approximation and estimation of number of species ⋮ Efficient shape-constrained inference for the autocovariance sequence from a reversible Markov chain ⋮ Estimation of the complexity of a finite mixture distribution: from well- to less known methods

Cites Work

• Unnamed Item
• On Multiply Monotone Distributions, Continuous or Discrete, with Applications
• Nonparametric estimation of multivariate scale mixtures of uniform densities
• Estimation of a discrete probability under constraint of \(k\)-monotonicity
• On asymptotics of the discrete convex LSE of a p.m.f.
• The geometry of mixture likelihoods: A general theory
• Estimation of the mixing distribution for a normal mean with applications to the compound decision problem
• Consistency of maximum likelihood estimators for certain nonparametric families, in particular: Mixtures
• Mixtures of exponential distributions
• Least-squares estimation of a convex discrete distribution
• Nonparametric estimation of species richness using discrete \(k\)-monotone distributions
• Testing \(k\)-monotonicity of a discrete distribution. Application to the estimation of the number of classes in a population
• Fourier methods for estimating mixing densities and distributions
• Estimation of a convex function: Characterizations and asymptotic theory.
• A review of reliable maximum likelihood algorithms for semiparametric mixture models
• Weak convergence and empirical processes. With applications to statistics
• Estimation of a discrete monotone distribution
• Estimation of a \(k\)-monotone density: limit distribution theory and the spline connection
• Consistency of maximum likelihood estimators in a large class of deconvolution models
• Asymptotic Statistics
• The Support Reduction Algorithm for Computing Non‐Parametric Function Estimates in Mixture Models
• Note on Completely Monotone Densities
• A Remark on Completely Monotonic Sequences, with an Application to Summability
• Deconvolution with arbitrarily smooth kernels

This page was built for publication: Least squares estimation of a completely monotone pmf: from analysis to statistics