Random sampling of continuous-parameter stationary processes: Statistical properties of joint density estimators

DOI10.1016/0047-259X(88)90077-2zbMath0672.62087OpenAlexW2046710993MaRDI QIDQ1120234

Elias Masry

Publication date: 1988

Published in: Journal of Multivariate Analysis (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/0047-259x(88)90077-2

zbMATH Keywords

kernel estimatorsdiscrete-time observationsmixing processescentral limittheoremsrenewal point processesconsistency in quadratic meancontinuous-parameter processesestimator covariance calculationsestimators of multivariate densities

Mathematics Subject Classification ID

Estimation in multivariate analysis (62H12) Nonparametric estimation (62G05) Non-Markovian processes: estimation (62M09)

Related Items

Inheritance of strong mixing and weak dependence under renewal sampling, Independent sampling of a stochastic process

Cites Work

• Probability density estimation from sampled data
• Polynomial Interpolation of Randomly Sampled Bandlimited Functions and Processes
• Recovery of randomly sampled signals by simple interpolators
• Non-parametric covariance estimation from irregularly-spaced data
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