Joint asymptotic normality of kernel estimates under dependence conditions, with application to hazard rate

DOI10.1080/10485259208832534zbMath1360.62137OpenAlexW2096483877MaRDI QIDQ3432320

George G. Roussas, Lanh Tat Tran

Publication date: 16 April 2007

Published in: Journal of Nonparametric Statistics (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1080/10485259208832534

Mathematics Subject Classification ID

Nonparametric estimation (62G05)

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Recursive estimation of the transition distribution function of a Markov process: Asymptotic normality ⋮ Nonparametric estimation under long memory dependence ⋮ A study on weighted dynamic survival and failure extropies

Cites Work

• Asymptotic normality of the kernel estimate under dependence conditions: Application to hazard rate
• Some mixing properties of time series models
• Hazard rate estimation under dependence conditions
• Some asymptotic properties of an estimate of the survival function under dependence conditions
• The mixing property of bilinear and generalised random coefficient autoregressive models
• Recursive probability density estimation for weakly dependent stationary processes
• On the Strong Mixing Property for Linear Sequences
• Moment bounds for stationary mixing sequences