Parameter estimation for first-order bifurcating autoregressive processes with Weibull innova\-tions

DOI10.1016/j.spl.2011.08.014zbMath1225.62131OpenAlexW2057415801MaRDI QIDQ645457

Chenhua Zhang

Publication date: 15 November 2011

Published in: Statistics \& Probability Letters (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/j.spl.2011.08.014

zbMATH Keywords

regular variationpoint processtail indexHill's estimator

Mathematics Subject Classification ID

Time series, auto-correlation, regression, etc. in statistics (GARCH) (62M10) Asymptotic distribution theory in statistics (62E20) Point estimation (62F10) Point processes (e.g., Poisson, Cox, Hawkes processes) (60G55)

Related Items

Estimation for a first-order bifurcating autoregressive process with heavy-tail innovations

Cites Work

• Unnamed Item
• Unnamed Item
• Unnamed Item
• Unnamed Item
• Least-squares estimation for bifurcating autoregressive processes
• Estimation for first-order autoregressive processes with positive or bounded innovations
• Asymptotic analysis for bifurcating autoregressive processes via a martingale approach
• On Interchanging Limits and Integrals
• The Bifurcating Autoregression Model in Cell Lineage Studies
• Smoothing the Hill Estimator
• Asymptotic behavior of hill's estimator for autoregressive data
• Theory & Methods: Inference for the Extended Bifurcating Autoregressive Model for Cell Lineage Studies
• Non-Gaussian bifurcating models and quasi-likelihood estimation
• Extensions of the bifurcating autoregressive model for cell lineage studies
• Maximum Likelihood Estimation for a First‐Order Bifurcating Autoregressive Process with Exponential Errors
• A Multivariate Exponential Distribution