Notes on estimating inverse-Gaussian and gamma subordinators under high-frequency sampling

DOI10.1007/s10463-007-0131-7zbMath1294.62039OpenAlexW2089526481MaRDI QIDQ734414

Hiroki Masuda

Publication date: 13 October 2009

Published in: Annals of the Institute of Statistical Mathematics (Search for Journal in Brave)

Full work available at URL: http://hdl.handle.net/2324/3395

zbMATH Keywords

efficient estimationoptimal ratehigh-frequency samplinggamma subordinatorinverse-Gaussian subordinator

Mathematics Subject Classification ID

Asymptotic distribution theory in statistics (62E20) Point estimation (62F10) Exact distribution theory in statistics (62E15)

Related Items (4)

On the local asymptotic behavior of the likelihood function for Meixner Lévy processes under high-frequency sampling ⋮ Shrinkage estimation for the mean of the inverse Gaussian population ⋮ Local asymptotic normality for Student-Lévy processes under high-frequency sampling ⋮ Moment-based estimation for parameters of general inverse subordinator

Cites Work

• Unnamed Item
• Unnamed Item
• Unnamed Item
• Unnamed Item
• Uniform asymptotic normality of the maximum likelihood estimator
• Asymptotic inference in Levy processes of the discontinuous type
• Ruin probabilities and decompositions for general perturbed risk processes.
• A note on estimation for gamma and stable processes
• Generating Random Variates Using Transformations with Multiple Roots
• Inference for gamma and stable processes
• Asymptotic Statistics
• Parametric Estimation for Subordinators and Induced OU Processes

This page was built for publication: Notes on estimating inverse-Gaussian and gamma subordinators under high-frequency sampling