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pro vyhledávání: '"Hufnagel, Nicole"'
Autor:
Hufnagel, Nicole, Andraus, Sergio
Multivariate Bessel processes, otherwise known as radial Dunkl processes, are stochastic processes defined in a Weyl chamber that are repelled from the latter's boundary by a singular drift with a strength given by the multiplicity function $k$. It i
Externí odkaz:
http://arxiv.org/abs/2312.05420
Publikováno v:
In Econometrics and Statistics October 2024 32:73-87
Autor:
Hufnagel, Nicole, Andraus, Sergio
We consider systems of multiple Brownian particles in one dimension that repel mutually via a logarithmic potential on the real line, more specifically the Dyson model. These systems are characterized by a parameter that controls the strength of the
Externí odkaz:
http://arxiv.org/abs/2109.08707
Gaussian quasi-likelihood estimation of the parameter $\theta$ in the square-root diffusion process is studied under high frequency sampling. Different from the previous study of Overbeck and Ryd\'{e}n(1998) under low-frequency sampling, high-frequen
Externí odkaz:
http://arxiv.org/abs/2103.15457
In this paper we derive martingale estimating functions for the dimensionality parameter of a Bessel process based on the eigenfunctions of the diffusion operator. Since a Bessel process is non-ergodic and the theory of martingale estimating function
Externí odkaz:
http://arxiv.org/abs/2007.12521
Akademický článek
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Autor:
Woerner, Jeannette, Hufnagel, Nicole
In this paper we derive martingale estimating functions for the dimensionality parameter of a Bessel process based on the eigenfunctions of the diffusion operator. Since a Bessel process is non-ergodic and the theory of martingale estimating function
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::e18e721c4f5b3b4fb7e675ff76b7a3a6
Publikováno v:
Statistical Inference for Stochastic Processes; Jul2022, Vol. 25 Issue 2, p337-353, 17p