Estimation of parameters for discretely observed diffusion processes with a variety of rates for information

被引：0
作者：
Yasutaka Shimizu
机构：
[1] Osaka University,Graduate School of Engineering Science
[2] Japan Science and Technology Agency,undefined
[3] CREST,undefined
来源：
Annals of the Institute of Statistical Mathematics | 2012年 / 64卷
关键词：
Parametric inference; Non-ergodic diffusions; Discrete observations; Consistency; Rates of convergence; Normalized information;
D O I：
暂无
中图分类号：
学科分类号：
摘要：
A specific form of stochastic differential equation with unknown parameters are considered. We do not necessarily assume ergodicity or recurrency, and any moment conditions for the true process, but some tightness conditions for an information-like quantity. The interest is to estimate the parameters from discrete observations the step size of which tends to zero. Consistency and the rate of convergence of proposed estimators are presented. The rate is deduced naturally from the rate for the information-like quantities.
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页码：545 / 575
页数：30
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