This paper is concerned with estimation of the drift parameter in a class of continuous state branching processes by use of the estimating function theory (Heyde, 1992, J. Statist. Plann. Inference 33, 121-129). The main interests are to develop a method of estimating the parameter in case when only
β¦ LIBER β¦
Optimal sampling for density estimation in continuous time
β Scribed by D. Blanke; B. Pumo
- Book ID
- 108549517
- Publisher
- John Wiley and Sons
- Year
- 2003
- Tongue
- English
- Weight
- 299 KB
- Volume
- 24
- Category
- Article
- ISSN
- 0143-9782
No coin nor oath required. For personal study only.
π SIMILAR VOLUMES
Optimal estimation for continuous state
β
Yongdai Kim
π
Article
π
1998
π
Elsevier Science
π
English
β 553 KB
A minimax optimal estimator for continuo
β
Somnath Datta
π
Article
π
1995
π
Elsevier Science
π
English
β 404 KB
Accurate rates of density estimators for
β
D. Blanke; D. Bosq
π
Article
π
1997
π
Elsevier Science
π
English
β 316 KB
We specify necessary conditions for getting parametric convergence rate of kernel density estimators. For continuoustime processes observed over [0, T], we show that two possible exact rates are (In T)/T and 1/T, according to the nature of sample paths.
Asymptotic Normality for Density Kernel
β
Denis Bosq; Florence Merlevède; Magda Peligrad
π
Article
π
1999
π
Elsevier Science
π
English
β 153 KB
In this paper, we build a central limit theorem for triangular arrays of sequences which satisfy a mild mixing condition. This result allows us to study asymptotic normality of density kernel estimators for some classes of continuous and discrete time processes.
Optimal Estimation of Qubit States with
β
MΔdΔlin GuΕ£Δ; Bas Janssens; Jonas Kahn
π
Article
π
2007
π
Springer
π
English
β 518 KB
Locally optimal window widths for kernel
β
William R. Schucany
π
Article
π
1989
π
Elsevier Science
π
English
β 396 KB