𝔖 Bobbio Scriptorium
✦   LIBER   ✦

On the asymptotic variance of the continuous-time kernel density estimator

✍ Scribed by Martin Sköld; Ola Hössjer


Publisher
Elsevier Science
Year
1999
Tongue
English
Weight
119 KB
Volume
44
Category
Article
ISSN
0167-7152

No coin nor oath required. For personal study only.


📜 SIMILAR VOLUMES


Estimation of the Asymptotic Variance of
✍ Armelle Guillou; Florence Merlevède 📂 Article 📅 2001 🏛 Elsevier Science 🌐 English ⚖ 196 KB

In order to construct confidence sets for a marginal density f of a strictly stationary continuous time process observed over the time interval [0, T ], it is necessary to have at one's disposal a Central Limit Theorem for the kernel density estimator f T . In this paper we address the question of n

Asymptotic Normality for Density Kernel
✍ Denis Bosq; Florence Merlevède; Magda Peligrad 📂 Article 📅 1999 🏛 Elsevier Science 🌐 English ⚖ 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.

On the asymptotic normality of multistag
✍ Carlos Tenreiro 📂 Article 📅 2003 🏛 Elsevier Science 🌐 English ⚖ 264 KB

The estimation of integrated density derivatives is a crucial problem which arises in data-based methods for choosing the bandwidth of kernel and histogram estimators. In this paper, we establish the asymptotic normality of a multistage kernel estimator of such quantities, by showing that under some

On the asymptotic mean integrated square
✍ Jan Mielniczuk 📂 Article 📅 1997 🏛 Elsevier Science 🌐 English ⚖ 357 KB

Hall and Hart (1990) proved that the mean integrated squared error (MISE) of a marginal kernel density estimator from an infinite moving average process X1, )(2 .... may be decomposed into the sum of MISE of the same kernel estimator for a random sample of the same size and a term proportional to th