Some asymptotic properties of an estimate of the survival function under dependence conditions
โ Scribed by George G. Roussas
- Publisher
- Elsevier Science
- Year
- 1989
- Tongue
- English
- Weight
- 632 KB
- Volume
- 8
- Category
- Article
- ISSN
- 0167-7152
No coin nor oath required. For personal study only.
๐ SIMILAR VOLUMES
The sole purpose of this paper is to establish asymptotic normality of the usual kernel estimate of the marginal probability density function of a strictly stationary sequence of associated random variables. In much of the discussions and derivations, the term association is used to include both pos
Let (X 1 , Y 1 ), (X 2 , Y 2 ), ..., be d+1 dimensional random vectors which are distributed as (X, Y). Let %(x) be the conditional median, that is, We consider the problem of estimating %(x) from the data (X 1 , Y 1 ), ..., (X n , Y n ) which are :-mixing dependence. L 1 -norm kernel estimators of