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Asymptotic normality of conditional density estimation under truncated, censored and dependent data.
- Source :
-
Communications in Statistics: Theory & Methods . 2020, Vol. 49 Issue 22, p5371-5391. 21p. - Publication Year :
- 2020
-
Abstract
- In this paper, we focus on the left-truncated and right-censored model, and construct the local linear and Nadaraya-Watson type estimators of the conditional density. Under suitable conditions, we establish the asymptotic normality of the proposed estimators when the observations are assumed to be a stationary α-mixing sequence. Finite sample behavior of the estimators is investigated via simulations too. [ABSTRACT FROM AUTHOR]
- Subjects :
- *DENSITY
*ASYMPTOTIC normality
*CENSORING (Statistics)
Subjects
Details
- Language :
- English
- ISSN :
- 03610926
- Volume :
- 49
- Issue :
- 22
- Database :
- Academic Search Index
- Journal :
- Communications in Statistics: Theory & Methods
- Publication Type :
- Academic Journal
- Accession number :
- 146195841
- Full Text :
- https://doi.org/10.1080/03610926.2019.1619769