In some long term studies, a series of dependent and possibly censored failure times may be observed. Suppose that the failure times have a common marginal distribution function having a density, and the nonparametric estimation of density and hazard rate under random censorship is of our interest.
β¦ LIBER β¦
Kernel estimation of conditional density with truncated, censored and dependent data
β Scribed by Liang, Han-Ying; Liu, Ai-Ai
- Book ID
- 120406232
- Publisher
- Elsevier Science
- Year
- 2013
- Tongue
- English
- Weight
- 835 KB
- Volume
- 120
- Category
- Article
- ISSN
- 0047-259X
No coin nor oath required. For personal study only.
π SIMILAR VOLUMES
Kernel Density and Hazard Rate Estimatio
β
Zongwu Cai
π
Article
π
1998
π
Elsevier Science
π
English
β 266 KB
Asymptotic properties of conditional dis
β
Han-Ying Liang, Jacobo de UΓ±a-Γlvarez, MarΓa del Carmen Iglesias-PΓ©rez
π
Article
π
2012
π
CrossRef test prefix
π
English
β 725 KB
Bandwidth Selection in Density Estimatio
β
C. SΓ‘nchez-Sellero; W. GonzΓ‘lez-Manteiga; R. Cao
π
Article
π
1999
π
Springer Japan
π
English
β 669 KB
Nonlinear wavelet density estimation wit
β
Si-Li Niu
π
Article
π
2011
π
John Wiley and Sons
π
English
β 236 KB
On self-consistent estimators and kernel
β
Jian-Jian Ren
π
Article
π
1997
π
Elsevier Science
π
English
β 667 KB
We study the detailed structure (in a large sample) of the self-consistent estimators of the survival functions with doubly censored data. We also introduce the kernel-type density estimators based on the self-consistent estimators, and using our results on the structure of the self-consistent estim
Bandwidth selection for kernel density e
β
Moreira, C.; Van Keilegom, I.
π
Article
π
2013
π
Elsevier Science
π
English
β 482 KB