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PreprintCC BY-NC 4.0HAL

SMOOTH DIVERGENCES ESTIMATION FOR CENSORED SURVIVAL DATA

  • Justin Moutsouka
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Abstract

This paper,we consider semiparameter models defined by moments constraints,with unknown parameter,for righ censored data.We derives estimates and converges properties for the parameter of interest,by means of minimizing the robust density power divergence methodology of Basu, Harris, Hjort, and Jones (Biometrika, 85, 549-559, 1998) to the case of censored survival data between the considered model and the Kaplan and Meier (7) empirical measure.The coonsistency properties of the proposed estimates are studied.

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Cite

BibTeXRIS
BibTeX
@misc{moutsouka2026smooth,
  title = {{SMOOTH DIVERGENCES ESTIMATION FOR CENSORED SURVIVAL DATA}},
  author = {Justin Moutsouka},
  howpublished = {HAL},
  year = {2026},
  month = oct,
  url = {https://hal.science/hal-05776804v1},
  note = {CC BY-NC 4.0},
}
RIS
TY  - UNPB
TI  - SMOOTH DIVERGENCES ESTIMATION FOR CENSORED SURVIVAL DATA
AU  - Justin Moutsouka
PY  - 2026
DA  - 2026/10/03
PB  - HAL
UR  - https://hal.science/hal-05776804v1
AB  - This paper,we consider semiparameter models defined by moments constraints,with unknown parameter,for righ censored data.We derives estimates and converges properties for the parameter of interest,by means of minimizing the robust density power divergence methodology of Basu, Harris, Hjort, and Jones (Biometrika, 85, 549-559, 1998) to the case of censored survival data between the considered model and the Kaplan and Meier (7) empirical measure.The coonsistency properties of the proposed estimates are studied.
ER  -