JP Journal of Biostatistics

The JP Journal of Biostatistics is a highly regarded open-access international journal indexed in the Emerging Sources Citation Index (ESCI). It focuses on the application of statistical theory and methods in resolving problems in biological, biomedical, and agricultural sciences. The journal encourages the submission of experimental papers that employ relevant algorithms and also welcomes survey articles in the fields of biostatistics and epidemiology.

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ESTIMATION OF PROBABILITY DENSITY FUNCTION AND INTENSITY FUNCTION OF THE SURVIVAL OF STOMACH CANCER PATIENTS USING REAL POLYNOMIALS

Authors

  • K. Ratheesan

Keywords:

nonparametric estimation, polynomial density estimator, intensity estimation, stomach cancer.

DOI:

https://doi.org/10.17654/0973514322010

Abstract

Various parametric and nonparametric approaches are available in the literature for estimating the probability density function and intensity function of the censored data. A retrospective study was carried out on the stomach cancer patients who registered in a tertiary cancer centre during the years 2010 and 2011. Their treatment and demographic characteristics have been studied. The density function and intensity function were estimated using a real polynomial that Rudin used to prove Stone-Weierstrass theorem.

Received: November 28, 2021 
Revised: January 24, 2022 
Accepted: January 29, 2022

References

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K. Ratheesan and P. Anilkumar, Smoothing intensities of counting processes by using polynomial, JP Journal of Biostatistics 18(2) (2021), 209-230.

M. Rosenblatt et al., Remarks on some nonparametric estimates of a density function, Ann. Math. Statist. 27(3) (1956), 832-837.

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W. Nelson, Theory and application of hazard plotting for censored failure data, Technometrics 14 (1972), 945-966.

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Published

2022-02-10

Issue

Vol. 20 (2022)

Section

Articles

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How to Cite

ESTIMATION OF PROBABILITY DENSITY FUNCTION AND INTENSITY FUNCTION OF THE SURVIVAL OF STOMACH CANCER PATIENTS USING REAL POLYNOMIALS. (2022). JP Journal of Biostatistics, 20, 1-10. https://doi.org/10.17654/0973514322010

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