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Abstract

Open Access Biostatistics & Bioinformatics

Robust Estimation in Gompertz Diffusion Model of Tumor Growth

  • Open or Close Jaya PN Bishwal*

    Department of Mathematics and Statistics, University of North Carolina at Charlotte, USA

    *Corresponding author: Jaya PN Bishwal, Department of Mathematics and Statistics, University of North Carolina at Charlotte, 376 Fretwell Building, 9201 University City Blvd, Charlotte, NC 28223, USA

Submission: January 27, 2018; Published: May 10, 2018

DOI: 10.31031/OABB.2018.01.000521

ISSN 2578-0247
Volume1 Issue4

Abstract

Stochastic Gompertz diffusion model describes the in vivo tumor growth. The drift parameter describes the intrinsic growth rate (mitosis rate) of the tumor. The paper introduces some new approximate minimum contrast estimators of the tumor growth acceleration parameter in the Gompertz diffusion model based on discretely sampled data which are robust and studies their asymptotic distributional properties with precise rates of convergence.

Keywords: Itȏ stochastic differential equation; Gompertz diffusion process; Black-Karasinski model; Discrete observations; Approximate minimum contrast estimators; Robustness; efficiency; Berry-Esseen bound

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