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Open Access Biostatistics & Bioinformatics
Robust Estimation in Gompertz Diffusion Model of Tumor Growth
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
ISSN: 2578-0247Volume1 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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