Calibrating Functional Parameters in the Ion Channel Models of Cardiac Cells. Issue 514 (2nd April 2016)

• Record Type: Journal Article
• Authors: Plumlee, Matthew; Joseph, V. Roshan; Yang, Hui
• Is Part Of: Journal of the American Statistical Association. Volume 111:Issue 514(2016)
• Page Start: 500
• Page End: 509
• Publication Date: 2016-04-02
• Subjects: Calibration -- Computer experiment -- Functional response -- High-dimensional parameters -- Simulation experiment; Statistics -- Periodicals; Statistics -- Periodicals; Statistiques -- Périodiques; États-Unis -- Statistiques -- Périodiques; 519.5
• DOI: 10.1080/01621459.2015.1119695
• Languages: English
• ISSNs: 0162-1459

Abstract

ABSTRACT: Computational modeling is a popular tool to understand a diverse set of complex systems. The output from a computational model depends on a set of parameters that are unknown to the designer, but a modeler can estimate them by collecting physical data. In the described study of the ion channels of ventricular myocytes, the parameter of interest is a function as opposed to a scalar or a set of scalars. This article develops a new modeling strategy to nonparametrically study the functional parameter using Bayesian inference with Gaussian process prior distributions. A new sampling scheme is devised to address this unique problem.