Please use this identifier to cite or link to this item: http://dspace.library.iitb.ac.in/xmlui/handle/100/15119
Title: Selection of a stroke risk model based on transcranial Doppler ultrasound velocity
Authors: MUKHOPADHYAY, S
DAS, I
DAS, K
Keywords: Dantzig Selector
Gibbs Sampling
Optimization
Parallel Genetic Algorithm
Sickle Cell Disease
Stochastic Search Variable Selection
Issue Date: 2012
Publisher: TAYLOR & FRANCIS LTD
Citation: JOURNAL OF APPLIED STATISTICS, 39(12)2699-2712
Abstract: Increased transcranial Doppler ultrasound (TCD) velocity is an indicator of cerebral infarction in children with sickle cell disease (SCD). In this article, the parallel genetic algorithm ( PGA) is used to select a stroke risk model with TCD velocity as the response variable. Development of such a stroke risk model leads to the identification of children with SCD who are at a higher risk of stroke and their treatment in the early stages. Using blood velocity data from SCD patients, it is shown that the PGA is an easy-to-use computationally variable selection tool. The results of the PGA are also compared with those obtained from the stochastic search variable selection method, the Dantzig selector and conventional techniques such as stepwise selection and best subset selection.
URI: http://dx.doi.org/10.1080/02664763.2012.725463
http://dspace.library.iitb.ac.in/jspui/handle/100/15119
Appears in Collections:Article

Files in This Item:
There are no files associated with this item.


Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.