Title :
Classifying scatterbrains by their reaction based on method of functional data
Author :
Yizhi, Chen ; Jinchang, Li
Author_Institution :
Coll. of Stat. & Math., ZheJiang Gongshang Univ., Hangzhou, China
Abstract :
In this paper, we present a nonparametric statistical method for functional data analysis. We actually work with the functions obtained by taking logarithms of the densities and differentiating, one aspect of this transformation is that it makes a normal density into a straight line. We work with the probability density function, describing the reaction-time distributions. By studying a density function, we explore the use of functional principal components analysis to get a sense of how the density functions vary from student to student. The result of this paper is giving some help for computational classifying of human´s attention with the aid of their reaction-time.
Keywords :
behavioural sciences computing; data analysis; pattern classification; principal component analysis; statistical distributions; functional data analysis; human attention classification; nonparametric statistical method; principal component analysis; probability density function; reaction-time distribution; scatterbrain classification; Analytical models; density; distribution; estimation; functional data;
Conference_Titel :
Future Information Technology and Management Engineering (FITME), 2010 International Conference on
Conference_Location :
Changzhou
Print_ISBN :
978-1-4244-9087-5
DOI :
10.1109/FITME.2010.5654827