Categorical Functional Data Analysis. The cfda R Package

被引：2
作者：
Preda, Cristian [1 ,2 ,3 ]
Grimonprez, Quentin [4 ]
Vandewalle, Vincent [3 ,5 ]
机构：
[1] Univ Lille, CNRS, UMR 8524, Lab Paul Painleve, F-59000 Lille, France
[2] Romanian Acad, Inst Stat & Appl Math, Bucharest 050711, Romania
[3] Inria Lille Nord Europe, MODAL, F-59655 Villeneuve Dascq, France
[4] DiagRAMS Technol, F-59000 Lille, France
[5] Univ Lille, CHU Lille, ULR 2694, Biostat Dept,METRICS, F-59000 Lille, France
来源：
MATHEMATICS | 2021年 / 9卷 / 23期
关键词：
functional data; categorical data; stochastic process; multiple correspondence analysis;
D O I：
10.3390/math9233074
中图分类号：
O1 [数学];
学科分类号：
0701 ; 070101 ;
摘要：
Categorical functional data represented by paths of a stochastic jump process with continuous time and a finite set of states are considered. As an extension of the multiple correspondence analysis to an infinite set of variables, optimal encodings of states over time are approximated using an arbitrary finite basis of functions. This allows dimension reduction, optimal representation, and visualisation of data in lower dimensional spaces. The methodology is implemented in the cfda R package and is illustrated using a real data set in the clustering framework.
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收藏
页数：31
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