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An Application of the Orthogonal Series Estimators in the Classification Of Mixed Variables
Author(s) -
Wojciechowski T.
Publication year - 1988
Publication title -
biometrical journal
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.108
H-Index - 63
eISSN - 1521-4036
pISSN - 0323-3847
DOI - 10.1002/bimj.4710300808
Subject(s) - estimator , series (stratigraphy) , mathematics , multivariate random variable , realization (probability) , element (criminal law) , statistics , random variable , construct (python library) , population , combinatorics , computer science , paleontology , demography , sociology , political science , law , biology , programming language
Suppose we have two general populations π 1 , π 2 . Each object belonging to the population π i , i = 1, 2 is characterized by a random vector X ′ = ( Z ′, Y ′), where Z is discrete and Y is continuous. On a certain element which is a member of a one of the two populations a realization π′ 0 =( z ′ 0 , y ′ 0 ) of the random vector X has been observed and we want to classify that element. One of the possible methods of doing it is to estimate the density functions of X in π 1 and π 2 and construct an estimated classification rule. In this paper the density estimates based on the orthogonal series (Hall, 1983) will be employed and the classification rule will be examined on a practical example.