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Prediction Models in Configural Frequency Analysis
Author(s) -
Heilmann W.R.,
Lienert G. A.,
Maly V.
Publication year - 1979
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.4710210110
Subject(s) - mathematics , statistics , variable (mathematics) , sampling (signal processing) , class (philosophy) , computer science , artificial intelligence , mathematical analysis , filter (signal processing) , computer vision
Configural frequency analysis models are presented for predicting a discrete criterion variable from combining 2 or more discrete predictor variables nonparametrically. Predictions are made via so‐called prediction types which allow to predict a criterion class from combined predictor classes. Prediction types are implicitely defined as cells of a 2‐dimensional contingeney table with rows as predictor combinations and columns as criterion classes. The CFA is extended for two criteria, and for stratified sampling.