Missing Data Imputation for Categorical Variables

Dealing with missing data is a crucial part of everyday data analysis. The IMIC algorithm is a missing data imputation method that can handle mixed numerical and categorical datasets. However, the categorical data are crucial for this work. This paper proposes the new improvement of the IMIC algorit...

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Bibliographic Details
Main Authors: Jaroslav Horníček, Hana Řezanková
Format: Article
Language:English
Published: Czech Statistical Office 2022-09-01
Series:Statistika: Statistics and Economy Journal
Subjects:
Online Access:https://www.czso.cz/documents/10180/167607763/32019722q3_249-260_hornicek_analyses.pdf/23e277ec-e001-4036-9809-ceda5dda950d?version=1.1