New smoothed location models integrated with PCA and two types of MCA for handling large number of mixed continuous and binary variables
The issue of classifying objects into groups when measured variables in an experiment are mixed has attracted the attention of statisticians.The Smoothed Location Model (SLM) appears to be a popular classification method to handle data containing both continuous and binary variables simultaneously.H...
Main Authors: | Hamid, Hashibah, P.A.H., Ngu, Mohd Alipiah, Fathilah |
---|---|
Format: | Article |
Language: | English |
Published: |
Universiti Putra Malaysia Press
2018
|
Subjects: | |
Online Access: | https://repo.uum.edu.my/id/eprint/24407/1/PJST%20%2026%201%202018%20%20247%20260.pdf |
Similar Items
-
The performance of smoothed location model with PCA+Indicator MCA and PCA+Adjusted MCA
by: Ngu, Penny Ai Huong, et al.
Published: (2016) -
Multiple correspondence analysis for handling large binary variables in smoothed location model
by: Ngu, Penny Ai Huong, et al.
Published: (2015) -
Winsorized and Smoothed Estimation of the Location Model in Mixed Variables Discrimination
by: Hamid, Hashibah
Published: (2018) -
Some investigations on the LDA when handling large number of variable
by: Hamid, Hashibah, et al.
Published: (2010) -
New Location Model Based on Automatic Trimming and Smoothing Approaches
by: Hamid, Hashibah
Published: (2018)