A Comparison of Principal Component Analysis and Maximum Likelihood Factor Analysis in Bank Health Ratio

F. Firdaus, Sigit Nugroho, Hary Widodo
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引用次数: 2

Abstract

The use of factor analysis methods to reduce variable dimensions is generally known and has been used in various disciplines. The two famous extraction methods of factor analysis are principal component analysis and maximum likelihood. This study aimed to compare both, principal component analysis and maximum likelihood. By their constructed matrix correlation, applied to bank financial ratios. The study is developed from an initial set of 22 ratios of healthy indexed banks. The use of bank financial data aims to identify the structure of the financial ratio of healthy indexed banks. There are 10 variables satisfying the criteria of factor analysis techniques to be considered in the analysis. Both principal component analysis and maximum likelihood suggest three factors that can be used to represent 10 variables.Keywords: factor analysis; principal component analysis; maximum likelihood; financial ratios; bank health.
银行健康比率的主成分分析与最大似然因子分析之比较
使用因子分析方法来降低变量维度是众所周知的,并已在各个学科中使用。因子分析中两种著名的提取方法是主成分分析和极大似然分析。本研究旨在比较两者,主成分分析和最大似然。通过其构造的矩阵相关性,应用于银行财务比率。这项研究是根据22家健康指数银行的初始比率发展而来的。银行财务数据的使用旨在识别健康指数银行的财务比率结构。在分析中有10个满足因子分析技术标准的变量需要考虑。主成分分析和最大似然分析表明,三个因素可以用来表示10个变量。关键词:因子分析;主成分分析;最大似然;财务比率;银行的健康状况。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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