The skew-t factor analysis model
碩士 === 國立中興大學 === 統計學研究所 === 101 === Factor analysis(FA) is a classical data reduction technique that seeks a potentially lower number of unobserved variables accounting for most correlation among the observed variables. This thesis presents an extension of the FA model by assuming jointly a restr...
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| Format: | Others |
| Language: | en_US |
| Published: |
2013
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| Online Access: | http://ndltd.ncl.edu.tw/handle/a39dwt |
| Summary: | 碩士 === 國立中興大學 === 統計學研究所 === 101 === Factor analysis(FA) is a classical data reduction technique that seeks a potentially lower number of unobserved variables accounting for most correlation among the observed variables. This thesis presents an extension of the FA model by assuming jointly a restricted version of multivariate skew t distribution for the latent factors and unobservable errors, called the skew-t FA model. The proposed model shows robustness to violations of normality assumptions of the underlying latent factors and provides flexibility in capturing extra skewness as well as heavier tails of the observed data. A computationally feasible EM-type algorithm is developed for computing maximum likelihood estimates of the parameters. The usefulness of the proposed methodology is illustrated by a real-life example and result also demonstrates its better performance over various existing methods.
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