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  • About
  • The Global ETD Search service is a free service for researchers to find electronic theses and dissertations. This service is provided by the Networked Digital Library of Theses and Dissertations.
    Our metadata is collected from universities around the world. If you manage a university/consortium/country archive and want to be added, details can be found on the NDLTD website.

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Spelling suggestions: "subject:"normal latner variable model"" "subject:"normal patnet variable model""

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混合連續與間斷資料之馬式距離的穩健估計 / Robust estimation of the Mahalanobis distance for multivariate data mixed with continuous and discrete variables

任嘉珩, Jen , Chia Heng Unknown Date (has links)
本研究採用Lee 和Poon 所提出的隱藏常態變數模型來估計混合連續與間斷型變數之參數估計，並估計其馬式距離。此外，並利用穩健估計來估計混合型資料參數及其馬式距離，可在有離群值時解決最大蓋似估計的不穩定。 / Poon and Lee (1987) applied normal latent variable model to deal with the parameters estimation for the data mixed with continuous and discrete variables and Bedrick et al. (2000) used this idea to evaluate the Mahalanobis distance. In this thesis, we extend a similar idea to robustly estimate Multivariate Data Mixed with Continuous and Discrete Variables with the same model. Furthermore, we evaluate the Mahalanobis distance which can determine similarity of variables. The proposed method can overcome the unreliability of MLE while there exist outliers in the data.
混合型資料
隱藏常態變數模型
穩健估計
馬式距離
mixed data
normal latnet variable model
robust estimation
Mahalanobis distacne
minimum covariance determinant

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