A Latent-Class Model for Clustering Incomplete Linear and Circular Data in Marine Studies

10.6339/JDS.2011.09(4).947

Francesco Lagona；Marco Picone

Circular data ； cross-validation ； EM algorithm ； Gamma distribution ； latent classes ； marine data ； missing values ； Von Mises distribution

Journal of Data Science

9卷4期（2011 / 10 / 01）

585 - 605

英文

Identification of representative regimes of wave height and direction under different wind conditions is complicated by issues that relate to the specification of the joint distribution of variables that are defined on linear and circular supports and the occurrence of missing values. We take a latent-class approach and jointly model wave and wind data by a finite mixture of conditionally independent Gamma and von Mises distributions. Maximum-likelihood estimates of parameters are obtained by exploiting a suitable EM algorithm that allows for missing data. The proposed model is validated on hourly marine data obtained from a buoy and two tide gauges in the Adriatic Sea.

1. 蔡易昇(2011)。自動化之3D人物表面材質恢復之研究。淡江大學資訊工程學系碩士班學位論文。2011。1-87。