Analysis of multivariate skew normal models with incomplete data |
| |
Authors: | Tsung I Lin Hsiu J Ho Chiang L Chen |
| |
Institution: | aDepartment of Applied Mathematics, National Chung Hsing University, Taichung 402, Taiwan;bInstitute of Statistics, National Chung Hsing University, Taichung 402, Taiwan |
| |
Abstract: | We establish computationally flexible methods and algorithms for the analysis of multivariate skew normal models when missing values occur in the data. To facilitate the computation and simplify the theoretic derivation, two auxiliary permutation matrices are incorporated into the model for the determination of observed and missing components of each observation. Under missing at random mechanisms, we formulate an analytically simple ECM algorithm for calculating parameter estimation and retrieving each missing value with a single-valued imputation. Gibbs sampling is used to perform a Bayesian inference on model parameters and to create multiple imputations for missing values. The proposed methodologies are illustrated through a real data set and comparisons are made with those obtained from fitting the normal counterparts. |
| |
Keywords: | ECM algorithm Gibbs sampler MSN model Multiple imputation Multivariate truncated normal Posterior distributions |
本文献已被 ScienceDirect 等数据库收录! |