TY - JOUR
AU - Marijus Radavičius
PY - 2010/12/21
Y2 - 2021/05/08
TI - The EM algorithm for general Gaussian model with latent variables
JF - Lietuvos matematikos rinkinys
JA - LMR
VL - 51
IS - proc. LMS
SE - Articles
DO - 10.15388/LMR.2010.76
UR - https://www.journals.vu.lt/LMR/article/view/17864
AB - The problem of estimating parameters of Gaussian vector when only its (nonlinear) transformation is observed is addressed. The EM algorithm equations to calculate maximum likelihood estimator are derived. In particular, closed-form formulas of the EM algorithm are derived in the case when only the minimum of two endogenous variables satisfying Gaussian regression model is observed.
ER -