EM Algorithm for Maximum Likelihood Estimation by Non-Precise
Information // The EM algorithm is a powerful tool for
computing maximum likelihood estimates with incomplete data.
This package will help to applying EM algorithm based on
triangular and trapezoidal fuzzy numbers (as two kinds of
incomplete data). A method is proposed for estimating the
unknown parameter in a parametric statistical model when the
observations are triangular or trapezoidal fuzzy numbers. This
method is based on maximizing the observed-data likelihood
defined as the conditional probability of the fuzzy data; for
more details and formulas see Denoeux (2011)
doi:10.1016/j.fss.2011.05.022.