CRAN/E | EM.Fuzzy

EM.Fuzzy

EM Algorithm for Maximum Likelihood Estimation by Non-Precise Information

Installation

About

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.

Key Metrics

Version 1.0
Published 2018-08-16 2088 days ago
Needs compilation? no
License LGPL (≥ 3)
CRAN checks EM.Fuzzy results

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Maintainer

Maintainer

Abbas Parchami

parchami@uk.ac.ir

Authors

Abbas Parchami

(Department of Statistics, Faculty of Mathematics and Computer, Shahid Bahonar University of Kerman, Kerman, Iran)

Material

Reference manual
Package source

macOS

r-release

arm64

r-oldrel

arm64

r-release

x86_64

r-oldrel

x86_64

Windows

r-devel

x86_64

r-release

x86_64

r-oldrel

x86_64

Imports

FuzzyNumbers
DISTRIB