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EM.Fuzzy  

EM Algorithm for Maximum Likelihood Estimation by Non-Precise Information
View on CRAN: Click here


Download and install EM.Fuzzy package within the R console
Install from CRAN:
install.packages("EM.Fuzzy")

Install from Github:
library("remotes")
install_github("cran/EM.Fuzzy")

Install by package version:
library("remotes")
install_version("EM.Fuzzy", "1.0")



Attach the package and use:
library("EM.Fuzzy")
Maintained by
Abbas Parchami
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2018-08-16
Latest Update: 2018-08-16
Description:
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) .
How to cite:
Abbas Parchami (2018). EM.Fuzzy: EM Algorithm for Maximum Likelihood Estimation by Non-Precise Information. R package version 1.0, https://cran.r-project.org/web/packages/EM.Fuzzy
Previous versions and publish date:
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Other packages that cited EM.Fuzzy R package
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Other R packages that EM.Fuzzy depends, imports, suggests or enhances
Functions, R codes and Examples using the EM.Fuzzy R package
Some associated functions: EM.Fuzzy-package . EM.Trapezoidal . EM.Triangular . 
Some associated R codes: EM.Trapezoidal.R . EM.Triangular.R .  Full EM.Fuzzy package functions and examples
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