Package: EM.Fuzzy 1.0
Abbas Parchami
EM.Fuzzy: 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>.
Authors:
EM.Fuzzy_1.0.tar.gz
EM.Fuzzy_1.0.tar.gz(r-4.5-noble)EM.Fuzzy_1.0.tar.gz(r-4.4-noble)
EM.Fuzzy_1.0.tgz(r-4.4-emscripten)EM.Fuzzy_1.0.tgz(r-4.3-emscripten)
EM.Fuzzy.pdf |EM.Fuzzy.html✨
EM.Fuzzy/json (API)
| # Install 'EM.Fuzzy' in R: |
| install.packages('EM.Fuzzy', repos = c('https://cran.r-universe.dev', 'https://cloud.r-project.org')) |
This package does not link to any Github/Gitlab/R-forge repository. No issue tracker or development information is available.
Last updated 6 years agofrom:47d114ee0f. Checks:OK: 2. Indexed: yes.
| Target | Result | Date |
|---|---|---|
| Doc / Vignettes | OK | Sep 12 2024 |
| R-4.5-linux | OK | Sep 12 2024 |
Exports:EM.TrapezoidalEM.Triangular
Dependencies:DISTRIBFuzzyNumbers
Readme and manuals
Help Manual
| Help page | Topics |
|---|---|
| EM Algorithm for Maximum Likelihood Estimation by Non-Precise Information | EM.Fuzzy-package EM.Fuzzy |
| MLE by EM algorithm based on Trapezoidal Fuzzy Data | EM.Trapezoidal |
| MLE by EM algorithm based on Triangular Fuzzy Data | EM.Triangular |