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MERO  

Performing Monte Carlo Expectation Maximization Random Forest Imputation for Biological Data
View on CRAN: Click here


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

Install from Github:
library("remotes")
install_github("cran/MERO")

Install by package version:
library("remotes")
install_version("MERO", "0.1.2")



Attach the package and use:
library("MERO")
Maintained by
Mohamed Soudy
[Scholar Profile | Author Map]
First Published: 2022-02-09
Latest Update: 2023-02-24
Description:
Perform missing value imputation for biological data using the random forest algorithm, the imputation aim to keep the original mean and standard deviation consistent after imputation.
How to cite:
Mohamed Soudy (2022). MERO: Performing Monte Carlo Expectation Maximization Random Forest Imputation for Biological Data. R package version 0.1.2, https://cran.r-project.org/web/packages/MERO. Accessed 07 Apr. 2025.
Previous versions and publish date:
0.1.0 (2022-02-09 20:40), 0.1.1 (2022-03-01 00:10)
Other packages that cited MERO R package
View MERO citation profile
Other R packages that MERO depends, imports, suggests or enhances
Complete documentation for MERO
Functions, R codes and Examples using the MERO R package
Some associated functions: EvalImp . MERO . PlotCorrelateMean . RMSE . 
Some associated R codes: EvalImp.R . MERO.R . PlotCorrelateMean.R . RMSE.R .  Full MERO package functions and examples
Downloads during the last 30 days
03/0803/0903/1003/1103/1203/1303/1403/1503/1603/1703/1803/1903/2003/2103/2203/2303/2403/2503/2603/2703/2803/3003/3104/0104/0204/0304/0404/05Downloads for MERO0246810121416TrendBars

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