MERO

The function is used to impute the missing data using Monte Carlo Expectation Maximization Random Forest Imputation

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.

Mohamed Soudy

Performing Monte Carlo Expectation Maximization Random Forest
Imputation for Biological Data

MERO function

<dl><dt>Data</dt>
<dd>a data matrix with missing values. The columns correspond to the variables and the rows to the observations.</dd>
<dt>ntree</dt>
<dd>number of trees to grow in each forest.</dd>
<dt>Nsets</dt>
<dd>number of simulations/ data sets to be generated.</dd></dl>

Arguments

Mohamed Soudy <a href="/link/Mohmedsoudy2009%40gmail.com?package=MERO&version=0.1.2" data-mini-rdoc="MERO::Mohmedsoudy2009@gmail.com">Mohmedsoudy2009@gmail.com</a>

Author

Perform Monte Carlo Expectation Maximization Random Forest Imputation — MERO

<dl>

<dt>Data</dt>
<dd>a data matrix with missing values. The columns correspond to the variables and the rows to the observations.</dd>


<dt>ntree</dt>
<dd>number of trees to grow in each forest.</dd>


<dt>Nsets</dt>
<dd>number of simulations/ data sets to be generated.</dd>

</dl>

Mohamed Soudy <a href='mailto:Mohmedsoudy2009@gmail.com'>Mohmedsoudy2009@gmail.com</a>

MERO: Perform Monte Carlo Expectation Maximization Random Forest Imputation

Description

Usage

Value

Arguments

Author