Apply a Function to a Data Frame Split by Factors

A general implementation of Structural Equation Models
with latent variables (MLE, 2SLS, and composite likelihood
estimators) with both continuous, censored, and ordinal
outcomes (Holst and Budtz-Joergensen (2013) <doi:10.1007/s00180-012-0344-y>).
Mixture latent variable models and non-linear latent variable models
(Holst and Budtz-Joergensen (2020) <doi:10.1093/biostatistics/kxy082>).
The package also provides methods for graph exploration (d-separation,
back-door criterion), simulation of general non-linear latent variable
models, and estimation of influence functions for a broad range of
statistical models.

Klaus Holst

lava

Latent Variable Models

Klaus K. Holst

Brice Ozenne

Thomas Gerds

By function

<dl><dt>x</dt>
<dd>Data frame</dd>
<dt>INDICES</dt>
<dd>Indices (vector or list of indices, vector of column names, or formula of column names)</dd>
<dt>FUN</dt>
<dd>A function to be applied to data frame subsets of 'data'.</dd>
<dt>COLUMNS</dt>
<dd>(Optional) subset of columns of x to work on</dd>
<dt>array</dt>
<dd>if TRUE an array/matrix is always returned</dd>
<dt>...</dt>
<dd>Additional arguments to lower-level functions</dd></dl>

Arguments

Author

Apply a Function to a Data Frame Split by Factors — By

<dl>

<dt>x</dt>
<dd>Data frame</dd>


<dt>INDICES</dt>
<dd>Indices (vector or list of indices, vector of column names, or formula of column names)</dd>


<dt>FUN</dt>
<dd>A function to be applied to data frame subsets of 'data'.</dd>


<dt>COLUMNS</dt>
<dd>(Optional) subset of columns of x to work on</dd>


<dt>array</dt>
<dd>if TRUE an array/matrix is always returned</dd>


<dt>...</dt>
<dd>Additional arguments to lower-level functions</dd>

</dl>

By: Apply a Function to a Data Frame Split by Factors

Description

Usage

Arguments

Author

Details

Examples