List of fitting functions or models

modelList

data

Number of folds (default 5, 0 splits in 1:n/2, n/2:n with last part
used for testing)

Performance measure (default RMSE)

perf

seed

function applied to each fold with results send to each model

shared

Additional arguments parsed to models in modelList and perf

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 (2019) <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

cv function

<dl><dt>modelList</dt>
<dd>List of fitting functions or models</dd>
<dt>data</dt>
<dd>data.frame</dd>
<dt>K</dt>
<dd>Number of folds (default 5, 0 splits in 1:n/2, n/2:n with last part
used for testing)</dd>
<dt>rep</dt>
<dd>Number of repetitions (default 1)</dd>
<dt>perf</dt>
<dd>Performance measure (default RMSE)</dd>
<dt>seed</dt>
<dd>Optional random seed</dd>
<dt>shared</dt>
<dd>function applied to each fold with results send to each model</dd>
<dt>...</dt>
<dd>Additional arguments parsed to models in modelList and perf</dd></dl>

Arguments

Author

Cross-validation — cv

<dl>

<dt>modelList</dt>
<dd>List of fitting functions or models</dd>


<dt>data</dt>
<dd>data.frame</dd>


<dt>K</dt>
<dd>Number of folds (default 5, 0 splits in 1:n/2, n/2:n with last part
used for testing)</dd>


<dt>rep</dt>
<dd>Number of repetitions (default 1)</dd>


<dt>perf</dt>
<dd>Performance measure (default RMSE)</dd>


<dt>seed</dt>
<dd>Optional random seed</dd>


<dt>shared</dt>
<dd>function applied to each fold with results send to each model</dd>


<dt>...</dt>
<dd>Additional arguments parsed to models in modelList and perf</dd>

</dl>

cv: Cross-validation

Description

Usage

Arguments

Author

Details

Examples