simulated

simulated.tidyvpcobj

The simulated function is used for specifying simulated input data and variables for VPC. Note: Simulated data must not
contain missing DV and may require filtering <code>MDV == 0</code> before generating VPC. The ordering of observed and simulated
data must also be consistent, with replicates in simulated data stacked on top of each other.

Perform a Visual Predictive Check (VPC), while accounting for
stratification, censoring, and prediction correction. Using piping from
'magrittr', the intuitive syntax gives users a flexible and powerful method
to generate VPCs using both traditional binning and a new binless approach
Jamsen et al. (2018) <doi:10.1002/psp4.12319> with Additive Quantile
Regression (AQR) and Locally Estimated Scatterplot Smoothing (LOESS)
prediction correction.

James Craig

tidyvpc

VPC Percentiles and Prediction Intervals

Olivier Barriere

Benjamin Rich

Samer Mouksassi

Bill Denney

Kris Jamsen

Certara USA, Inc. 

simulated function

<dl><dt>o</dt>
<dd>A <code>tidyvpcobj</code>.</dd>
<dt>...</dt>
<dd>Other arguments.</dd>
<dt>data</dt>
<dd>A <code>data.frame</code> of simulated data.</dd>
<dt>ysim</dt>
<dd>Numeric y-variable, typically named DV.</dd>
<dt>xsim</dt>
<dd>Numeric x-variable, typically named TIME.</dd></dl>

Arguments

Specify simulated dataset and variables for VPC — simulated

<dl>

<dt>o</dt>
<dd>A <code>tidyvpcobj</code>.</dd>


<dt>...</dt>
<dd>Other arguments.</dd>


<dt>data</dt>
<dd>A <code>data.frame</code> of simulated data.</dd>


<dt>ysim</dt>
<dd>Numeric y-variable, typically named DV.</dd>


<dt>xsim</dt>
<dd>Numeric x-variable, typically named TIME.</dd>

</dl>

simulated: Specify simulated dataset and variables for VPC

Description

Usage

Value

Arguments

See Also

Examples