predict.SMNclmm

Predicted values are obtained through conditional expectation. For details, see Schumacher, Lachos, and Matos (2021).

models

It fits scale mixture of skew-normal linear mixed models using either an expectation–maximization (EM) type algorithm or its accelerated version (Damped Anderson Acceleration with Epsilon Monotonicity, DAAREM), including some possibilities for modeling the within-subject dependence <doi:10.18637/jss.v115.i07>.

Fernanda L Schumacher

skewlmm

Scale Mixture of Skew-Normal Linear Mixed Models

Fernanda L. Schumacher

Larissa A. Matos

Victor H. Lachos

Katherine A. L. Valeriano

Nicholas Henderson

Ravi Varadhan

predict.SMNclmm function

<dl> <dt>object</dt>
<dd>An object inheriting from class <code>SMNclmm</code>, representing
 a fitted scale mixture normal linear mixed model.</dd> <dt>newData</dt>
<dd>A data frame for which response variable should be predicted, including covariates, groupVar and possibly timeVar. If missing or <code>NULL</code>, fitted values are returned.</dd> <dt>...</dt>
<dd>Additional arguments.</dd></dl>

Arguments

Fernanda L. Schumacher, Larissa A. Matos, Victor H. Lachos and Katherine L. Valeriano

Author

Prediction of future observations from an smn.clmm object — predict.SMNclmm

<dl>

 <dt>object</dt>
<dd>An object inheriting from class <code>SMNclmm</code>, representing
 a fitted scale mixture normal linear mixed model.</dd>

 <dt>newData</dt>
<dd>A data frame for which response variable should be predicted, including covariates, groupVar and possibly timeVar. If missing or <code>NULL</code>, fitted values are returned.</dd>

 <dt>...</dt>
<dd>Additional arguments.</dd>

</dl>

predict.SMNclmm: Prediction of future observations from an smn.clmm object

Description

Usage

Value

Arguments

Author

References

See Also