residual.llike.lmerBayes: Calculate likelihood of residual standard deviation, given...
In forestgeo/ctfs: Tools for the Analysis of Forest Dynamics
Description
Calculate likelihood of residual standard deviation, given observations plus
the predicting model and data (to make predictions).
This likelihood does not depend on the hyperparameters. It does require data
and prediction for every single random effect.
Simply check a single SD parameter for sign.
Usage
1
2
residual.llike.lmerBayes(test, whichtest, data, trueN, model, sdpar,
fullpar, sdmodel, badparam, errormodel = "Gauss", ...)
Arguments
badparam
The name of a function (unquoted) that tests a set of model
parameters for validity; must return TRUE if parameters are valid,
otherwise FALSE.
forestgeo/ctfs documentation built on May 3, 2019, 6:44 p.m.
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Description
Calculate likelihood of residual standard deviation, given observations plus the predicting model and data (to make predictions).
This likelihood does not depend on the hyperparameters. It does require data and prediction for every single random effect.
Simply check a single SD parameter for sign.
Usage
1 2 | residual.llike.lmerBayes(test, whichtest, data, trueN, model, sdpar,
fullpar, sdmodel, badparam, errormodel = "Gauss", ...)
|
Arguments
badparam |
The name of a function (unquoted) that tests a set of model parameters for validity; must return TRUE if parameters are valid, otherwise FALSE. |
R Package Documentation
Browse R Packages
We want your feedback!
Note that we can't provide technical support on individual packages. You should contact the package authors for that.
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