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.
1 2 | residual.llike.modelBayes(test, whichtest, data, trueN, model, sdpar,
fullpar, sdmodel, badparam, errormodel = "Gauss", debug = FALSE, ...)
|
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. |
debug |
Logical. If TRUE, call browser to debug. |
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