| predict.SLik_j {Infusion} | R Documentation |
Evaluate log-likelihood for given parameters
Description
As the Title says. Implemented as a method of the predict generic, for objects created by the up-to-date workflow using gaussian mixture modelling of a joint distribution of parameters and statistics (hence the newdata argument, shared by many predict methods; but these newdata should be parameter values, not data).
Usage
## S3 method for class 'SLik_j'
predict(
object, newdata, log = TRUE, which = "lik",
tstat = t(attr(object$logLs, "stat.obs")),
solve_t_chol_sigma_lists = object$clu_params$solve_t_chol_sigma_lists,
...)
Arguments
object |
an object of class |
newdata |
A matrix, whose rows each contain a full vector of the fitted parameters; or a single vector. If parameter names are not provided (as column names in the matrix case), then the vector is assumed to be ordered as |
log |
Boolean: whether to return log-likelihood or likelihood. |
which |
|
tstat |
The data (as projected summary statistics). Defaults to the data input in the inference procedure (i.e., the projected statistics used as |
solve_t_chol_sigma_lists |
For programming purposes. Do not change this argument. |
... |
For consistency with the generic. Currently ignored. |
Value
Numeric: a single value, or a vector of (log-)likelihoods for different rows of the input newdata.
Examples
## see help("example_reftable")