summary.rpql: Summary of GLMM fitted using regularized PQL.
In emitanaka/rpql: Regularized PQL for Joint Selection in GLMMs

A summary of the results from applying rpql.

## S3 method for class 'rpql'
summary(object, ...)

## S3 method for class 'summary.rpql'
print(x,...)

A list (some of which is printed) containing the following elements:

`Call`	The matched call.
`fixed`	Estimated fixed effects coefficients.
`ranef`	A list with each element being a matrix of estimated random effects coefficients.
`ran.cov`	A list with each element being a estimated random effects covariance matrix.
`logLik`	PQL log-likelihood value at convergence.
`family`	The `family` argument, i.e. response type.
`pen.type,lambda`	Penalties used for selection and the corresponding tuning parameter values.
`ics`	A vector containing the number of estimated, non-zero parameters, and three information criterion. Please see the help file for `rpql` for details on these criteria.
`id`	The `id` argument, i.e. list of IDs.
`nonzero.fixef`	A vector indexing which of the estimated fixed effect coefficients are non-zero.
`nonzero.ranef`	A list with each element being a vector indexing which of the estimated random effects are non-zero, i.e. which of the diagonal elements in the corresponding element of `ran.cov` are non-zero.