print.sdreport

Print parameter estimates and give convergence diagnostic based on
gradient and Hessian.

With this tool, a user should be able to quickly implement
complex random effect models through simple C++ templates. The package combines
'CppAD' (C++ automatic differentiation), 'Eigen' (templated matrix-vector
library) and 'CHOLMOD' (sparse matrix routines available from R) to obtain
an efficient implementation of the applied Laplace approximation with exact
derivatives. Key features are: Automatic sparseness detection, parallelism
through 'BLAS' and parallel user templates.

Kasper Kristensen

Template Model Builder: A General Random Effect Tool Inspired by
'ADMB'

Brad Bell

Hans Skaug

Arni Magnusson

Casper Berg

Anders Nielsen

Martin Maechler

Theo Michelot

Mollie Brooks

Alex Forrence

Christoffer Moesgaard Albertsen

Cole Monnahan

print.sdreport function

<dl><dt>x</dt>
<dd>Output from <code>sdreport</code></dd>
<dt>...</dt>
<dd>Not used</dd></dl>

Arguments

Print brief model summary — print.sdreport

<dl>

<dt>x</dt>
<dd>Output from <code>sdreport</code></dd>


<dt>...</dt>
<dd>Not used</dd>

</dl>

Print brief model summary

print.sdreport: Print brief model summary

Description

Usage

Arguments