ordregr.object {ordgam} | R Documentation |
Object resulting from the fit of a proportional odds model using 'ordregr'
Description
An object returned by the ordregr
function: this is a list
with various components related to the fit of such a model.
Value
A ordregr
object is a list with following elements:
val
:
Value of the log-posterior at convergence.val.start
:
Value of the log-posterior at the start of the Newton-Raphson (N-R) algorithm.theta
:
(Penalized) MLE or MAP of the regression coefficients.grad
:
Gradient of the log-posterior attheta
.Hessian
:
Hessian of the log-posterior attheta
.iter
:
Number of iterations of the N-R algorithm.Hessian0
:
Hessian of the (non-penalized) log-likelihood attheta
.Sigma.theta
:
Variance-covariance of 'theta'.ED.full
:
Effective degrees of freedom associated to each regression parameter, penalized parameters included.se.theta
:
Standard errors of the regression coefficents.theta.mat
:
Matrix containing the point estimate, standard error, credible interval, Z-score and P-value fortheta
.nc
:
Number of categories for the ordinal response.nalpha
:
Number of intercepts in the proportional odds model (=nc
-1) .nbeta
:
Number of regression parameters (intercepts excluded).nfixed
:
Number of non-penalized regression parameters.ci.level
:
Nominal coverage of the credible intervals (Default: .95).n
:
Sample size.call
:
Function call.descending
:
Logical indicating if the odds of the response taking a value in the upper scale should be preferred over values in the lower scale.use.prior
:
Logical indicating if a prior (such as a penalty) is assumed for the regression parameters.lpost
:
Value of the log-posterior at convergence.levidence
:
Log of the marginal likelihood (also named 'evidence').
Author(s)
Philippe Lambert p.lambert@uliege.be
References
Lambert, P. and Gressani, 0. (2023) Penalty parameter selection and asymmetry corrections to Laplace approximations in Bayesian P-splines models. Statistical Modelling. <doi:10.1177/1471082X231181173>. Preprint: <arXiv:2210.01668>.