Maximum Pseudolikelihood Estimation for an Ordinal Markov Random Field Model

The function mple estimates the parameters for the ordinal MRF by optimizing the joint pseudolikelihood with the Newton-Raphson method.

Usage

mple(
  x,
  convergence_criterion = sqrt(.Machine$double.eps),
  maximum_iterations = 1000,
  thresholds,
  interactions
)

x: A dataframe or matrix with n rows and p columns, containing binary and ordinal variables for n independent observations and p variables in the network. Variables are recoded as non-negative integers (0, 1, ..., m) if not done already. Unobserved categories are collapsed into other categories after recoding. See reformat_data for details.
convergence_criterion: The convergence criterion for the pseudoposterior values in the EM algorithm. Defaults to sqrt(.Machine$double.eps).
maximum_iterations: The maximum number of EM iterations used. Defaults to 1e3. A warning is issued if the procedure has not converged in maximum_iterations iterations.
thresholds: A matrix with p rows and max(m) columns, containing the category thresholds for each node. Used as starting values in the Newton-Raphson procedure. Optional.
interactions: A matrix with p rows and p columns, containing the pairwise association estimates in the off-diagonal elements. Used as starting values in the Newton-Raphson procedure. Optional.

A list containing:

interactions: A matrix with p rows and p columns, containing the maximum pseudolikelihood estimates of the pairwise associations in the off-diagonal elements.
thresholds: A matrix with p rows and max(m) columns, containing the maximum pseudolikelihood estimates of the category thresholds for each node.