dd_ML_est: Optimize GAM Model Parameters with Fixed betaP

In franciscorichter/emphasis: Evolutionary Modeling on Phylogenetic Applications with Simulations and Importance Sampling

Optimize GAM Model Parameters with Fixed betaP

Description

This function optimizes the parameters of a given Generalized Additive Model (GAM) with the constraint that betaP is fixed at zero. It applies penalties to discourage selecting parameter values near the boundaries of their respective intervals, aiming to find optimal values of mu, lambda, and betaN that minimize the estimated log likelihood.

Usage

dd_ML_est(pgam)

Arguments

pgam	A GAM model object for which the log likelihood is to be optimized. The model should include mu, lambda, betaN, and betaP as parameters.

Value

A list containing the optimized parameter values (pars) and the minimized log likelihood value (ml).

Examples

# Assuming you have a GAM model 'pgam' fitted with parameters including mu, lambda, betaN, betaP
result <- dd_ML_est(pgam)
print(result$pars)  # Optimized parameters
print(result$ml)    # Minimized log likelihood

franciscorichter/emphasis documentation built on Feb. 19, 2024, 7:36 p.m.