v0.1.0 - Initial Release

numerical.mle v0.1.0

Initial release of the numerical.mle R package for numerical maximum likelihood estimation.

Features

Configuration System

• mle_config() - Base configuration for convergence criteria
• mle_config_gradient() - Gradient descent with fixed learning rate
• mle_config_linesearch() - Adaptive step size via backtracking line search
• mle_constraint() - Domain constraints with support checking and projection

Core Solvers

• mle_gradient_ascent() - First-order gradient-based optimization
• mle_newton_raphson() - Second-order optimization using Fisher information

Meta-Solvers

• mle_grid_search() - Exhaustive grid search over parameter space
• mle_random_restart() - Multiple random initializations for global optimization

Function Transformers

• with_subsampling() - Stochastic gradient ascent via mini-batching
• with_penalty() - Regularization with L1, L2, or elastic net penalties

Convenience Wrappers

• mle_grad() - Quick gradient ascent with sensible defaults
• mle_nr() - Quick Newton-Raphson with sensible defaults
• with_constraint() - Apply constraints to any solver

Installation

# Install from GitHub
devtools::install_github("queelius/numerical.mle")

Documentation

Full documentation available at: https://queelius.github.io/numerical.mle/