rlsm: R package for least squares Monte Carlo

TL;DR

The rlsm package in R implements the least squares Monte Carlo method, enabling users to experiment with various regression tools and compute bounds for the value function in stochastic decision problems.

Contribution

This paper introduces the rlsm package, providing an accessible implementation of least squares Monte Carlo with duality-based bounds for the first time in R.

Findings

Facilitates experimentation with regression tools in Monte Carlo simulations.

Provides bounds for the true value function using duality methods.

Simplifies implementation of least squares Monte Carlo in R.

Abstract

This short paper briefly describes the implementation of the least squares Monte Carlo method in the rlsm package. This package provides users with an easy manner to experiment with the large amount of R regression tools on any regression basis and reward functions. This package also computes lower and upper bounds for the true value function via duality methods.