# Multimode: An R Package for Mode Assessment

## TL;DR

The paper introduces the R package multimode, which offers various nonparametric tools and graphical methods for assessing the number and location of modes in data, aiding in distribution analysis.

## Contribution

It presents new R package utilities that integrate multiple exploratory and formal testing approaches for multimodality assessment in a user-friendly way.

## Key findings

- Provides graphical tools like SiZer map and mode tree for mode pattern identification.
- Implements formal tests based on critical bandwidth and excess mass methods.
- Includes functions for estimating mode locations with real data examples.

## Abstract

In several applied fields, multimodality assessment is a crucial task as a previous exploratory tool or for determining the suitability of certain distributions. The goal of this paper is to present the utilities of the R package multimode, which collects different exploratory and testing nonparametric approaches for determining the number of modes and their estimated location. Specifically, some graphical tools, allowing for the identification of mode patterns, based on the kernel density estimation are provided (SiZer map, mode tree or mode forest). Several formal testing procedures for determining the number of modes are described in this paper and implemented in the multimode package, including methods based on the ideas of the critical bandwidth, the excess mass or using a combination of both. This package also includes a function for estimating the modes locations and different classical data examples that have been considered in mode testing literature.