amps


This function finds the peaks and antimodes by way of 
distribution density estimation. It may be convenient to think
of this function as finding the global and local maxima and
the local minima of a data vector. Note that the global minimum
is asymptotically zero ("0")from based on distribution theory;
for practical purposes, double checking the global minimum is 
good practice. Just run ("min(x))")


mode

Amplitude

Antimode

Peak

Designed with a dual purpose of
accurately estimating the mode (or modes) as well as characterizing
the modality of data. The specific application area includes complex
or mixture distributions particularly in a big data environment.
The heterogeneous nature of (big) data may require deep introspective
statistical and machine learning techniques, but these statistical tools
often fail when applied without first understanding the data. In small
datasets, this often isn't a big issue, but when dealing with large scale
data analysis or big data thoroughly inspecting each dimension
typically yields an O(n^n-1) problem. As such, dealing with big data
require an alternative toolkit. This package not only identifies the
mode or modes for various data types, it also provides a programmatic
way of understanding the modality (i.e. unimodal, bimodal, etc.) of
a dataset (whether it's big data or not). See
<http://www.sdeevi.com/modes_package> for examples and discussion.

Sathish Deevi

modes

Find the Modes and Assess the Modality of Complex and Mixture
Distributions, Especially with Big Datasets

amps function

A helper function to find the amplitudes by finding the
peaks and antimodes of a data vector.

amps: A helper function to find the amplitudes by finding the peaks and antimodes of a data vector.

Description

Usage

Arguments

Examples