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#+TITLE: LMSCPP

[[https://opensource.org/licenses/MIT][https://img.shields.io/badge/license-MIT-green.svg]]

* Installation

The following instructions will install all executables defined in the folder *models* to the
folder *.local/bin* in your home directory. So it is important to have the folder *~/.local/bin* in your
*PATH* environmental variable. Before proceeding make sure you have the GMP library installed in your system.

#+BEGIN_SRC bash
git clone "https://github.com/thiagotps/lmscpp"
cd lmscpp
cmake -DCMAKE_INSTALL_PREFIX=~/.local -S . -B build
cmake --build build -j n # where 'n' must be replaced by the number of cores in your machine
cmake --install build --component lmscpp
#+END_SRC

This project includes some tests for make sure that everything is working properly.
To run the tests, just execute *ctest -V* inside the /build/ directory.

A good way for learning how to use the library defined in /lib/ is to read /classical.cpp/ or /skewness.cpp/ inside the
/models/ folder. To learn how to use the executables defined by these source files, read the /.sh/ tests in the /scripts/ folder.

As an example, the *skewness* binary has the following options. Other executables can show a similar help message
by passing the /--help/ flag.
#+BEGIN_SRC text
Usage: /home/thiago/.local/bin/skewness [options]

Optional arguments:
-h --help       	show this help message and exit
--readcache     	The cache file to use.
--writecache    	The cache file to write.
-N              	filter length[Required]
-M              	data length[Required]
-b --beta       	β
--sv2 --sigmav2 	variance (σᵥ²)
-n --niter      	Number of iterations.
-o --output     	The file where the output will be stored.
--indmode       	ia or eea[Required]
--outmode       	sk or mse[Required]
-d --dist       	gauss or lap
#+END_SRC

About

The software used to calculate the theoretical and empirical results for the articles about the exact expectation analysis of the LMS adaptive filtering.

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