markovneat library

markov chains in java

License	The Apache License, Version 2.0
Categories	Net
GroupId	net.andreinc
ArtifactId	markovneat
Last Version	1.8
Release Date	Feb 9, 2021
Type	jar
Description	markovneat library markov chains in java
Project URL	https://github.com/nomemory/markovneat
Source Code Management	https://github.com/nomemory/markovneat

Download markovneat

Filename	Size
markovneat-1.8.pom
markovneat-1.8.jar	9 KB
markovneat-1.8-sources.jar	5 KB
markovneat-1.8-javadoc.jar	392 KB

How to add to project

Apache Maven

<!-- https://jarcasting.com/artifacts/net.andreinc/markovneat/ -->
<dependency>
    <groupId>net.andreinc</groupId>
    <artifactId>markovneat</artifactId>
    <version>1.8</version>
</dependency>

Gradle Groovy

// https://jarcasting.com/artifacts/net.andreinc/markovneat/
implementation 'net.andreinc:markovneat:1.8'

Gradle Kotlin

// https://jarcasting.com/artifacts/net.andreinc/markovneat/
implementation ("net.andreinc:markovneat:1.8")

Apache Buildr

'net.andreinc:markovneat:jar:1.8'

Apache Ivy

<dependency org="net.andreinc" name="markovneat" rev="1.8">
  <artifact name="markovneat" type="jar" />
</dependency>

Groovy Grape

@Grapes(
@Grab(group='net.andreinc', module='markovneat', version='1.8')
)

Scala SBT

libraryDependencies += "net.andreinc" % "markovneat" % "1.8"

Leiningen

[net.andreinc/markovneat "1.8"]

Dependencies

test (1)

Group / Artifact	Type	Version
junit : junit	jar	4.13.1

Project Modules

There are no modules declared in this project.

Markov chains in Java.

Installing

Maven:

<dependency>
  <groupId>net.andreinc</groupId>
  <artifactId>markovneat</artifactId>
  <version>1.8</version>
</dependency>

Gradle:

implementation 'net.andreinc:markovneat:1.8'

You can also create a "fat" jar using the shadowJar gradle tasks:

gradle shadowJar

The jar will be generated in /build/libs/markovneat*.jar.

Example 1 - Modelling a simple discrete-time markov chain

A directed graph is used bellow to picture the state transitions for a Markov Chain.

The states represent whether a hypothetical stock market is exhibiting a bull market, bear market, or stagnant market trend during a given week.

(See Market trends).

With the markovneat library this can be modelled using the following code:

 MChain<String> marketMChain = new MChain<>();

// Transitioning from "BULL" to "BULL" has a 90% chance
marketMChain.add(new MState<>("BULL"), "BULL", 0.9);
// Transitioning from "BULL" to "BEAR" has a 7,5% chance
marketMChain.add(new MState<>("BULL"), "BEAR", 0.075);
// Transitioning from "BULL" to "STAGNANT" has a 2,5% chance
marketMChain.add(new MState<>("BULL"), "STAGNANT", 0.025);

marketMChain.add(new MState<>("BEAR"), "BEAR", 0.8);
marketMChain.add(new MState<>("BEAR"), "BULL", 0.15);
marketMChain.add(new MState<>("BEAR"), "STAGNANT", 0.05);

marketMChain.add(new MState<>("STAGNANT"), "STAGNANT", 0.5);
marketMChain.add(new MState<>("STAGNANT"), "BULL", 0.25);
marketMChain.add(new MState<>("STAGNANT"), "BEAR", 0.25);

marketMChain.generate(10000).forEach(System.out::println);

Output:

STAGNANT
BULL
BULL
BULL
BULL
... and so on

Versions

Version
1.8 Feb 9, 2021