Map_probKt

All Implemented Interfaces:


public final class Map_probKt

Nested Class Summary

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Field Summary

Fields
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Constructor Summary

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Enum Constant Summary

Enum Constants
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Method Summary

Modifier and Type	Method	Description
`final static Matrix`	`map_prob(MatrixCell MAP)`	Computes the equilibrium distribution of the underlying continuous-time Markov chain for a MAP.
`final static Matrix`	`map_prob(Matrix D0, Matrix D1)`	Computes the equilibrium distribution of the underlying continuous-time Markov chain for a MAP.

Methods inherited from class java.lang.Object
clone, equals, finalize, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait

- Constructor Detail
- Method Detail
  - map_prob
```
 final static Matrix map_prob(MatrixCell MAP)
```
    Computes the equilibrium distribution of the underlying continuous-time Markov chain for a MAP.
    This function calculates the steady-state probabilities of the continuous-time Markov chain underlying a Markovian Arrival Process (MAP). The equilibrium distribution is computed by solving the system Q*π = 0, where Q = D0 + D1 is the infinitesimal generator matrix.
    
    Parameters:
    
    MAP - The Markovian Arrival Process stored in a MatrixCell, containing the (D0, D1) matrices
    
    Returns:
    
    The equilibrium distribution as a Matrix (row vector)
  - map_prob
```
 final static Matrix map_prob(Matrix D0, Matrix D1)
```
    Computes the equilibrium distribution of the underlying continuous-time Markov chain for a MAP.
    This function calculates the steady-state probabilities of the continuous-time Markov chain underlying a Markovian Arrival Process (MAP) given the D0 and D1 matrices directly.
    
    Parameters:
    
    D0 - The hidden transition matrix of the MAP
    
    D1 - The visible transition matrix of the MAP
    
    Returns:
    
    The equilibrium distribution as a Matrix (row vector)