This method returns the stationary vector in matricial form of a markovchain object.

steadyStates(object)

Arguments

object

A discrete markovchain object

Value

A matrix corresponding to the stationary states

Note

The steady states are identified starting from which eigenvectors correspond to identity eigenvalues and then normalizing them to sum up to unity. When negative values are found in the matrix, the eigenvalues extraction is performed on the recurrent classes submatrix.

References

A First Course in Probability (8th Edition), Sheldon Ross, Prentice Hall 2010

See also

Author

Giorgio Spedicato

Examples

statesNames <- c("a", "b", "c")
markovB <- new("markovchain", states = statesNames, transitionMatrix =
                matrix(c(0.2, 0.5, 0.3, 0, 1, 0, 0.1, 0.8, 0.1), nrow = 3,
                byrow = TRUE, dimnames=list(statesNames,statesNames)),
               name = "A markovchain Object" 
)       
steadyStates(markovB)
#>      a b c
#> [1,] 0 1 0