SpecGap: Stationary distribution of a matrix and its spectral gap

In IndTestPP: Tests of Independence and Analysis of Dependence Between Point Processes in Time

Description

This function calculates the stationary distribution of the transition matrix of a Markov chain process and its spectral gap.

Usage

SpecGap(P)

Arguments

P	Matrix. It must be a markovian matrix.

Details

The spectral gap of a matrix P measures the convergence speed of P to a matrix P_I with all the rows equal to (π_1,π_2,... π_k), the stationary distribution of P. It takes values in [0,1].

The spectral gap of a transition matrix can be used as a dependence measure between the marginal processes defined by a marked Poisson procces with discrete marks generated by a Markov chain with that transition matrix, see Cebrian et al (2020) for details.

Value

A list with elements

SG	Spectral gap value of the matrix.
pi	Vector of the stationary distribution of the matrix.

References

Cebrian, A.C., Abaurrea, J. and Asin, J. (2020). Testing independence between two point processes in time. Journal of Simulation and Computational Statistics.

See Also

DepNHPPMarked

Examples

P<-cbind(c(0.7, 0.1, 0.2), c(0.2, 0.7, 0.1), c(0.1, 0.2, 0.7))
SpecGap(P)

IndTestPP documentation built on Aug. 29, 2020, 1:06 a.m.