sample_path: Sample path from the distribution of an endpoint-conditioned...

In ECctmc: Simulation from Endpoint-Conditioned Continuous Time Markov Chains

Description

Sample path from the distribution of an endpoint-conditioned CTMC.

Usage

sample_path(a, b, t0, t1, Q, method = "mr", npaths = 1, eigen_vals = NULL,
  eigen_vecs = NULL, inverse_vecs = NULL, P = NULL)

Arguments

a, b	States at the left and right endpoints of the interval, given as row numbers of the CTMC rate matrix
t0, t1	Times for the left and right endpoints of the interval.
Q	CTMC rate matrix.
method	Either "mr" corresponding to modified rejection sampling, or "unif" for uniformization.
npaths	optional argument for the number of sample paths to simulate.
eigen_vals	optional vector of eigen values of Q (assumes all eigen values are real).
eigen_vecs	optional matrix of eigen vectors of Q.
inverse_vecs	optional inverse of the eigen vector matrix.
P	optional transition probability matrix over the interval

Value

sample_path returns either a matrix with a sample path or a list of matrices of sample paths.

Examples

sample_path(1, 2, 0, 5, matrix(c(-0.49, 0.49, 0.51, -0.51), nrow = 2, byrow = TRUE))

ECctmc documentation built on May 2, 2019, 6:48 a.m.