sim_markov_forward: Simulate Markov chain.

Description Usage Arguments Value See Also Examples

Description

sim_markov_forward returns a simulated realisation of a Markov chain given known start point.

Usage

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sim_markov_forward(num_states, fixed_values, behav_params)

Arguments

num_states

Numeric, number of (behavioural) states in the Markov chain.

fixed_values

List with components:

inc_times

Vector of length two, start and end times of the simulation.

inc_behav

Vector of length one, start known value (behaviour) of the simulation.

behav_params

List with components:

lambda

Vector of length num_states, switching rates out of each state.

q

Sqaure matrix size num_states, probability of switching from (row) each state to (column) another. Diagonal elements are NA.

Value

List with the components:

times

Vector, switching times of the simulation. Includes the fixed end points.

states

Vector, states at switching times of the simulation. Includes the fixed end points.

See Also

Other Markov chain simulations: calc_markov_steady_state, sim_markov_backward, sim_markov_bridge

Examples

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end_points <- list(inc_times = c(0,10),
                   inc_behav = c(3))
param <- list(lambda = c(0.1,0.2,0.3),
              q = matrix(c(NA,0.5,0.3,0.35,NA,0.7,0.65,0.5,NA),nrow=3))

set.seed(123)
sim_markov_forward(3, end_points, param)
# $times
# [1]  0.000000  2.811524 10.000000
#
# $states
# [1] 3 1 1

set.seed(2712)
sim_markov_forward(3, end_points, param)
# $times
# [1]  0.000000  1.898085  3.603405  4.275325 10.000000
#
# $states
# [1] 3 2 1 3 3

a-parton/CTStepTurn documentation built on May 14, 2019, 4:17 p.m.