simulation: Markov Chain Simulation

In SonmezOzan/mc_1.0.3: Markov Chains

Description

Simulates discrete markov chain with state space

Usage

mc.simulation(pijdef, type, N, initial.state,...)

Arguments

pijdef	The transition probabilities, either in matrix form or a function For now only matrix form, until the infinite case is incorporated
type	Type of markov chain, either 'discrete' or 'continuous'.
N	Number of steps of the markov chain being simulated
initial.state	Initial state that the chain will start from
...	Additional argument for continuous markov chain type.

Details

This function will simulate discrete markov chain for a given transition probability matrix, if the initial state is not specified then it will be randomly generated from the state space.

Value

pijdef	The original transition matrix
simulated.states	N Simulated states based on the transition matrix

Author(s)

Teresa Filshtein <[e-mail]>, Ozan Sonmez <[e-mail]>, Rex Cheung <[e-mail]>, and Norm Matloff <[e-mail]>

Examples

t.matrix = t(matrix(c(0.1,0.2,0.7,0.4,0.5,0.1,0,0.4,0.6),3,3))
mc.simulation(t.matrix, "discrete", 100, 1)$simulated.states

SonmezOzan/mc_1.0.3 documentation built on May 9, 2019, 9:57 p.m.