# dtmc

Create discrete-time Markov chain

## Description

`dtmc`

creates a discrete-time, finite-state, time-homogeneous Markov chain from a specified state transition matrix.

After creating a `dtmc`

object, you can analyze the structure and
evolution of the Markov chain, and visualize the Markov chain in various ways, by using
the object
functions. Also, you can use a `dtmc`

object to specify the
switching mechanism of a Markov-switching dynamic regression model (`msVAR`

).

To create a switching mechanism, governed by threshold transitions and threshold
variable data, for a threshold-switching dynamic regression model, see `threshold`

and
`tsVAR`

.

## Creation

### Description

creates the discrete-time Markov chain object `mc`

= dtmc(`P`

)`mc`

specified by the state transition matrix `P`

.

optionally associates the names `mc`

= dtmc(`P`

,`'StateNames'`

,stateNames)`stateNames`

to the
states.

### Input Arguments

## Properties

## Object Functions

`dtmc`

objects require a fully specified transition matrix `P`

.

## Examples

## Alternatives

You also can create a Markov chain object using `mcmix`

.

## References

[1]
Gallager, R.G. *Stochastic Processes: Theory for Applications.* Cambridge, UK: Cambridge University Press, 2013.

[2]
Haggstrom, O. *Finite Markov Chains and Algorithmic Applications.* Cambridge, UK: Cambridge University Press, 2002.

[3]
Hamilton, James D. *Time Series Analysis*. Princeton, NJ: Princeton University Press, 1994.

[4]
Norris, J. R. *Markov Chains.* Cambridge, UK: Cambridge University Press, 1997.

**Introduced in R2017b**