Markovmoments

The function <code>Markovmoments</code> computes the expectation, variance, autocovariance and autocorrelation of a Markov process.

It computes the solutions to a generic stochastic growth model for a given set of user supplied parameters. It includes
the solutions to the model, plots of the solution,
a summary of the features of the model, a function that covers different types of consumption preferences,
and a function that computes the moments of a Markov process.
Merton, Robert C (1971) <doi:10.1016/0022-0531(71)90038-X>,
Tauchen, George (1986) <doi:10.1016/0165-1765(86)90168-0>,
Wickham, Hadley (2009, ISBN:978-0-387-98140-6 ).

Thomas Vigie

sgmodel

Solves a Generic Stochastic Growth Model with a Representative
Agent

Markovmoments function

<dl><dt>states</dt>
<dd>A numerical vector with the states of the Markov process.</dd>
<dt>ptm</dt>
<dd>The probability transition matrix, a square matrix of dimension length(states) whose columns sum to one.</dd>
<dt>...</dt>
<dd>Additional arguments.</dd></dl>

Arguments

Markovmoments — Markovmoments

<dl>

<dt>states</dt>
<dd>A numerical vector with the states of the Markov process.</dd>


<dt>ptm</dt>
<dd>The probability transition matrix, a square matrix of dimension length(states) whose columns sum to one.</dd>


<dt>...</dt>
<dd>Additional arguments.</dd>

</dl>

Markovmoments: Markovmoments

Description

Usage

Value

Arguments

Examples