multi_rnorm

Generate random numbers from a multivariate normal distribution.
It can be used to create correlated random numbers.

Temporally autocorrelated populations are correlated in their vital rates (growth, death, etc.) from year to year. It is very common for populations, whether they be bacteria, plants, or humans, to be temporally autocorrelated. This poses a challenge for stochastic population modeling, because a temporally correlated population will behave differently from an uncorrelated one.
This package provides tools for simulating populations with white noise (no temporal autocorrelation), red noise (positive temporal autocorrelation), and blue noise (negative temporal autocorrelation). The algebraic formulation for autocorrelated noise comes from Ruokolainen et al. (2009) <doi:10.1016/j.tree.2009.04.009>. Models for unstructured populations and for structured populations (matrix models) are available.

July Pilowsky

colorednoise

Simulate Temporally Autocorrelated Populations

multi_rnorm function

<dl><dt>n</dt>
<dd>The number of samples desired for each variable.</dd>
<dt>mean</dt>
<dd>A vector giving the mean of each variable.</dd>
<dt>sd</dt>
<dd>A valid covariance matrix.</dd></dl>

Arguments

Generate Correlated Normal Random Numbers — multi_rnorm

<dl>

<dt>n</dt>
<dd>The number of samples desired for each variable.</dd>


<dt>mean</dt>
<dd>A vector giving the mean of each variable.</dd>


<dt>sd</dt>
<dd>A valid covariance matrix.</dd>

</dl>

multi_rnorm: Generate Correlated Normal Random Numbers

Description

Usage

Value

Arguments

Examples