 noise in spatial data sets is said to be spatially autocorrelated, while colored noise in time series is said to be temporally autocorrelated. In this package we only deal with the latter.</p>
<p>Expressed in math, colored noise can be modeled with the following equation, where <span class="math inline">\(\omega\)</span> is a random standard normal variable, and <span class="math inline">\(\epsilon\)</span> is a temporally autocorrelated variable:</p>
<p><span class="math inline">\(\epsilon_{t + 1} = k\eps