title: Random generation of a finite Gaussian Markov Chain
body: <p>Everything that I want to do is done through this code</p>
  <pre><code>sd = 1
  v = c(0)
  
  for (i in 1:10) {
    rnorm(1,v[i],sd) -&gt; v[i+1]
  }
  v
  </code></pre>
  <p>But I want to build confidence on Markov Chains, starting through chain generation. There are many packages in <code>R</code> dealing with discrete Markov Chains generation, but ideally I would like a function like this:</p>
  <p>PSEUDOCODE:</p>
  <p><code>rGaussMC(n = 10, start_value = 0, sd = 1)</code></p>
  <p>I am open to suggestions for packages, and I am interested in knowing strengths and cool features of those packages.</p>
  <p>I would be interested in one package that collects RNG functions for many processes, not only Gaussian.</p>