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<h1 class="nopad">Table of Contents</h1>
<div style="margin-left: 1em;" class="toc-section">
<a href="#toc0">Overview</a>
<div style="margin-left: 1em;" class="toc-entry">
<a href="#clojure.contrib.probabilities.monte-carlo/discrete">discrete</a>
</div><div style="margin-left: 1em;" class="toc-entry">
<a href="#clojure.contrib.probabilities.monte-carlo/exponential">exponential</a>
</div><div style="margin-left: 1em;" class="toc-entry">
<a href="#clojure.contrib.probabilities.monte-carlo/lognormal">lognormal</a>
</div><div style="margin-left: 1em;" class="toc-entry">
<a href="#clojure.contrib.probabilities.monte-carlo/n-sphere">n-sphere</a>
</div><div style="margin-left: 1em;" class="toc-entry">
<a href="#clojure.contrib.probabilities.monte-carlo/normal">normal</a>
</div><div style="margin-left: 1em;" class="toc-entry">
<a href="#clojure.contrib.probabilities.monte-carlo/normal-box-muller">normal-box-muller</a>
</div><div style="margin-left: 1em;" class="toc-entry">
<a href="#clojure.contrib.probabilities.monte-carlo/random-stream">random-stream</a>
</div><div style="margin-left: 1em;" class="toc-entry">
<a href="#clojure.contrib.probabilities.monte-carlo/reject">reject</a>
</div><div style="margin-left: 1em;" class="toc-entry">
<a href="#clojure.contrib.probabilities.monte-carlo/sample">sample</a>
</div><div style="margin-left: 1em;" class="toc-entry">
<a href="#clojure.contrib.probabilities.monte-carlo/sample-mean">sample-mean</a>
</div><div style="margin-left: 1em;" class="toc-entry">
<a href="#clojure.contrib.probabilities.monte-carlo/sample-mean-variance">sample-mean-variance</a>
</div><div style="margin-left: 1em;" class="toc-entry">
<a href="#clojure.contrib.probabilities.monte-carlo/sample-reduce">sample-reduce</a>
</div><div style="margin-left: 1em;" class="toc-entry">
<a href="#clojure.contrib.probabilities.monte-carlo/sample-sum">sample-sum</a>
</div>
<br />
</div>
</div>
</div>
<div id="content-tag"><h1 id="overview">API for <span id="namespace-name">probabilities.monte-carlo</span>
<span id="branch-name">(master branch)</span></h1>
by <span id="author">Konrad Hinsen</span><br />
<br />Usage:
<pre>
(ns your-namespace
(:require <span id="long-name">clojure.contrib.probabilities.monte-carlo</span>))
</pre><pre>
</pre><h2>Overview</h2>
<pre id="namespace-docstr">Monte-Carlo method support
Monte-Carlo methods transform an input random number stream
(usually having a continuous uniform distribution in the
interval [0, 1)) into a random number stream whose distribution
satisfies certain conditions (usually the expectation value
is equal to some desired quantity). They are thus
transformations from one probability distribution to another one.
This library represents a Monte-Carlo method by a function that
takes as input the state of a random number stream with
uniform distribution (see
clojure.contrib.probabilities.random-numbers) and returns a
vector containing one sample value of the desired output
distribution and the final state of the input random number
stream. Such functions are state monad values and can be
composed using operations defined in clojure.contrib.monads.</pre>
<br />
<h2>Public Variables and Functions</h2>
<div id="var-entry">
<br />
<hr />
<h2 id="clojure.contrib.probabilities.monte-carlo/discrete">discrete</h2>
<span id="var-type">function</span><br />
<pre id="var-usage">Usage: (discrete dist)
</pre>
<pre id="var-docstr">A discrete distribution, defined by a map dist mapping values
to probabilities. The sum of probabilities must be one.</pre>
</div><div id="var-entry">
<br />
<hr />
<h2 id="clojure.contrib.probabilities.monte-carlo/exponential">exponential</h2>
<span id="var-type">function</span><br />
<pre id="var-usage">Usage: (exponential lambda)
</pre>
<pre id="var-docstr">Transform a sequence of uniform random numbers in the interval [0, 1)
into a sequence of exponential random numbers with parameter lambda.</pre>
</div><div id="var-entry">
<br />
<hr />
<h2 id="clojure.contrib.probabilities.monte-carlo/lognormal">lognormal</h2>
<span id="var-type">function</span><br />
<pre id="var-usage">Usage: (lognormal mu sigma)
</pre>
<pre id="var-docstr">Transform a sequence of uniform random numbesr in the interval [0, 1)
into a sequence of lognormal random numbers with mean mu and standard
deviation sigma.</pre>
</div><div id="var-entry">
<br />
<hr />
<h2 id="clojure.contrib.probabilities.monte-carlo/n-sphere">n-sphere</h2>
<span id="var-type">function</span><br />
<pre id="var-usage">Usage: (n-sphere n r)
</pre>
<pre id="var-docstr">Return a uniform distribution of n-dimensional vectors inside an
n-sphere of radius r.</pre>
</div><div id="var-entry">
<br />
<hr />
<h2 id="clojure.contrib.probabilities.monte-carlo/normal">normal</h2>
<span id="var-type">function</span><br />
<pre id="var-usage">Usage: (normal mu sigma)
</pre>
<pre id="var-docstr">Transform a sequence urs of uniform random number in the interval [0, 1)
into a sequence of normal random numbers with mean mu and standard
deviation sigma.</pre>
</div><div id="var-entry">
<br />
<hr />
<h2 id="clojure.contrib.probabilities.monte-carlo/normal-box-muller">normal-box-muller</h2>
<span id="var-type">function</span><br />
<pre id="var-usage">Usage: (normal-box-muller mu sigma)
</pre>
<pre id="var-docstr">Transform a sequence of uniform random numbers in the interval [0, 1)
into a sequence of normal random numbers with mean mu and standard
deviation sigma.</pre>
</div><div id="var-entry">
<br />
<hr />
<h2 id="clojure.contrib.probabilities.monte-carlo/random-stream">random-stream</h2>
<span id="var-type">function</span><br />
<pre id="var-usage">Usage: (random-stream distribution random-stream-state)
</pre>
<pre id="var-docstr">Define a random stream by a distribution and the state of a
random number stream with uniform distribution in [0, 1).</pre>
</div><div id="var-entry">
<br />
<hr />
<h2 id="clojure.contrib.probabilities.monte-carlo/reject">reject</h2>
<span id="var-type">function</span><br />
<pre id="var-usage">Usage: (reject p dist)
</pre>
<pre id="var-docstr">Return the distribution that results from rejecting the values from
dist that do not satisfy predicate p.</pre>
</div><div id="var-entry">
<br />
<hr />
<h2 id="clojure.contrib.probabilities.monte-carlo/sample">sample</h2>
<span id="var-type">function</span><br />
<pre id="var-usage">Usage: (sample n dist)
</pre>
<pre id="var-docstr">Return the distribution of samples of length n from the
distribution dist</pre>
</div><div id="var-entry">
<br />
<hr />
<h2 id="clojure.contrib.probabilities.monte-carlo/sample-mean">sample-mean</h2>
<span id="var-type">function</span><br />
<pre id="var-usage">Usage: (sample-mean n dist)
</pre>
<pre id="var-docstr">Return the distribution of the mean over n samples from the
distribution dist</pre>
</div><div id="var-entry">
<br />
<hr />
<h2 id="clojure.contrib.probabilities.monte-carlo/sample-mean-variance">sample-mean-variance</h2>
<span id="var-type">function</span><br />
<pre id="var-usage">Usage: (sample-mean-variance n dist)
</pre>
<pre id="var-docstr">Return the distribution of the mean-and-variance (a vector containing
the mean and the variance) over n samples from the distribution dist</pre>
</div><div id="var-entry">
<br />
<hr />
<h2 id="clojure.contrib.probabilities.monte-carlo/sample-reduce">sample-reduce</h2>
<span id="var-type">function</span><br />
<pre id="var-usage">Usage: (sample-reduce f n dist)
(sample-reduce f val n dist)
</pre>
<pre id="var-docstr">Returns the distribution of the reduction of f over n samples from the
distribution dist.</pre>
</div><div id="var-entry">
<br />
<hr />
<h2 id="clojure.contrib.probabilities.monte-carlo/sample-sum">sample-sum</h2>
<span id="var-type">function</span><br />
<pre id="var-usage">Usage: (sample-sum n dist)
</pre>
<pre id="var-docstr">Return the distribution of the sum over n samples from the
distribution dist.</pre>
</div>
</div>
</div>
</div>
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