# API for probabilities.monte-carlo - clojure-contribv1.1 (stable)

Full namespace name: clojure.contrib.probabilities.monte-carlo

## Overview

```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.```

## discrete

function
```Usage: (discrete dist)
```
```A discrete distribution, defined by a map dist mapping values
to probabilities. The sum of probabilities must be one.```
Source

## exponential

function
```Usage: (exponential lambda)
```
```Transform a sequence of uniform random numbers in the interval [0, 1)
into a sequence of exponential random numbers with parameter lambda.```
Source

## lognormal

function
```Usage: (lognormal mu sigma)
```
```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.```
Source

## n-sphere

function
```Usage: (n-sphere n r)
```
```Return a uniform distribution of n-dimensional vectors inside an
Source

## normal

function
```Usage: (normal mu sigma)
```
```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.```
Source

## normal-box-muller

function
```Usage: (normal-box-muller mu sigma)
```
```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.```
Source

## random-stream

function
```Usage: (random-stream distribution random-stream-state)
```
```Define a random stream by a distribution and the state of a
random number stream with uniform distribution in [0, 1).```
Source

## reject

function
```Usage: (reject p dist)
```
```Return the distribution that results from rejecting the values from
dist that do not satisfy predicate p.```
Source

## sample

function
```Usage: (sample n dist)
```
```Return the distribution of samples of length n from the
distribution dist```
Source

## sample-mean

function
```Usage: (sample-mean n dist)
```
```Return the distribution of the mean over n samples from the
distribution dist```
Source

## sample-mean-variance

function
```Usage: (sample-mean-variance n dist)
```
```Return the distribution of the mean-and-variance (a vector containing
the mean and the variance) over n samples from the distribution dist```
Source

## sample-reduce

function
```Usage: (sample-reduce f n dist)
(sample-reduce f val n dist)
```
```Returns the distribution of the reduction of f over n samples from the
distribution dist.```
Source

## sample-sum

function
```Usage: (sample-sum n dist)
```
```Return the distribution of the sum over n samples from the
distribution dist.```
Source
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