Difference between revisions of "Multinomial"

Revision as of 18:40, 23 February 2016

Multinomial(N, theta, I)

Returns the Multinomial Distribution.

The multinomial distribution is a generalization of the Binomial distribution to «N» possible outcomes. For example, if you were to roll a fair die «N» times, an outcome would be the number of times each of the six numbers appears. Theta would be the probability of each outcome, where Sum(theta, I) = 1, and index «I» is the list of possible outcome. If «theta» doesn't sum to 1, it is normalized.

Each sample is a vector indexed by «I» indicating the number of times the corresponding outcome (die number) occurred during that sample point. Each sample will have the property that Sum(result, I) = N.

Syntax:

Multinomial(N, theta: postiive; I: Index)

Library

Multivariate Distributions.ana

@@ Line 1: / Line 1: @@
-[[category:Multivariate Distribution Functions]]
+[[Category: Multivariate Distribution Functions]]
-[[Category:Doc Status C]] <!-- For Lumina use, do not change -->
+[[Category: Multivariate Distributions library functions]]
+[[Category: Doc Status C]] <!-- For Lumina use, do not change -->
-= Multinomial( N,theta : postiive ; I : Index ) =
+== Multinomial(N, theta, I) ==
 Returns the Multinomial Distribution.
-The multinomial distribution is a generalization of the [[Binomial]] distribution to N possible outcomes.  For example, if you were to roll a fair die N times, an outcome would be the number of times each of the six numbers appears.  Theta would be the probability of each outcome, where [[Sum]](theta,I)=1, and index I is the list of possible outcome.  If theta doesn't sum to 1, it is normalized.
+The multinomial distribution is a generalization of the [[Binomial]] distribution to «N» possible outcomes.  For example, if you were to roll a fair die «N» times, an outcome would be the number of times each of the six numbers appears.  Theta would be the probability of each outcome, where <code>Sum(theta, I) = 1</code>, and index «I» is the list of possible outcome.  If «theta» doesn't sum to 1, it is normalized.
-Each sample is a vector indexed by I indicating the number of times the corresponding outcome (die number) occurred during that sample point.  Each sample will have the property that [[Sum]]( result, I ) = N.
+Each sample is a vector indexed by «I» indicating the number of times the corresponding outcome (die number) occurred during that sample point.  Each sample will have the property that <code>Sum(result, I) = N</code>.
-= Library =
+[[Syntax]]:
+:[[Multinomial]](N, theta: postiive; I: Index)
+== Library ==
 Multivariate Distributions.ana
-= See Also =
+== See Also ==
 * [[Binomial]]
+* [[Sum]]
+* [[Multivariate distributions]]