MATLAB File Help: prtRvMultinomial
prtRvMultinomial
  prtRvMultinomial  Multinomial random variable
 
    RV = prtRvMultinomial creates a prtRvMultinomial object
    with an unknown number of categories with unspecified probabilities
    These properties can be set manually or by using the MLE method.
 
    prtRvMultinomial operates on count matrices. Therfore, the DRAW()
    method outputs a matrix that is N x nCategories and has a single 1
    in each row. To draw integer categories you can use the
    DRAWINTEGER() method.  Similarly, the MLE function takes a count
    matrix as an input. Type help prtRvMultinomial.mle for more
    information.
 
    RV = prtRvMultinomial(PROPERTY1, VALUE1,...) creates a
    prtRvMultinomial object RV with properties as specified by 
    PROPERTY/VALUE pairs.
 
    A prtRvMultinomial object inherits all properties from the
    prtRv class. In addition, it has the following properties:
 
    nCategories   - number of integers modeled by the RV
    probabilities - A 1 x nCategories vector of doubles less than 1
                    that sum to 1, representing the probability of
                    each of the integers
    
   A prtRvMultinomial object inherits all methods from the prtRv
   class. The MLE  method can be used to set the parameters from data.
   In addition, it has the the following methods:
    
    x = R.drawIntegers(N) - Draws N integers with the corresponding
                            probabilities
 
   Example:
   
   data = rand(100,5);                  % Uniformly random data
   X = bsxfun(@eq,data,max(data,[],2)); % Generate data that has a 
                                        % single 1 in each row
 
   RV = prtRvMultinomial;               % Generate a prtRvMultinomial
   RV = mle(RV,X);                      % Estimate the parameters
 
   RV.plotPdf()                         % Plot the pdf (pmf)
See also
Class Details
Superclasses prtRv, prtRvMemebershipModel
Sealed false
Construct on load false
Constructor Summary
prtRvMultinomial Multinomial random variable 
Property Summary
dataSet The training prtDataSet, only stored if verboseStorage is true.  
dataSetSummary Structure that summarizes prtDataSet. 
isCrossValidateValid  
isSupervised  
isTrained Indicates if prtAction object has been trained. 
nCategories The number of categories 
name  
nameAbbreviation  
plotOptions  
probabilities  
showProgressBar  
userData User specified data 
verboseStorage Specifies whether or not to store the training prtDataset. 
Method Summary
  cdf Output the cdf of the random variable evaluated at the points specified 
  crossValidate Cross validate prtAction using prtDataSet and cross validation keys. 
  draw Draw random samples from the distribution described by the prtRv object 
  drawIntegers DRAW Draw random integer samples from the distribution described by the prtRv object 
  get get the object properties 
  initializeMixtureMembership  
  kfolds Perform K-folds cross-validation of prtAction 
  logPdf Output the log pdf of the random variable evaluated at the points specified 
  mle RV = RV.mle(X) computes the maximum likelihood estimate based 
  optimize Optimize action parameter by exhaustive function maximization. 
  pdf Output the pdf of the random variable evaluated at the points specified 
  plotCdf Not implemented for this prtRv 
  plotLogPdf Plot the pdf of the prtRv 
  plotPdf Plot the pdf of the RV 
  run Run a prtAction object on a prtDataSet object. 
  set set the object properties 
  train Train a prtAction object using training a prtDataSet object.