MATLAB File Help: prtRv
prtRv
  prtRv Base class for all prt random variables
 
    This is an abstract class from which all prt random variables
    inherit. It can not be instantiated. prtRv contains the following 
    properties:
 
    name           - Name of the random variable.
    userData       - Structure for holding additional related to the
                     random variable.
    nDimensions    - Number of dimensions of the vector space
                     represented by the random variable.
 
    The prtRv class has the following methods
 
    plotPdf - Plot the pdf of the random variable
    plotCdf - Plot the cdf of the random variable
 
    The prtRv class has the following methods, most of which are
    overloaded. If a method is not overloaded, it is because it is not
    possible to implement the functionality.
 
    pdf - Output the pdf of the random variable evaluated at the points
          specified
 
    logPdf - Output the log-pdf of the random variable evaluated at the
             points specified (for many distributions, this can be
             calculated more easily than simply log(pdf(R,X))
 
    cdf - Output the cdf of the random variable evaluated at the
          points specified
 
    draw - Draw samples from the random variable
 
    mle - Perform maximum likelihood estimation of the objects parameters 
          using the specified data
See also
Class Details
Superclasses prtAction
Sealed false
Construct on load false
Constructor Summary
prtRv Base class for all prt random variables 
Property Summary
dataSet The training prtDataSet, only stored if verboseStorage is true.  
dataSetSummary Structure that summarizes prtDataSet. 
isCrossValidateValid Indicates whether or not cross-validation is a valid operation 
isSupervised Specifies if the prtAction requires a labeled dataSet 
isTrained Indicates if prtAction object has been trained. 
name Descriptive name of prtAction object. 
nameAbbreviation Shortened name for the prtAction object. 
plotOptions  
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 
  get get the object properties 
  kfolds Perform K-folds cross-validation of prtAction 
  logPdf Output the log pdf of the random variable evaluated at the points specified 
  mle Compute the maximum likelihood estimate  
  optimize Optimize action parameter by exhaustive function maximization. 
  pdf Output the pdf of the random variable evaluated at the points specified 
  plotCdf Plot the cdf of the prtRv 
  plotLogPdf Plot the pdf of the prtRv 
  plotPdf Plot the pdf of the prtRv 
  run Run a prtAction object on a prtDataSet object. 
  set set the object properties 
  train Train a prtAction object using training a prtDataSet object.