MATLAB File Help: 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

Superclasses	prtAction
Sealed	false
Construct on load	false

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.

	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.