PD
= ProbDistUnivKernel(X
)PD
= ProbDistUnivKernel(X
, param1
, val1
, param2
, val2
,
...)
creates PD
= ProbDistUnivKernel(X
)PD
,
a ProbDistUnivKernel object, which represents a nonparametric probability
distribution, based on a normal kernel smoothing function.
specifies optional parameter name/value pairs, as
described in the Parameter/Values table. Parameter and value names
are case insensitive. PD
= ProbDistUnivKernel(X
, param1
, val1
, param2
, val2
,
...)
ProbDistUnivKernel
will be removed in a future
release. To create and fit probability distribution objects, use makedist
and fitdist
instead.
X  A column vector of data.

Parameter  Values  

'censoring'  A Boolean vector the same size as
 
'frequency'  A vector the same size as
 
'kernel'  A string specifying the type of kernel smoother to use. Choices are:
 
'support'  Any of the following to specify the support:
 
'width'  A value specifying the bandwidth of the kernel smoothing window. The default is optimal for estimating normal densities, but you may want to choose a smaller value to reveal features such as multiple modes. 
PD  An object in the 
[1] Bowman, A. W., and A. Azzalini. Applied Smoothing Techniques for Data Analysis. New York: Oxford University Press, 1997.