NCL Home > Documentation > Functions > Statistics, Extreme values

extval_pareto

Calculates the probability (PDF) and cumulative (CDF) distribution functions of the Pareto distributions (Generalized, Type I, TYpe II) given the shape, scale and location parameters.

Available in version 6.4.0 and later.

Prototype

load "$NCARG_ROOT/lib/ncarg/nclscripts/csm/extval.ncl"

	function extval_pareto (
		x          : numeric,  
		shape  [*] : numeric,  
		scale  [*] : numeric,  
		center [*] : numeric,  
		ptype  [1] : integer,  
		opt    [1] : integer   
	)

	return_val [ variable of type list containing 2 variables [/ PDF, CDF /] 

Arguments

x

A numeric array.

shape

One dimensional array containing the shape parameter(s).

scale

One dimensional array containing the scale parameter(s). Must be the same size as shape.

center

One dimensional array containing the center (aka, location) parameter(s). If ptype=0, it must be the same size as shape. The argument is ignored for ptype=1 or 2.

ptype

An integer which specifies which distribution:

  • ptype=0 means the Generalized Pareto
  • ptype=1 means the Pareto Type I
  • ptype=2 means the Pareto Type II

opt

Currently, not used. Set to zero.

Return value

A variable of type 'list.' The list contains two variables: the PDF and the CDF. See Example(s).

Description

Use the equations associated with the Pareto distribution to derive the associated PDFs and CDFs.

See Also

Extreme Value functions

Examples

Example 1


   N      = 100
   xMin   = 0.05
   xMax   = 5.5
   x      = fspan(xMin,xMax,N)

   shape  = (/0.5, 1.0, 2.0, 3.0, 1.0, 2.0, 3.0/)
   scale  = (/1.0, 1.0, 1.0, 1.0, 2.0, 2.0, 2.0/)
   center = (/0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0/)

; Generate PDF and GDF distribution

   ptype  = 0                              ; Generalized Pareto
   pdfcdf = extval_pareto(x, shape, scale, center, ptype, 0)  ; return a variable of type 'list'
   pdf    = pdfcdf[0]                      ; explicitly extract the 2 returned variables (for convenience only).
   cdf    = pdfcdf[1]
   delete(pdfcdf)       ; not necessary

   printVarSummary(pdf)
   printVarSummary(cdf)

The (edited) ourput is:

   Variable: pdf
   Type: float
   Total Size: 5600 bytes
               1400 values
   Number of Dimensions: 2
   Dimensions and sizes:	[7] x [200]
   Coordinates: 
   Number Of Attributes: 5
     _FillValue :	9.96921e+36
     long_name :	Pareto: Generalized: PDF
     shape :	( 0.5,  1,  2,  3,  1,  2,  3 )
     scale :	(  1,  1,  1,  1,  2,  2,  2 )
     location :	(  0,  0,  0,  0,  0,  0,  0 )
   (0)	 
   (0)	Pareto: Generalized: PDF : min=0.0233236   max=0.863838
   
   Variable: cdf
   Type: float
   Total Size: 5600 bytes
               1400 values
   Number of Dimensions: 2
   Dimensions and sizes:	[7] x [200]
   Coordinates: 
   Number Of Attributes: 5
     _FillValue :	9.96921e+36
     long_name :	Pareto: Generalized: CDF
     shape :	( 0.5,  1,  2,  3,  1,  2,  3 )
     scale :	(  1,  1,  1,  1,  2,  2,  2 )
     location :	(  0,  0,  0,  0,  0,  0,  0 )
   (0)	 
   (0)	Pareto: Generalized: CDF : min=0.0455188   max=0.918367