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extval_mlegev

Estimates the shape, scale and location parameters for the Generalized Extreme-Value (GEV) distribution using Maximum-Likelihood Estimation (MLE).

Available in version 6.4.0 and later.

Prototype

	function extval_mlegev (
		x        : numeric,  
		dims [*] : integer,  
		opt  [1] : logical   
	)

	return_val  :  float or double

Arguments

A variable of numeric type and any dimensionality. Most commonly, x(N), x(N,J) or x(N,J,I)

dims

The dimension(s) of x on which to calculate the MLE of shape, scale and location. Must be consecutive and monotonically increasing. Usually, dims=0 (corresponding to 'N').

opt

Not used. Set to False.

Return value

The output will be double if x is double and float otherwise.

The output dimensions will be based on x's dimensions, with the 'N' dimensions removed and a rightmost dimension of size 6 added:

If x(N) the output will be out(6)
If x(N,J) the output will be (J,6)
If x(N,J,I) the output will be out(J,I,6)
If x(K,N,J,I) the output will be out(K,J,I,6)

Description

Given a series, extval_mlegev calculates the maximum-likelihood estimates (MLEs) of the parameters of the generalized extreme value distribution (GEV) and their standard errors. The parameters are: (i) shape, (ii) location (aka, center), and (iii) scale.

GEV(x) = exp(-[1+shape*((x-locp)/scale)]^(-1/shape))

Note: Several sources and software packages use different conventions for the sign of the shape parameter.

REFERENCE(S):

  Algorithm AS 215:
  Maximum-Likelihood Estimation of the Parameters of the Generalized Extreme-Value Distribution
  J. R. M. Hosking
  Journal of the Royal Statistical Society. Series C (Applied Statistics) 
  Vol. 34, No. 3 (1985), pp. 301-310
  URL:  http://www.jstor.org/stable/2347483
  Code: http://ftp.uni-bayreuth.de/math/statlib/apstat/215

  Wikipedia: Generalized extreme value distribution

Examples

Example 1:

   flood = (/ 312,590,248,670,365,770,465,545,315,115,232,260,655,675,  \
              455,1020,700,570,853,395,926,99,680,121,976,916,921,191,  \
              187,377,128,582,744,710,520,672,645,655,918,512,255,1126, \
              1386,1394,600,950,731,700,1407,1284,165,1496,809         /)

   vals  = extval_mlegev (flood, 0, False)    ; dims=0
   print(vals)                                ; vals(6)

The edited output is:

                           MLE
   (0)	487.1327           location 
   (1)	308.7767           scale
   (2)	0.0936752          shape
                           standard errors of each parameter
   (3)	49.00172           location
   (4)	35.84376           scale
   (5)	0.120576           shape

The R software tool returns the following:


   > install.packages("ismev")
   > library(ismev)

   > flood.data <- c(312,590,248,670,365,770,465,545,315,115,232,260,655,675,
   +                 455,1020,700,570,853,395,926,99,680,121,976,916,921,191,
   +                 187,377,128,582,744,710,520,672,645,655,918,512,255,1126,
   +                 1386,1394,600,950,731,700,1407,1284,165,1496,809)
   > gev.fit(flood)
   or
   > x <- gev.fit(flood.data)
   > x
   
   $data
    [1]  312  590  248  670  365  770  465  545  315  115  232  260  655  675  455
   [16] 1020  700  570  853  395  926   99  680  121  976  916  921  191  187  377
   [31]  128  582  744  710  520  672  645  655  918  512  255 1126 1386 1394  600
   [46]  950  731  700 1407 1284  165 1496  809
   
   $mle
   [1] 487.07202252 308.76501616  -0.09363131   <=== vals(0:2)
   
   $cov                                          not returned by NCL
               [,1]        [,2]        [,3]
   [1,] 2400.938119  582.553044 -2.56354404
   [2,]  582.553044 1284.941994 -2.10272869
   [3,]   -2.563544   -2.102729  0.01453902
   
   $se
   [1] 48.9993686 35.8460876  0.1205778        <=== vals(3:5)