gpfit
Parameter estimates and confidence intervals for generalized Pareto data.
paramhat = gpfit (x) returns maximum likelihood estimates
of the parameters of the two-parameter generalized Pareto distribution given
the data in x. params(1) is the SHAPE parameter and
params(2) is the SCALE parameter. gpfit does not fit a LOCATION
parameter.
[paramhat, paramci] = gpfit (x) returns 95%
confidence intervals for the parameter estimates.
[…] = gpfit (x, alpha) returns 100*(1 - alpha)
percent confidence intervals for the parameter estimates.
Pass in [] for alpha to use the default values.
[…] = gpfit (x, alpha, options) specifies
control parameters for the iterative algorithm used to compute ML estimates
with the fminsearch function. options is a structure with the
following fields {default values}:
Other functions for the generalized Pareto, such as gpcdf, allow a
LOCATION parameter. However, gpfit does not estimate LOCATION, and it
must be assumed known, and subtracted from x before calling
gpfit.
When shape = 0 and location = 0, the generalized Pareto
distribution is equivalent to the exponential distribution. When
shape > 0 and location = scale / shape,
the generalized Pareto distribution is equivalent to the Pareto distribution.
The mean of the generalized Pareto distribution is not finite when
shape >= 1, and the variance is not finite when
shape >= 1/2. When shape >= 0, the generalized
Pareto distribution has positive density for x > location,
or, when shape < 0, for
0 <= (x - location) / scale <= -1 / shape.
See also: gpcdf, gpinv, gppdf, gprnd, gplike, gpstat
Source Code: gpfit