gplike
              Negative log-likelihood for the generalized Pareto distribution.
 nlogL = gplike (params, x) returns the negative
 log-likelihood of the data in x corresponding to the generalized Pareto
 distribution with (1) shape parameter k and (2) scale parameter
 sigma given in the two-element vector params.  gplike
 does not allow a location parameter and it must be assumed known, and
 subtracted from x before calling gplike.
 [nlogL, acov] = gplike (params, x) returns
 the inverse of Fisher’s information matrix, acov.  If the input
 parameter values in params are the maximum likelihood estimates, the
 diagonal elements of acov are their asymptotic variances.   acov
 is based on the observed Fisher’s information, not the expected information.
 When k = 0 and mu = 0, the Generalized Pareto CDF
 is equivalent to the exponential distribution.  When k > 0 and
 mu = k / k the Generalized Pareto is equivalent to
 the Pareto distribution.  The mean of the Generalized Pareto is not finite
 when k >= 1 and the variance is not finite when
 k >= 1/2.  When k >= 0, the Generalized Pareto
 has positive density for x > mu, or, when
 mu < 0, for
 0 <= (x - mu) / sigma <= -1 / k.
Further information about the generalized Pareto distribution can be found at https://en.wikipedia.org/wiki/Generalized_Pareto_distribution
See also: gpcdf, gpinv, gppdf, gprnd, gpfit, gpstat
Source Code: gplike