help for gevfit

Fitting a generalized extreme value distribution by maximum likelihood

gevfit
depvar
[weight]
[if exp]
[in range]
[
shapevar(varlist_a)
scalevar(varlist_b)
location var(varlist_c)
robust
cluster(clustervar)
level(#)
maximize_options
]

by ... : may be used with gevfit; see help
by.

fweights and aweights are allowed; see help weights.

Description

gevfit fits by maximum likelihood a three-parameter generalized
extreme value distribution.

Options

shapevar(), scalevar() and locationvar() allow the user to specify
each parameter as a function of the
covariates specified in the respective variable list. A constant term is
always included in each equation.

robust specifies that the Huber/White/sandwich estimator
of variance is to be used in place of the traditional calculation; see
[U] 23.14 Obtaining robust variance estimates. robust
combined with cluster() allows observations which are not
independent within cluster (although they must be independent between
clusters).

cluster(clustervar) specifies that the observations
are independent across groups (clusters) but not necessarily within groups.
clustervar specifies to which group each observation belongs; e.g.,
cluster(personid) in data with repeated observations on individuals. See
[U] 23.14 Obtaining robust variance estimates. Specifying cluster()
implies robust.

level(#) specifies the confidence level, in percent,
for the confidence intervals of the coefficients; see help level.

nolog suppresses the iteration log.

maximize_options control the maximization process; see
help maximize. If you are seeing many "(not concave)" messages in the
log, using the difficult option may help convergence.

Example

. use yearly_rain

. gevfit rain

Author

Scott Merryman, Risk Management Agency (USDA)
scott.merryman@gmail.com

Acknowledgements

This is based on betafit by Nick Cox, Stephen Jenkins, and Maarten Buis.

References

Coles, Stuart. 2001. An Introduction to Statistical Modeling of Extreme Values.
London: Springer-Verlag

Cole, Stuart and Luis Pericchi. 2003. Anticipating catastrophes through extreme value modelling.
Journal Of The Royal Statistical Society Series C, Royal Statistical Society, vol. 52(4), pages 405-416.

Also see

Online: help for gumbelfit (if installed), help for gevd (if installed)