st: -weibullfit-, -qweibull-, -pweibull- from SSC

["Nick Cox" <n.j.cox@durham.ac.uk>]

Thanks to Kit Baum, a new package -weibullfit- is available from 
SSC. Stata 8.1 is required. Use -ssc- to install if interested. 

This package is written by Stephen Jenkins and myself. 

The main program -weibullfit- fits a two-parameter Weibull distribution
by maximum likelihood, optionally as dependent on covariates. 

In addition, existing packages -qweibull- and -pweibull- that plot
q-q and p-p plots for observed data versus results from a fitted Weibull
by maximum likelihood have been revised so that they call -weibullfit-. 

Some of you will know that existing Stata command -streg- offers 
support for Weibull distributions, and/or that the existing (but 
now not documented) command -weibull- does so too. The main 
reasons for a separate -weibullfit- are 

1. Its support of a different parameterisation, one that 
is popular in some sciences. It is relatively easy to relate this to 
Stata's favourite parameterisation, with or without -nlcom-, but nothing

beats direct support for convenience. 

2. Its support for at least some models not available under -streg-. 

3. Its independence of Stata's survival time facilities. Conversely, 
-weibullfit- is innocent of survival complexities and has nothing 
to offer -st- users. 

4. Its link to -qweibull- and -pweibull-. 

5. Most users would find -weibull- difficult to use in the absence
of documentation. 

-wbull-, dating from 1998, remains a stand-alone package on 
SSC for fitting Weibull distributions (without covariates). 
Only Stata 5 is required for that. 
 
-weibullfit- is the latest in a series of packages for fitting 
distributions, optionally as dependent on covariates, using maximum 
likelihood. Authors are Stephen Jenkins, Maarten Buis, Philippe Van 
Kerm and myself. Distributions treated similarly are 

beta
Dagum
Dirichlet 
gamma 
generalised beta of the second kind 
Gumbel 
inverse gamma 
inverse Gaussian
lognormal 
Singh-Maddala 
Type I Pareto

I suspect a few others may follow intermittently as the mood takes one
or more of us. 

Nick 
n.j.cox@durham.ac.uk 

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