SOFTWARE/STATA

 

Maximum Likelihood**

Various methods available

  • Linear-form methods; no need to code derivatives
  • No-derivative methods; no need to code derivatives
  • First-derivative methods; must code first derivative
  • Second-derivative methods; must code first and second derivatives
  • Write code in ado or Mata

Debugger

  • utility to verify that the log-likelihood works
  • ability to trace the execution of the log-likelihood evaluator
  • Comparison of numerical and analytic derivatives

Techniques

  • modified Newton–Raphson
  • Davidon–Fletcher–Powell (DFP)
  • Broyden–Fletcher–Goldfarb–Shanno (BFGS)
  • Berndt–Hall–Hall–Hausman (BHHH)

Variance matrix estimators

  • observed information matrix (Hessian matrix)
  • outer product of the gradients (OPG)
  • Huber/White/robust and cluster–robust
  • bootstrap
  • jackknife
  • survey design, including multistage and stratified designs

 

Built-in features

  • calculate robust standard errors
  • include weights
  • include linear constraints
  • use clustered data
  • calculate scores
  • automatic support for survey data
  • graph convergence path
  • redisplay results
  • specify initial values
  • maximize difficult functions
  • control convergence criteria
  • use standard output or create your own
Maximum likelihood estimation example

* New in Stata 12

** Updated in Stata 12

© Copyright StataCorp LP 1996-2011.


 
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