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EXTREME: Stata module to fit models used in univariate extreme value theory

Author

Listed:
  • David Roodman

    ()

Abstract

extreme estimates the most-used models in univariate extreme value theory, using Maximum Likelihood: the generalized Pareto distribution (GPD), which is appropriate for modeling exceedances of a threshold; the generalized extreme value distribution (GEV), which is appropriate for modeling block maxima; and the extension of the GEV for multiple order statistics for blocks. extreme also provides a variety of diagnostic and profile plots. extreme's major novelty is the ability to compute the Cox-Snell small-sample bias correction for all models fit. The correction for the GPD is derived in Giles, Feng, and Godwin (2015). The correction for the GEV, including for multiple order statistics, is new. The correction is also extended to non-stationary models. Maximum Likelihood is always biased in finite samples, and the bias can be significant in the small samples often used in extreme value analysis.

Suggested Citation

  • David Roodman, 2015. "EXTREME: Stata module to fit models used in univariate extreme value theory," Statistical Software Components S457953, Boston College Department of Economics, revised 18 Dec 2017.
  • Handle: RePEc:boc:bocode:s457953
    Note: This module should be installed from within Stata by typing "ssc install extreme". Windows users should not attempt to download these files with a web browser.
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    File URL: http://fmwww.bc.edu/repec/bocode/e/extreme.ado
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    File URL: http://fmwww.bc.edu/repec/bocode/e/extreme_small.ado
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    File URL: http://fmwww.bc.edu/repec/bocode/e/extreme_estimate.ado
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    File URL: http://fmwww.bc.edu/repec/bocode/e/extreme_p.ado
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    File URL: http://fmwww.bc.edu/repec/bocode/e/extreme.mata
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    File URL: http://fmwww.bc.edu/repec/bocode/e/extreme.sthlp
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    File URL: http://fmwww.bc.edu/repec/bocode/l/lextreme.mlib
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    File URL: http://fmwww.bc.edu/repec/bocode/d/dowjones.dta
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