Optimal estimators for threshold-based quality measures

Aaron Abrams*, Sandy Ganzell, Henry Landau, Zeph Landau, James Pommersheim, Eric Zaslow

*Corresponding author for this work

Research output: Contribution to journalArticle


We consider a problem in parametric estimation: given n samples from an unknown distribution, we want to estimate which distribution, from a given one-parameter family, produced the data. Following Schulman and Vazirani (2005), we evaluate an estimator in terms of the chance of being within a specified tolerance of the correct answer, in the worst case. We provide optimal estimators for several families of distributions on . We prove that for distributions on a compact space, there is always an optimal estimator that is translation invariant, and we conjecture that this conclusion also holds for any distribution on . By contrast, we give an example showing that, it does not hold for a certain distribution on an infinite tree.

Original languageEnglish (US)
Article number752750
JournalJournal of Probability and Statistics
StatePublished - Dec 1 2010

ASJC Scopus subject areas

  • Statistics and Probability

Fingerprint Dive into the research topics of 'Optimal estimators for threshold-based quality measures'. Together they form a unique fingerprint.

  • Cite this