Interval estimation in the presence of nuisance parameters. 1. Bayesian approach

Joel Heinrich; Craig Blocker; John Conway; Luc Demortier; Louis Lyons; Giovanni Punzi; Pekka K. Sinervo

Interval estimation in the presence of nuisance parameters. 1. Bayesian approach

Data Analysis, Statistics and Probability 2007-05-23 v1

Authors: Joel Heinrich , Craig Blocker , John Conway , Luc Demortier , Louis Lyons , Giovanni Punzi , Pekka K. Sinervo

Abstract

We address the common problem of calculating intervals in the presence of systematic uncertainties. We aim to investigate several approaches, but here describe just a Bayesian technique for setting upper limits. The particular example we study is that of inferring the rate of a Poisson process when there are uncertainties on the acceptance and the background. Limit calculating software associated with this work is available in the form of C functions.

Keywords

bayesian inference time series analysis statistical algorithms

Cite

@article{arxiv.physics/0409129,
  title  = {Interval estimation in the presence of nuisance parameters. 1. Bayesian approach},
  author = {Joel Heinrich and Craig Blocker and John Conway and Luc Demortier and Louis Lyons and Giovanni Punzi and Pekka K. Sinervo},
  journal= {arXiv preprint arXiv:physics/0409129},
  year   = {2007}
}

Comments

CDF Statistics Committee http://www-cdf.fnal.gov/physics/statistics/ Report, LaTeX, 30 pages, 11 eps files

Interval estimation in the presence of nuisance parameters. 1. Bayesian approach

Abstract

Keywords

Cite

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