Correcting the Minimization Bias in Searches for Small Signals

We discuss a method for correcting the bias in the limits for small signals if those limits were found based on cuts that were chosen by minimizing a criterion such as sensitivity. Such a bias is commonly present when a "minimization" and an "evaluation" are done at the same time. We propose to use a variant of the bootstrap to adjust the limits. A Monte Carlo study shows that these new limits have correct coverage.Comment: 14 pages, 5 figue

Limits and Confidence Intervals in the Presence of Nuisance Parameters

We study the frequentist properties of confidence intervals computed by the method known to statisticians as the Profile Likelihood. It is seen that the coverage of these intervals is surprisingly good over a wide range of possible parameter values for important classes of problems, in particular whenever there are additional nuisance parameters with statistical or systematic errors. Programs are available for calculating these intervals.Comment: 6 figure

Estimating a Signal In the Presence of an Unknown Background

We describe a method for fitting distributions to data which only requires knowledge of the parametric form of either the signal or the background but not both. The unknown distribution is fit using a non-parametric kernel density estimator. The method returns parameter estimates as well as errors on those estimates. Simulation studies show that these estimates are unbiased and that the errors are correct

Confidence Intervals and Upper Bounds for Small Signals in the Presence of Background Noise

We discuss a new method for setting limits on small signals in the presence of background noise. The method is based on a combination of a two dimensional confidence region and the large sample approximation to the likelihood ratio test statistic. It automatically quotes upper limits for small signals and two-sided confidence intervals for larger samples. We show that this method gives the correct coverage and also has good power.Comment: Document was created by Sciword V3.0, it consists of one main document (lrt.tex), eight figures (figure1.eps - figure8.eps) and one table (table.tex). Paper was revised after being accepted for publication in NIM A Paper was revised after being accepted for publication in NIM

A Test for the Presence of a Signal, with Multiple Channels and Marked Poisson

We describe a statistical hypothesis test for the presence of a signal based on the likelihood ratio statistic. We derive the test for a special case of interest. We study extensions of the test to cases where there are multiple channels and to marked Poisson distributions. We show the results of a number of performance studies which indicate that the test works very well, even far out in the tails of the distribution and with multiple channels and marked Poisson.Comment: 21 pages, 6 figue

Attention delays perceived stimulus offset

AbstractYeshurun and Levy (2003) [Transient spatial attention degrades temporal resolution. Psychological Science, 14, 225 –231.] have suggested that visual attention enhances the activation of the parvocellular system and thus delays the perceived offset of a stimulus. We tested this assumption in a spatial cueing paradigm in which participants responded to stimulus offset. Consistent with this assumption, offset reaction time (RT) was prolonged for attended compared to unattended stimuli. For onset RT, however, we confirmed the well-known spatial cueing effect that attention speeds up the detection of stimulus onset. The results provide direct evidence for the proposal made by Yeshurun and Levy

Management of cancer pain in adult patients: ESMO Clinical Practice Guidelines.

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Including Systematic Uncertainties in Confidence Interval Construction for Poisson Statistics

One way to incorporate systematic uncertainties into the calculation of confidence intervals is by integrating over probability density functions parametrizing the uncertainties. In this note we present a development of this method which takes into account uncertainties in the prediction of background processes, uncertainties in the signal detection efficiency and background efficiency and allows for a correlation between the signal and background detection efficiencies. We implement this method with the Feldman & Cousins unified approach with and without conditioning. We present studies of coverage for the Feldman & Cousins and Neyman ordering schemes. In particular, we present two different types of coverage tests for the case where systematic uncertainties are included. To illustrate the method we show the relative effect of including systematic uncertainties the case of dark matter search as performed by modern neutrino tel escopes.Comment: 23 pages, 10 figures, replaced to match published versio

Search for Rare and Forbidden 3-body Di-muon Decays of the Charmed Mesons D+ and Ds+

Using a high statistics sample of photo-produced charm particles from the FOCUS experiment at Fermilab, we report results of a search for eight rare and Standard-Model-forbidden decays: D+, Ds+ > h+/- muon-/+ muon+ (with h=pion or Kaon). Improvement over previous results by a factor of 1.7--14 is realized. Our branching ratio upper limit D+ > pion+ muon- muon+ of 8.8E-6 at the 90% C.L. is below the current MSSM R-Parity violating constraint.Comment: 17 pages, 7 figure file