Confidence with confidence intervals

On Increasing Confidence in Confidence Intervals

A set of N data elements (xI +•.• + X~)/N and variance of the th The r moment of the data elements elements is used to estimate E(xr ). th r x1' •.•• xN has r moment E(x)= th r 2r 2 r r moment Var(x ) = E(x )-E (x ). in an arbitrary subset of k Over all the choices of the sample, the mean error is zero and the mean squared error N-k r k(N-I) Var(x). A little-known theorem by Marlow shows that t...

Probabilistic Intervals of Confidence

Abstract: High accuracy should not be the only goal of classification: information concerning probable alternatives diagnoses, probability of these diagnoses, evaluation of confidence in classification, are also important. Neural models are used just to obtain the winner class but do not provide any justification for their recommendations – they work as black boxes. A method which determine con...

Credibility of Confidence Intervals

Classical confidence intervals are often misunderstood by particle physicists and the general public alike. The confusion arises from the two different definitions of probability in common use. As a result, there is general dissatisfaction when confidence intervals are empty or they exclude parameter values for which the experiment is insensitive. In order to clarify these issues, the relation ...

Exact Confidence Intervals

Fiducial Generalized Confidence Intervals

Generalized pivotal quantities (GPQs) and generalized confidence intervals (GCIs) have proven to be useful tools for making inferences in many practical problems. Although GCIs are not guaranteed to have exact frequentist coverage, a number of published and unpublished simulation studies suggest that the coverage probabilities of such intervals are sufficiently close to their nominal value so a...