Accurate confidence intervals for binomial proportion and Poisson rate estimation.
TLDR
Accurate confidence interval estimators for proportions, rates, and their differences are described and MATLAB programs are made available and the resulting confidence intervals are validated and compared to common methods.About:
This article is published in Computers in Biology and Medicine.The article was published on 2003-11-01 and is currently open access. It has received 108 citations till now. The article focuses on the topics: Robust confidence intervals & CDF-based nonparametric confidence interval.read more
Citations
More filters
Journal ArticleDOI
A Binomial Model for Radiated Immunity Measurements
TL;DR: In this article, a statistical analysis of immunity testing in EMC based on binomial distributions is proposed, which aims at extracting the immunity properties of a device from its probability of failure during a test.
Journal ArticleDOI
Validation of $k$ -Nearest Neighbor Classifiers
TL;DR: A method to compute probably approximately correct error bounds for k-nearest neighbor classifiers by withholding some training data and using the validation set to bound the difference in error rates between the holdout classifier and the classifier based on all training data.
Book ChapterDOI
Robustness Properties and Confidence Interval Reliability Issues
TL;DR: This chapter discusses the robustness and reliability of the estimators of the probability of a rare event (or, more generally, of the expectation of some function of rare events) with respect to rarity: is the estimator accurate as rarity increases?
Journal ArticleDOI
Estimating the risk of rare complications: is the 'rule of three' good enough?
John Ludbrook,Michael J. Lew +1 more
TL;DR: The clinical problem: If a surgeon has performed a particular operation on n consecutive patients without major complications, what is the long‐term risk of major complications after performing many more such operations?
Journal ArticleDOI
Comparing predicted prices in auctions for online advertising
TL;DR: In this paper, the authors show that by taking a maximum among estimates, publishers inadvertently select ads based on a combination of actual expected revenue and inaccurate estimation of expected revenue, which can result in a large increase in expected revenue loss.
References
More filters
Journal ArticleDOI
The use of confidence or fiducial limits illustrated in the case of the binomial
C. J. Clopper,E. S. Pearson +1 more
Book
Univariate Discrete Distributions
TL;DR: In this paper, the authors propose a family of Discrete Distributions, which includes Hypergeometric, Mixture, and Stopped-Sum Distributions (see Section 2.1).
Journal ArticleDOI
Univariate Discrete Distributions.
Book
Introductory Probability and Statistical Applications
TL;DR: The introduction to Probability 2nd Edition Problem Solutions and Probability An Introduction With Statistical Applications, as well as an Introduction to Basic Statistics And Probability.
Related Papers (5)
Approximate is Better than “Exact” for Interval Estimation of Binomial Proportions
Alan Agresti,Brent A. Coull +1 more
The use of confidence or fiducial limits illustrated in the case of the binomial
C. J. Clopper,E. S. Pearson +1 more