Showing papers by "Anne Chao published in 1992"

Estimating the Number of Classes via Sample Coverage

Abstract: Assume that a random sample is drawn from a population with unknown number of classes and possibly unequal class probabilities. A nonparametric estimation technique is proposed to estimate the number of classes using the idea of sample coverage, which is defined as the sum of the cell probabilities of the observed classes. Since expected sample coverage can be well estimated, we were motivated to find its role in the estimation of the number of classes. This work generalizes the result of Esty to a nonparametric approach and extends Darroch and Ratcliff to incorporate the heterogeneity of the class probabilities. The coefficient of variation of the class sizes is shown to play an important role in the recommended estimation procedures. The performance of the proposed estimators is investigated by means of Monte Carlo simulations.

Estimating population size for capture-recapture data when capture probabilities vary by time and individual animal.

Abstract: There have been no estimators of population size associated with the capture-recapture model when the capture probabilities vary by time and individual animal. This work proposes a nonparametric estimation technique that is appropriate for such a model using the idea of sample coverage, which is defined as the proportion of the total individual capture probabilities of the captured animals. A simulation study was carried out to show the performance of the proposed estimation procedure. Numerical results indicate that it generally works satisfactorily when the coefficient of variation of the individual capture probabilities is relatively large. An example is also given for illustration.

On Optimal Stopping Rules in Software Reliability

Abstract: : Software testing, or debugging, is one of the most important components in software development It has been estimated that in many projects, the time accounted for debugging can be around 50% of the total development effort There is an obvious question in the debugging process, that is when to stop One naive answer is, of course, the process continues until there are no bugs (errors) in the program However, this is a very difficult goal to achieve For most commercial software, the release requirement is usually not 100% error free, but an acceptable error rate Again, to determine when a debugging process has reached this stage is difficult The best bet is often an estimate of the future error rate However, the accuracy of the estimate may not be very high, depending on the estimation formula, and more seriously, on the assumptions that the formula is based upon