Wararit Panichkitkosolkul. Bootstrap methods for estimating the confidence interval for the population mean of the zero-truncated Poisson-Amarendra distribution and their application. (). King Mongkut's University of Technology North Bangkok. Central Library. : , 2023.
Bootstrap methods for estimating the confidence interval for the population mean of the zero-truncated Poisson-Amarendra distribution and their application
Abstract:
The modeling of zero-truncated count data is of primary interest in many areas. Recently, the zero-truncated Poisson-Amarendra distribution has been proposed for such data. However, the confidence interval estimation of the population mean has not yet been examined. In this paper, confidence interval estimation based on percentile, simple, biased-corrected and accelerated bootstrap methods was examined in terms of coverage probability and average interval length via Monte Carlo simulation. The results indicated that attaining the nominal confidence level using the bootstrap methods was not possible for small sample sizes regardless of the other settings. Moreover, when the sample size was large, the performances of the methods were not substantially different. Overall, the bias-corrected and accelerated bootstrap method outperformed the others, even for small sample sizes. Last, the bootstrap methods were used to calculate the confidence intervals for the population mean of the zero-truncated Poisson-Amarendra distribution via two numerical examples, the results of which match those from the simulation study
King Mongkut's University of Technology North Bangkok. Central Library