Author/Authors :
yildiztepe, engin dokuz eylül üniversitesi, tınaztepe yerleşkesi - fen fakültesi - istatistik bölümü, turkey , özdemir, a.fırat dokuz eylül üniversitesi, tınaztepe yerleşkesi - fen fakültesi - istatistik bölümü, turkey
Title Of Article :
A SIMULATION STUDY OF BOOTSTRAP CONFIDENCE INTERVALS FOR THE LOCATION OF ASYMMETRIC AND HEAVY TAILED DISTRIBUTIONS
Abstract :
Bootstrap methodology is a modern statistical tool which enables us making statistical inference when the sampling distribution of the estimator is not known. Although the underlying idea is the same in all bootstrap methods, one might come across so many variations in the literature. In this study, the coverage accuracy of four most commonly used bootstrap confidence interval methods was assessed for various asymmetric and heavy tailed distributions with an exhaustive Monte Carlo simulation. In most of the cases, it has been found that the coverage accuracy of bootstrap percentile method is close to nominal for robust estimators of location.
NaturalLanguageKeyword :
Bootstrap , Confidence interval , Coverage accuracy , Robust estimators of location
JournalTitle :
Anadolu University Journal of Science and Technology. A : Applied Sciences and Engineering
