2014/02/14 by Michail Tsagris, Christina Beneki, Hossein Hassani · 1 citation
Decision Sciences · Mathematics · #Advanced Statistical Process Monitoring #Applied mathematics #Asymptotic distribution #CDF-based nonparametric confidence interval #Confidence distribution #Confidence interval #Cumulative distribution function #Distribution (mathematics) #Estimator #Half-normal distribution #Mathematical analysis #Mathematics #Maximum likelihood #Normal distribution #Principle of maximum entropy #Probabilistic and Robust Engineering Design #Probability density function #Q-function #Series (stratigraphy) #Statistical Distribution Estimation and Applications #Statistics #Taylor series #Truncated normal distribution #stat.ME
paper · pdf · doi:10.3390/math2010012
published as Mathematics 2014, 2(1), 12-28 · Published in Mathematics. http://www.mdpi.com/2227-7390/2/1/12
arxiv created 2014/02/14 · openalex publication_date 2014/02/14 · arxiv updated 2014/02/17 · openalex created_date 2025/10/10 · openalex updated_date 2026/08/05
The characteristic function of the folded normal distribution and its moment function are derived. The entropy of the folded normal distribution and the Kullback–Leibler from the normal and half normal distributions are approximated using Taylor series. The accuracy of the results are also assessed using different criteria. The maximum likelihood estimates and confidence intervals for the parameters are obtained using the asymptotic theory and bootstrap method. The coverage of the confidence intervals is also examined.