%0 Generic
%D 2016
%T Early Detection of Placement for Success in an Online Quantitative Class
%A Hsieh,Ping-Hung
%A Chang,Xiaohui
%A Olstad,Andrew
%K Business Analytics
%K MBA
%K Supply Chain
%B Joint Statistical Meetings
%C Chicago, IL
%8 2016
%G eng
%2 c
%4 144709447680
%$ 144709447680
%0 Conference Paper
%B Intern. Conf. on Inf. Systems (ICIS) 2015
%D 2015
%T Estimation and Visualization of Digital Library Content Similarities
%A Reitsma,Reindert
%A Hsieh,Ping-Hung
%A Robson,Robby
%K BIS
%K MBA
%K Supply Chain
%X We report on a process for similarity estimation and two-dimensional mapping of lesson materials stored in a Web-based K12 Science, Technology, Engineering and Mathematics (STEM) digital library. The process starts with automated removal of all information which should not be included in the similarity estimations followed by automated indexing. Similarity estimation itself is conducted through a natural language processing algorithm which heavily relies on bigrams. The resulting similarities are then used to compute a Sammon-map; i.e., a projection in n dimensions, the item-to-item distances of which best reflect the input similarities. In this paper we concentrate on specification and validation of this process. The similarity results show almost 100% precision-by-rank in the top three to five ranks. Sammon mapping in two dimensions corresponds well with the digital libraryâ€˜s table of content.
%B Intern. Conf. on Inf. Systems (ICIS) 2015
%8 2015
%G eng
%2 b
%4 105616928768
%$ 105616928768
%0 Journal Article
%J Variance: advancing the science of risk
%D 2009
%T Extreme Value Analysis for Partitioned Insurance Loss
%A Henry III,John B.
%A Hsieh,Ping-Hung
%K MBA
%K Supply Chain
%X The heavy-tailed nature of insurance claims requires that special attention be put into the analysis of the tail behavior of a loss distribution. It has been demonstrated that the distribution of large claims of several lines of insurance have Pareto-type tails. As a result, estimating the tail index, which is a measure of the heavy-tailedness of a distribution, has received a great deal of attention. Although numerous tail index estimators have been proposed in the literature, many of them require detailed knowledge of individual losses and are thus inappropriate for insurance data in partitioned form. In this study we bridge this gap by developing a tail index estimator suitable for partitioned loss data. This estimator is robust in the sense that no particular global density is assumed for the loss distribution. Instead we focus only on fitting the model in the tail of the distribution where it is believed that the Pareto-type form holds. Strengths and weaknesses of the proposed estimator are explored through simulation and an application of the estimator to real world partitioned insurance data is given.
%B Variance: advancing the science of risk
%V 3
%P 214 - 238
%8 2009
%G eng
%N 2
%2 a
%4 22474360833
%$ 22474360833
%0 Generic
%D 2004
%T On Examining Asymmetric Behavior of Price Limit Moves
%A Hsieh,Ping-Hung
%A Yang,J. Jimmy
%K MBA
%K Supply Chain
%B National Joint Statistical Meetings
%C Toronto, Canada
%8 2004
%G eng
%2 c
%4 646834176
%$ 646834176
%0 Journal Article
%J Computational Statistics and Data Analysis
%D 2002
%T An Exploratory First Step in Teletraffic Data Modeling: Evaluation of Long-run Performance of Parameter Estimators
%A Hsieh,Ping-Hung
%K MBA
%K Supply Chain
%X Examination of the tail behavior of a distribution F that generates teletraffic measurements is an important first step toward building a network model that explains the link between heavy tails and long-range dependence exhibited in such data. When knowledge of the tail behavior of F is vague, the family of the generalized Pareto distributions (GPDs) can be used to approximate the tail probability of F, and the value of its shape parameter characterizes the tail behavior. To detect tail behavior of F between two host computers on a network, the estimation procedure must be carried out over all possible combinations of host computers, and thus, the performance of the estimator under repeated use becomes the primary concern. In this article, we evaluate the long-run performance of several existing estimation procedures and propose a Bayes estimator to overcome some of the shortcomings. The conditions in which the procedures perform well in the long run are reported, and a simple rule of thumb for choosing an appropriate estimator for the task of repeated estimation is recommended.
%B Computational Statistics and Data Analysis
%V 40
%P 263-283
%8 2002
%G eng
%N 2
%2 a
%4 646813696
%$ 646813696