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UID:WILD_APRICOT_EVENT_3740909_SESSION_1
DTSTART:20200219T070000Z
DTEND:20200219T083000Z
SUMMARY:SA Branch Meeting - Prof Omer Ozturk
LOCATION:Engineering & Math EM212\, North Terrace\, The University of Adelaide
DESCRIPTION:https://statsoc.org.au/event-3740909\n\nBranch Meeting - Wednesday\, 19th February 2020\n The South Australian Branch of the Statistical Society would like to invite you to the February meeting of the 2020 program.\n Venue: Engineering and Math Science Building\, Room EM212\, North Terrace\, The University of Adelaide. A campus map is available at http://www.adelaide.edu.au/campuses/northtce/. \n ***Please note that most entrance doors to Adelaide University buildings close at 6pm so make sure you arrive in time for the talk.\n Time:\n 5:30pm - Refreshments in the Lecture Theatre\n 6:05pm - General Meeting Talk\n 7:30pm - A dinner will be held after the meeting at Jasmin Restaurant\, 31 Hindmarsh Square\, Adelaide SA 5000. Please RSVP for dinner to aarti.gulyani@sahmri.com by 17th February as we are usually unable to change the booking numbers at the last minute.\n Speaker: Professor Omer Ozturk\, The Ohio State University\n\n Topic: Probability-proportional-to-size ranked-set sampling from stratified populations\n\n Abstract\n This paper constructs a probability proportional-to-size (PPS) ranked-set sample from a stratified population. A PPS-ranked-set sample created stochastically ordered random variables in a sample using a PPS sampling design with selection probabilities approximately proportional to size of the units. The stochastic order relies on relative positions (ranks) of units among each other in small comparison sets. Hence\, the ranks induce more structure (stratification) in the sample in addition to the data structure created by unequal selection probabilities in a PPS sample. This added data structure makes the PPS-ranked set sample more informative than a PPS-sample.\n The stratified PPS-ranked-set sample is constructed by selecting a PPS-ranked-set sample from each stratum population. The paper constructs unbiased estimators for the population mean\, total and their variances. The new sampling design is applied to an apple production data to estimate the total apple production.\n\n Biography\n Professor Ozturk joined the statistics faculty in 1996. He currently serves as an associate editor for Environmental and Ecological Statistics\, Statistics and Probability Letters\, Communications in Statistics- Data Analysis and Simulation\, and Communications in Statistics- Theory and Methods. His research interest lies in developing inference under a set of relaxed distributional assumptions that may include parametric\, nonparametric and robust inference under different sampling conditions. The primary focus is on the construction of sampling designs that increases information content of each measured observation while keeping the sampling cost minimal. His research was funded by NSA and NSF. He was frequently invited to US Census Bureau as a Summer at Census Scholar. He served as publication officer in the section of nonparametric statistics in ASA. He was Elected fellow of ASA in 2010.\n\nFeel free to forward this meeting notice to colleagues\, all welcome. \n\n
DTSTAMP:20201031T104822Z
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