Middle East Technical University Institute of Applied Mathematics Seminars

Model Based Inference using Ranked Set Samples
Könül Bayramoğlu Kavlak
Actuarial Science, Hacettepe University, Turkey
Özet : This study develops statistical inference based on super population model in a finite population setting using ranked set samples (RSS). The samples are constructed without replacement. It is shown that the sample mean of RSS is model unbiased and has smaller mean square prediction error (MSPE) than the MSPE of a simple random sample mean. Using an unbiased estimator of MSPE, the paper also constructs a prediction confidence interval for the population mean. A small scale simulation study shows that estimator is as good as or better than simple random sample (SRS) estimator when the quality of ranking information in RSS is low or high, respectively, and the cost ratio of obtaining a single unit in RSS and SRS is not very high. Simulation study also indicates that coverage probabilities of prediction intervals are very close to the nominal coverage probabilities. Proposed inferential procedure is applied to a real data set.
  Tarih : 02.04.2019
  Saat : 15:40
  Yer : Hayri Körezlioğlu Seminar Room, IAM
  Dil : English
  Web : http://iam.metu.edu.tr/event-calendars#colloquia
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