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Home  >  Transactions of NAMP VOL 14

14. ORDER STATISTICS APPROACH TO ESTIMATING MISSING DATA IN FLEXIBLE ELLIPTICAL PROCESSES by A.T. SÓYÍNKÁ, A.A. OLÓSUNDE, A.O. WÁLÉ-ORÒJO and K.M. YUSUFF Volume 14, (January - March, 2021 Issue)
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ORDER STATISTICS APPROACH TO ESTIMATING MISSING DATA IN FLEXIBLE ELLIPTICAL PROCESSES

A.T. SÓYÍNKÁ, A.A. OLÓSUNDE, A.O. WÁLÉ-ORÒJO and 1K.M. YUSUFF

Department of Statistics Federal University of Agriculture, Alabata, Abeokuta, Ogun State, Nigeria.

Department of Mathematics, Obafemi Awolowo University, Ile-ife, Osun state, Nigeria.

Abstract

Despite the fact that aging effects is a phenomenon that is unavoidable and must be given proper follow up attention by every individual; the inadequacy of good and relatively affordable health services has been the major discouragement for many individuals from following up with their health status. This trend of lack of follow up data has created some missing link and thus pose a huge setback to research and development due to data missing at random (on blood pressure history, liver function history, kidney function history and so on of individuals). Hence in this study we obtain the estimate of the parameters of  th order statistics exponential power distribution which is a member of elliptical contoured family and also develop the model to obtain the missing value(s) within data set that are exponential power distributed using order statistics approach. The maximum likelihood estimation method was used to obtain the  th order statistics scale and the location parameters while kurtosis maximization was used to determine the shape parameter via normalp. The missing value(s) are obtained by maximizing the joint order statistics distribution within a single data set that is truncated at a missing point  . Application to missing data in the weights of depressive patients at the psycho-geriatric clinic of the Federal Neuro-Psychiatric Hospital Aro Abeokuta was used to demonstrate the workability of the model.

Keywords: Order statistics, exponential power distribution, parameter estimation, missing at random.

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