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240 – Computationally Intensive Methods for Estimation and Inference
A Missing Technique for Estimating Univariate Multiple Missing Values: An Advanced Resampling Method for Correlated Observations
Silvia Irin Sharna
Department of Computer Science, Ball State University
Mian Arif Shams Adnan
Department of Computer Science, Ball State University
Rahmatullah Imon
Department of Mathematical Sciences, Ball State University
Since a missing value resembles not only an unknown data of an unknown probability distribution but also their unknown characteristics, it is better to construct a basket of characteristics based on assumed missing values. The missing technique, as demonstrated by Sharna et al (2016), is a kind of check and balance method for estimating a missing value. In this paper we offer an extended version of the iterative estimation method for more than one missing value. This paper also demonstrates a resampling method for generating 1 or 2 correlated observations from the same distribution from where the original sample is drawn.