Estimation and Prediction Based on K-Record Values from Logistic Distribution

Abstract

Abtsrcat In this paper, we consider k-record values arising from logistic distribution. We derive some recurrence relations for the single and product moments of the upper k-record values from logistic distribution. After computing the means, variances and covariances of the upper k-record values, we determine the best linear unbiased estimators for the location and scale parameters of logistic distribution. The best linear unbiased predictor of future k-record values is also determined. Finally, a real data is given to illustrate the inference procedures developed in this paper.