In this paper, we investigate some inferential properties of the upper record Lomax distribution. Also, we will estimate the upper record of the Lomax distribution parameters using methods, Moment (MME), Maximum Likelihood (MLE), Kullback-Leibler Divergence of the Survival function (DLS) and Baysian. Finally, we will compare these methods using the Monte Carlo simulation.

In a sequence of random variables, record values are observations that exceed or fall below the current extreme value.Now consider a sequence of pairwise random variables  {(Xi,Yi), i>=1}, when the experimenter is interested in studying just thesequence of records of the first component, the second component associated with a record value of the first one is termed the concomitant of that ...

Suppose that a geometrically distributed number of observations are available from an absolutely continuous distribution function $F$, within this set of observations denote the random number of records by $M$. This is called geometric random record model. In this paper, characterizations of $F$ are provided in terms of the subsequences entropies of records conditional on events ${M geq n}$ or ...

In this paper, we consider the record statistics at the time when the nth record of any kind (either an upper or lower) is observed based on a sequence of independent random variables with identical continuous distributions of bounded support. We provide sharp upper bounds for expectations of record range and current upper record increment. We also present numerical evaluations of the so obtain...

The goal of this thesis is to examine methods of statistical inference based on upper record values. This includes estimation of parameters based on samples of record values and prediction of future record values. We first define and discuss record times and record values and their distributions. Then we propose an efficient algorithm to generate random samples of record values. The algorithm, ...

In this study we, give some new explicit expressions and recurrence relations satisfied by marginal and joint moment generating functions of k−th upper record values from extended type II generalized logistic distribution. Next we show that results for upper record values of this distribution can be derived from our result as special cases. Further, a characterizing result of this distribution ...