Suppose F_X is a continuous distribution function (DF) of an RV X. If we kept the withdrawal observations from time to time from F_X, then an observation that is larger than all the drawn observations previously is called a record and its value is called an upper record value or a record value. Let {R_n} be the sequence of the observed record values and let f_X be the probability density function (PDF) of X. Furthermore, we adopt R_0=X. Then, the PDF of R_n
The FI is a vital criterion in statistical inference especially in large sample studies in estimation theory. In this paper, we will define the form of the FI for the DF (see Kharazmi and Asadi, 2018). The FI related to the distribution parameters give us feed back how much information about an unknown parameter from a sample and FI is connecting with the efficiency of an estimator and sufficiency of a statistic. When we have an unknown parameter in the DF from which the sample is drawn, and when the sample is sufficiently huge, the Knowing FI helps tracking down limits on the variance of a given estimator of that parameter and to rough the testing appropriation of this estimator.

The Fisher information (FI) about the shape-parameter vectors of the Huang-Kotz FGM (HK-FGM) is investigated. We study analytically and numerically the Fisher information matrix (FIM) and Shanon entropy related to the record values and their concomitants for HK-FGM.