Length Biased Weighted Ishita Distribution and Its Applications on Real Life Data Sets

In this paper, we introduce a new extension within the realm of statistical distributions, presenting the “length-biased Ishita distribution.” This distribution stands out as part of the esteemed category of weighted distributions, particularly the length-biased variation. Through meticulous analysis, we explore the mathematical and statistical properties of this novel distribution and reveal its distinct characteristics. Using the robust methodology of maximum likelihood estimation, we accurately estimate the model parameters, enhancing our understanding of its behavior. To demonstrate the practical utility and advantages of the length-biased Ishita distribution, we apply it to a real-world temporal dataset. This empirical analysis highlights its superior performance and adaptability, offering valuable insights into its potential applications across various domains.