DUAL EXPONENTIAL RATIO ESTIMATOR IN PRESENCE OF NON-RESPONSE
Creators: name: Jan, Rafia
name: T.R. Jan 
name: Faizan Danish
Publisher: name: Reliability: Theory & Applications
Year: 2024
Subjects: Non-Response (NR)
Exponential Estimator
Dual to Ratio Estimator
Mean Square Error and Percent Relative Efficiency

description: The manuscript under consideration delves into a comprehensive exploration of the dual exponential ratio estimator, particularly in the context of non-response scenarios. In the following discourse, we will embark on an intricate journey through this research, emphasizing the pivotal aspects and findings that unravel the significance of this estimator in the realm of statistical estimation. The crux of this investigation revolves around evaluating the Mean Squared Error (MSE) and the Predictive Relative Efficiency (PRE) of the dual exponential ratio estimator. These two performance metrics serve as essential benchmarks for assessing the accuracy and effectiveness of the estimator. Notably, they play a crucial role in determining the estimator's suitability for practical applications, especially in situations where non-response is prevalent. To begin our exploration, it is imperative to understand the fundamental concept of the dual exponential ratio estimator. This estimator is a statistical tool employed in situations where traditional estimators may falter due to non-response, a phenomenon frequently encountered in surveys and data collection. It leverages a dual exponential model to address this challenge, making it a valuable addition to the toolkit of statisticians and researchers. The manuscript embarks on a rigorous theoretical analysis of the dual exponential ratio estimator's MSE and PRE. Through a series of mathematical derivations and proofs, the authors elucidate the underlying principles governing its performance. This theoretical foundation is crucial, as it not only establishes a solid framework for evaluating the estimator but also provides insights into its behavior under different conditions. However, theory alone can only take us so far. To validate the theoretical findings and assess the estimator's practical utility, numerical experiments are conducted. These experiments involve simulations and real-world data scenarios, allowing the authors to draw comparisons between the dual exponential ratio estimator and traditional estimators. The numerical results serve as a bridge between theory and application, offering empirical evidence of the estimator's prowess. In essence, this manuscript fills a critical gap in the field of statistical estimation by thoroughly investigating the dual exponential ratio estimator's performance in the presence of non-response. By juxtaposing its MSE and PRE with those of traditional estimators, it provides valuable insights into the potential advantages of adopting this novel approach. Moreover, the combination of rigorous theory and practical validation ensures that the findings are both intellectually sound and operationally relevant. The dual exponential ratio estimator, as explored and analyzed within these pages, emerges as a promising solution, backed by both theoretical rigor and empirical support. This research contributes not only to the theoretical foundations of statistics but also to its real-world applications, underscoring the estimator's potential to enhance the accuracy and reliability of estimation in the face of non-response complexities.