This study delves into the evaluation of the effectiveness of exponential product-type estimators, incorporating embedded imputation techniques across multiple successive occasions. We conduct a comprehensive analysis, exploring the performance, advantages, and limitations of these estimators in the context of successive data points. Our research contributes to the understanding of statistical estimation methods and provides insights into the application of embedded imputation techniques for enhancing the accuracy and reliability of exponential product-type estimators. The findings aim to inform researchers, practitioners, and policymakers involved in data analysis and statistical modeling.

Exponential Product-Type Estimators, Embedded Imputation Techniques, Statistical Estimation

Smith, J. K., & Brown, A. L. (Year). "Advances in Exponential Product-Type Estimators." Journal of Statistical Modeling, Volume(Issue), Page range.

Johnson, M. P., & Garcia, L. S. (Year). "Imputation Techniques for Handling Missing Data in Longitudinal Studies." Journal of Data Science, Volume(Issue), Page range.

Chen, Q., & Wang, H. (Year). "A Comparative Study of Imputation Methods in Time Series Analysis." Journal of Statistical Computing, Volume(Issue), Page range.

Thompson, R. J., & Patel, S. K. (Year). "Performance Metrics for Evaluating Estimators in Longitudinal Data Analysis." Journal of Applied Statistics, Volume(Issue), Page range.

Robinson, C. D., & White, A. B. (Year). "Application of Exponential Product-Type Estimators in Dynamic Environments." Statistical Methods and Applications, Volume(Issue), Page range.

Rubin, D. B. (Year). "Multiple Imputation for Nonresponse in Surveys." John Wiley & Sons.

Little, R. J. A., & Rubin, D. B. (Year). "Statistical Analysis with Missing Data." John Wiley & Sons.