Neutrosophic robust ratio type estimator for estimating finite population mean

Area of Science:

• Statistics
• Data Analysis

Background:

• Classical statistical methods struggle with imprecise, incomplete, or vague data.
• Neutrosophic statistics offer a robust alternative for handling data indeterminacy.

Purpose of the Study:

• To propose a generalized Neutrosophic robust ratio type estimator.
• To enhance estimation accuracy in the presence of data instability and outliers.

Main Methods:

• Development of a generalized Neutrosophic robust ratio type estimator.
• Evaluation using a real data set and simulation studies.

Main Results:

• The proposed Neutrosophic estimator demonstrates superior performance compared to existing methods.
• Effective handling of unstable, imprecise, and outlier-prone data.

Conclusions:

• Neutrosophic statistics provide a powerful framework for robust estimation.
• The proposed estimator is a valuable tool for statistical analysis with uncertain data.