Neutrosophic robust ratio type estimator for estimating finite population mean
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View abstract on PubMed
Summary
This summary is machine-generated.This study introduces a generalized Neutrosophic robust ratio type estimator to address issues with unstable or incomplete data. The new method offers improved accuracy, especially when dealing with outliers, outperforming traditional estimators.
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.
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