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<p>This paper emphasizes the significance of circular statistics for the analysis of data characterized by angular measurements having inherent cyclicity which is contrary to the traditional linear data we usually observe. We introduce a novel circular probability distribution namely truncated wrapped Akash (TWA) distribution and illustrate its use in two distinct datasets. The study systematically explores key statistical properties of the proposed distribution like the moments, thereby providing insights into circular data structures. Estimation of parameters was conducted using Maximum Likelihood Estimation (MLE), Least Squares (LS), and Weighted Least Squares (WLS) methods. We conducted comparative analysis based on model selection criteria such as AIC and BIC which demonstrated that the TWA distribution achieves a superior fit to the data relative to existing circular models. Our findings highlight the effectiveness of incorporating truncation in circular distributions, offering flexibility and applicability for environmental and geological datasets and broader applications in related scientific domains.</p>

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Enhanced modeling of directional data using truncated wrapped Akash distribution for geological and environmental applications

  • 期刊论文

  • 发表日期：

    2026年1月27日

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  • K. M. Sakthivel,
  • Alicia Mathew

摘要

This paper emphasizes the significance of circular statistics for the analysis of data characterized by angular measurements having inherent cyclicity which is contrary to the traditional linear data we usually observe. We introduce a novel circular probability distribution namely truncated wrapped Akash (TWA) distribution and illustrate its use in two distinct datasets. The study systematically explores key statistical properties of the proposed distribution like the moments, thereby providing insights into circular data structures. Estimation of parameters was conducted using Maximum Likelihood Estimation (MLE), Least Squares (LS), and Weighted Least Squares (WLS) methods. We conducted comparative analysis based on model selection criteria such as AIC and BIC which demonstrated that the TWA distribution achieves a superior fit to the data relative to existing circular models. Our findings highlight the effectiveness of incorporating truncation in circular distributions, offering flexibility and applicability for environmental and geological datasets and broader applications in related scientific domains.