A Zero Inflated Power Sine Sine Dagum Distribution for Modeling Heavy-Tailed Data with Excess Zeros
DOI:
https://doi.org/10.62054/ijdm/0302.02Abstract
This paper introduces a new flexible distribution, termed the Zero-Inflated Power Sine Sine Dagum (ZIPSSD) distribution, for modeling data characterized by excess zeros and heavy-tailed behavior. The proposed model extends the classical Dagum distribution through a sine-based transformation and incorporates a zero-inflation mechanism, resulting in a mixed discrete--continuous framework with enhanced flexibility. Key statistical properties of the ZIPSSD distribution are derived, including the probability density function, cumulative distribution function, survival function, hazard rate, quantile function, and moments. Parameter estimation is performed using the maximum likelihood approach, and a Monte Carlo simulation study is conducted to assess the performance of the estimators. The applicability of the model is demonstrated using rainfall data, where the ZIPSSD distribution provides a better fit than competing zero-inflated models based on likelihood and goodness-of-fit measures. Overall, the proposed model offers a robust and effective framework for modeling zero-inflated continuous data.References
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