Semiparametric regression models have become a cornerstone in statistical modeling, offering a nuanced approach that melds the strengths of parametric and nonparametric methodologies. The parametric component allows for the incorporation of a structured and well-defined relationship between variables, capturing the known aspects of the data’s behavior. Simultaneously, the nonparametric component introduces flexibility by accommodating intricate patterns that may defy simple parametric representations.