A new simple detection function for line transect sampling

We introduce a new parametric detection function for modeling the density of perpendicular distances in line transect sampling. The proposed model, based on an exponential function, satisfies the shoulder condition at the origin—unlike the classical exponential model—while preserving a monotonic decreasing form with distance from the transect line. Simulation studies show that across a wide range of target densities, the proposed model performs favorably, often surpassing both the classical exponential and half-normal models. In addition, the proposed model is discussed in the context of more flexible multi-parameter detection functions, and its practical implementation within standard model selection frameworks is highlighted.