Typical success-rate prediction models for tapping exclude targets near screen edges. However, design constraints often force such placements, and in scrollable user interfaces, any element can move close to the screen edges. In this work, we model how target-edge distance affects touch pointing accuracy. We propose the Skewed Dual Normal Distribution Model, which assumes the tap-coordinate distribution is skewed by a nearby edge. The results showed that as targets approached the edge, the distribution's peak shifted toward the edge, and its tail extended away. In contrast to prior reports, the success rate improved when the target touched the edge, suggesting a strategy of ``tapping the target together with the edge.'' Our model predicts success rates across a wide range of conditions, including edge-adjacent targets. Through three experiments of horizontal, vertical, and 2D pointing, we demonstrated the generalizability and utility of our proposed model.

翻译：典型的点击成功率预测模型通常排除屏幕边缘附近的目标。然而，设计约束常迫使目标置于此类位置，且在可滚动用户界面中，任何元素都可能移动至屏幕边缘附近。本研究针对目标与屏幕边缘距离如何影响触控点击精度进行建模。我们提出倾斜双正态分布模型，该模型假设点击坐标分布受邻近边缘影响而发生倾斜。结果表明，当目标趋近边缘时，分布峰值向边缘偏移，其尾部则向远离方向延伸。与先前研究报告相反，当目标触及边缘时成功率反而提升，这暗示了“将目标与边缘一同点击”的策略。我们的模型能预测包含边缘邻接目标在内的广泛条件下的成功率。通过水平、垂直及二维指向三种实验，我们验证了所提模型的泛化能力与实用性。