Implementation of higher-order asymptotics to S-plus

Higher-order asymptotics is an active area of development in theoretical statistics. However, most existing work in higher-order asymptotics is directed to the theoretical aspects. This paper attempts to incorporate higher-order inference procedures to S-plus, a widely used software in statistics. Algorithm is developed in the settings of generalized linear models and nonlinear regression models. The proposed algorithm generalizes the standard S-plus functions “glim” and “nls” in the sense that both the first-order and higher-order p-values are provided, and its manipulation is straightforward.