A production function satisfying the Regular Ultra Passum (RUP) law is characterized by increasing returns to scale followed by decreasing returns to scale along any expansion path, which is referred to as S-shape function. Although there are existing nonparametric estimators imposing the RUP law, they impose additional strong assumptions such as: deterministic model, homotheticity or constant elasticity of scale. This paper proposes an iterative algorithm to estimate adaptively a function that satisfies the RUP law while relaxing these other assumptions.