We construct a family of estimators for a regression function based on a sample following a qdistribution. Our approach is nonparametric, using kernel methods built from operations that leverage the properties of q-calculus. Furthermore, under appropriate assumptions, we establish the weak convergence and strong consistency of this family of estimators.

翻译：我们基于服从q分布的样本构造了一类回归函数的估计量。该方法采用非参数途径，利用基于q-微积分运算特性构建的核方法。此外，在适当假设条件下，我们证明了该类估计量的弱收敛性与强相合性。