In this paper we propose a new nonparametric regression algorithm based on Fuzzy systems with overlapping concepts. We analyze its consistency properties, showing that it is capable to reconstruct an infinite-dimensional class of function when the size of the (noisy) dataset grows to infinity. Moreover convergence to the target function is guaranteed in Sobolev norms so ensuring uniform converg...

We consider nonparametric identification and estimation in a nonseparable model where a continuous regressor of interest is a known, deterministic, but kinked function of an observed assignment variable. This design arises in many institutional settings where a policy variable (such as weekly unemployment benefits) is determined by an observed but potentially endogenous assignment variable (lik...

We consider nonparametric identification and estimation in a nonseparable model where a continuous regressor of interest is a known, deterministic, but kinked function of an observed assignment variable. This design arises in many institutional settings where a policy variable (such as weekly unemployment benefits) is determined by an observed but potentially endogenous assignment variable (lik...

COVID-19 incidence is analyzed at the provinces of some Spanish Communities during period February-October, 2020. Two infinite-dimensional regression approaches are tested. The first one implemented in framework introduced Ruiz-Medina, Miranda and Espejo (2019). Specifically, a bayesian adopted estimation pure point spectrum temporal autocorrelation operator, characterizing second-order structu...