A polycentric network consists of urban functional areas with significant growth potential in the settlement network and a transport infrastructure that effectively interconnects them. Polycentric development is a key instrument for promoting economic competitiveness, social cohesion and environmental sustainability, and its assessment has a particular importance for the European strategies. The paper aims to assess the level of polycentricity of Romania based on a methodology developed by changing the one used in ESPON 1.1.1 by replacing the GDP with the turnover, multimodal accessibility with accessibility, and using a threshold of 30,000 inhabitants instead of 50,000 for the centres of functional urban areas. The results, consisting of country rankings based on size, location, connectivity, and polycentricity, were compared to those of ESPON 1.1.1. Romania ranked fifth in the top from the Polycentricity Index of ESPON countries, with a medium high level of polycentricity.

For estimating regression function we can use many proceedings. In this paper, we have chosen to apply scaling functions to the estimation of regression functions. When one knows many bivariate date with the values of two variables, in the goal to express a correlation between the two variables we use the regression function. The raw estimator of this function must be "smoothed out" in some way to get a final estimator. For this, we use the scaling functions, examples of such function being the Battle-Lemarié family and Daubechies family. After introducing several notions (multiresolution analysis, filter and projection of function onto approximation spaces), these are applied to obtain the estimators. In the last part, we present the algorithm for estimating nonparametric regression function through the scaling functions.