Nonparametric statistics include nonparametric descriptive statistics, statistical models, inference, and statistical tests.The model structure of nonparametric models is not specified a priori ...

Even if the data are distributed normally, nonparametric methods are often almost as powerful as parametric methods. Most nonparametric methods are based on taking the ranks of a variable and ...

Four new nonparametric estimators of static CoVaR are proposed. They are shown to be consistent and asymptotically normal under random sampling. Their performance is compared in simulation studies.

Nonparametric tests robustly compare skewed or ranked data. Figure 1: A sample can be easily tested against a reference value using the sign test without any assumptions about the population ...

Stefan Sperlich, , Lijian Yang, Nonparametric Estimation and Testing of Interaction in Additive Models, Econometric Theory, Vol. 18, No. 2 (Apr., 2002), pp. 197-251 Free online reading for over 10 ...

Statistical Science, Vol. 33, No. 4, Special Issue on Nonparametric Inference Under Shape Constraints (November 2018), pp. 568-594 (27 pages) We consider the problem of nonparametric regression under ...

This paper designs a Bayesian nonparametric covariance estimator by integrating the pooling method, vector moving average adjustment and synchronization with data augmentation. The proposed covariance ...

The conventional growth-accounting approach to estimating the sources of economic growth requires unrealistically strong assumptions about the competitiveness of factor markets and the form of the ...