This survey intends to collect the developments on Goodness-of-Fit for regression models
during the last 20 years, from the very first origins with the proposals based on the idea of …

Useful in the theoretical and empirical analysis of nonlinear time series data, semiparametric
methods have received extensive attention in the economics and statistics communities over …

We propose a sound approach to bandwidth selection in nonparametric kernel testing. The
main idea is to find an Edgeworth expansion of the asymptotic distribution of the test …

Diffusion models play an essential role in modeling continuous-time stochastic processes in
the financial field. Therefore, several proposals have been developed in the last decades to …

This paper considers a class of nonparametric autoregressive models with nonstationarity.
We propose a nonparametric kernel test for the conditional mean and then establish an …

It is commonly accepted that some financial data may exhibit long-range dependence, while
other financial data exhibit intermediate-range dependence or short-range dependence …

This paper proposes a class of locally stationary diffusion processes. The model has a time
varying but locally linear drift and a volatility coefficient that is allowed to vary over time and …

This paper proposes an asymmetric kernel-based method for nonparametric estimation of
scalar diffusion models of spot interest rates. We derive the asymptotic theory for the …

High-frequency financial data can be collected as a sequence of time-ordered curves, such
as intraday prices. The Functional Data Analysis (FDA) framework offers a powerful …

Almost all economic activities in modern societies are scattered through space and time.
Transport processes, as a consequence, pervade everyday life and they have deep impact …