This paper considers the nonparametric M-estimator in a nonlinear cointegration type model. The local time density argument, which was developed by Phillips and Park (1998) [6] and Wang and Phillips (2009) [9], is applied to establish the asymptotic theory for the nonparametric...

We study a random design regression model generated by dependent observations, when the regression function itself (or its [nu]-th derivative) may have a change or discontinuity point. A method based on the local polynomial fits with one-sided kernels to estimate the location and the jump size...

Let be a set of observations from a stationary jointly associated process and [theta](x) be the conditional median, that is, . We consider the problem of estimating [theta](x) based on the L1-norm kernel and establish asymptotic normality of the resulting estimator [theta]n(x).

In this paper, we consider testing for additivity in a class of nonparametric stochastic regression models. Two test statistics are constructed and their asymptotic distributions are established. We also conduct a small sample study for one of the test statistics through a simulated example.