This paper proposes a nonparametric regression using asymmetric kernel functions for nonnegative, absolutely regular processes, and specializes this technique to estimating scalar diffusion models of spot interest rate. We illustrate the advantages of asymmetric kernel estimators for bias...

We propose a class of counting process models for analysing firing times of an ensemble of neurons. We allow the counting process intensities to be unspecified, unknown functions of the times passed since the most recent firings. Under this assumption we derive a class of statistics with their...

Consider a p-variate counting process N = (...) with jump times {...}. Suppose that the intensity of jumps ... of ... at time t depends on the other components, i. e. ..., where the ... are unknown, nonrandom functions. From observing one single trajectory of the processes N over an increasing...

Consider a semiparametric model yi = xi' beta + g(ti )+ei; i = 1;2..., n, error ei are i.i.d. random variables from unknown distribution f(e). In this paper, we propose a nonlinear wavelet estimator ^f(e) of f(e) based on residuals ê =yi - ^yi here restriction of uniformly continuous on f(e)...

It is commonly found in empirical studies that nominal interest rates contain a unit root, implying that these variables have a permanent memory. One of the characteristics of a nonstationary time series is that it has no tendency to return to its mean values, meaning that the series is trending...

This paper shows the uniform consistency in probability of modified kernel estimators towards the Baire functions representing the conditional variances and contemporaneous conditional covariances provided the data generating process is given by a strictly stationary solution of a nonparametric...

We analyze the asymptotic behaviour of kernel

This paper attempts to analyze the impact of German unification on the position that Germany holds within the European Monetary System (EMS), i.\ e.\ on the asymmetry in the EMS. Applying kernel estimation and bootstrap methods we can corroborate the result of previous studies that Germany's...

This paper shows the uniform consistency in probability of a modified kernel estimator towards the Baire function representing the conditional variance provided the data generating process is given by a strictly stationary solution of a parametric ARCH(q)- model.