This paper is concerned with the nonparametric estimation of regression quantiles where the response variable is randomly censored. Using results on the strong uniform convergence of U-processes, we derive a global Bahadur representation for the weighted local polynomial estimators, which is...

The problem of predicting 0-1-events is considered under general conditions, including stationary processes with short and long memory as well as processes with changing distribution patterns. Nonparametric estimates of the probability function and prediction intervals are obtained.

The paper continues the authors’ work (Freise et al. The adaptive Wynn-algorithm in generalized linear models with univariate response. arXiv:1907.02708, 2019) on the adaptive Wynn algorithm in a nonlinear regression model. In the present paper the asymptotics of adaptive least squares...

This paper provides an example of a linear regression model with predetermined stochastic regressors for which the sufficient condition for strong consistency of the ordinary least squares estimator by Lai & Wei (1982, Annals of Statistics) is not met. Nevertheless, the estimator is strongly...

This paper investigates the asymptotic properties of the ordinary least squares (OLS) estimator of structural parameters in a stylised macroeconomic model in which agents are boundedly rational and use an adaptive learning rule to form expectations of the endogenous variable. In particular, when...

This paper compares two approaches to analyzing longitudinal discrete-time binary outcomes. Dynamic binary response models focus on state occupancy and typically specify low-order Markovian state dependence. Multi-spell duration models focus on transitions between states and typically allow for...

In this paper, we analyze the problem of congestion and quality loss of data transmission through the Internet from an economic perspective. We show that due to the congestion problem, quality sensitive services are likely to be crowded out by high volume but less quality sensitive applications...

This paper deals with optimal window width choice in non-parametric lag- or spectral window estimation of the spectral density of a stationary zero-mean process. Several approaches are reviewed: the cross-validation based methods described by Hurvich (1985), Beltrao & Bloomfield (1987) and...