This paper addresses the problem of estimation of a nonparametric regression function from selectively observed data …-step estimation procedures are proposed and their rates of convergence are derived. Pointwise asymptotic distribution of the …

unconditional moment estimation. In the empirical application, we focus on two diff erent applications. We estimate the association …

model we exploit the link between the Asymmetric Laplace Distribution and maximum likelihood estimation for quantile …-variance relationship. Mean Squared Error estimation is discussed. Extensive model-based simulations are used for comparing the proposed …

Modern systems of official statistics require the timely estimation of area-specific densities of sub …-parametric kernel density estimation that reverses the rounding process by using a Bayesian measurement error model. The methodology is …

kernel density estimates (KDE) offer advantages over classical choropleth maps. However, kernel density estimation needs … aggregates for kernel density estimation. Their algorithm simulates "exact" geo-coordinates which reflect the information on the …, the original algorithm is modified to cope with the estimation of a ratio of two densities. Our empirical examples refer …