In a large class of statistical inverse problems it is necessary to suppose that the transformation that is inverted is known. Although, in many applications, it is unrealistic to make thisâ€¦ (More)

It is common, in deconvolution problems, to assume that the measurement errors are identically distributed. In many real life applications however, this condition is not satisfied and theâ€¦ (More)

Kernel methods for deconvolution have attractive features, and prevail in the literature. However, they have disadvantages, which include the fact that they are usually suitable only for cases whereâ€¦ (More)

Group testing is a procedure employed to reduce the cost and increase the speed of large screening studies where infection or contamination of individuals is detected by a test carried out on aâ€¦ (More)

The triangular model is a very popular way to capture endogeneity. In this model, an outcome is determined by an endogenous regressor, which in turn is caused by an instrument in a first stage. Inâ€¦ (More)

Abstract: This paper deals with the problem of estimating a density based on observations which are contaminated by a normally distributed error whose variance is unknown. In the case of a completelyâ€¦ (More)

In the classical errors-in-variables problem, the goal is to estimate a regression curve from data in which the explanatory variable is measured with error. In this context, nonparametric methodsâ€¦ (More)

In the popular deconvolution problem, the goal is to estimate a curve f from data that only allow direct estimation of another curve g, the convolution of f and a so-called error density. Unlike theâ€¦ (More)

Technology and health care : official journal ofâ€¦

1997

The effects of chronic toxic occupational factors and functional disorders of the central nervous system (CNS) in chemical industry were studied. These factors cause various stages of chronicâ€¦ (More)

Abstract: We consider a statistical experiment where two types of contaminated data are observed. Therein, both data sets are affected by additive measurement errors but the scaling factors of theâ€¦ (More)