We propose a new method to find spatially adaptive smoothing splines. This new method breaks down the interval [0, 1] into p disjoint sub-intervals. Then we define p functional components in [0, 1], which have two importantfeatures. First, the purpose of each of these p components is to estimate...

We introduce a new method to robustifying inference that can be applied in any situation where a parametric likelihood is available. The key feature is that data from the postulated parametric models are assumed to be measured with error where the measurement error distribution is chosen to...

In many clinical studies, researchers are mainly interested in studying the effects of some prognostic factors on the hazard of failure from a specific cause while individuals may failure from multiple causes. This leads to a competing risks problem. Often, due to various reasons such as finite...

Inference on treatment effect in a pretest–posttest study is a routine objective in medicine, public health, and other fields, and a number of approaches have been advocated. Typically, subjects are randomized to two treatments, the response is measured at baseline and a prespecified...

Stochastic Volatility (SV) models play an integral role in modeling time varyingvolatility, with widespread application in finance. Due to the absence of a closed form likelihoodfunction, estimation is a challenging problem. In the presence of outliers, and the highkurtosis prevalent in...

This thesis investigates the determinants of the use of debt and leasing in the UK using a comprehensive measure of debt and leases, in recognition of the link between lease and debt-type financing decisions, based on financial contracting theory and the tax advantage hypothesis. The design of...

In vielen Anwendungen ist es notwendig, die stochastische Schwankungen der maximalen Abweichungen der nichtparametrischen Schätzer von Quantil zu wissen, zB um die verschiedene parametrische Modelle zu überprüfen. Einheitliche Konfidenzbänder sind daher für nichtparametrische Quantil...

Let (X1, Y1), . . ., (Xn, Yn) be i.i.d. rvs and let l(x) be the unknown p-quantile regression curve of Y on X. A quantile-smoother ln(x) is a localised, nonlinear estimator of l(x). The strong uniform consistency rate is established under general conditions. In many applications it is necessary...

In 1978, Roger Koenker and Gilbert Bassett, Jr. introduced a new econometric estimation method and entitled it quantile regression. Since then, many subsequent authors have elaborated and extended the underlying theoretical framework. Other contributions have successfully applied the procedure...

We estimate the public wage gap in France for the period 1990-2002, both at the mean andat different quantiles of the wage distribution, for men and women separately. We account forunobserved heterogeneity by using fixed effects estimations on panel data and, departingfrom usual practice, allow...