This paper presents estimation methods and asymptotic theory for the analysis of a nonparametrically specified conditional quantile process. Two estimators based on local linear regressions are proposed. The first estimator applies simple inequality constraints while the second uses...

For classification problems with ordinal attributes very often the class attribute should increase with each or some of the explaining attributes. These are called classification problems with monotonicity constraints. Classical decision tree algorithms such as CART or C4.5 generally do not...

We addresses a variant of the classical one dimensional bin-packing problem where several types of bins with unequal sizes and costs are presented. Each bin-type includes limited and/or unlimited identical bins. The goal is to minimize the total cost of bins needed to store a given set of items,...

For classification problems with ordinal attributes very often the class attribute should increase with each or some of the explaining attributes. These are called classification problems with monotonicity constraints. Classical decision tree algorithms such as CART or C4.5 generally do not...

I extend Myersonʼs [R. Myerson, Optimal auction design, Math. Oper. Res. 6 (1981) 58–73] ironing technique to more general objective functions. The approach is based on a generalized notion of virtual surplus which can be maximized pointwise even when the monotonicity constraint implied by...

In nonparametric mean regression various methods for bandwidth choice exist. These methods can roughly be divided into plug-in methods and methods based on penalizing functions. This paper uses the approach based on penalizing functions and adapt it to nonparametric quantile regression...

There are many environments in econometrics which require nonseparable modeling of a structural disturbance. In a nonseparable model, key conditions are validity of instrumental variables and monotonicity of the model in a scalar unobservable. Under these conditions the nonseparable model is...

In nonparametric mean regression various methods for bandwidth choice exist. These methods can roughly be divided into plug-in methods and methods based on penalizing functions. This paper uses the approach based on penalizing functions and adapt it to nonparametric quantile regression...