distribution. We generalize the iterative Plug-in algorithm for local linear quantile regression with double kernel smoothing in … section (4.5). In section (4.6), we present an iterative-Plug-in algorithm for the local linear quantile regression. In … section (4.7), we discuss the consistency and the asymptotic normality of the plug-in algorithm. In chapter 5, we apply the …

We describe an algorithm that is able to compute the solution of a singular linear difference system under rational … expectations. The algorithm uses the Generalized Schur Factorization and is illustrated by a simple example. …

regarding continuity, subadditivity, and monotonicity. We present an exact algorithm to compute the weighted-mean trimmed …, the algorithm builds on methods from computational geometry. A characterization of a region's facets is used, and … solved by the introduction of a tree-based order. The algorithm has been programmed in C++ and is available as an R package. …

periods with a high degree of precision. We use the iterative cumulative sum of squares algorithm to detect multiple shifts in …

uses the Expectation-Maximization (EM) algorithm. The EM algorithm is sensitive to initial values of HMM parameters and is …

In this paper an algorithm is proposed to find an integral solution of (nonlinear) complementarity problems. The … algorithm starts with a nonnegative integral point and generates a unique sequence of adjacent integral simplices of varying … dimension. Conditions are stated under which the algorithm terminates with a simplex one of whose vertices is an integral …

provide a polynomial time algorithm for computing the nucleolus of the restricted games corresponding to a class of games with …

; we will also describe an algorithm that computes the universal basin of attraction of a social outcome in O(M3 log M …