Smoothing techniques for curve estimation : proceedings of workshop held in Heidelberg, April 2-4, 1979

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Bibliographic Information

Smoothing techniques for curve estimation : proceedings of workshop held in Heidelberg, April 2-4, 1979

edited by Th. Gasser and M. Rosenblatt

（Lecture notes in mathematics, 757）

Springer-Verlag, 1979

  • : Berlin
  • : New York

Available at  / 76 libraries

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Note

"The workshop ... has taken place as part of the activities of the Sonderforschungsbereich 123, "Stochastic Mathematical Models."

Includes bibliographies and index

Description and Table of Contents

Volume

: New York ISBN 9780387097060

Description

Parallel Scientific Computing and Optimization introduces new developments in the construction, analysis, and implementation of parallel computing algorithms. This book presents 23 self-contained chapters, including survey chapters and surveys, written by distinguished researchers in the field of parallel computing. Each chapter is devoted to some aspects of the subject: parallel algorithms for matrix computations, parallel optimization, management of parallel programming models and data, with the largest focus on parallel scientific computing in industrial applications. This volume is intended for scientists and graduate students specializing in computer science and applied mathematics who are engaged in parallel scientific computing.

Table of Contents

Preface.- Part I Parallel Algorithms for Matrix Computations.- RECSY and SCASY Library Software: Recursive Blocked and Parallel Algorithms for Sylvester-type Matrix Equations with Some Applications.- Parallelization of Linear Algebra Algorithms Using ParSol Library of Mathematical Objects.- The Developments of an Object-Oriented Parallel Block Preconditioning Framework.- A Sparse Linear System Solver Used in a Distributed and Heterogenous Grid Computing Environment.- Parallel Diagonalization Preformance on High Performance Computers.- Part II Parallel Optimization.- Parallel Global Optimization in Multidimensional Scaling.- High Performance Parallel Support Vector Machine Training.- Parallel Branch and Bound Algorithm with Combination of Lipschitz Bounds over Multidimensional Simplices for Multicore Computers.- Experimental Investigation of Local Searches for Optimization of Grillage-Type Foundations.- Part III Management of Parallel Programming Models and Data.- Comparison of the UK National Supercomputer Services: HPCx and HECToR.- DL_POLY_3 I/O: Analysis, Alternatives, and Future Strategies.- Mixed Mode Programming on HPCx.- A Structure Conveying Parallelisable Modelling Language for Mathematical Programming.- Computational Requirements for Pulsar Searches with the Square Kilometre Array.- Part IV Parallel Scientific Computing in Industrial Applications.- Parallel Multiblock Multigrid Algorithms for Poroelastic Models.- A Parallel Solver for the 3D Simulation of Flows Through Oil Filters.- High Performance Computing in Jet Aerodynamics.- Parallel Numerical Solver for the Simulation of the Heat Conduction in Electrical Cables.- Orthogonalization Procedure for Antisymmetrization of j-shell States.- Parallel Direct Numerical Simulation of an Annular Gas-Liquid Two-Phase Jet with Swirl.- Parallel Numerical Algorithm for the Traveling Wave Model.- Parallel Algorithm for Cell Dynamics Simulation of Soft Nano-Structured Matter.- Docking and Molecular Dynamics Simulationof Complexes of High and Low Reactive Substrates with Peroxidases.- Index.
Volume

: Berlin ISBN 9783540097068

Table of Contents

Nonparametric curve estimation.- A tree-structured approach to nonparametric multiple regression.- Kernel estimation of regression functions.- Total least squares.- Some theoretical results on Tukey's 3R smoother.- Bias- and efficiency-robustness of general M-estimators for regression with random carriers.- Approximate conditional-mean type smoothers and interpolators.- Optimal convergence properties of kernel estimates of derivatives of a density function.- Density quantile estimation approach to statistical data modelling.- Global measures of deviation for kernel and nearest neighbor density estimates.- Some comments on the asymptotic behavior of robust smoothers.- Cross-validation techniques for smoothing spline functions in one or two dimensions.- Convergence rates of "thin plate" smoothing splines wihen the data are noisy.

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