Best quadrature formulas and splines
From MaRDI portal
Publication:5921441
DOI10.1016/0021-9045(71)90040-2zbMath0228.41004OpenAlexW1993745359MaRDI QIDQ5921441
Publication date: 1971
Published in: Journal of Approximation Theory (Search for Journal in Brave)
Full work available at URL: https://doi.org/10.1016/0021-9045(71)90040-2
Related Items
Multivariate splines: a probabilistic perspective ⋮ On a class of best nonlinear approximation problems ⋮ Optimale Quadraturformeln und Perfektsplines ⋮ On a Method of Carasso and Laurent for Constructing Interpolating Splines ⋮ Asymptotically optimal quadrature rules for uniform splines over the real line ⋮ Comparison theorems for monosplines and best one-sided approximation ⋮ Best quadrature formulas and splines ⋮ The fundamental theorem of algebra for monosplines satisfying boundary conditions ⋮ Multiple zeros and applications to optimal linear functionals ⋮ On a nonlinear characterization problem for monosplines ⋮ Beste Quadraturformeln für Integrale mit einer Gewichtsfunktion ⋮ Splines with maximal zero sets ⋮ The sign-regularity properties of Green's functions for a special class of mixed boundary-value problems ⋮ A modern retrospective on probabilistic numerics ⋮ Beste Quadraturformeln für Inzidenzmatrizen ohne ungerade gestützte Sequenzen ⋮ Monotonicity of quadrature formulae of Gauss type and comparison theorems for monosplines ⋮ Quadrature formulae and Hermite-Birkhoff interpolation
Cites Work
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Einige Eigenschaften Wilfscher Quadraturformeln
- Periodic boundary-value problems with cyclic totally positive Green's functions with applications to periodic spline theory
- Total positivity, interpolation by splines, and Green's functions of differential operators
- On Monosplines of Least Deviation and Best Quadrature Formulae
- On Monosplines of Least Square Deviation and Best Quadrature Formulae II
- Designs for Regression Problems with Correlated Errors
- Designs for Regression Problems With Correlated Errors: Many Parameters
- On the Regression Design Problem of Sacks and Ylvisaker
- Minimal Interpolation and Approximation in Hilbert Spaces