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Journal Article
2011, ISBN 1420077554, xxiv, 370
Book
01/2019, ISBN 3038976679
.... The great need for reliable software in the scientific community conveys a continuous stimulus to develop new and better performing numerical methods that are able to grasp the particular features... 
structured matrices | curl | numerical methods | time fractional differential equations | hierarchical splines | finite difference methods | null-space | highly oscillatory problems | stochastic Volterra integral equations | differential equations | displacement rank | constrained Hamiltonian problems | Hermite | hyperbolic partial differential equations | higher-order finite element methods | continuous geometric average | Volterra integro | spectral (eigenvalue) and singular value distributions | generalized locally Toeplitz sequences | Obreshkov methods | B-spline | discontinuous Galerkin methods | adaptive methods | Cholesky factorization | energy-conserving methods | order | collocation method | Poisson problems | time harmonic Maxwell’s equations and magnetostatic problems | tree | multistep methods | stochastic differential equations | optimal basis | finite difference method | elementary differential | gradient system | Runge | conservative problems | line integral methods | stochastic multistep methods | Hamiltonian Boundary Value Methods | Kutta | limited memory | boundary element method | convergence | analytical solution | preconditioners | asymptotic stability | collocation methods | histogram specification | local refinement | edge-preserving smoothing | numerical analysis | THB-splines | BS methods | barrier options | stump | shock waves and discontinuities | mean-square stability | Volterra integral equations | high order discontinuous Galerkin finite element schemes | B-splines | vectorization and parallelization | initial value problems | one-step methods | scientific computing | fractional derivative | linear systems | Hamiltonian problems | low rank completion | ordinary differential equations | mixed-index problems | edge-histogram | Hamiltonian PDEs | matrix ODEs | HBVMs | floating strike Asian options | generalized Schur algorithm | Galerkin method | symplecticity | high performance computing | isogeometric analysis | discretization of systems of differential equations | curl operator
eBook
2016, 1, Chapman & Hall/CRC monographs on statistics & applied probability, ISBN 9781482219593, Volume 149, 298
.... Exploring the advantages of this approach, State-Space Methods for Time Series Analysis: Theory, Applications and Software presents many computational procedures that can be applied to a previously specified linear model in state-space form... 
Statistics for Business | Mathematics & Statistics for Engineers | Statistical Theory & Methods | Finance & Economics | Time-series analysis | State-space methods
eBook
1990, 1st ed., Monographs on statistics and applied probability, ISBN 0412343908, Volume 43., xv, 335
.... These methods relax the linear assumption of many standard models and allow analysts to uncover structure in the data that might otherwise have been missed... 
Modèles linéaires (Statistique) | Linear models (Statistics) | Smoothing (Statistics) | Regression analysis | Analyse de régression | Lissage (Statistique) | Statistical Theory & Methods
Book
2017, 1st ed., ISBN 9781118456057, 275
Comprehensive theoretical overview of kernel smoothing methods with motivating examples Kernel smoothing is a flexible nonparametric curve estimation method that is applicable when parametric... 
MATHEMATICS | Probability & Statistics | General | Smoothing (Statistics)
eBook
The annals of applied statistics, ISSN 1932-6157, 6/2012, Volume 6, Issue 2, pp. 719 - 752
...) the graph-guided-fused-lasso penalty, generalized from the fused-lasso penalty. For both types of penalties, due to their nonseparability and nonsmoothness, developing an efficient optimization method remains a challenging problem... 
Regression coefficients | Error rates | Approximation | Optimal solutions | Linear regression | Machine learning | Breast cancer | Mathematical vectors | Data smoothing | Gradient method | Proximal gradient | Structured sparsity | Sparse regression | Smoothing | Optimization | Statistics & Probability | Physical Sciences | Mathematics | Science & Technology | smoothing | optimization | structured sparsity | proximal gradient
Journal Article
2003, ISBN 9789812384560, xx, 449
Book
1993, 1, Pitman research notes in mathematics series, ISBN 0582234352, Volume 294., 161
Multigrid methods are among the most efficient iterative methods for the solution of linear systems which arise in many large scale scientific calculations... 
Multigrid methods (Numerical analysis) | Differential Equations
Book
09/2018, Chapman & Hall/CRC Monographs on Statistics and Applied Probability, ISBN 9781482219593, 298
.... Exploring the advantages of this approach, State-Space Methods for Time Series Analysis: Theory, Applications and Software presents many computational procedures that can be applied to a previously specified linear model in state-space form... 
Mathematics & Statistics for Engineers | STMnetBASE | SCI-TECHnetBASE | VARMAX | STATSnetBASE | Filtering and smoothing | state-space model | subspace methods | time series | state-space representation | E4 MATLAB toolbox | signal extraction | Missing data | Statistical Theory & Methods | model estimation | Statistics for Business, Finance & Economics
eBook
SIAM review, ISSN 0036-1445, 3/2010, Volume 52, Issue 1, pp. 113 - 147
Journal Article