- Referenced in 978 articles
- Kernel smoothing refers to a general methodology for recovery of the underlying structure in data ... required for a comprehensive understanding of kernel smoothing, and hence smoothing problems in general ... given to the problem of choosing the smoothing parameter.par For the study of the book ... research in the field of kernel smoothing. But the bibliographical notes...
- Referenced in 631 articles
- pages, is devoted to the optimization of smooth functions. The methods studied in this first ... treatment of both, optimization methods for smooth and for noisy functions is a unique feature...
- Referenced in 551 articles
- effective for solving constrained optimization problems with smooth nonlinear functions in the objective and constraints ... discuss an SQP algorithm that uses a smooth augmented Lagrangian merit function and makes explicit...
- Referenced in 758 articles
- interest even to experts on smoothing, and they are a third possible audience. This book...
- Referenced in 293 articles
- Smoothing spline ANOVA models Nonparametric function estimation with stochastic data, otherwise known as smoothing ... ample desktop and laptop computing power, smoothing methods are now finding their ways into everyday ... methods have proved successful for univariate smoothing, ones practical in multivariate settings number far less ... Smoothing spline ANOVA models are a versatile family of smoothing methods derived through roughness penalties...
- Referenced in 458 articles
- both. The nonlinear functions must be smooth. Stable numerical methods are employed throughout. Features include...
- Referenced in 426 articles
- basic ideas to several samples, semiparametric and smooth models. Significance and confidence intervals...
- Referenced in 344 articles
- accessible and the author used a fairly smooth way even in the case of advanced...
- Referenced in 329 articles
- choose various multigrid cycles, transfer operators, smoothing methods, and nested iteration, and defect correction. Cell...
- Referenced in 147 articles
- Fortran 77 subroutines for minimizing a smooth function subject to constraints, which may include simple ... bounds on the variables, linear constraints, and smooth nonlinear constraints. The user provides subroutines...
- Referenced in 197 articles
- effective for solving linear, quadratic, and nonlinear smooth optimization problems, both convex and nonconvex...
- Referenced in 155 articles
- analysing univariate time series forecasts including exponential smoothing via state space models and automatic ARIMA...
- Referenced in 153 articles
- combination. They are designed to interact very smoothly. Computer algebra system (CAS). Education...
- Referenced in 148 articles
- consider the problem of minimizing a smooth objective function f of n real variables...
- Referenced in 142 articles
- statistics, Fry plots, pair correlation function, kernel smoothed intensity, relative risk estimation with cross-validated...
- Referenced in 142 articles
- package of Fortran subroutines for calculating smoothing splines for various kinds of data and geometries...
- Referenced in 99 articles
- mgcv: Mixed GAM Computation Vehicle with GCV/AIC/REML smoothness estimation. Routines for GAMs and other generalized ... ridge regression with multiple smoothing parameter selection by GCV, REML or UBRE/AIC. Also GAMMs. Includes...
- Referenced in 133 articles
- already quite immense. This paper applies a smoothing technique and an accelerated first-order algorithm...
- Referenced in 129 articles
- user to write their own wavelet smoothing routine making use of the function ebayesthresh...
- Referenced in 125 articles
- black-box classes to construct highly-scalable smoothed aggregation preconditioners. ML preconditioners have been used...