• # nprobust

• Referenced in 2 articles [sw30833]
• Robust Estimation and Inference Methods using Local Polynomial Regression and Kernel Density Estimation. Tools ... statistical analysis using local polynomial regression and kernel density estimation methods as described in Calonico ... local polynomial point estimation and robust bias-corrected inference, lpbwselect() for local polynomial bandwidth selection ... kdrobust() for kernel density point estimation and robust bias-corrected inference, kdbwselect() for kernel density...
• # SPEED

• Referenced in 32 articles [sw08653]
• deal with a non-uniform polynomial degree distribution as well as a locally varying mesh ... kernel, whereas illustrative examples are discussed to highlight the engineering applications of the method...
• # npsp

• Referenced in 3 articles [sw31433]
• classes and methods for multidimensional: linear binning, local polynomial kernel regression, density and variogram estimation...
• # SingularIntegralEquations

• Referenced in 10 articles [sw22771]
• singular integral equations. We develop a spectral method for solving univariate singular integral equations over ... intervals by utilizing Chebyshev and ultraspherical polynomials to reformulate the equations as almost-banded infinite ... approximations for sparse representations of the bivariate kernels. The resulting system can be solved ... Julia software package ‘SingularIntegralEquations.jl’ implements our method with a convenient, user-friendly interface...
• # kerdec

• Referenced in 1 article [sw39523]
• methods, including multivariate kernel deconvolution density estimation and deconvolution version of local constant polynomial regression...
• # ChebCoInt

• Referenced in 4 articles [sw32042]
• Approximating the approximant: A numerical code for polynomial compression of discrete integral operators. The action ... integral operators, discretized by a suitable quadrature method, can be compressed and accelerated by means ... with respect to other well-known fast methods: its effectiveness rests on the “smoothing effect ... nonlinear instances, with both smooth and nonsmooth kernels. We describe a Matlab toolbox which implements...
• # Algorithm 967

• Referenced in 6 articles [sw23693]
• sums with volume integrals. Particle $N$-body methods can be used to accelerate such integrals ... high-order piecewise Chebyshev polynomials and an octree data structure to represent the input ... approximation of the near-field and the Kernel Independent FMM (KIFMM) for the far-field...
• # npbr

• Referenced in 1 article [sw15636]
• approaches to nonparametric boundary estimation. The selected methods are concerned with empirical, smoothed, unrestricted ... based on piecewise polynomials, splines, local linear fitting, extreme values and kernel smoothing. The package ... Monte Carlo comparisons among these different estimation methods. Its use is illustrated via a number...
• # smoots

• Referenced in 1 article [sw35248]
• estimated. The estimation is conducted via local polynomial regression using an automatically selected bandwidth obtained ... Nadaraya-Watson kernel smoother is also built-in as a comparison. The methods...
• # ViennaMath

• Referenced in 1 article [sw12918]
• open-source implementation of a symbolic math kernel in C++. The library provides a unified ... such as implementations of the finite element method. A non-exhaustive list of features ... differentiation of arbitrary expressions; Symbolic integration of polynomials; LaTeX converter: Directly generates LaTeX code from...
• # SympGPR

• Referenced in 1 article [sw39176]
• method, whereas a sum kernel results in a fast explicit method from this approach. Both ... methods in terms of numerical integration but fulfill a complementary purpose. The developed methods ... regression of the flow map with orthogonal polynomials. Chaotic behavior is studied on the standard...
• # scgwr

• Referenced in 1 article [sw28372]
• large-scale geographically weighted regression with polynomial kernels. While a number of studies have developed ... Monte Carlo simulation. Then, we apply these methods to a residential land analysis...
• # iMPTCE-Hnetwork

• Referenced in 1 article [sw39601]
• alternative pipeline is to design efficient computational methods. In this study, we proposed a powerful ... which incorporated the support vector machine (polynomial kernel) as the basic classifier. The ten-fold...