
StatLSSVM
 Referenced in 1 article
[sw24463]
 Nonparametric Regression via StatLSSVM. We present a new MATLAB toolbox under Windows and Linux ... nonparametric regression estimation based on the statistical library for least squares support vector machines (StatLSSVM ... necessary in order to perform standard nonparametric regression, regression with correlated errors and robust regression...

semsfa
 Referenced in 2 articles
[sw33881]
 first step semiparametric or nonparametric regression techniques are used to relax parametric restrictions...

regtools
 Referenced in 1 article
[sw27435]
 Tools. Tools for linear, nonlinear and nonparametric regression and classification. Parametric fit assessment using nonparametric ... multiclass classification. Nonparametric regression for general dimension, locallylinear option. Nonlinear regression with EickertWhite...

regpro
 Referenced in 1 article
[sw19267]
 package regpro: Nonparametric Regression. Tools are provided for (1) nonparametric regression (kernel, local linear...

NonpModelCheck
 Referenced in 1 article
[sw15235]
 Model Checking and Variable Selection in Nonparametric Regression. Provides tests of significance for covariates ... groups of covariates) in a fully nonparametric regression model and a variable (or group) selection...

groc
 Referenced in 1 article
[sw24173]
 Components. Robust multiple or multivariate linear regression, nonparametric regression on orthogonal components, classical or robust...

npROCRegression
 Referenced in 1 article
[sw32474]
 Nonparametric ROC Regression Modelling. Implements several nonparametric regression approaches for the inclusion of covariate information...

pyStoNED
 Referenced in 1 article
[sw40063]
 Regression and Frontier Estimation. Shapeconstrained nonparametric regression is a growing area in econometrics, statistics ... expectile regression have bridged the longstanding gap between the conventional deterministicnonparametric and stochastic ... userfriendly tool for the multivariate convex regression, convex ... quantile regression, convex expectile regression, isotonic regression, stochastic nonparametric envelopment of data, and related methods...

MedTree
 Referenced in 3 articles
[sw12469]
 which is of use for nonparametric discrimination and regression. In this paper, we present...

monreg
 Referenced in 2 articles
[sw25513]
 package monreg: Nonparametric Monotone Regression. Estimates monotone regression and variance functions in a nonparametric model...

quantreg.nonpar
 Referenced in 1 article
[sw37935]
 Nonparametric Series Quantile Regression. Implements the nonparametric quantile regression method developed by Belloni, Chernozhukov ... derivatives based on series approximations to the nonparametric part of the model. Provides pointwise...

haldensify
 Referenced in 1 article
[sw35416]
 Algorithms for nonparametric estimation of conditional densities based on a pooled hazard regression formulation ... highly adaptive lasso, a nonparametric regression function for efficient estimation with fast convergence under mild...

acepack
 Referenced in 2 articles
[sw32424]
 AVAS for Selecting Multiple Regression Transformations. Two nonparametric methods for multiple regression transform selection...

cosso
 Referenced in 1 article
[sw23471]
 package cosso: Fit Regularized Nonparametric Regression Models Using COSSO Penalty. COSSO is a new regularization...

McSpatial
 Referenced in 2 articles
[sw16522]
 Locally weighted regression, semiparametric and conditionally parametric regression, fourier and cubic spline functions ... probit, kdensity functions and counterfactuals, nonparametric quantile regression and conditional density functions, MachadoMata...

KyPlot
 Referenced in 2 articles
[sw00496]
 least squares or maximum likelihood methods, polynomial regression, Bspline fitting, piecewise polynomial interpolation ... procedures, such as various parametric and nonparametric tests, regression analysis, procedures for multivariate analysis (principal...

CVTresh
 Referenced in 1 article
[sw25942]
 core of the wavelet approach to nonparametric regression is thresholding of wavelet coefficients. This paper...

MOTABAR
 Referenced in 2 articles
[sw12739]
 Moving Taylor Bayesian regression for nonparametric multidimensional function estimation with possibly correlated errors. We study ... novel nonparametric method for estimating the value and several derivatives of an unknown, sufficiently smooth ... correlation structure. The method, moving Taylor Bayesian regression (MOTABAR), uses Bayesian updating to find...

BART
 Referenced in 5 articles
[sw32161]
 Regression Trees. Bayesian Additive Regression Trees (BART) provide flexible nonparametric modeling of covariates for continuous...

lspartition
 Referenced in 2 articles
[sw30834]
 package lspartition: Nonparametric Estimation and Inference Procedures using PartitioningBased Least Squares Regression. Tools ... statistical analysis using partitioningbased least squares regression as described in Cattaneo, Farrell and Feng ... Feng (2019b, ): lsprobust() for nonparametric point estimation of regression functions and their derivatives...