- Referenced in 761 articles
- regression texts treat either parametric or nonparametric regression exclusively. In this book the authors argue ... that nonparametric regression can be viewed as a relatively simple extension of parametric regression...
- Referenced in 1018 articles
- simplest nonparametric curve estimation setting, namely density and regression estimation. Special attention is given...
- Referenced in 67 articles
- ftnonpar: Features and Strings for Nonparametric Regression. The package contains R-functions to perform ... methods in nonparametric regression and density estimation, described in Davies, P. L. and Kovac...
- Referenced in 71 articles
- package sm: Smoothing methods for nonparametric regression and density estimation. This is software linked...
- Referenced in 438 articles
- regression, categorical data analysis, multivariate analysis, survival analysis, psychometric analysis, cluster analysis, and nonparametric analysis...
- Referenced in 99 articles
- BART: Bayesian additive regression trees. We develop a Bayesian “sum-of-trees” model where each ... posterior. Effectively, BART is a nonparametric Bayesian regression approach which uses dimensionally adaptive random basis...
- Referenced in 36 articles
- Wavelet Estimators in Nonparametric Regression: A Comparative Simulation Study. Wavelet analysis has been found ... powerful tool for the nonparametric estimation of spatially-variable objects ... discuss in detail wavelet methods in nonparametric regression, where the data are modelled as observations...
- Referenced in 64 articles
- Based Models: Implementation of BART: Bayesian Additive Regression Trees. We develop a Bayesian ... posterior. Effectively, BART is a nonparametric Bayesian regression approach which uses dimensionally adaptive random basis...
- Referenced in 24 articles
- Generalized linear, mixed effects and nonparametric regression models. Linear models are central to the practice ... surveys the techniques that grow from the regression model, presenting three extensions to that framework ... models (GLMs), mixed effect models, and nonparametric regression models. The author’s treatment is thoroughly...
- Referenced in 31 articles
- CMARS: A new contribution to nonparametric regression with multivariate adaptive regression splines supported by continuous...
- Referenced in 21 articles
- bnpmr: Bayesian monotonic nonparametric regression. Implements the Bayesian nonparametric monotonic regression method described in Bornkamp...
- Referenced in 461 articles
- with single samples from parametric and nonparametric models. Chapter 3 extends the basic ideas ... deal with resampling methods appropriate for linear regression models, generalized linear models and nonlinear models...
- Referenced in 22 articles
- distribution function from contaminated data; (2) nonparametric regression model with errors-in-variables...
- Referenced in 111 articles
- nonparametric tests of significance and consistent model specification tests for parametric mean regression models...
- Referenced in 317 articles
- Smoothing spline ANOVA models Nonparametric function estimation with stochastic data, otherwise known as smoothing ... unified framework. Methods are developed for (i) regression with Gaussian and non-Gaussian responses...
- Referenced in 72 articles
- DPpackage: Bayesian Semi- and Nonparametric Modeling in R. Data analysis sometimes requires the relaxation ... probability distributions or the space of all regression functions. Unfortunately, posterior distributions ranging over function ... programs for the implementation of some Bayesian nonparametric and semiparametric models in R, DPpackage. Currently ... characteristic curve analysis, interval-censored data, binary regression data, item response data, longitudinal and clustered...
- Referenced in 10 articles
- package erboost: Nonparametric Multiple Expectile Regression via ER-Boost. Expectile regression is a nice tool ... based gradient boosting estimator for nonparametric multiple expectile regression...
- Referenced in 58 articles
- package MNM: Multivariate Nonparametric Methods. An Approach Based on Spatial Signs and Ranks , The package ... sample problems, shape estimation and testing, linear regression and principal components...
- Referenced in 7 articles
- multivariate regression smoothers. This paper presents a practical and simple fully nonparametric multivariate smoothing procedure ... underlying smoothness of the true regression function. Our estimator is easily computed by successive application ... knowledge, no other adaptive fully nonparametric regression estimator is available without constrained assumption such ... available at CRAN, implements the proposed multivariate nonparametric method...
- Referenced in 5 articles
- Implementation of Bayesian Adaptive Regression Splines (BARS) in C with S and R Wrappers. BARS ... engine to perform spline-based generalized nonparametric regression. It has been shown to work well...