• gbm

  • Referenced in 55 articles [sw07994]
  • Generalized Boosted Regression Models. This package implements extensions to Freund and Schapire’s AdaBoost algorithm ... Friedman’s gradient boosting machine. Includes regression methods for least squares, absolute loss, t-distribution...
  • VisualUTA

  • Referenced in 112 articles [sw16231]
  • value functions which result from an ordinal regression. The preference information provided by the decision ... called reference alternatives. The preference model built via ordinal regression ... compatible with the preference information. Using this model, one can define two relations...
  • SAS/STAT

  • Referenced in 438 articles [sw18788]
  • statistical analyses, including analysis of variance, regression, categorical data analysis, multivariate analysis, survival analysis, psychometric ... nonparametric analysis. A few examples include mixed models, generalized linear models, correspondence analysis, and structural...
  • BLINPLUS

  • Referenced in 32 articles [sw37140]
  • error in one or more model covariates logistic regression coefficients, their standard errors, and odds ... specified by the user (the ”weights”). Regression model parameters from Cox models (PROC PHREG ... linear regression models (PROC REG) can also be corrected. A validation study is required...
  • StFinMetrics

  • Referenced in 38 articles [sw29976]
  • fractional ARIMA and GARCH); time series regression modelling and systems of regression equations; state space...
  • quantreg

  • Referenced in 162 articles [sw04356]
  • package quantreg: Quantile Regression. Estimation and inference methods for models of conditional quantiles: Linear...
  • SINDy

  • Referenced in 29 articles [sw30277]
  • recently proposed data-driven modelling framework that uses sparse regression techniques to identify nonlinear ... models. With the goal of low-order models of a fluid flow, we combine this ... models, hereafter referred to as Galerkin regression models, incorporate many beneficial aspects of Galerkin projection ... data and satisfies necessary constraints. Galerkin regression models also readily generalize to include higher-order...
  • PcGets

  • Referenced in 44 articles [sw01937]
  • RETINA with PcGets, a well-known automatic modeling method proposed by D. Hendry. We point ... sample over the usual linear regression model and over some models like PcGets. Thus, both...
  • betareg

  • Referenced in 51 articles [sw15449]
  • package betareg: Beta Regression. Beta regression for modeling beta-distributed dependent variables, e.g., rates ... proportions. In addition to maximum likelihood regression (for both mean and precision of a beta ... well as finite mixture models and recursive partitioning for beta regressions are provided...
  • gss

  • Referenced in 317 articles [sw06099]
  • settings number far less. Smoothing spline ANOVA models are a versatile family of smoothing methods ... unified framework. Methods are developed for (i) regression with Gaussian and non-Gaussian responses ... likelihood method and the construction of multivariate models with built-in ANOVA decompositions. Extensive discussions ... devoted to model construction, smoothing parameter selection, computation, and asymptotic convergence. Most of the computational...
  • ordinal

  • Referenced in 30 articles [sw12561]
  • package ordinal: Regression Models for Ordinal Data. Implementation of cumulative link (mixed) models also known ... ordered regression models, proportional odds models, proportional hazards models for grouped survival times and ordered...
  • CAViaR

  • Referenced in 189 articles [sw04424]
  • CAViaR: Conditional autoregressive value at risk by regression quantiles. Value at risk ... conditional autoregressive value at risk (CAViaR) model specifies the evolution of the quantile over time ... autoregressive process and estimates the parameters with regression quantiles. Utilizing the criterion that each period ... information, we introduce a new test of model adequacy, the dynamic quantile test. Applications...
  • spdep

  • Referenced in 39 articles [sw04578]
  • unweighted SAR and CAR spatial regression models, semi-parametric and Moran eigenvector spatial filtering...
  • party

  • Referenced in 28 articles [sw07330]
  • inference trees which embed tree-structured regression models into a well defined theory of conditional ... inference procedures. This non-parametric class of regression trees is applicable to all kinds ... parametric models (e.g. linear models, GLMs or survival regression) employing parameter instability tests for split ... Extensible functionality for visualizing tree-structured regression models is available...
  • faraway

  • Referenced in 24 articles [sw04357]
  • Generalized linear, mixed effects and nonparametric regression models. Linear models are central to the practice ... Faraway’s critically acclaimed Linear Models with R examined regression and analysis of variance, demonstrated ... techniques that grow from the regression model, presenting three extensions to that framework: generalized linear ... GLMs), mixed effect models, and nonparametric regression models. The author’s treatment is thoroughly modern...
  • KernSmooth

  • Referenced in 1008 articles [sw04586]
  • sets without the imposition of a parametric model. The main goal of this book ... nonparametric curve estimation setting, namely density and regression estimation. Special attention is given...
  • gcmr

  • Referenced in 31 articles [sw07433]
  • class of Gaussian copula models for marginal regression analysis of non-normal dependent observations ... natural extension of traditional linear regression models with normal correlated errors. Any kind of continuous ... validating the adequacy of the assumed multivariate model. Methodology is implemented in a R package ... data, longitudinal studies, survival analysis and spatial regression...
  • glmmAK

  • Referenced in 28 articles [sw13218]
  • estimation in the logistic regression with both binary (logit model) and multinomial response (cumulative logit ... model), and in the Poisson regression (log-linear model). Secondly, Bayesian estimation based ... MCMC in the logistic and Poisson regression model with random effects whose distribution is specified...
  • metafor

  • Referenced in 33 articles [sw12291]
  • mixed-effects models to such data, carry out moderator and meta-regression analyses, and create ... variety of suitable generalized linear (mixed-effects) models ... mixed-effects (conditional) logistic and Poisson regression models). Finally, the package provides functionality for fitting...
  • rstanarm

  • Referenced in 25 articles [sw15609]
  • package rstanarm: Bayesian Applied Regression Modeling via Stan. Estimates pre-compiled regression models using...