- Referenced in 560 articles
- Lasso and elastic-net regularized generalized linear models. Extremely efficient procedures for fitting the entire ... linear regression, logistic and multinomial regression models, poisson regression and the Cox model. Two recent...
- Referenced in 426 articles
- ideas to several samples, semiparametric and smooth models. Significance and confidence intervals are the subjects ... with resampling methods appropriate for linear regression models, generalized linear models and nonlinear models...
- Referenced in 758 articles
- regression is based on penalized regression splines and mixed models. Every model in this book ... special case of the linear mixed model or its generalized counterpart. This book is very ... scientists with only a moderate background in regression, though familiarity with matrix and linear algebra ... have a good working knowledge of linear models and the desire to begin using more...
- Referenced in 491 articles
- with robust methods. This includes regression methodology including model selections and multivariate statistics where...
- Referenced in 96 articles
- package rms: Regression Modeling Strategies , Regression modeling, testing, estimation, validation, graphics, prediction, and typesetting ... functions for binary and ordinal logistic regression models and the Buckley-James multiple regression model ... models. rms works with almost any regression model, but it was especially written to work ... spatially correlated observations, generalized linear models, and quantile regression...
- Referenced in 119 articles
- squares estimates for a univariate nonlinear regression model and generalized least squares estimates ... multivariate nonlinear regression model. Use the SUR option for both. Other options...
- Referenced in 153 articles
- Competing Risks. Estimation, testing and regression modeling of subdistribution functions in competing risks, as described...
- Referenced in 103 articles
- model specification tests for parametric mean regression models and parametric quantile regression models, among others...
- Referenced in 123 articles
- general framework for finite mixtures of regression models using the EM algorithm. FlexMix provides...
- Referenced in 117 articles
- representations, such as linear and nonlinear regression models and generalized linear models. Many aspects...
- Referenced in 82 articles
- package timereg: Flexible regression models for survival data. Programs for Martinussen and Scheike (2006), ‘Dynamic ... Regression Models for Survival Data’, Springer Verlag. Plus more recent developments. Additive survival model, semiparametric ... cumulative residuals, excess risk models and more. Flexible competing risks regression including GOF-tests...
- Referenced in 94 articles
- structural equation models, and random-effects regression models that are based on continuous latent variables...
- Referenced in 94 articles
- free software for estimating structured additive regression models (). In addition, functions that allow...
- Referenced in 84 articles
- training and plotting classification and regression models...
- Referenced in 61 articles
- dating structural changes in (linear) regression models. strucchange features tests/methods from the generalized fluctuation test ... fluctuation processes. Finally, the breakpoints in regression models with structural changes can be estimated together...
- Referenced in 77 articles
- manipulation of discrete and limited dependent variable models, LIMDEP 10 is now unsurpassed ... forms of the linear regression model, and stochastic frontier, discrete choice and limited dependent variable...
- Referenced in 70 articles
- robustness against mis-specification of the probability model. In the Bayesian context, this is accomplished ... probability distributions or the space of all regression functions. Unfortunately, posterior distributions ranging over function ... implementation of some Bayesian nonparametric and semiparametric models in R, DPpackage. Currently, DPpackage includes models ... clustered data using generalized linear mixed models, and regression data using generalized additive models...
- Referenced in 62 articles
- depth measurements, atypical curves detection, regression models, supervised classification, unsupervised classification and functional analysis...
- Referenced in 40 articles
- fitting item response and latent regression models. It provides a comprehensive and flexible range ... models, multidimensional item response models, latent regression models and drawing plausible values...
- Referenced in 54 articles
- 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...