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 Topic > Regression Models
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20 projects in result set.
0. arm - R functions for processing lm, glm, mer and polr outputs.
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Registered: 2008-04-09 23:40 |
1. partykit: Recursive Partytioning Toolkit - Infrastructure for representing, summarizing, and visualizing tree-structured models. It can be used for constructing or reading tree models from different sources (rpart, RWeka, PMML), sharing
functionality for print/plot/predict methods.
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- Topic : Machine Learning : Recursive Partitioning [Filter]
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- Topic : Software Development [Filter]
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Registered: 2008-09-30 11:39 |
2. blupsurv - Tools for fitting proportional hazards models to clustered
recurrent events data. Nested frailties are modeled by their
best linear unbiased predictors under an auxiliary Poisson model.
Univariate and bivariate recurrent events processes are permitted.
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- Development Status : 4 - Beta [Filter]
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- Topic : Biostatistics & Medical Statistics [Filter]
- Topic : Multivariate Statistics [Filter]
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Registered: 2008-06-14 13:52 |
3. splinesurv - A package containing utilities for nonparametric Bayesian analysis of clustered survival data. The baseline hazard function and frailty density are modeled using penalized B-splines. Regression and spline parameters are estimated via MCMC.
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- Topic : Bayesian Statistics : Specific Model Fitting [Filter]
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- Topic : Regression Models [Filter]
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Registered: 2008-01-08 16:50 |
4. Classification and Regression Training - The caret packages contain functions for tuning predictive models, pre-processing, variable importance and other tools related to machine learning and pattern recognition. Parallel processing versions of the main package are also included.
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- Topic : Machine Learning : Model Selection and Validation [Filter]
- Topic : Regression Models [Filter]
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Registered: 2008-06-05 19:31 |
5. Bias reduction in GLMs - brglm provides brglm.fit which is an alternative method to glm.fit that works under the usual glm interface.
Estimation is either by correcting the bias of the maximum likelihood estimates or using an adjusted-score approach to improving bias.
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- Topic : Regression Models [Filter]
- Topic : Social Sciences : Analysis of Categorical and Count Data [Filter]
- Topic : Social Sciences : Linear and Generalized Linear Models [Filter]
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Registered: 2011-08-20 14:19 |
6. addendum - Utility functions that should have been in R: easy glmnet, pretty graphing and swift debugging and profiling.
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- Topic : Machine Learning : Model Selection and Validation [Filter]
- Topic : Multivariate Statistics : Missing Data [Filter]
- Topic : Regression Models [Filter]
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Registered: 2011-06-17 13:35 |
7. lme4 - Mixed-effects models - An R package for fitting and analyzing linear, nonlinear and generalized linear mixed models.
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- Topic : Social Sciences : Linear and Generalized Linear Models [Filter]
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Registered: 2007-08-17 17:27 |
8. Linear quantile mixed models - This project is aimed at developing an R package to fit and analyse quantile regression models with random effects.
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- Topic : Robust Statistics [Filter]
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Registered: 2012-05-15 16:23 |
9. Diagnostic and prognostic meta-analysis - This package provides functions for diagnostic and prognostic meta-analyses. It estimates univariate, bivariate and multivariate models, and allows the aggregation of previously published prediction models with new data.
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- Development Status : 3 - Alpha [Filter]
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- Topic : Biostatistics & Medical Statistics [Filter]
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Registered: 2012-08-09 13:01 |
10. sampleSelection: Limited Dependent Vari. - Packages for limited dependent variables: censored regression (Tobit) models (pkg censReg), interval regression models (pkg intReg), multivariate probit models (pkg mvProbit), and sample selection (Heckman) models (pkg sampleSelection)
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- Topic : Econometrics : Microeconometrics [Filter]
- Topic : Regression Models [Filter]
- Topic : Social Sciences : Linear and Generalized Linear Models [Filter]
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Registered: 2008-09-19 09:08 |
11. R package nlstools - The R package nlstools: a toolbox for nonlinear regression diagnostics
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Registered: 2009-02-24 11:54 |
12. Finite Mixure of AFT and FMR models - FMRS package provides estimation and variable selection in Finite Mixture of Accelerated Failure Time Regression (FMAFTR) and Finite Mixture of Regression (FMR) models with a large number of covariates and/or right censoring and heterogeneous structure.
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- Topic : Machine Learning : Model Selection and Validation [Filter]
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Registered: 2016-03-07 02:31 |
13. semtools: Methods for SEMs - semtools - Methods for Diagnostic Testing of Structural Equation Models
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Registered: 2010-09-21 22:15 |
14. gbm - Generalized Boosted Models. Adding additional functionality to the gbm package, including additional robust regression methods, a new binomial classification method, and multinomial classification.
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- Topic : Machine Learning : Boosting [Filter]
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Registered: 2009-06-02 16:27 |
15. BradleyTerry2 - BradleyTerry2 provides facilities to specify, fit and evaluate Bradley-Terry models for pairwise comparisons. Models may incorporate object-specific, subject-specific, or contest-specific variables, as well as random effects.
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Registered: 2010-04-28 10:52 |
16. frontier: Stochastic Frontier Analysis - Maximum Likelihood Estimation of Stochastic Frontier Production and Cost Functions. Two specifications are available: the error components model (Battese and Coelli, 1992) and the efficiency effects model (Battese and Coelli, 1995).
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- Topic : Econometrics : Further Regression Models [Filter]
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Registered: 2008-10-19 20:27 |
17. logisticDx - Diagnostic tests for logistic regression. Includes 15x common diagnostic tests including leverage, dChi-square and dBhat per covariate pattern. Also plots for same.
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Registered: 2012-09-10 02:59 |
18. Forecasting with Artificial Intelligence - The package ForAI uses machine learning methods such as artificial neural networks, support vector regression, extreme learning machines, and evolutionary algorithms for forecasting and prediction.
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Registered: 2012-01-22 07:45 |
19. Dynamic Treatment Regimes - A package implementing several modern methods to estimate Dynamic Treatment Regimes: Q-Learning, Interactive Q-Learning, and two value-search methods each using Augmented Inverse Probability Weighted Estimators or Inverse Probability Weighted Estimators.
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Registered: 2015-01-20 22:09 |
