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Topic > Robust Statistics |
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4 projects in result set.
0. Ranking Methods for Factorial Designs - Ranking methods for the analysis of factorial experiments with independent observations. |
- Development Status : 6 - Mature [Filter]
- Environment : Console (Text Based) [Filter]
- Intended Audience : Developers [Filter]
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- License : OSI Approved : GNU General Public License (GPL) [Filter]
- Natural Language : English [Filter]
- Operating System : Microsoft : Windows [Filter]
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- Topic : Robust Statistics [Filter]
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Registered: 2016-04-28 05:13 |
1. Dependency modeling toolbox - Model-based tools for the discovery and analysis of statistical dependencies between data sources. |
- Development Status : 5 - Production/Stable [Filter]
- Environment : Console (Text Based) [Filter]
- Environment : Other Environment [Filter]
- Intended Audience : Developers [Filter]
- Intended Audience : End Users/Desktop [Filter]
- Intended Audience : Other Audience (Now Filtering)
- License : OSI Approved : BSD License [Filter]
- Natural Language : English [Filter]
- Operating System : OS Independent [Filter]
- Programming Language : R (Now Filtering)
- Topic : Machine Learning : Bayesian Methods [Filter]
- Topic : Multivariate Statistics : Latent Variable Approaches [Filter]
- Topic : Robust Statistics [Filter]
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Registered: 2010-04-08 11:22 |
2. Structural equation modeling - Several SEM related packages are developed for conducting structural equation modeling. |
- Development Status : 5 - Production/Stable [Filter]
- Intended Audience : Developers [Filter]
- Intended Audience : End Users/Desktop [Filter]
- Intended Audience : Other Audience (Now Filtering)
- License : OSI Approved : GNU General Public License (GPL) [Filter]
- Natural Language : English [Filter]
- Operating System : MacOS [Filter]
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- Programming Language : R (Now Filtering)
- Topic : Multivariate Statistics : Latent Variable Approaches [Filter]
- Topic : Robust Statistics [Filter]
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Registered: 2011-09-26 14:13 |
3. Generalized iLUCK-models - Interval/imprecise probability models allowing non-stochastic uncertainty in Bayesian analysis by defining sets of conjugate priors such that the set of posteriors, obtained by updating each prior in the set by Bayes' rule, is still easy to handle. |
- Development Status : 2 - Pre-Alpha [Filter]
- Intended Audience : Developers [Filter]
- Intended Audience : End Users/Desktop [Filter]
- Intended Audience : Other Audience (Now Filtering)
- License : OSI Approved : GNU General Public License (GPL) [Filter]
- Programming Language : R (Now Filtering)
- Topic : Bayesian Statistics [Filter]
- Topic : Other/Nonlisted Topic [Filter]
- Topic : Robust Statistics [Filter]
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Registered: 2010-03-06 00:28 |