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Topic > Robust Statistics |
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7 projects in result set.
0. Dependency modeling toolbox - Model-based tools for the discovery and analysis of statistical dependencies between data sources. |
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- 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 |
1. RobKalman - Package robKalman implements several robustifications of rhe classical Kalman filter; a common filtering iterface for all robustifications is provided as well as S4-classes for state space models and filtering results. |
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- Topic : Robust Statistics [Filter]
- Topic : Time Series [Filter]
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Registered: 2007-11-06 20:07 |
2. robust-ts: Robust Time Series - "robust-ts" is a collaborative project to provide robustifications to the basic time series procedures from package stats. A target will be chapter 8 in "Robust Statistics, Theory and Methods" by Maronna, Martin and Yohai; 2006. |
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Registered: 2007-11-06 20:18 |
3. bootBCa - Function BCa finds confidence intervals using Efron's nonparametric bias-corrected and accelerated (BCa) bootstrap method. It supports adaptive determination of the number of bootstrap replications and requires less memory than other implementations. |
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Registered: 2014-07-22 16:16 |
4. Local Depth - The package "localdepth" contains functions for the evaluation of some Depth functions and their corresponding local versions, namely Local Depths. Simplicial, Ellipsoid and Mahalanobis Depths are implemented for general dimension. |
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- Topic : Cluster Analysis : Hierarchical Clustering [Filter]
- Topic : Multivariate Statistics [Filter]
- Topic : Robust Statistics [Filter]
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Registered: 2008-09-16 15:34 |
5. distr - S4 classes for distributions - Project distr currently hosts pkg's distr, distrEx, distrSim, distrTEst, distrTeach, distrMod, distrDoc, startupmsg, SweaveListingUtils, distrEllipse, distrRnews, setRNG. For reference, see also vignette "distr" in pkg distrDoc. |
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Registered: 2007-11-06 19:55 |
6. Robust time series analysis - Provides various approaches for robust estimation of (partial) autocorrelation and autocovariance. There are also procedures for robust fitting and filtering of AR(p) processes as well as for robust change point detection. |
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Registered: 2014-11-11 15:14 |