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 Topic > Time Series
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9 projects in result set.
0. 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 |
1. niftir - Read and write neuroimaging (nifti) data files into native R data structures (array and big matrices). Also includes functions for the mining of brain connectivity data, including conducting Connectome-Wide Association Studies (CWAS).
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Registered: 2010-12-16 06:17 |
2. SegAnnot - SegAnnot calculates the least squares segmentation for piecewise constant annotated noisy signals.
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Registered: 2012-11-27 16:58 |
3. xts - extensible time series - Provide uniform handling of R's different time-based data classes, allowing
user-level customization and extension, while simplifying cross-class interoperability.
This project has moved from R-Forge to GitHub :
https://github.com/joshuaulrich/xts
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- Topic : Econometrics : Basic Time Series Infrastructure [Filter]
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Registered: 2008-01-03 18:11 |
4. R-Hydro - Hydrological models and tools to represent and analyze hydrological data
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Registered: 2009-04-26 20:49 |
5. Rwave: time-frequency analysis in 1-D - Rwave is a library of R functions which provide an environment for the time-frequency analysis of 1-D signals. It was originally written for Splus by Rene Carmona, Bruno Torresani, and Wen L. Hwang.
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Registered: 2009-05-27 13:22 |
6. surveillance - The R package 'surveillance' implements statistical methods for the modeling and monitoring of time series of counts, proportions and categorical data, as well as for the modeling of continuous-time point processes of epidemic phenomena.
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Registered: 2007-06-19 14:46 |
7. waveslim: Wavelet methods for 1/2/3D - Basic wavelet routines for the processing/analysis/inference of time series, images and 3D arrays. The code provided here is based on Percival and Walden (2000); Gencay, Selcuk and Whitcher (2001); Kingsbury (1999); and Selesnick (200?).
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Registered: 2009-02-26 17:20 |
8. 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 |
