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7 projects in result set.
0. Sequence analysis for social scientists - TraMineR is intended for mining and visualizing sequences of states or events. Its primary aim is the analysis of longitudinal data in the social science field but many of its features may also apply to non temporal data such as text or DNA sequences. |
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Activity Percentile: 44.44
Registered: 2010-04-13 10:26 |
1. rm.plot - rm.plot (for raw-means-plot) is a function for visualizing results of experimental designs with up to two factors. It plots both raw data (background) and factor means (foreground) to provide a more accurate visualization of the underlying distribution. |
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Registered: 2011-12-01 19:52 |
2. CulturalAnalytics - Code for statistical analysis and plotting of image properties for use in the Digital Humanities. |
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Registered: 2011-10-29 20:57 |
3. gEcon - gEcon is a framework for developing and solving large scale DSGE models. It consists of simple and intuitive model description language and an interface with a set of solvers in R. FOCs, steady state and linearisation equations are derived automatically. |
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- Topic : Econometrics : Time Series Modelling [Filter]
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Registered: 2013-10-06 11:13 |
4. RNetLogo (Discontinued) - RNetLogo is an interface to the agent-based modelling plattform NetLogo. NL can be embedded into the R environment with headless (no GUI) and interactive GUI mode. It provides functions to load models, execute commands and to get values from reporters. |
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- Topic : Bioinformatics [Filter]
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Registered: 2011-08-19 15:59 |
5. prefmod - analysis of preferences - Fits loglinear Bradley-Terry and pattern models for paired comparisons, rankings, and ratings. Some treatment of MCAR and MNAR. Design matrices for analysing real and derived (from ratings or rankings) paired comparison data using a loglinear approach. |
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Registered: 2009-01-06 11:54 |
6. DDIwR - This package provides functions to read DDI based metadata documentation, and write dedicated setup files for R, SPSS, Stata and SAS to read an associated .csv file containing the raw data, apply labels for variables and values and treat missing data. |
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Registered: 2014-08-11 10:08 |