Search Results for "statistical"
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Showing 9 open source projects for "statistical"
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TXM
Unicode XML TEI text analysis platform
...rubrique61&lang=en TXM offers a comprehensive range of analysis tools (concordances, collocate search, frequency lists, etc.) based on the powerfull CQP full text search engine (http://cwb.sourceforge.net) and a range of statistical functions (factorial analysis, classification, cooccurrency analysis, etc.) based on R packages (http://www.r-project.org). Read the scientific background at the Textométrie project web site http://textometrie.ens-lyon.fr/?lang=en. Read a full description at the TEI Tools wiki http://wiki.tei-c.org/index.php/TXM. -
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KMWin
Kaplan-Meier for Windows
KMWin (Kaplan-Meier for Windows) is a convenient tool for graphical presentation of results from Kaplan-Meier survival time analysis. The programme is based on the statistical software environment R and provides an easy to use graphical interface. As an introduction, see http://dx.plos.org/10.1371/journal.pone.0038960#s2. -
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rcqp
R interface to the Corpus Query Protocol
Implements the Corpus Query Protocol as a package for the R statistical environment. It allows to query linguistic corpora and manipulate the data as native R objects. It is based on the CWB software. -
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Corbata
CORe microBiome Analysis Tools
Corbata is a set of statistical tools that can be used to analyze the core microbiome across a set of samples. -
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Excelsi-R
Excel's Interface to R
Excelsi-R is an Excel add-in that allows Excel spreadsheets to harness the power of the R statistical language by connecting to a running R process. R does not need to be installed on the computer running Excel, but it does require access to an R instance running Rserve (which can be on a remote computer). It supports incorporating R plots and graphs in an Excel workbook. -
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Chinese I Ching R Algorithms
Chinese I Ching Algorithms implemented with R programming
...The derived theories like "Eight Diagrams", "Five Elements" became the foundation of nearly all academic fields in acient Chinese. As a result, the theories are also the high concentration of many practical and statistical experience in China during her thousands-of-year history. This project tries to realize these algorithms with statistical programming. Overcoming the long span has important meanings. First, we can verify the validity of algorithm with big data. Second, we can put them into unprecedented wide application in the age of data. ... -
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BiomeNet
BAYESIAN INFERENCE OF METABOLIC DIVERGENCE AMONG MICROBIAL COMMUNITIES
Metagenomics yields enormous numbers of microbial sequences that can be assigned a metabolic function. Using such data to infer community-level metabolic divergence is hindered by the lack of a suitable statistical framework. Here, we describe a novel hierarchical Bayesian model, called BiomeNet (Bayesian inference of metabolic networks), for inferring differential prevalence of metabolic networks among microbial communities. To infer the structure of community-level metabolic interactions, BiomeNet applies a mixed-membership modelling framework to enzyme abundance information. ... -
8
phcfM
R package for modelling anthropogenic deforestation
...It was named after the REDD+ pilot-project 'programme holistique de conservation des forêts à Madagascar'. phcfM includes two main functions: (i) demography(), to model the population growth with time in a hierarchical Bayesian framework using population census data and Gaussian linear mixed models and (ii) deforestation(), to model the deforestation process in a hierarchical Bayesian framework using land-cover change data and Binomial logistic regression models with variable time-intervals between land-cover observations. The two functions use embedded Gibbs samplers written in C++ with the Scythe statistical library to reduce computational time. -
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EnvStats
An R Package for Environmental Statistics
...The EnvStats package, along with the R software environment, provides comprehensive and powerful software for environmental data analysis. EnvStats brings the major environmental statistical methods found in the literature and regulatory guidance documents into one statistical package, along with an extensive hypertext help system that explains what these methods do, how to use these methods, and where to find them in the environmental statistics literature. Also included are numerous built-in data sets from regulatory guidance documents and the environmental statistics literature. ... -
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