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r-rollbar
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Reports errors and messages to Rollbar, the error tracking platform <https://rollbar.com>.
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2025-04-22 |
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r-roi
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The R Optimization Infrastructure ('ROI') is a sophisticated framework for handling optimization problems in R. More information can be found on the 'ROI' homepage <http://roi.r-forge.r-project.org/>.
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2025-04-22 |
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r-rodm
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This package implements an interface to Oracle Data Mining (ODM). It provides an ideal environment for rapid development of demos and proof of concept data mining studies. It facilitates the prototyping of vertical applications and makes ODM and the RDBMS environment easily accessible to statisticians and data analysts familiar with R but not fluent in SQL or familiar with the database environment. It also facilitates the benchmarking and testing of ODM functionality including the production of summary statistics, performance metrics and graphics. It enables the scripting and control of production data mining methodologies from a high-level environment. Oracle Data Mining (ODM) is an option of Oracle Relational Database Management System (RDBMS) Enterprise Edition (EE). It contains several data mining and data analysis algorithms for classification, prediction, regression, clustering, associations, feature selection, anomaly detection, feature extraction, and specialized analytics. It provides means for the creation, management and operational deployment of data mining models inside the database environment. For more information consult the entry for "Oracle Data Mining" in Wikipedia (en.wikipedia.org).
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2025-04-22 |
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r-rode
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Show physics, math and engineering students how an ODE solver is made and how effective R classes can be for the construction of the equations that describe natural phenomena. Inspiration for this work comes from the book on "Computer Simulations in Physics" by Harvey Gould, Jan Tobochnik, and Wolfgang Christian. Book link: <http://www.compadre.org/osp/items/detail.cfm?ID=7375>.
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2025-04-22 |
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r-rodbcdbi
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An implementation of R's DBI interface using ODBC package as a back-end. This allows R to connect to any DBMS that has a ODBC driver.
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2025-04-22 |
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r-rodam
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'ODAM' (Open Data for Access and Mining) is a framework that implements a simple way to make research data broadly accessible and fully available for reuse, including by a script language such as R. The main purpose is to make a data set accessible online with a minimal effort from the data provider, and to allow any scientists or bioinformaticians to be able to explore the data set and then extract a subpart or the totality of the data according to their needs. The Rodam package has only one class, 'odamws', that provides methods to allow you to retrieve online data using 'ODAM' Web Services. This obviously requires that data are implemented according the 'ODAM' approach , namely that the data subsets were deposited in the suitable data repository in the form of TSV files associated with their metadata also described in TSV files. See <http://www.slideshare.net/danieljacob771282/odam-open-data-access-and-mining>.
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2025-04-22 |
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r-rocwogs
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Function to estimate the ROC Curve of a continuous-scaled diagnostic test with the help of a second imperfect diagnostic test with binary responses.
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2025-04-22 |
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r-rocnit
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Non-inferiority test and diagnostic test are very important in clinical trails. This package is to get a p value from the non-inferiority test for ROC curves from diagnostic test.
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2025-04-22 |
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r-rocit
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Sensitivity (or recall or true positive rate), false positive rate, specificity, precision (or positive predictive value), negative predictive value, misclassification rate, accuracy, F-score- these are popular metrics for assessing performance of binary classifier for certain threshold. These metrics are calculated at certain threshold values. Receiver operating characteristic (ROC) curve is a common tool for assessing overall diagnostic ability of the binary classifier. Unlike depending on a certain threshold, area under ROC curve (also known as AUC), is a summary statistic about how well a binary classifier performs overall for the classification task. ROCit package provides flexibility to easily evaluate threshold-bound metrics. Also, ROC curve, along with AUC, can be obtained using different methods, such as empirical, binormal and non-parametric. ROCit encompasses a wide variety of methods for constructing confidence interval of ROC curve and AUC. ROCit also features the option of constructing empirical gains table, which is a handy tool for direct marketing. The package offers options for commonly used visualization, such as, ROC curve, KS plot, lift plot. Along with in-built default graphics setting, there are rooms for manual tweak by providing the necessary values as function arguments. ROCit is a powerful tool offering a range of things, yet it is very easy to use.
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2025-04-22 |
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r-roccv
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Cross validate large genetic data while specifying clinical variables that should always be in the model using the function cv(). An ROC plot from the cross validation data with AUC can be obtained using rocplot(), which also can be used to compare different models. Framework was built to handle genetic data, but works for any data.
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2025-04-22 |
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r-rocc
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Functions for a classification method based on receiver operating characteristics (ROC). Briefly, features are selected according to their ranked AUC value in the training set. The selected features are merged by the mean value to form a metagene. The samples are ranked by their metagene value and the metagene threshold that has the highest accuracy in splitting the training samples is determined. A new sample is classified by its metagene value relative to the threshold. In the first place, the package is aimed at two class problems in gene expression data, but might also apply to other problems.
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2025-04-22 |
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r-robustx
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Robustness -- 'eXperimental', 'eXtraneous', or 'eXtraordinary' Functionality for Robust Statistics. In other words, methods which are not yet well established, often related to methods in package 'robustbase'.
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2025-04-22 |
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r-robustrankaggreg
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Methods for aggregating ranked lists, especially lists of genes. It implements the Robust Rank Aggregation (Kolde et. al in preparation) and some other simple algorithms for the task. RRA method uses a probabilistic model for aggregation that is robust to noise and also facilitates the calculation of significance probabilities for all the elements in the final ranking.
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2025-04-22 |
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r-robumeta
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Functions for conducting robust variance estimation (RVE) meta-regression using both large and small sample RVE estimators under various weighting schemes. These methods are distribution free and provide valid point estimates, standard errors and hypothesis tests even when the degree and structure of dependence between effect sizes is unknown. Also included are functions for conducting sensitivity analyses under correlated effects weighting and producing RVE-based forest plots.
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2025-04-22 |
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r-robrsvd
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This package provides the function to calculate SVD, regularized SVD, robust SVD and robust regularized SVD method. The robust SVD methods use alternating iteratively reweighted least squares methods. The regularized SVD uses generalized cross validation to choose the optimal smoothing parameters.
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2025-04-22 |
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r-robcor
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Robust pairwise correlations based on estimates of scale, particularly on "FastQn" one-step M-estimate.
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2025-04-22 |
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r-robastrda
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Includes 'sysdata.rda' file for packages of the 'RobASt' - family of packages; is currently used by package 'RobExtremes' only.
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2025-04-22 |
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r-roauth
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Provides an interface to the OAuth 1.0 specification allowing users to authenticate via OAuth to the server of their choice.
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2025-04-22 |
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r-rnumerai
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Routines to interact with the Numerai Machine Learning Tournament API <https://numer.ai>. The functionality includes the ability to automatically download the current tournament data, submit predictions, and to get information for your user. General 'GraphQL' queries can also be executed.
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2025-04-22 |
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r-rnr
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Apply sensitivity analysis for offline policy evaluation, as implemented in Jung et al. (2017) <arXiv:1702.04690> based on Rosenbaum and Rubin (1983) <http://www.jstor.org/stable/2345524>.
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2025-04-22 |
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r-rnpn
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Programmatic interface to the Web Service methods provided by the National 'Phenology' Network (<https://usanpn.org/>), which includes data on various life history events that occur at specific times.
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2025-04-22 |
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r-rngforgpd
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Generation of univariate and multivariate data that follow the generalized Poisson distribution. The details of the univariate part are explained in Demirtas (2017), and the multivariate part is an extension of the correlated Poisson data generation routine that was introduced in Yahav and Shmueli (2012).
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2025-04-22 |
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r-rnetlogo
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Interface to use and access Wilensky's 'NetLogo' (Wilensky 1999) from R using either headless (no GUI) or interactive GUI mode. Provides functions to load models, execute commands, and get values from reporters. Mostly analogous to the 'NetLogo' 'Mathematica' Link <https://github.com/NetLogo/Mathematica-Link>.
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2025-04-22 |
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r-rneos
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Within this package the XML-RPC API to NEOS <https://neos-server.org/neos/> is implemented. This enables the user to pass optimization problems to NEOS and retrieve results within R.
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2025-04-22 |
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r-rnentropy
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An implementation of a method based on information theory devised for the identification of genes showing a significant variation of expression across multiple conditions. Given expression estimates from any number of RNA-Seq samples and conditions it identifies genes or transcripts with a significant variation of expression across all the conditions studied, together with the samples in which they are over- or under-expressed. Zambelli et al. (2018) <doi:10.1093/nar/gky055>.
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2025-04-22 |
