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r-optimalcutpoints
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Computes optimal cutpoints for diagnostic tests or continuous markers. Various approaches for selecting optimal cutoffs have been implemented, including methods based on cost-benefit analysis and diagnostic test accuracy measures (Sensitivity/Specificity, Predictive Values and Diagnostic Likelihood Ratios). Numerical and graphical output for all methods is easily obtained.
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2025-04-22 |
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r-optigrab
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public |
Parse options from the command-line using a simple, clean syntax. It requires little or no specification and supports short and long options, GNU-, Java- or Microsoft- style syntaxes, verb commands and more.
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2025-04-22 |
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r-optifunset
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A single function 'options.ifunset(...)' is contained herewith, which allows the user to set a global option ONLY if it is not already set. By this token, for package maintainers this function can be used in preference to the standard 'options(...)' function, making provision for THEIR end user to place 'options(...)' directives within their '.Rprofile' file, which will not be overridden at the point when a package is loaded.
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2025-04-22 |
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r-optextras
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Tools to assist in safely applying user generated objective and derivative function to optimization programs. These are primarily function minimization methods with at most bounds and masks on the parameters. Provides a way to check the basic computation of objective functions that the user provides, along with proposed gradient and Hessian functions, as well as to wrap such functions to avoid failures when inadmissible parameters are provided. Check bounds and masks. Check scaling or optimality conditions. Perform an axial search to seek lower points on the objective function surface. Includes forward, central and backward gradient approximation codes.
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2025-04-22 |
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r-optauc
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Searches for optimal linear combination of multiple diagnostic tests (markers) that maximizes the area under the receiver operating characteristic curve (AUC); performs an approximated cross-validation for estimating the AUC associated with the estimated coefficients.
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2025-04-22 |
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r-ops
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Comparison of data by Pearson product-moment correlation coefficients is prone to outliers. The problem can be alleviated by normalizing data with outliers before computing the Pearson correlation coefficient. The sample provides such normalization by optimal power space transformation.
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2025-04-22 |
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r-opportunistic
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Computes the routing distribution, the expectation of the number of broadcasts, transmissions and receptions considering an Opportunistic transport model. It provides theoretical results and also estimated values based on Monte Carlo simulations.
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2025-04-22 |
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r-opi
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Implementation of the Open Perimetry Interface (OPI) for simulating and controlling visual field machines using R. The OPI is a standard for interfacing with visual field testing machines (perimeters). It specifies basic functions that allow many visual field tests to be constructed. As of October 2017 it is fully implemented on the Octopus 900 and partially on the Heidelberg Edge Perimeter, the Kowa AP 7000, the CrewT imo and the Centervue Compass. It also has a cousin: the R package 'visualFields', which has tools for analysing and manipulating visual field data.
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2025-04-22 |
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r-operator.tools
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Provides a collection of utilities that allow programming with R's operators. Routines allow classifying operators, translating to and from an operator and its underlying function, and inverting some operators (e.g. comparison operators), etc. All methods can be extended to custom infix operators.
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2025-04-22 |
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r-operators
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A set of binary operators for common tasks such as regex manipulation.
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2025-04-22 |
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r-opera
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Misc methods to form online predictions, for regression-oriented time-series, by combining a finite set of forecasts provided by the user.
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2025-04-22 |
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r-opennlpdata
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Apache OpenNLP jars and basic English language models.
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2025-04-22 |
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r-openintro
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Supplemental functions and data for 'OpenIntro' resources, which includes open-source textbooks and resources for introductory statistics at <http://www.openintro.org>. The package contains data sets used in our open-source textbooks along with custom plotting functions for reproducing book figures. Note that many functions and examples include color transparency; some plotting elements may not show up properly (or at all) when run in some versions of Windows operating system.
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2025-04-22 |
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r-opalr
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Data integration Web application for biobanks by 'OBiBa'. 'Opal' is the core database application for biobanks. Participant data, once collected from any data source, must be integrated and stored in a central data repository under a uniform model. 'Opal' is such a central repository. It can import, process, validate, query, analyze, report, and export data. 'Opal' is typically used in a research center to analyze the data acquired at assessment centres. Its ultimate purpose is to achieve seamless data-sharing among biobanks. This 'Opal' client allows to interact with 'Opal' web services and to perform operations on the R server side. 'DataSHIELD' administration tools are also provided.
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2025-04-22 |
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r-oor
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Implementation of optimistic optimization methods for global optimization of deterministic or stochastic functions. The algorithms feature guarantees of the convergence to a global optimum. They require minimal assumptions on the (only local) smoothness, where the smoothness parameter does not need to be known. They are expected to be useful for the most difficult functions when we have no information on smoothness and the gradients are unknown or do not exist. Due to the weak assumptions, however, they can be mostly effective only in small dimensions, for example, for hyperparameter tuning.
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2025-04-22 |
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r-oompadata
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This is a data-only package to provide example data for other packages that are part of the "Object-Oriented Microrray and Proteomics Analysis" suite of packages. These are described in more detail at the package URL.
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2025-04-22 |
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r-oompabase
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Provides the class unions that must be preloaded in order for the basic tools in the OOMPA (Object-Oriented Microarray and Proteomics Analysis) project to be defined and loaded. It also includes vectorized operations for row-by-row means, variances, and t-tests. Finally, it provides new color schemes. Details on the packages in the OOMPA project can be found at <http://oompa.r-forge.r-project.org/>.
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2025-04-22 |
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r-oomisc
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Includes miscellaneous functions.
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2025-04-22 |
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r-ontologyindex
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Functions for reading ontologies into R as lists and manipulating sets of ontological terms - 'ontologyX: A suite of R packages for working with ontological data', Greene et al 2017 <doi:10.1093/bioinformatics/btw763>.
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2025-04-22 |
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r-onnx
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R Interface to 'ONNX' - Open Neural Network Exchange <https://onnx.ai/>. 'ONNX' provides an open source format for machine learning models. It defines an extensible computation graph model, as well as definitions of built-in operators and standard data types.
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2025-04-22 |
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r-onetwosamples
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In this package, we introduce an R function one_two_sample() which can deal with one and two (normal) samples. For one normal sample x, the function reports descriptive statistics, plot, interval estimation and test of hypothesis of x. For two normal samples x and y, the function reports descriptive statistics, plot, interval estimation and test of hypothesis of x and y, respectively. It also reports interval estimation and test of hypothesis of mu1-mu2 (the difference of the means of x and y) and sigma1^2 / sigma2^2 (the ratio of the variances of x and y), tests whether x and y are from the same population, finds the correlation coefficient of x and y if x and y have the same length.
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2025-04-22 |
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r-onetr
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Provides a series of functions designed to enable users to easily search and interact with occupational data from the O*NET API <www.onetonline.org>. The package produces parsed and listed XML data for custom interactions, or pre-packaged functions for easy extraction of specific data (e.g., Knowledge, Skills, Abilities, Work Styles, etc.).
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2025-04-22 |
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r-oner
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Implements the One Rule (OneR) Machine Learning classification algorithm (Holte, R.C. (1993) <doi:10.1023/A:1022631118932>) with enhancements for sophisticated handling of numeric data and missing values together with extensive diagnostic functions. It is useful as a baseline for machine learning models and the rules are often helpful heuristics.
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2025-04-22 |
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r-oncotree
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Contains functions to construct and evaluate directed tree structures that model the process of occurrence of genetic alterations during carcinogenesis.
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2025-04-22 |
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r-oncomodel
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Computing probabilistic tree models for oncogenesis based on genetic data using maximum likelihood.
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2025-04-22 |
