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r-pack
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public |
Functions to easily convert data to binary formats other programs/machines can understand.
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2024-01-16 |
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r-p3state.msm
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Contains functions for data preparation, prediction of transition probabilities, estimating semi-parametric regression models and for implementing nonparametric estimators for other quantities. See Meira-Machado and Roca-Pardiñas (2011) <doi:10.18637/jss.v038.i03>.
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2024-01-16 |
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r-oxcaar
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A set of tools that enables using 'OxCal' from within R. 'OxCal' (<https://c14.arch.ox.ac.uk/oxcal.html>) is a standard archaeological tool intended to provide 14C calibration and analysis of archaeological and environmental chronological information. 'OxcAAR' allows simple calibration with 'Oxcal' and plotting of the results as well as the execution of sophisticated ('OxCal') code and the import of the results of bulk analysis and complex Bayesian sequential calibration.
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2024-01-16 |
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r-oz
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Functions for plotting Australia's coastline and state boundaries.
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2024-01-16 |
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r-oxybs
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Provides utilities for processing of Oxy-Bisulfite microarray data (e.g. via the Illumina Infinium platform, <http://www.illumina.com>) with tandem arrays, one using conventional bisulfite conversion, the other using oxy-bisulfite conversion.
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2024-01-16 |
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r-overlapping
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Functions for estimating the overlapping area of two or more kernel density estimations from empirical data.
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2024-01-16 |
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r-osrm
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An interface between R and the 'OSRM' API. 'OSRM' is a routing service based on 'OpenStreetMap' data. See <http://project-osrm.org/> for more information. This package enables the computation of routes, trips, isochrones and travel distances matrices (travel time and kilometric distance).
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2024-01-16 |
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r-owea
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An implementation of optimal weight exchange algorithm Yang(2013) <doi:10.1080/01621459.2013.806268> for three models. They are Crossover model with subject dropout, crossover model with proportional first order residual effects and interference model. You can use it to find either A-opt or D-opt approximate designs. Exact designs can be automatically rounded from approximate designs and relative efficiency is provided as well.
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2024-01-16 |
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r-overture
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Simplifies MCMC setup by automatically looping through sampling functions and saving the results. Reduces the memory footprint of running MCMC and saves samples to disk as the chain runs. Allows samples from the chain to be analyzed while the MCMC is still running. Provides functions for commonly performed operations such as calculating Metropolis acceptance ratios and creating adaptive Metropolis samplers. References: Roberts and Rosenthal (2009) <doi:10.1198/jcgs.2009.06134>.
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2024-01-16 |
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r-outliers
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A collection of some tests commonly used for identifying outliers.
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2024-01-16 |
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r-outbreaks
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Empirical or simulated disease outbreak data, provided either as RData or as text files.
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2024-01-16 |
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r-otutable
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Analyses of OTU tables produced by 16S rRNA gene amplicon sequencing, as well as example data. It contains the data and scripts used in the paper Linz, et al. (2017) "Bacterial community composition and dynamics spanning five years in freshwater bog lakes," <doi: 10.1128/mSphere.00169-17>.
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2024-01-16 |
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r-oro.nifti
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Functions for the input/output and visualization of medical imaging data that follow either the 'ANALYZE', 'NIfTI' or 'AFNI' formats. This package is part of the Rigorous Analytics bundle.
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2024-01-16 |
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r-otrselect
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A penalized regression framework that can simultaneously estimate the optimal treatment strategy and identify important variables. Appropriate for either censored or uncensored continuous response.
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2024-01-16 |
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r-ote
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public |
Functions for creating ensembles of optimal trees for regression, classification (Khan, Z., Gul, A., Perperoglou, A., Miftahuddin, M., Mahmoud, O., Adler, W., & Lausen, B. (2019). (2019) <doi:10.1007/s11634-019-00364-9>) and class membership probability estimation (Khan, Z, Gul, A, Mahmoud, O, Miftahuddin, M, Perperoglou, A, Adler, W & Lausen, B (2016) <doi:10.1007/978-3-319-25226-1_34>) are given. A few trees are selected from an initial set of trees grown by random forest for the ensemble on the basis of their individual and collective performance. Three different methods of tree selection for the case of classification are given. The prediction functions return estimates of the test responses and their class membership probabilities. Unexplained variations, error rates, confusion matrix, Brier scores, etc. are also returned for the test data.
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2024-01-16 |
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r-osrmr
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Wrapper around the 'Open Source Routing Machine (OSRM)' API <http://project-osrm.org/>. 'osrmr' works with API versions 4 and 5 and can handle servers that run locally as well as the 'OSRM' webserver.
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2024-01-16 |
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r-oshka
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Expands quoted language by recursively replacing any symbol that points to quoted language with the language it points to. The recursive process continues until only symbols that point to non-language objects remain. The resulting quoted language can then be evaluated normally. This differs from the traditional 'quote'/'eval' pattern because it resolves intermediate language objects that would interfere with evaluation.
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2024-01-16 |
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r-origami
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A general framework for the application of cross-validation schemes to particular functions. By allowing arbitrary lists of results, origami accommodates a range of cross-validation applications. This implementation was first described by Coyle and Hejazi (2018) <doi:10.21105/joss.00512>.
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2024-01-16 |
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r-osdr
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Provides routines for finding an Optimal System of Distinct Representatives (OSDR), as defined by D.Gale (1968) <doi:10.1016/S0021-9800(68)80039-0>.
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2024-01-16 |
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r-osdesign
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A suite of functions for the design of case-control and two-phase studies, and the analysis of data that arise from them. Functions in this packages provides Monte Carlo based evaluation of operating characteristics such as powers for estimators of the components of a logistic regression model. For additional detail see: Haneuse S, Saegusa T and Lumley T (2011)<doi:10.18637/jss.v043.i11>.
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2024-01-16 |
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r-oscillatorgenerator
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The supplied code allows for the generation of discrete time series of oscillating species. General shapes can be selected by means of individual functions, which are widely customizable by means of function arguments. All code was developed in the Biological Information Processing Group at the BioQuant Center at Heidelberg University, Germany.
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2024-01-16 |
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r-orthopolynom
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A collection of functions to construct sets of orthogonal polynomials and their recurrence relations. Additional functions are provided to calculate the derivative, integral, value and roots of lists of polynomial objects.
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2024-01-16 |
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r-orthopanels
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Implements the orthogonal reparameterization approach recommended by Lancaster (2002) to estimate dynamic panel models with fixed effects (and optionally: panel specific intercepts). The approach uses a likelihood-based estimator and produces estimates that are asymptotically unbiased as N goes to infinity, with a T as low as 2.
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2024-01-16 |
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r-orthogonalsplinebasis
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Represents the basis functions for B-splines in a simple matrix formulation that facilitates, taking integrals, derivatives, and making orthogonal the basis functions.
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2024-01-16 |
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r-orsifronts
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A data set package with the "Orsi" and "Park/Durand" fronts as 'SpatialLinesDataFrame' objects. The Orsi et al. (1995) fronts are published at the Southern Ocean Atlas Database Page, and the Park et al. (2019) fronts are published at the 'SEANOE' Altimetry-derived Antarctic Circumpolar Current fronts page, please see package CITATION for details.
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2024-01-16 |
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r-orientlib
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Representations, conversions and display of orientation SO(3) data. See the orientlib help topic for details.
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2024-01-16 |
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r-oriclust
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A user-friendly R-based software package for gene clustering. Clusters are given by genes matched to prespecified profiles across various ordered treatment groups. It is particularly useful for analyzing data obtained from short time-course or dose-response microarray experiments.
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2024-01-16 |
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r-orgmassspecr
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Organic/biological mass spectrometry data analysis.
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2024-01-16 |
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r-org
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A system to help you organize projects. Most analyses have three (or more) main sections: code, results, and data, each with different requirements (version control/sharing/encryption). You provide folder locations and 'org' helps you take care of the details.
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2024-01-16 |
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r-ores
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A connector to ORES (<https://ores.wmflabs.org/>), an AI project to provide edit scoring for content on Wikipedia and other Wikimedia projects. This lets a researcher identify if edits are likely to be reverted, damaging, or made in good faith.
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2024-01-16 |
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r-optweight
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Use optimization to estimate weights that balance covariates for binary, multinomial, and continuous treatments in the spirit of Zubizarreta (2015) <doi:10.1080/01621459.2015.1023805>. The degree of balance can be specified for each covariate. In addition, sampling weights can be estimated that allow a sample to generalize to a population specified with given target moments of covariates.
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2024-01-16 |
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r-ordmonreg
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We consider the problem of estimating two isotonic regression curves g1* and g2* under the constraint that they are ordered, i.e. g1* <= g2*. Given two sets of n data points y_1, ..., y_n and z_1, ..., z_n that are observed at (the same) deterministic design points x_1, ..., x_n, the estimates are obtained by minimizing the Least Squares criterion L(a, b) = sum_{i=1}^n (y_i - a_i)^2 w1(x_i) + sum_{i=1}^n (z_i - b_i)^2 w2(x_i) over the class of pairs of vectors (a, b) such that a and b are isotonic and a_i <= b_i for all i = 1, ..., n. We offer two different approaches to compute the estimates: a projected subgradient algorithm where the projection is calculated using a PAVA as well as Dykstra's cyclical projection algorithm.
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2024-01-16 |
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r-ordinallbm
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It implements functions for simulation and estimation of the ordinal latent block model (OLBM), as described in Corneli, Bouveyron and Latouche (2019).
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2024-01-16 |
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r-orderstats
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All the methods in this package generate a vector of uniform order statistics using a beta distribution and use an inverse cumulative distribution function for some distribution to give a vector of random order statistic variables for some distribution. This is much more efficient than using a loop since it is directly sampling from the order statistic distribution.
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2024-01-16 |
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r-ordinalcont
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A regression framework for response variables which are continuous self-rating scales such as the Visual Analog Scale (VAS) used in pain assessment, or the Linear Analog Self-Assessment (LASA) scales in quality of life studies. These scales measure subjects' perception of an intangible quantity, and cannot be handled as ratio variables because of their inherent non-linearity. We treat them as ordinal variables, measured on a continuous scale. A function (the g function) connects the scale with an underlying continuous latent variable. The link function is the inverse of the CDF of the assumed underlying distribution of the latent variable. A variety of link functions are currently implemented. Such models are described in Manuguerra et al (2020) <doi:10.18637/jss.v096.i08>.
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2024-01-16 |
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r-ordfacreg
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In biomedical studies, researchers are often interested in assessing the association between one or more ordinal explanatory variables and an outcome variable, at the same time adjusting for covariates of any type. The outcome variable may be continuous, binary, or represent censored survival times. In the absence of a precise knowledge of the response function, using monotonicity constraints on the ordinal variables improves efficiency in estimating parameters, especially when sample sizes are small. This package implements an active set algorithm that efficiently computes such estimators.
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2024-01-16 |
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r-ordering
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Functions to test/check/verify/investigate the ordering of vectors. The 'is_[strictly_]*' family of functions test vectors for 'sorted', 'monotonic', 'increasing', 'decreasing' order; 'is_constant' and 'is_incremental' test for the degree of ordering. `ordering` provides a numeric indication of ordering -2 (strictly decreasing) to 2 (strictly increasing).
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2024-01-16 |
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r-orddisp
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Estimate location-shift models or rating-scale models accounting for response styles (RSRS) for the regression analysis of ordinal responses.
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2024-01-16 |
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r-orcutt
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Solve first order autocorrelation problems using an iterative method. This procedure estimates both autocorrelation and beta coefficients recursively until we reach the convergence (8th decimal as default). The residuals are computed after estimating Beta using EGLS approach and Rho is estimated using the previous residuals.
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2024-01-16 |
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r-orclus
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Functions to perform subspace clustering and classification.
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2024-01-16 |
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r-optional
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Introduces optional types with some() and none, as well as match_with() from functional languages.
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2024-01-16 |
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r-optr
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Solves linear systems of form Ax=b via Gauss elimination, LU decomposition, Gauss-Seidel, Conjugate Gradient Method (CGM) and Cholesky methods.
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2024-01-16 |
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r-optiscale
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Optimal scaling of a data vector, relative to a set of targets, is obtained through a least-squares transformation subject to appropriate measurement constraints. The targets are usually predicted values from a statistical model. If the data are nominal level, then the transformation must be identity-preserving. If the data are ordinal level, then the transformation must be monotonic. If the data are discrete, then tied data values must remain tied in the optimal transformation. If the data are continuous, then tied data values can be untied in the optimal transformation.
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2024-01-16 |
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r-optparse
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A command line parser inspired by Python's 'optparse' library to be used with Rscript to write "#!" shebang scripts that accept short and long flag/options.
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2024-01-16 |
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r-optionstrat
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Utilizes the Black-Scholes-Merton option pricing model to calculate key option analytics and perform graphical analysis of various option strategies. Provides functions to calculate the option premium and option greeks of European-style options.
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2024-01-16 |
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r-optimx
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Provides a replacement and extension of the optim() function to call to several function minimization codes in R in a single statement. These methods handle smooth, possibly box constrained functions of several or many parameters. Note that function 'optimr()' was prepared to simplify the incorporation of minimization codes going forward. Also implements some utility codes and some extra solvers, including safeguarded Newton methods. Many methods previously separate are now included here. This is the version for CRAN.
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2024-01-16 |
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r-optionpricing
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Efficient Monte Carlo Algorithms for the price and the sensitivities of Asian and European Options under Geometric Brownian Motion.
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2024-01-16 |
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r-optimstrat
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Intended to assist in the choice of the sampling strategy to implement in a survey.
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2024-01-16 |
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r-openstreetmap
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Accesses high resolution raster maps using the OpenStreetMap protocol. Dozens of road, satellite, and topographic map servers are directly supported, including Apple, Mapnik, Bing, and stamen. Additionally raster maps may be constructed using custom tile servers. Maps can be plotted using either base graphics, or ggplot2. This package is not affiliated with the OpenStreetMap.org mapping project.
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2024-01-16 |
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r-optimparallel
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Provides a parallel version of the L-BFGS-B method of optim(). The main function of the package is optimParallel(), which has the same usage and output as optim(). Using optimParallel() can significantly reduce the optimization time.
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2024-01-16 |
