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r-clusterbootstrap
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Provides functionality for the analysis of clustered data using the cluster bootstrap.
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2025-04-22 |
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r-circoutlier
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Detection of outliers in circular-circular regression models, modifying its and estimating of models parameters.
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2025-04-22 |
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r-circmle
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A series of wrapper functions to implement the 10 maximum likelihood models of animal orientation described by Schnute and Groot (1992) <DOI:10.1016/S0003-3472(05)80068-5>. The functions also include the ability to use different optimizer methods and calculate various model selection metrics (i.e., AIC, AICc, BIC).
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2025-04-22 |
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r-chemospec
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A collection of functions for top-down exploratory data analysis of spectral data including nuclear magnetic resonance (NMR), infrared (IR), Raman, X-ray fluorescence (XRF) and other similar types of spectroscopy. Includes functions for plotting and inspecting spectra, peak alignment, hierarchical cluster analysis (HCA), principal components analysis (PCA) and model-based clustering. Robust methods appropriate for this type of high-dimensional data are available. ChemoSpec is designed for structured experiments, such as metabolomics investigations, where the samples fall into treatment and control groups. Graphical output is formatted consistently for publication quality plots. ChemoSpec is intended to be very user friendly and to help you get usable results quickly. A vignette covering typical operations is available.
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2025-04-22 |
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r-chemospec2d
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A collection of functions for exploratory chemometrics of 2D spectroscopic data sets such as COSY (correlated spectroscopy) and HSQC (heteronuclear single quantum coherence) 2D NMR (nuclear magnetic resonance) spectra. 'ChemoSpec2D' deploys methods aimed primarily at classification of samples and the identification of spectral features which are important in distinguishing samples from each other. Each 2D spectrum (a matrix) is treated as the unit of observation, and thus the physical sample in the spectrometer corresponds to the sample from a statistical perspective. In addition to chemometric tools, a few tools are provided for plotting 2D spectra, but these are not intended to replace the functionality typically available on the spectrometer. 'ChemoSpec2D' takes many of its cues from 'ChemoSpec' and tries to create consistent graphical output and to be very user friendly.
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2025-04-22 |
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r-cde
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Facilitates searching, download and plotting of Water Framework Directive (WFD) reporting data for all waterbodies within the UK Environment Agency area. The types of data that can be downloaded are: WFD status classification data, Reasons for Not Achieving Good (RNAG) status, objectives set for waterbodies, measures put in place to improve water quality and details of associated protected areas. The site accessed is <https://environment.data.gov.uk/catchment-planning/>. The data are made available under the Open Government Licence v3.0 <https://www.nationalarchives.gov.uk/doc/open-government-licence/version/3/>. This package has been peer-reviewed by rOpenSci (v. 0.4.0).
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2025-04-22 |
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r-canprot
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Datasets are collected here for differentially (up- and down-) expressed proteins identified in proteomic studies of cancer and in cell culture experiments. Tables of amino acid compositions of proteins are used for calculations of chemical composition, projected into selected basis species. Plotting functions are used to visualize the compositional differences and thermodynamic potentials for proteomic transformations.
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2025-04-22 |
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r-bios2cor
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Utilities for computation and analysis of correlation/co-variation in multiple sequence alignments and in side chain motions during molecular dynamics simulations. Features include the computation of correlation/co-variation scores using a variety of scoring functions between either sequence positions in alignments or side chain dihedral angles in molecular dynamics simulations and to analyze the correlation/co-variation matrix through a variety of tools including network representation and principal components analysis. In addition, several utility functions are based on the R graphical environment to provide friendly tools for help in data interpretation. Examples of sequence co-variation analysis and utility tools are provided in: Pele J, Moreau M, Abdi H, Rodien P, Castel H, Chabbert M. (2014) <doi:10.1002/prot.24570>. This work was supported by the French National Research Agency (Grant number: ANR-11-BSV2-026).
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2025-04-22 |
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r-binseqtest
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For a series of binary responses, create stopping boundary with exact results after stopping, allowing updating for missing assessments.
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2025-04-22 |
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r-comparec
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Proposed by Harrell, the C index or concordance C, is considered an overall measure of discrimination in survival analysis between a survival outcome that is possibly right censored and a predictive-score variable, which can represent a measured biomarker or a composite-score output from an algorithm that combines multiple biomarkers. This package aims to statistically compare two C indices with right-censored survival outcome, which commonly arise from a paired design and thus resulting two correlated C indices.
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2025-04-22 |
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r-comat
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Builds co-occurrence matrices based on spatial raster data. It includes creation of weighted co-occurrence matrices (wecoma) and integrated co-occurrence matrices (incoma; Vadivel et al. (2007) <doi:10.1016/j.patrec.2007.01.004>).
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2025-04-22 |
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r-colourvalues
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Maps one of the viridis colour palettes, or a user-specified palette to values. Viridis colour maps are created by Stéfan van der Walt and Nathaniel Smith. They were set as the default palette for the 'Python' 'Matplotlib' library, introduced at SciPy 2015 conference <http://scipy2015.scipy.org/ehome/index.php?eventid=115969&>. Other palettes available in this library have been derived from 'RColorBrewer' <https://CRAN.R-project.org/package=RColorBrewer> and 'colorspace' <https://CRAN.R-project.org/package=colorspace> packages.
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2025-04-22 |
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r-collutils
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Provides some low level functions for processing PLINK input and output files.
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2025-04-22 |
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r-collections
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Provides high performance container data types such as Queue, Stack, Deque, Dict and OrderedDict. Benchmarks <https://randy3k.github.io/collections/articles/benchmark.html> have shown that these containers are asymptotically more efficient than those offered by other packages.
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2025-04-22 |
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r-coenoflex
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Simulates the composition of samples of vegetation according to gradient-based vegetation theory. Features a flexible algorithm incorporating competition and complex multi-gradient interaction.
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2025-04-22 |
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r-codep
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Computation of Multiscale Codependence Analysis and spatial eigenvector maps, as an additional feature.
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2025-04-22 |
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r-codadiags
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Markov chain Monte Carlo burn-in based on "bridge" statistics, in the way of coda::heidel.diag, but including non asymptotic tabulated statistics.
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2025-04-22 |
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r-coda.base
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A minimum set of functions to perform compositional data analysis using the log-ratio approach introduced by John Aitchison (1982) <http://www.jstor.org/stable/2345821>. Main functions have been implemented in c++ for better performance.
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2025-04-22 |
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r-cobs
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Qualitatively Constrained (Regression) Smoothing Splines via Linear Programming and Sparse Matrices.
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2025-04-22 |
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r-cobra
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This package performs prediction for regression-oriented problems, aggregating in a nonlinear scheme any basic regression machines suggested by the context and provided by the user. If the user has no valuable knowledge on the data, four defaults machines wrappers are implemented so as to cover a minimal spectrum of prediction methods. If necessary, the computations may be parallelized. The method is described in Biau, Fischer, Guedj and Malley (2013), "COBRA: A Nonlinear Aggregation Strategy".
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2025-04-22 |
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r-cna
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Provides comprehensive functionalities for causal modeling with Coincidence Analysis (CNA), which is a configurational comparative method of causal data analysis that was first introduced in Baumgartner (2009) <doi:10.1177/0049124109339369>, and generalized in Baumgartner & Ambuehl (2018) <doi:10.1017/psrm.2018.45>. CNA is related to Qualitative Comparative Analysis (QCA), but contrary to the latter, it is custom-built for uncovering causal structures with multiple outcomes and it builds causal models from the bottom up by gradually combining single factors to complex dependency structures until the requested thresholds of model fit are met. The new functionalities provided by this package version include functions for evaluating and benchmarking the correctness of CNA's output, a function determining whether a solution is an INUS model, a function bringing non-INUS expressions into INUS form, and a function for identifying cyclic models. The package vignette has been updated accordingly.
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2025-04-22 |
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r-cmprskqr
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Estimation, testing and regression modeling of subdistribution functions in competing risks using quantile regressions, as described in Peng and Fine (2009) <DOI:10.1198/jasa.2009.tm08228>.
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2025-04-22 |
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r-cmprsk
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Estimation, testing and regression modeling of subdistribution functions in competing risks, as described in Gray (1988), A class of K-sample tests for comparing the cumulative incidence of a competing risk, Ann. Stat. 16:1141-1154 <DOI:10.1214/aos/1176350951>, and Fine JP and Gray RJ (1999), A proportional hazards model for the subdistribution of a competing risk, JASA, 94:496-509, <DOI:10.1080/01621459.1999.10474144>.
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2025-04-22 |
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r-cmf
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Collective matrix factorization (CMF) finds joint low-rank representations for a collection of matrices with shared row or column entities. This code learns variational Bayesian approximation for CMF, supporting multiple likelihood potentials and missing data, while identifying both factors shared by multiple matrices and factors private for each matrix.
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2025-04-22 |
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r-clv
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Package contains most of the popular internal and external cluster validation methods ready to use for the most of the outputs produced by functions coming from package "cluster". Package contains also functions and examples of usage for cluster stability approach that might be applied to algorithms implemented in "cluster" package as well as user defined clustering algorithms.
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2025-04-22 |
