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r-coconut
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Allows for pooled analysis of microarray data by batch-correcting control samples, and then applying the derived correction parameters to non-control samples to obtain bias-free, inter-dataset corrected data.
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2025-04-22 |
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r-coclust
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A copula based clustering algorithm that finds clusters according to the complex multivariate dependence structure of the data generating process. The updated version of the algorithm is described in Di Lascio, F.M.L. and Giannerini, S. (2016). "Clustering dependent observations with copula functions". Statistical Papers, p.1-17. <doi:10.1007/s00362-016-0822-3>.
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2025-04-22 |
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r-cobiclust
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Implementation of a probabilistic method for biclustering adapted to overdispersed count data. It is a Gamma-Poisson Latent Block Model. It also implements two selection criteria in order to select the number of biclusters.
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2025-04-22 |
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r-cnorm
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Conventional methods for producing standard scores in psychometrics or biometrics are often plagued with "jumps" or "gaps" (i.e., discontinuities) in norm tables and low confidence for assessing extreme scores. The continuous norming method introduced by A. Lenhard et al. (2016), <doi:10.1177/1073191116656437>, generates continuous test norm scores on the basis of the raw data from standardization samples, without requiring assumptions about the distribution of the raw data: Norm scores are directly established from raw data by modeling the latter ones as a function of both percentile scores and an explanatory variable (e.g., age). The method minimizes bias arising from sampling and measurement error, while handling marked deviations from normality, addressing bottom or ceiling effects and capturing almost all of the variance in the original norm data sample.
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2025-04-22 |
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r-cmrutils
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A collection of useful helper routines developed by students of the Center for Mathematical Research, Stankin, Moscow.
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2025-04-22 |
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r-cmplot
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Manhattan plot, a type of scatter plot, was widely used to display the association results. However, it is usually time-consuming and laborious for a non-specialist user to write scripts and adjust parameters of an elaborate plot. Moreover, the ever-growing traits measured have necessitated the integration of results from different Genome-wide association study researches. Circle Manhattan Plot is the first open R package that can lay out Genome-wide association study P-value results in both traditional rectangular patterns, QQ-plot and novel circular ones. United in only one bull's eye style plot, association results from multiple traits can be compared interactively, thereby to reveal both similarities and differences between signals.
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2025-04-22 |
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r-cmocean
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Perceptually uniform palettes for commonly used variables in oceanography as functions taking an integer and producing character vectors of colours. See Thyng, K.M., Greene, C.A., Hetland, R.D., Zimmerle, H.M. and S.F. DiMarco (2016) <doi:10.5670/oceanog.2016.66> for the guidelines adhered to when creating the palettes.
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2025-04-22 |
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r-cmna
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Provides the source and examples for James P. Howard, II, "Computational Methods for Numerical Analysis with R," <http://howardjp.github.io/cmna/>, a book on numerical methods in R.
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2025-04-22 |
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r-cmm
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Quite extensive package for maximum likelihood estimation and weighted least squares estimation of categorical marginal models (CMMs; e.g., Bergsma and Rudas, 2002, <http://www.jstor.org/stable/2700006?; Bergsma, Croon and Hagenaars, 2009, <DOI:10.1007/b12532>.
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2025-04-22 |
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r-cmls
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Solves multivariate least squares (MLS) problems subject to constraints on the coefficients, e.g., non-negativity, orthogonality, equality, inequality, monotonicity, unimodality, smoothness, etc. Includes flexible functions for solving MLS problems subject to user-specified equality and/or inequality constraints, as well as a wrapper function that implements 24 common constraint options. Also does k-fold or generalized cross-validation to tune constraint options for MLS problems. See ten Berge (1993, ISBN:9789066950832) for an overview of MLS problems, and see Goldfarb and Idnani (1983) <doi:10.1007/BF02591962> for a discussion of the underlying quadratic programming algorithm.
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2025-04-22 |
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r-cmce
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Implements the Bayesian calibration model described in Pratola and Chkrebtii (2018) <DOI:10.5705/ss.202016.0403> for stochastic and deterministic simulators. Additive and multiplicative discrepancy models are currently supported. See <http://www.matthewpratola.com/software> for more information and examples.
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2025-04-22 |
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r-cmc
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Calculation and plot of the stepwise Cronbach-Mesbah Curve
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2025-04-22 |
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r-cmaes
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Single objective optimization using a CMA-ES.
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2025-04-22 |
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r-clvalid
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Statistical and biological validation of clustering results.
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2025-04-22 |
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r-clustsig
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A complimentary package for use with hclust; simprof tests to see which (if any) clusters are statistically different. The null hypothesis is that there is no a priori group structure. See Clarke, K.R., Somerfield, P.J., and Gorley R.N. 2008. Testing of null hypothesis in exploratory community analyses: similarity profiles and biota-environment linkage. J. Exp. Mar. Biol. Ecol. 366, 56-69.
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2025-04-22 |
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r-clustmixtype
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Functions to perform k-prototypes partitioning clustering for mixed variable-type data according to Z.Huang (1998): Extensions to the k-Means Algorithm for Clustering Large Data Sets with Categorical Variables, Data Mining and Knowledge Discovery 2, 283-304, <DOI:10.1023/A:1009769707641>.
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2025-04-22 |
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r-clustertend
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Calculate some statistics aiming to help analyzing the clustering tendency of given data. In the first version, Hopkins' statistic is implemented.
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2025-04-22 |
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r-clusterrepro
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This is a function for validating microarray clusters via reproducibility, based on the paper referenced below.
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2025-04-22 |
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r-clusterranktest
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Nonparametric rank based tests (rank-sum tests and signed-rank tests) for clustered data, especially useful for clusters having informative cluster size and intra-cluster group size.
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2025-04-22 |
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r-clusterpower
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Calculate power for cluster randomized trials (CRTs) that compare two means, two proportions, or two counts using closed-form solutions. In addition, calculate power for cluster randomized crossover trials using Monte Carlo methods. For more information, see Reich et al. (2012) <doi:10.1371/journal.pone.0035564>.
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2025-04-22 |
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r-clusternomics
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Integrative context-dependent clustering for heterogeneous biomedical datasets. Identifies local clustering structures in related datasets, and a global clusters that exist across the datasets.
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2025-04-22 |
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r-clusterhap
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One haplotype is a combination of SNP (Single Nucleotide Polymorphisms) within the QTL (Quantitative Trait Loci). clusterhap groups together all individuals of a population with the same haplotype. Each group contains individual with the same allele in each SNP, whether or not missing data. Thus, clusterhap groups individuals, that to be imputed, have a non-zero probability of having the same alleles in the entire sequence of SNP's. Moreover, clusterhap calculates such probability from relative frequencies.
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2025-04-22 |
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r-clustergenomics
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The Partitioning Algorithm based on Recursive Thresholding (PART) is used to recursively uncover clusters and subclusters in the data. Functionality is also available for visualization of the clustering.
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2025-04-22 |
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r-clustergeneration
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We developed the clusterGeneration package to provide functions for generating random clusters, generating random covariance/correlation matrices, calculating a separation index (data and population version) for pairs of clusters or cluster distributions, and 1-D and 2-D projection plots to visualize clusters. The package also contains a function to generate random clusters based on factorial designs with factors such as degree of separation, number of clusters, number of variables, number of noisy variables.
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2025-04-22 |
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r-cluster.datasets
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A collection of data sets for teaching cluster analysis.
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2025-04-22 |
