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r-climatestability
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public |
Climate stability measures are not formalized in the literature and tools for generating stability metrics from existing data are nascent. This package provides tools for calculating climate stability from raster data encapsulating climate change as a series of time slices. The methods follow Owens and Guralnick. Submitted, Biodiversity Informatics.
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2023-06-16 |
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r-chords
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public |
Maximum likelihood estimation in respondent driven samples.
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2023-06-16 |
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r-cmm
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public |
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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2023-06-16 |
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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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2023-06-16 |
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r-clustergenomics
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public |
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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2023-06-16 |
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r-cin
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Many experiments in neuroscience involve randomized and fast stimulation while the continuous outcome measures respond at much slower time scale, for example event-related fMRI. This package provide valid statistical tools with causal interpretation under these challenging settings, without imposing model assumptions.
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2023-06-16 |
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r-colt
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A collection of command-line color styles based on the 'crayon' package. 'Colt' styles are defined in themes that can easily be switched, to ensure command line output looks nice on dark as well as light consoles.
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2023-06-16 |
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r-colr
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public |
Powerful functions to select and rename columns in dataframes, lists and numeric types by 'Perl' regular expression. Regular expression ('regex') are a very powerful grammar to match strings, such as column names.
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2023-06-16 |
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r-colorr
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public |
Color palettes for EPL, MLB, NBA, NHL, and NFL teams.
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2023-06-16 |
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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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2023-06-16 |
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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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2023-06-16 |
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r-clv
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public |
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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2023-06-16 |
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r-cloudutil
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Provides means of plots for comparing utilization data of compute systems.
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2023-06-16 |
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r-clikcorr
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A profile likelihood based method of estimation and inference on the correlation coefficient of bivariate data with different types of censoring and missingness.
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2023-06-16 |
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r-citccmst
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public |
This package implements the approach to assign tumor gene expression dataset to the 6 CIT Colon Cancer Molecular Subtypes described in Marisa et al 2013.
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2023-06-16 |
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r-choplump
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Choplump Tests are Permutation Tests for Comparing Two Groups with Some Positive but Many Zero Responses
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2023-06-16 |
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r-commandr
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An S4 representation of the Command design pattern. The Operation class is a simple implementation using closures and supports forward and reverse (undo) evaluation. The more complicated Protocol framework represents each type of command (or analytical protocol) by a formal S4 class. Commands may be grouped and consecutively executed using the Pipeline class. Example use cases include logging, do/undo, analysis pipelines, GUI actions, parallel processing, etc.
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2023-06-16 |
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r-comclim
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Computes community climate statistics for volume and mismatch using species' climate niches either unscaled or scaled relative to a regional species pool. These statistics can be used to describe biogeographic patterns and infer community assembly processes. Includes a vignette outlining usage.
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2023-06-16 |
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r-coindeskr
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Extract real-time Bitcoin price details by accessing 'CoinDesk' Bitcoin price Index API <https://www.coindesk.com/api/>.
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2023-06-16 |
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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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2023-06-16 |
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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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2023-06-16 |
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r-collections
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public |
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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2023-06-16 |
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r-clustmmdd
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An implementation of a variable selection procedure in clustering by mixture models for discrete data (clustMMDD). Genotype data are examples of such data with two unordered observations (alleles) at each locus for diploid individual. The two-fold problem of variable selection and clustering is seen as a model selection problem where competing models are characterized by the number of clusters K, and the subset S of clustering variables. Competing models are compared by penalized maximum likelihood criteria. We considered asymptotic criteria such as Akaike and Bayesian Information criteria, and a family of penalized criteria with penalty function to be data driven calibrated.
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2023-06-16 |
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r-clust.bin.pair
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Tests, utilities, and case studies for analyzing significance in clustered binary matched-pair data. The central function clust.bin.pair uses one of several tests to calculate a Chi-square statistic. Implemented are the tests Eliasziw (1991) <doi:10.1002/sim.4780101211>, Obuchowski (1998) <doi:10.1002/(SICI)1097-0258(19980715)17:13%3C1495::AID-SIM863%3E3.0.CO;2-I>, Durkalski (2003) <doi:10.1002/sim.1438>, and Yang (2010) <doi:10.1002/bimj.201000035> with McNemar (1947) <doi:10.1007/BF02295996> included for comparison. The utility functions nested.to.contingency and paired.to.contingency convert data between various useful formats. Thyroids and psychiatry are the canonical datasets from Obuchowski and Petryshen (1989) <doi:10.1016/0165-1781(89)90196-0> respectively.
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2023-06-16 |
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r-cloudml
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Interface to the Google Cloud Machine Learning Platform <https://cloud.google.com/ml-engine>, which provides cloud tools for training machine learning models.
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2023-06-16 |
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r-cleanerr
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How to deal with missing data?Based on the concept of almost functional dependencies, a method is proposed to fill missing data, as well as help you see what data is missing. The user can specify a measure of error and how many combinations he wish to test the dependencies against, the closer to the length of the dataset, the more precise. But the higher the number, the more time it will take for the process to finish. If the program cannot predict with the accuracy determined by the user it shall not fill the data, the user then can choose to increase the error or deal with the data another way.
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2023-06-16 |
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r-clamr
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Implementation of the Wilkinson and Ivany (2002) approach to paleoclimate analysis, applied to isotope data extracted from clams.
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2023-06-16 |
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r-commentr
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public |
Functions to produce nicely formatted comments to use in R-scripts (or Latex/HTML/markdown etc). A comment with formatting is printed to the console and can then be copied to a script.
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2023-06-16 |
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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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2023-06-16 |
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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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2023-06-16 |
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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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2023-06-16 |
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r-chromomap
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Provides interactive, configurable and elegant graphics visualization of the chromosomes or chromosome regions of any living organism allowing users to map chromosome elements (like genes, SNPs etc.) on the chromosome plot. It introduces a special plot viz. the "chromosome heatmap" that, in addition to mapping elements, can visualize the data associated with chromosome elements (like gene expression) in the form of heat colors which can be highly advantageous in the scientific interpretations and research work. Because of the large size of the chromosomes, it is impractical to visualize each element on the same plot. However, the plot provides a magnified view for each of chromosome locus to render additional information and visualization specific for that location. You can map thousands of genes and can view all mappings easily. Users can investigate the detailed information about the mappings (like gene names or total genes mapped on a location) or can view the magnified single or double stranded view of the chromosome at a location showing each mapped element in sequential order. The package provide multiple features like visualizing multiple sets, chromosome heat-maps, group annotations, adding hyperlinks, and labelling. The plots can be saved as HTML documents that can be customized and shared easily. In addition, you can include them in R Markdown or in R 'Shiny' applications.
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2023-06-16 |
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r-circstats
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Circular Statistics, from "Topics in Circular Statistics" (2001) S. Rao Jammalamadaka and A. SenGupta, World Scientific.
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2023-06-16 |
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r-colourlovers
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Provides access to the COLOURlovers <http://www.colourlovers.com/> API, which offers color inspiration and color palettes.
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2023-06-16 |
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r-coloredica
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It implements colored Independent Component Analysis (Lee et al., 2011) and spatial colored Independent Component Analysis (Shen et al., 2014). They are two algorithms to perform ICA when sources are assumed to be temporal or spatial stochastic processes, respectively.
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2023-06-16 |
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r-cmc
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Calculation and plot of the stepwise Cronbach-Mesbah Curve
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2023-06-16 |
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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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2023-06-16 |
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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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2023-06-16 |
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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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2023-06-16 |
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r-clustering.sc.dp
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public |
A dynamic programming algorithm for optimal clustering multidimensional data with sequential constraint. The algorithm minimizes the sum of squares of within-cluster distances. The sequential constraint allows only subsequent items of the input data to form a cluster. The sequential constraint is typically required in clustering data streams or items with time stamps such as video frames, GPS signals of a vehicle, movement data of a person, e-pen data, etc. The algorithm represents an extension of Ckmeans.1d.dp to multiple dimensional spaces. Similarly to the one-dimensional case, the algorithm guarantees optimality and repeatability of clustering. Method clustering.sc.dp can find the optimal clustering if the number of clusters is known. Otherwise, methods findwithinss.sc.dp and backtracking.sc.dp can be used.
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2023-06-16 |
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r-clsocp
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This package provides and implementation of a one step smoothing newton method for the solution of second order cone programming problems, originally described by Xiaoni Chi and Sanyang Liu.
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2023-06-16 |
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r-choroplethrmaps
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Contains 3 maps. 1) US States 2) US Counties 3) Countries of the world.
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2023-06-16 |
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r-cinid
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This package provides functions to compute a method for identifying the instar of Curculionid larvae from the observed distribution of the headcapsule size of mature larvae.
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2023-06-16 |
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r-ciplot
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Plot confidence interval from the objects of statistical tests such as t.test(), var.test(), cor.test(), prop.test() and fisher.test() ('htest' class), Tukey test [TukeyHSD()], Dunnett test [glht() in 'multcomp' package], logistic regression [glm()], and Tukey or Games-Howell test [posthocTGH() in 'userfriendlyscience' package]. Users are able to set the styles of lines and points. This package contains the function to calculate odds ratios and their confidence intervals from the result of logistic regression.
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2023-06-16 |
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r-cim
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Produces statistical indicators of the impact of migration on the socio-demographic composition of an area. Three measures can be used: ratios, percentages and the Duncan index of dissimilarity. The input data files are assumed to be in an origin-destination matrix format, with each cell representing a flow count between an origin and a destination area. Columns are expected to represent origins, and rows are expected to represent destinations. The first row and column are assumed to contain labels for each area. See Rodriguez-Vignoli and Rowe (2018) <doi:10.1080/00324728.2017.1416155> for technical details.
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2023-06-16 |
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r-choicedes
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Design functions for DCMs and other types of choice studies (including MaxDiff and other tradeoffs).
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2023-06-16 |
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r-chff
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The software matches the current history to the closest history in a time series to build a forecast.
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2023-06-16 |
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r-circular
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Circular Statistics, from "Topics in circular Statistics" (2001) S. Rao Jammalamadaka and A. SenGupta, World Scientific.
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2023-06-16 |
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r-cholwishart
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Sampling from the Cholesky factorization of a Wishart random variable, sampling from the inverse Wishart distribution, sampling from the Cholesky factorization of an inverse Wishart random variable, sampling from the pseudo Wishart distribution, sampling from the generalized inverse Wishart distribution, computing densities for the Wishart and inverse Wishart distributions, and computing the multivariate gamma and digamma functions.
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2023-06-16 |
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r-ccda
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This package implements the combined cluster and discriminant analysis method for finding homogeneous groups of data with known origin as described in Kovacs et. al (2014): Classification into homogeneous groups using combined cluster and discriminant analysis (CCDA). Environmental Modelling & Software. DOI: http://dx.doi.org/10.1016/j.envsoft.2014.01.010
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2023-06-16 |
