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r-bmrv
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Provides two Bayesian models for detecting the association between rare genetic variants and a trait that can be continuous, ordinal or binary. Bayesian latent variable collapsing model (BLVCM) detects interaction effect and is dedicated to twin design while it can also be applied to independent samples. Hierarchical Bayesian multiple regression model (HBMR) incorporates genotype uncertainty information and can be applied to either independent or family samples. Furthermore, it deals with continuous, binary and ordinal traits.
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2023-06-16 |
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r-bitrugs
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MCMC methods to estimate transmission dynamics and infection routes in hospitals using genomic sampling data.
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2023-06-16 |
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r-businessduration
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Calculates business duration between two dates. This excluding weekends, public holidays and non-business hours.
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2023-06-16 |
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r-breeze
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A collection of functions to analyse, visualize and interpret wind data and to calculate the potential energy production of wind turbines.
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2023-06-16 |
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r-bnviewer
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Bayesian networks provide an intuitive framework for probabilistic reasoning and its graphical nature can be interpreted quite clearly. Graph based methods of machine learning are becoming more popular because they offer a richer model of knowledge that can be understood by a human in a graphical format. The 'bnviewer' is an R Package that allows the interactive visualization of Bayesian Networks. The aim of this package is to improve the Bayesian Networks visualization over the basic and static views offered by existing packages.
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2023-06-16 |
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r-bndatagenerator
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Data generator based on Bayesian network model
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2023-06-16 |
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r-bmrbr
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Nuclear magnetic resonance (NMR) is a highly versatile analytical technique for studying molecular configuration, conformation, and dynamics, especially those of biomacromolecules such as proteins. Biological Magnetic Resonance Data Bank ('BMRB') is a repository for Data from NMR Spectroscopy on Proteins, Peptides, Nucleic Acids, and other Biomolecules. Currently, 'BMRB' offers an R package 'RBMRB' to fetch data, however, it doesn't easily offer individual data file downloading and storing in a local directory. When using 'RBMRB', the data will stored as an R object, which fundamentally hinders the NMR researches to access the rich information from raw data, for example, the metadata. Here, 'BMRBr' File Downloader ('BMRBr') offers a more fundamental, low level downloader, which will download original deposited .str format file. This type of file contains information such as entry title, authors, citation, protein sequences, and so on. Many factors affect NMR experiment outputs, such as temperature, resonance sensitivity and etc., approximately 40% of the entries in the 'BMRB' have chemical shift accuracy problems [1,2] Unfortunately, current reference correction methods are heavily dependent on the availability of assigned protein chemical shifts or protein structure. This is my current research project is going to solve, which will be included in the future release of the package. The current version of the package is sufficient and robust enough for downloading individual 'BMRB' data file from the 'BMRB' database <http://www.bmrb.wisc.edu>. The functionalities of this package includes but not limited: * To simplifies NMR researches by combine data downloading and results analysis together. * To allows NMR data reaches a broader audience that could utilize more than just chemical shifts but also metadata. * To offer reference corrected data for entries without assignment or structure information (future release). Reference: [1] E.L. Ulrich, H. Akutsu, J.F. Doreleijers, Y. Harano, Y.E. Ioannidis, J. Lin, et al., BioMagResBank, Nucl. Acids Res. 36 (2008) D402–8. <doi:10.1093/nar/gkm957>. [2] L. Wang, H.R. Eghbalnia, A. Bahrami, J.L. Markley, Linear analysis of carbon-13 chemical shift differences and its application to the detection and correction of errors in referencing and spin system identifications, J. Biomol. NMR. 32 (2005) 13–22. <doi:10.1007/s10858-005-1717-0>.
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2023-06-16 |
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r-blrpm
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Due to a limited availability of observed high-resolution precipitation records with adequate length, simulations with stochastic precipitation models are used to generate series for subsequent studies [e.g. Khaliq and Cunmae, 1996, <doi:10.1016/0022-1694(95)02894-3>, Vandenberghe et al., 2011, <doi:10.1029/2009WR008388>]. This package contains an R implementation of the original Bartlett-Lewis rectangular pulse model (BLRPM), developed by Rodriguez-Iturbe et al. (1987) <doi:10.1098/rspa.1987.0039>. It contains a function for simulating a precipitation time series based on storms and cells generated by the model with given or estimated model parameters. Additionally BLRPM parameters can be estimated from a given or simulated precipitation time series. The model simulations can be plotted in a three-layer plot including an overview of generated storms and cells by the model (which can also be plotted individually), a continuous step-function and a discrete precipitation time series at a chosen aggregation level.
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2023-06-16 |
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r-blockmessage
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Creates strings that show a text message in 8 by 8 block letters
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2023-06-16 |
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r-blme
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Maximum a posteriori estimation for linear and generalized linear mixed-effects models in a Bayesian setting. Extends 'lme4' by Douglas Bates, Martin Maechler, Ben Bolker, and Steve Walker.
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2023-06-16 |
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r-biom.utils
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Provides utilities to facilitate import, export and computation with the BIOM (Biological Observation Matrix) format (http://biom-format.org).
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2023-06-16 |
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r-blsm
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Provides a Bayesian latent space model for complex networks, either weighted or unweighted. Given an observed input graph, the estimates for the latent coordinates of the nodes are obtained through a Bayesian MCMC algorithm. The overall likelihood of the graph depends on a fundamental probability equation, which is defined so that ties are more likely to exist between nodes whose latent space coordinates are close. The package is mainly based on the model by Hoff, Raftery and Handcock (2002) <doi:10.1198/016214502388618906> and contains some extra features (e.g., removal of the Procrustean step, weights implemented as coefficients of the latent distances, 3D plots). The original code related to the above model was retrieved from <https://www.stat.washington.edu/people/pdhoff/Code/hoff_raftery_handcock_2002_jasa/>. Users can inspect the MCMC simulation, create and customize insightful graphical representations or apply clustering techniques.
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2023-06-16 |
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r-blockmodels
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Latent and Stochastic Block Model estimation by a Variational EM algorithm. Various probability distribution are provided (Bernoulli, Poisson...), with or without covariates.
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2023-06-16 |
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r-bigsplines
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Fits smoothing spline regression models using scalable algorithms designed for large samples. Seven marginal spline types are supported: linear, cubic, different cubic, cubic periodic, cubic thin-plate, ordinal, and nominal. Random effects and parametric effects are also supported. Response can be Gaussian or non-Gaussian: Binomial, Poisson, Gamma, Inverse Gaussian, or Negative Binomial.
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2023-06-16 |
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r-biocmanager
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A convenient tool to install and update Bioconductor packages.
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2023-06-16 |
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r-bindata
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Generation of correlated artificial binary data.
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2023-06-16 |
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r-bikeshare14
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Anonymised Bay Area bike share trip data for the year 2014. Also contains additional metadata on stations and weather.
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2023-06-16 |
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r-azurevmmetadata
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A simple interface to the instance metadata for a virtual machine running in Microsoft's 'Azure' cloud. This provides information about the VM's configuration, such as its processors, memory, networking, storage, and so on. Part of the 'AzureR' family of packages.
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2023-06-16 |
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r-biopn
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bioPN is a package suited to perform simulation of deterministic and stochastic systems of biochemical reaction networks. Models are defined using a subset of Petri Nets, in a way that is close at how chemical reactions are defined. For deterministic solutions, bioPN creates the associated system of differential equations "on the fly", and solves it with a Runge Kutta Dormand Prince 45 explicit algorithm. For stochastic solutions, bioPN offers variants of Gillespie algorithm, or SSA. For hybrid deterministic/stochastic, it employs the Haseltine and Rawlings algorithm, that partitions the system in fast and slow reactions. bioPN algorithms are developed in C to achieve adequate performance.
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2023-06-16 |
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r-bodenmiller
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This data package contains a subset of the Bodenmiller et al, Nat Biotech 2012 dataset for testing single cell, high dimensional analysis and visualization methods.
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2023-06-16 |
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r-biotic
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Calculates a range of UK freshwater invertebrate biotic indices including BMWP, Whalley, WHPT, Habitat-specific BMWP, AWIC, LIFE and PSI.
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2023-06-16 |
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r-binst
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Various supervised and unsupervised binning tools including using entropy, recursive partition methods and clustering.
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2023-06-16 |
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r-binr
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Implementation of algorithms for cutting numerical values exhibiting a potentially highly skewed distribution into evenly distributed groups (bins). This functionality can be applied for binning discrete values, such as counts, as well as for discretization of continuous values, for example, during generation of features used in machine learning algorithms.
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2023-06-16 |
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r-bimetallic
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A power calculator for Genome-wide association studies (GWAs) with combined gold (error-free) and silver (erroneous) phenotyping per McDavid A, Crane PK, Newton KM, Crosslin DR, et al. (2011)
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2023-06-16 |
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r-bigmemory.sri
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This package provides a shared resource interface for the bigmemory and synchronicity packages.
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2023-06-16 |
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r-bicorn
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Prior transcription factor binding knowledge and target gene expression data are integrated in a Bayesian framework for functional cis-regulatory module inference. Using Gibbs sampling, we iteratively estimate transcription factor associations for each gene, regulation strength for each binding event and the hidden activity for each transcription factor.
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2023-06-16 |
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r-assertive.datetimes
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A set of predicates and assertions for checking the properties of dates and times. This is mainly for use by other package developers who want to include run-time testing features in their own packages. End-users will usually want to use assertive directly.
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2023-06-16 |
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r-bild
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Performs logistic regression for binary longitudinal data, allowing for serial dependence among observations from a given individual and a random intercept term. Estimation is via maximization of the exact likelihood of a suitably defined model. Missing values and unbalanced data are allowed, with some restrictions.
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2023-06-16 |
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r-assertive.data
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A set of predicates and assertions for checking the properties of (country independent) complex data types. This is mainly for use by other package developers who want to include run-time testing features in their own packages. End-users will usually want to use assertive directly.
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2023-06-16 |
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r-anylib
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Made to make your life simpler with packages, by installing and loading a list of packages, whether they are on CRAN, Bioconductor or github. For github, if you do not have the full path, with the maintainer name in it (e.g. "achateigner/topReviGO"), it will be able to load it but not to install it.
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2023-06-16 |
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r-bnormnlr
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Implementation of Bayesian estimation in normal heteroscedastic nonlinear regression Models following Cepeda-Cuervo, (2001).
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2023-06-16 |
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r-blockrand
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Create randomizations for block random clinical trials. Can also produce a pdf file of randomization cards.
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2023-06-16 |
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r-bisrna
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Bisulfite-treated RNA non-conversion in a set of samples is analysed as follows : each sample's non-conversion distribution is identified to a Poisson distribution. P-values adjusted for multiple testing are calculated in each sample. Combined non-conversion P-values and standard errors are calculated on the intersection of the set of samples. For further details, see C Legrand, F Tuorto, M Hartmann, R Liebers, D Jakob, M Helm and F Lyko (2017) <doi:10.1101/gr.210666.116>.
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2023-06-16 |
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r-blatr
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A wrapper around the 'Blat' command line SMTP mailer for Windows. 'Blat' is public domain software, but be sure to read the license before use. It can be found at the Blat website http://www.blat.net.
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2023-06-16 |
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r-bigintegeralgos
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Features the multiple polynomial quadratic sieve algorithm for factoring large integers and a vectorized factoring function that returns the complete factorization of an integer. Utilizes the C library GMP (GNU Multiple Precision Arithmetic) and classes created by Antoine Lucas et al. found in the 'gmp' package.
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2023-06-16 |
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r-bvenn
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This package implements a simple alternative to the traditional Venn diagram. It depicts each overlap as a separate bubble with area proportional to the overlap size. Relation of the bubbles to input sets is shown by their their arrangement.
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2023-06-16 |
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r-bpp
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Implements functions to update Bayesian Predictive Power Computations after not stopping a clinical trial at an interim analysis. Such an interim analysis can either be blinded or unblinded. Code is provided for Normally distributed endpoints with known variance, with a prominent example being the hazard ratio.
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2023-06-16 |
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r-bor
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Transforms focal observations' data, where different types of social interactions can be recorded by multiple observers, into asymmetric data matrices. Each cell in these matrices provides counts on the number of times a specific type of social interaction was initiated by the row subject and directed to the column subject.
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2023-06-16 |
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r-bnpsd
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The Pritchard-Stephens-Donnelly (PSD) admixture model has k intermediate subpopulations from which n individuals draw their alleles dictated by their individual-specific admixture proportions. The BN-PSD model additionally imposes the Balding-Nichols (BN) allele frequency model to the intermediate populations, which therefore evolved independently from a common ancestral population T with subpopulation-specific FST (Wright's fixation index) parameters. The BN-PSD model can be used to yield complex population structures. Method described in Ochoa and Storey (2016) <doi:10.1101/083923>.
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2023-06-16 |
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r-blm
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Implements regression models for binary data on the absolute risk scale. These models are applicable to cohort and population-based case-control data.
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2023-06-16 |
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r-bivarripower
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Implements sample size calculations for bivariate random intercept regression model that are described in Comulada and Weiss (2010)
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2023-06-16 |
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r-bisect
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An implementation of Bisect, a method for inferring cell type composition of samples based on methylation sequencing data (Whole Genome Bisulfite Sequencing and Reduced Representation Sequencing). The method is specifically tailored for sequencing data, and therefore works better than methods developed for methylation arrays. It contains a supervised mode that requires a reference (the methylation probabilities in the pure cell types), and a semi-supervised mode, that requires cell counts for a subset of the samples, but does not require a reference.
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2023-06-16 |
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r-binom
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Constructs confidence intervals on the probability of success in a binomial experiment via several parameterizations
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2023-06-16 |
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r-bisectr
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Tools to find bad commits with git bisect. See https://github.com/wch/bisectr for examples and test script templates.
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2023-06-16 |
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r-binomialcftp
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Binomial random numbers are generated via the perfect sampling algorithm. At each iteration dual markov chains are generated and coalescence is checked. In case coalescence occurs, the resulting number is outputted. In case not, then the algorithm is restarted from T(t)=2*T(t) until coalescence occurs.
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2023-06-16 |
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r-bigml
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The 'bigml' package contains bindings for the BigML API. The package includes methods that provide straightforward access to basic API functionality, as well as methods that accommodate idiomatic R data types and concepts.
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2023-06-16 |
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r-bigreg
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Allows the user to carry out GLM on very large data sets. Data can be created using the data_frame() function and appended to the object with object$append(data); data_frame and data_matrix objects are available that allow the user to store large data on disk. The data is stored as doubles in binary format and any character columns are transformed to factors and then stored as numeric (binary) data while a look-up table is stored in a separate .meta_data file in the same folder. The data is stored in blocks and GLM regression algorithm is modified and carries out a MapReduce- like algorithm to fit the model. The functions bglm(), and summary() and bglm_predict() are available for creating and post-processing of models. The library requires Armadillo installed on your system. It probably won't function on windows since multi-core processing is done using mclapply() which forks R on Unix/Linux type operating systems.
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2023-06-16 |
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r-bsplinepsd
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Implementation of a Metropolis-within-Gibbs MCMC algorithm to flexibly estimate the spectral density of a stationary time series. The algorithm updates a nonparametric B-spline prior using the Whittle likelihood to produce pseudo-posterior samples and is based on the work presented in Edwards, M.C., Meyer, R. and Christensen, N., Statistics and Computing (2018). <doi.org/10.1007/s11222-017-9796-9>.
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2023-06-16 |
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r-bosonsampling
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Classical Boson Sampling using the algorithm of Clifford and Clifford (2017) <arXiv:1706.01260>. Also provides functions for generating random unitary matrices, evaluation of matrix permanents (both real and complex) and evaluation of complex permanent minors.
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2023-06-16 |
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r-bigmemory
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Create, store, access, and manipulate massive matrices. Matrices are allocated to shared memory and may use memory-mapped files. Packages 'biganalytics', 'bigtabulate', 'synchronicity', and 'bigalgebra' provide advanced functionality.
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2023-06-16 |
