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r-bio3d
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Utilities to process, organize and explore protein structure, sequence and dynamics data. Features include the ability to read and write structure, sequence and dynamic trajectory data, perform sequence and structure database searches, data summaries, atom selection, alignment, superposition, rigid core identification, clustering, torsion analysis, distance matrix analysis, structure and sequence conservation analysis, normal mode analysis, principal component analysis of heterogeneous structure data, and correlation network analysis from normal mode and molecular dynamics data. In addition, various utility functions are provided to enable the statistical and graphical power of the R environment to work with biological sequence and structural data. Please refer to the URLs below for more information.
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2023-06-16 |
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r-biglmm
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Regression for data too large to fit in memory. This package functions exactly like the 'biglm' package, but works with later versions of R.
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2023-06-16 |
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r-bfsl
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Provides the solution from York (1968) <doi:10.1016/S0012-821X(68)80059-7> for fitting a straight line to bivariate data with errors in both coordinates. It gives unbiased estimates of the intercept, slope and standard errors of the best-fit straight line to independent points with (possibly correlated) normally distributed errors in both x and y. Other commonly used errors-in-variables methods, such as orthogonal distance regression, geometric mean regression or Deming regression are special cases of York’s solution.
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2023-06-16 |
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r-bayest
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Provides an Markov-Chain-Monte-Carlo algorithm for Bayesian t-tests on the effect size. The underlying Gibbs sampler is based on a two-component Gaussian mixture and approximates the posterior distributions of the effect size, the difference of means and difference of standard deviations. A posterior analysis of the effect size via the region of practical equivalence is provided, too. For more details about the Gibbs sampler see Kelter (2019) <arXiv:1906.07524>.
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2023-06-16 |
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r-aws.ses
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A simple client package for the Amazon Web Services (AWS) Simple Email Service (SES) <http://aws.amazon.com/ses/> REST API.
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2023-06-16 |
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r-bgphazard
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Computes the hazard rate estimate as described by Nieto-Barajas and Walker (2002) and Nieto-Barajas (2003).
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2023-06-16 |
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r-bcra
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Functions provide risk projections of invasive breast cancer based on Gail model according to National Cancer Institute's Breast Cancer Risk Assessment Tool algorithm for specified race/ethnic groups and age intervals.
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2023-06-16 |
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r-bcpmeta
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A Bayesian approach to detect mean shifts in AR(1) time series while accommodating metadata (if available). In addition, a linear trend component is allowed.
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2023-06-16 |
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r-bbmv
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Provides a set of functions to fit general macroevolutionary models for continuous traits evolving in adaptive landscapes of any shape. This package implements the Fokker-Planck-Kolmogorov model (FPK), in which the trait evolves under random diffusion but is also subject to a force that pulls it towards specific values - this force can be of any shape. FPK has a version in which hard reflective bounds exist at the extremes of the trait interval: this second model is called BBMV.
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2023-06-16 |
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r-behavr
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Implements an S3 class based on 'data.table' to store and process efficiently ethomics (high-throughput behavioural) data.
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2023-06-16 |
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r-bbemkr
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Bayesian bandwidth estimation for Nadaraya-Watson type multivariate kernel regression with Gaussian error density
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2023-06-16 |
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r-bayloredpsych
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Functions and data used for Baylor University Educational Psychology Quantitative Courses
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2023-06-16 |
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r-assertive.types
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A set of predicates and assertions for checking the types of variables. 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-bibplots
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Currently, the package provides four functions for plotting and analyzing bibliometric data (JIF, Journal Impact Factor, and paper percentile values), beamplots with citations, and two plot function to visualize the result of a reference publication year spectroscopy (RPYS) analysis performed in the free software 'CRExplorer' (see <http://crexplorer.net>). Further extension to more plot variants is planned.
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2023-06-16 |
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r-bethel
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The sample size according to the Bethel's procedure.
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2023-06-16 |
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r-bestree
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Decision tree algorithm with a major feature added. Allows for users to define an ordering on the partitioning process. Resulting in Branch-Exclusive Splits Trees (BEST). Cedric Beaulac and Jeffrey S. Rosentahl (2019) <arXiv:1804.10168>.
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2023-06-16 |
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r-beanplot
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Plots univariate comparison graphs, an alternative to boxplot/stripchart/violin plot.
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2023-06-16 |
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r-aws.sns
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A simple client package for the Amazon Web Services ('AWS') Simple Notification Service ('SNS') 'API' <https://aws.amazon.com/sns/>.
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2023-06-16 |
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r-belex
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Tools for downloading historical financial data from the www.belex.rs.
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2023-06-16 |
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r-beast
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Assume that a temporal process is composed of contiguous segments with differing slopes and replicated noise-corrupted time series measurements are observed. The unknown mean of the data generating process is modelled as a piecewise linear function of time with an unknown number of change-points. The package infers the joint posterior distribution of the number and position of change-points as well as the unknown mean parameters per time-series by MCMC sampling. A-priori, the proposed model uses an overfitting number of mean parameters but, conditionally on a set of change-points, only a subset of them influences the likelihood. An exponentially decreasing prior distribution on the number of change-points gives rise to a posterior distribution concentrating on sparse representations of the underlying sequence, but also available is the Poisson distribution. See Papastamoulis et al (2017) <arXiv:1709.06111> for a detailed presentation of the method.
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2023-06-16 |
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r-bcaboot
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Computation of bootstrap confidence intervals in an almost automatic fashion.
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2023-06-16 |
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r-bayesmams
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Calculating Bayesian sample sizes for multi-arm trials where several experimental treatments are compared to a common control, perhaps even at multiple stages.
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2023-06-16 |
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r-aws.sqs
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A simple client package for the Amazon Web Services ('AWS') Simple Queue Service ('SQS') <https://aws.amazon.com/sqs/> 'API'.
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2023-06-16 |
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r-bgmfiles
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A collection of box-geometry model (BGM) files for the Atlantis ecosystem model. Atlantis is a deterministic, biogeochemical, whole-of-ecosystem model (see <http://atlantis.cmar.csiro.au/> for more information).
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2023-06-16 |
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r-berryfunctions
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Draw horizontal histograms, color scattered points by 3rd dimension, enhance date- and log-axis plots, zoom in X11 graphics, trace errors and warnings, use the unit hydrograph in a linear storage cascade, convert lists to data.frames and arrays, fit multiple functions.
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2023-06-16 |
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r-benchden
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Full implementation of the 28 distributions introduced as benchmarks for nonparametric density estimation by Berlinet and Devroye (1994). Includes densities, cdfs, quantile functions and generators for samples as well as additional information on features of the densities. Also contains the 4 histogram densities used in Rozenholc/Mildenberger/Gather (2010).
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2023-06-16 |
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r-bdp2
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Tools and workflow to choose design parameters in Bayesian adaptive single-arm phase II trial designs with binary endpoint (response, success) with possible stopping for efficacy and futility at interim analyses. Also contains routines to determine and visualize operating characteristics. See Kopp-Schneider et al. (2018) <doi:10.1002/bimj.201700209>.
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2023-06-16 |
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r-bayesvalidate
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BayesValidate implements the software validation method described in the paper "Validation of Software for Bayesian Models using Posterior Quantiles" (Cook, Gelman, and Rubin, 2005). It inputs a function to perform Bayesian inference as well as functions to generate data from the Bayesian model being fit, and repeatedly generates and analyzes data to check that the Bayesian inference program works properly.
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2023-06-16 |
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r-bayesni
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A Bayesian testing procedure for noninferiority trials with binary endpoints. The prior is constructed based on Bernstein polynomials with options for both informative and non-informative prior. The critical value of the test statistic (Bayes factor) is determined by minimizing total weighted error (TWE) criteria
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2023-06-16 |
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r-aws.lambda
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A simple client package for the Amazon Web Services ('AWS') Lambda 'API' <https://aws.amazon.com/lambda/>.
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2023-06-16 |
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r-bhm
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Contains tools to fit both predictive and prognostic biomarker effects using biomarker threshold models. Evaluate the treatment effect, biomarker effect and treatment-biomarker interaction using probability index measurement. Test for treatment-biomarker interaction using residual bootstrap method.
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2023-06-16 |
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r-bhh2
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Functions and data sets reproducing some examples in Box, Hunter and Hunter II. Useful for statistical design of experiments, especially factorial experiments.
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2023-06-16 |
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r-bgge
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Application of genome prediction for a continuous variable, focused on genotype by environment (GE) genomic selection models (GS). It consists a group of functions that help to create regression kernels for some GE genomic models proposed by Jarquín et al. (2014) <doi:10.1007/s00122-013-2243-1> and Lopez-Cruz et al. (2015) <doi:10.1534/g3.114.016097>. Also, it computes genomic predictions based on Bayesian approaches. The prediction function uses an orthogonal transformation of the data and specific priors present by Cuevas et al. (2014) <doi:10.1534/g3.114.013094>.
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2023-06-16 |
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r-beeswarm
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The bee swarm plot is a one-dimensional scatter plot like "stripchart", but with closely-packed, non-overlapping points.
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2023-06-16 |
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r-bb
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Barzilai-Borwein spectral methods for solving nonlinear system of equations, and for optimizing nonlinear objective functions subject to simple constraints. A tutorial style introduction to this package is available in a vignette on the CRAN download page or, when the package is loaded in an R session, with vignette("BB").
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2023-06-16 |
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r-aws.kms
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Client package for the 'AWS Key Management Service' <https://aws.amazon.com/kms/>, a cloud service for managing encryption keys.
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2023-06-16 |
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r-bgsimd
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Implement an efficient block Gibbs sampler with incomplete data from a multinomial distribution taking values from the k categories 1,2,...,k, where data are assumed to miss at random and each missing datum belongs to one and only one of m distinct non-empty proper subsets A1, A2,..., Am of 1,2,...,k and the k categories are labelled such that only consecutive A's may overlap.
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2023-06-16 |
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r-bbo
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This package provides an R implementation of Biogeography-Based Optimization (BBO), originally invented by Prof. Dan Simon, Cleveland State University, Ohio. This method is an application of the concept of biogeography, a study of the geographical distribution of biological organisms, to optimization problems. More information about this method can be found here: http://academic.csuohio.edu/simond/bbo/.
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2023-06-16 |
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r-bayfoxr
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A Bayesian, global planktic foraminifera core top calibration to modern sea-surface temperatures. Includes four calibration models, considering species-specific calibration parameters and seasonality.
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2023-06-16 |
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r-bayespiecewiseicar
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Fits a piecewise exponential hazard to survival data using a Hierarchical Bayesian model with an Intrinsic Conditional Autoregressive formulation for the spatial dependency in the hazard rates for each piece. This function uses Metropolis- Hastings-Green MCMC to allow the number of split points to vary. This function outputs graphics that display the histogram of the number of split points and the trace plots of the hierarchical parameters. The function outputs a list that contains the posterior samples for the number of split points, the location of the split points, and the log hazard rates corresponding to these splits. Additionally, this outputs the posterior samples of the two hierarchical parameters, Mu and Sigma^2.
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2023-06-16 |
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r-bdpv
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Computation of asymptotic confidence intervals for negative and positive predictive values in binary diagnostic tests in case-control studies. Experimental design for hypothesis tests on predictive values.
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2023-06-16 |
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r-baystar
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The manuscript introduces the BAYSTAR package, which provides the functionality for Bayesian estimation in autoregressive threshold models.
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2023-06-16 |
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r-bhat
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Functions for MLE, MCMC, CIs (originally in Fortran)
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2023-06-16 |
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r-betacal
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Fit beta calibration models and obtain calibrated probabilities from them.
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2023-06-16 |
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r-bayestreeprior
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Provides a way to simulate from the prior distribution of Bayesian trees by Chipman et al. (1998) <DOI:10.2307/2669832>. The prior distribution of Bayesian trees is highly dependent on the design matrix X, therefore using the suggested hyperparameters by Chipman et al. (1998) <DOI:10.2307/2669832> is not recommended and could lead to unexpected prior distribution. This work is part of my master thesis (expected 2016).
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2023-06-16 |
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r-aws.translate
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A client for 'AWS Translate' <https://aws.amazon.com/documentation/translate>, a machine translation service that will convert a text input in one language into a text output in another language.
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2023-06-16 |
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r-aws.transcribe
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Client for 'AWS Transcribe' <https://aws.amazon.com/documentation/transcribe>, a cloud transcription service that can convert an audio media file in English and other languages into a text transcript.
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2023-06-16 |
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r-beqi2
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Tool for analysing benthos data. It estimates several quality indices like the total abundance of species, species richness, Margalef's d, AZTI Marine Biotic Index (AMBI), and the BEQI-2 index. Furthermore, additional (optional) features are provided that enhance data preprocessing: (1) genus to species conversion, i.e.,taxa counts at the taxonomic genus level can optionally be converted to the species level and (2) pooling: small samples are combined to bigger samples with a standardized size to (a) meet the data requirements of the AMBI, (b) generate comparable species richness values and (c) give a higher benthos signal to noise ratio.
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2023-06-16 |
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r-benford.analysis
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Provides tools that make it easier to validate data using Benford's Law.
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2023-06-16 |
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r-bcgee
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Provides bias-corrected estimates for the regression coefficients of a marginal model estimated with generalized estimating equations. Details about the bias formula used are in Lunardon, N., Scharfstein, D. (2017) <doi:10.1002/sim.7366>.
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2023-06-16 |
