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r-additivitytests
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Implementation of the Tukey, Mandel, Johnson-Graybill, LBI, Tusell and modified Tukey non-additivity tests.
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2023-06-16 |
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r-ace2fastq
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The ACE file format is used in genomics to store contigs from sequencing machines. This tools converts it into FASTQ format. Both formats contain the sequence characters and their corresponding quality information. Unlike the FASTQ file, the ace file stores the quality values numerically. The conversion algorithm uses the standard Sanger formula. The package facilitates insertion into pipelines, and content inspection.
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2023-06-16 |
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r-aca
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Offers an interactive function for the detection of breakpoints in series.
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2023-06-16 |
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r-abodoutlier
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Performs angle-based outlier detection on a given dataframe. Three methods are available, a full but slow implementation using all the data that has cubic complexity, a fully randomized one which is way more efficient and another using k-nearest neighbours. These algorithms are specially well suited for high dimensional data outlier detection.
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2023-06-16 |
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r-abf2
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Loads ABF2 files containing gap-free data from electrophysiological recordings, as created by Axon Instruments/Molecular Devices software such as pClamp 10.
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2023-06-16 |
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r-akima
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Several cubic spline interpolation methods of H. Akima for irregular and regular gridded data are available through this package, both for the bivariate case (irregular data: ACM 761, regular data: ACM 760) and univariate case (ACM 433 and ACM 697). Linear interpolation of irregular gridded data is also covered by reusing D. J. Renkas triangulation code which is part of Akimas Fortran code. A bilinear interpolator for regular grids was also added for comparison with the bicubic interpolator on regular grids.
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2023-06-16 |
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r-alscpc
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Using of the accelerated line search algorithm for simultaneously diagonalize a set of symmetric positive definite matrices.
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2023-06-16 |
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r-algaeclassify
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Functions designed to facilitate the assignment of morpho-functional group (MFG) classifications to phytoplankton species based on a combination of taxonomy (Class,Order) and a suite of 7 binomial functional traits. Classifications can also be made using only a species list and a database of trait-derived classifications included in the package. MFG classifications are derived from Salmaso et al. (2015) <doi:10.1111/fwb.12520> and this reference should be cited when using the package. The 'algaeClassify' package is a product of the GEISHA (Global Evaluation of the Impacts of Storms on freshwater Habitat and Structure of phytoplankton Assemblages), funded by CESAB (Centre for Synthesis and Analysis of Biodiversity) and the USGS John Wesley Powell Center, with data and other support provided by members of GLEON (Global Lake Ecology Observation Network). This software is preliminary or provisional and is subject to revision. It is being provided to meet the need for timely best science. The software has not received final approval by the U.S. Geological Survey (USGS). No warranty, expressed or implied, is made by the USGS or the U.S. Government as to the functionality of the software and related material nor shall the fact of release constitute any such warranty. The software is provided on the condition that neither the USGS nor the U.S. Government shall be held liable for any damages resulting from the authorized on unauthorized use of the software.
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2023-06-16 |
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r-adaptmt
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Implementation of adaptive p-value thresholding (AdaPT), including both a framework that allows the user to specify any algorithm to learn local false discovery rate and a pool of convenient functions that implement specific algorithms. See Lei, Lihua and Fithian, William (2016) <arXiv:1609.06035>.
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2023-06-16 |
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r-acswr
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A book designed to meet the requirements of masters students. Tattar, P.N., Suresh, R., and Manjunath, B.G. "A Course in Statistics with R", J. Wiley, ISBN 978-1-119-15272-9.
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2023-06-16 |
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r-advdif4
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This software solves an Advection Bi-Flux Diffusive Problem using the Finite Difference Method FDM. Vasconcellos, J.F.V., Marinho, G.M., Zanni, J.H., 2016, Numerical analysis of an anomalous diffusion with a bimodal flux distribution. <doi:10.1016/j.rimni.2016.05.001>. Silva, L.G., Knupp, D.C., Bevilacqua, L., Galeao, A.C.N.R., Silva Neto, A.J., 2014, Formulation and solution of an Inverse Anomalous Diffusion Problem with Stochastic Techniques. <doi:10.5902/2179460X13184>. In this version, it is possible to include a source as a function depending on space and time, that is, s(x,t).
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2023-06-16 |
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r-adoptr
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Optimize one or two-arm, two-stage designs for clinical trials with respect to several pre-implemented objective criteria or implement custom objectives. Optimization under uncertainty and conditional (given stage-one outcome) constraints are supported. See Pilz M, Kunzmann K, Herrmann C, Rauch G, Kieser M. A variational approach to optimal two-stage designs. Statistics in Medicine. 2019;1–13. <doi:10.1002/sim.8291> for details.
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2023-06-16 |
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r-activedriver
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A mutation analysis tool that discovers cancer driver genes with frequent mutations in protein signalling sites such as post-translational modifications (phosphorylation, ubiquitination, etc). The Poisson generalised linear regression model identifies genes where cancer mutations in signalling sites are more frequent than expected from the sequence of the entire gene. Integration of mutations with signalling information helps find new driver genes and propose candidate mechanisms to known drivers. Reference: Systematic analysis of somatic mutations in phosphorylation signaling predicts novel cancer drivers. Juri Reimand and Gary D Bader. Molecular Systems Biology (2013) 9:637 <doi:10.1038/msb.2012.68>.
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2023-06-16 |
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r-abe
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Performs augmented backward elimination and checks the stability of the obtained model. Augmented backward elimination combines significance or information based criteria with the change in estimate to either select the optimal model for prediction purposes or to serve as a tool to obtain a practically sound, highly interpretable model. More details can be found in Dunkler et al. (2014) <doi:10.1371/journal.pone.0113677>.
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2023-06-16 |
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r-allpossiblespellings
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Contains functions possSpells.fnc and batch.possSpells.fnc.
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2023-06-16 |
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r-aidar
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Read objects from the AIDA (<http://aida.freehep.org/>) file and make them available as dataframes in R.
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2023-06-16 |
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r-acmer
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Implementation of estimator ACME, described in Wolpert (2015), ACME: A Partially Periodic Estimator of Avian & Chiropteran Mortality at Wind Turbines (submitted). Unlike most other models, this estimator supports decreasing-hazard Weibull model for persistence; decreasing search proficiency as carcasses age; variable bleed-through at successive searches; and interval mortality estimates. The package provides, based on search data, functions for estimating the mortality inflation factor in Frequentist and Bayesian settings.
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2023-06-16 |
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r-acceptancesampling
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Provides functionality for creating and evaluating acceptance sampling plans. Sampling plans can be single, double or multiple.
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2023-06-16 |
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r-amap.seq
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An Approximated Most Average Powerful Test with Optimal FDR Control with Application to RNA-seq Data
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2023-06-16 |
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r-alabama
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Augmented Lagrangian Adaptive Barrier Minimization Algorithm for optimizing smooth nonlinear objective functions with constraints. Linear or nonlinear equality and inequality constraints are allowed.
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2023-06-16 |
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r-adequacymodel
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The main application concerns to a new robust optimization package with two major contributions. The first contribution refers to the assessment of the adequacy of probabilistic models through a combination of several statistics, which measure the relative quality of statistical models for a given data set. The second one provides a general purpose optimization method based on meta-heuristics functions for maximizing or minimizing an arbitrary objective function.
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2023-06-16 |
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r-abps
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An implementation of the Abnormal Blood Profile Score (ABPS, part of the Athlete Biological Passport program of the World Anti-Doping Agency), which combines several blood parameters into a single score in order to detect blood doping (Sottas et al. (2006) <doi:10.2202/1557-4679.1011>). The package also contains functions to calculate other scores used in anti-doping programs, such as the OFF-score (Gore et al. (2003) <http://www.haematologica.org/content/88/3/333>), as well as example data.
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2023-06-16 |
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r-airthermo
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Deals with many computations related to the thermodynamics of atmospheric processes. It includes many functions designed to consider the density of air with varying degrees of water vapour in it, saturation pressures and mixing ratios, conversion of moisture indices, computation of atmospheric states of parcels subject to dry or pseudoadiabatic vertical evolutions and atmospheric instability indices that are routinely used for operational weather forecasts or meteorological diagnostics.
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2023-06-16 |
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r-adaptivetau
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Implements adaptive tau leaping to approximate the trajectory of a continuous-time stochastic process as described by Cao et al. (2007) The Journal of Chemical Physics <doi:10.1063/1.2745299> (aka. the Gillespie stochastic simulation algorithm). This package is based upon work supported by NSF DBI-0906041 and NIH K99-GM104158 to Philip Johnson and NIH R01-AI049334 to Rustom Antia.
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2023-06-16 |
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r-admisc
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Contains functions used across packages 'QCA', 'DDIwR', and 'venn'. Interprets and translates DNF - Disjunctive Normal Form expressions, for both binary and multi-value crisp sets, and extracts information (set names, set values) from those expressions. Other functions perform various other checks if possibly numeric (even if all numbers reside in a character vector) and coerce to numeric, or check if the numbers are whole. It also offers, among many others, a highly flexible recoding function.
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2023-06-16 |
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r-acs
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Provides a general toolkit for downloading, managing, analyzing, and presenting data from the U.S. Census (<https://www.census.gov/data/developers/data-sets.html>), including SF1 (Decennial short-form), SF3 (Decennial long-form), and the American Community Survey (ACS). Confidence intervals provided with ACS data are converted to standard errors to be bundled with estimates in complex acs objects. Package provides new methods to conduct standard operations on acs objects and present/plot data in statistically appropriate ways.
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2023-06-16 |
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r-acp
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Analysis of count data exhibiting autoregressive properties, using the Autoregressive Conditional Poisson model (ACP(p,q)) proposed by Heinen (2003).
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2023-06-16 |
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r-ac3net
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Infers directional conservative causal core (gene) networks. It is an advanced version of the algorithm C3NET by providing directional network. Gokmen Altay (2018) <doi:10.1101/271031>, bioRxiv.
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2023-06-16 |
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r-amelia
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A tool that "multiply imputes" missing data in a single cross-section (such as a survey), from a time series (like variables collected for each year in a country), or from a time-series-cross-sectional data set (such as collected by years for each of several countries). Amelia II implements our bootstrapping-based algorithm that gives essentially the same answers as the standard IP or EMis approaches, is usually considerably faster than existing approaches and can handle many more variables. Unlike Amelia I and other statistically rigorous imputation software, it virtually never crashes (but please let us know if you find to the contrary!). The program also generalizes existing approaches by allowing for trends in time series across observations within a cross-sectional unit, as well as priors that allow experts to incorporate beliefs they have about the values of missing cells in their data. Amelia II also includes useful diagnostics of the fit of multiple imputation models. The program works from the R command line or via a graphical user interface that does not require users to know R.
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2023-06-16 |
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r-algdesign
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Algorithmic experimental designs. Calculates exact and approximate theory experimental designs for D,A, and I criteria. Very large designs may be created. Experimental designs may be blocked or blocked designs created from a candidate list, using several criteria. The blocking can be done when whole and within plot factors interact.
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2023-06-16 |
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r-allanvar
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A collection of tools for stochastic sensor error characterization using the Allan Variance technique originally developed by D. Allan.
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2023-06-16 |
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r-alfr
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Allows you to connect to an 'Alfresco' content management repository and interact with its contents using simple and intuitive functions. You will be able to establish a connection session to the 'Alfresco' repository, read and upload content and manage folder hierarchies. For more details on the 'Alfresco' content management repository see <https://www.alfresco.com/ecm-software/document-management>.
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2023-06-16 |
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r-afc
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This is an implementation of the Generalized Discrimination Score (also known as Two Alternatives Forced Choice Score, 2AFC) for various representations of forecasts and verifying observations. The Generalized Discrimination Score is a generic forecast verification framework which can be applied to any of the following verification contexts: dichotomous, polychotomous (ordinal and nominal), continuous, probabilistic, and ensemble. A comprehensive description of the Generalized Discrimination Score, including all equations used in this package, is provided by Mason and Weigel (2009) <doi:10.1175/MWR-D-10-05069.1>.
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2023-06-16 |
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r-adwordsr
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Allows access to selected services that are part of the 'Google Adwords' API <https://developers.google.com/adwords/api/docs/guides/start>. 'Google Adwords' is an online advertising service by 'Google', that delivers Ads to users. This package offers a authentication process using 'OAUTH2'. Currently, there are two methods of data of accessing the API, depending on the type of request. One method uses 'SOAP' requests which require building an 'XML' structure and then sent to the API. These are used for the 'ManagedCustomerService' and the 'TargetingIdeaService'. The second method is by building 'AWQL' queries for the reporting side of the 'Google Adwords' API.
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2023-06-16 |
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r-adapttest
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The functions defined in this program serve for implementing adaptive two-stage tests. Currently, four tests are included: Bauer and Koehne (1994), Lehmacher and Wassmer (1999), Vandemeulebroecke (2006), and the horizontal conditional error function. User-defined tests can also be implemented. Reference: Vandemeulebroecke, An investigation of two-stage tests, Statistica Sinica 2006.
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2023-06-16 |
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r-acopula
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Archimax copulas are mixture of Archimedean and EV copulas. The package provides definitions of several parametric families of generator and dependence function, computes CDF and PDF, estimates parameters, tests for goodness of fit, generates random sample and checks copula properties for custom constructs. In 2-dimensional case explicit formulas for density are used, in the contrary to higher dimensions when all derivatives are linearly approximated. Several non-archimax families (normal, FGM, Plackett) are provided as well.
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2023-06-16 |
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r-acfmperiod
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Non-robust and robust computations of the sample autocovariance (ACOVF) and sample autocorrelation functions (ACF) of univariate and multivariate processes. The methodology consists in reversing the diagonalization procedure involving the periodogram or the cross-periodogram and the Fourier transform vectors, and, thus, obtaining the ACOVF or the ACF as discussed in Fuller (1995) <doi:10.1002/9780470316917>. The robust version is obtained by fitting robust M-regressors to obtain the M-periodogram or M-cross-periodogram as discussed in Reisen et al. (2017) <doi:10.1016/j.jspi.2017.02.008>.
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2023-06-16 |
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r-acclma
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The main function is plotLMA(sourcefile,header) that takes a data set and plots the appropriate LMA and ACC graphs. If no sourcefile (a string) was passed, a manual data entry window is opened. The header parameter indicates by TRUE/FALSE (false by default) if the source CSV file has a head row or not. The data set should contain only one independent variable (X) and one dependent varialbe (Y) and can contain a weight for each observation
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2023-06-16 |
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r-alphasimr
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The successor to the 'AlphaSim' software for breeding program simulation [Faux et al. (2016) <doi:10.3835/plantgenome2016.02.0013>]. Used for stochastic simulations of breeding programs to the level of DNA sequence for every individual. Contained is a wide range of functions for modeling common tasks in a breeding program, such as selection and crossing. These functions allow for constructing simulations of highly complex plant and animal breeding programs via scripting in the R software environment. Such simulations can be used to evaluate overall breeding program performance and conduct research into breeding program design, such as implementation of genomic selection. Included is the 'Markovian Coalescent Simulator' ('MaCS') for fast simulation of biallelic sequences according to a population demographic history [Chen et al. (2009) <doi:10.1101/gr.083634.108>].
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2023-06-16 |
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r-alpaca
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Provides a routine to concentrate out factors with many levels during the optimization of the log-likelihood function of the corresponding generalized linear model (glm). The package is based on the algorithm proposed by Stammann (2018) <arXiv:1707.01815> and is restricted to glm's that are based on maximum likelihood estimation and non-linear. It also offers an efficient algorithm to recover estimates of the fixed effects in a post-estimation routine and includes robust and multi-way clustered standard errors. Further the package provides an analytical bias-correction for binary choice models (logit and probit) derived by Fernandez-Val and Weidner (2016) <doi:10.1016/j.jeconom.2015.12.014>.
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2023-06-16 |
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r-aliner
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Functions are provided to calculate the 'ALINE' Distance between words as per (Kondrak 2000) and (Downey, Hallmark, Cox, Norquest, & Lansing, 2008, <doi:10.1080/09296170802326681>). The score is based on phonetic features represented using the Unicode-compliant International Phonetic Alphabet (IPA). Parameterized features weights are used to determine the optimal alignment and functions are provided to estimate optimum values using a genetic algorithm and supervised learning. See (Downey, Sun, and Norquest 2017, <https://journal.r-project.org/archive/2017/RJ-2017-005/index.html>.
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2023-06-16 |
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r-acrt
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Functions for testing affine hypotheses on the regression coefficient vector in regression models with autocorrelated errors.
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2023-06-16 |
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r-acet
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Twin models that are able to estimate the dynamic behaviour of the variance components in the classical twin models with respect to age using B-splines and P-splines.
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2023-06-16 |
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r-alluvial
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Creating alluvial diagrams (also known as parallel sets plots) for multivariate and time series-like data.
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2023-06-16 |
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r-aggregation
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Contains functionality for performing the following methods of p-value aggregation: Fisher's method [Fisher, RA (1932, ISBN: 9780028447308)], the Lancaster method (weighted Fisher's method) [Lancaster, HO (1961, <doi:10.1111/j.1467-842X.1961.tb00058.x>)], and Sidak correction [Sidak, Z (1967, <doi:10.1080/01621459.1967.10482935>)]. Please cite Yi et al., the manuscript corresponding to this package [Yi, L et al., (2017), <doi:10.1101/190199>].
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2023-06-16 |
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r-afpt
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Allows estimation and modelling of flight costs in animal (vertebrate) flight, implementing the aerodynamic power model described in Klein Heerenbrink et al. (2015) <doi:10.1098/rspa.2014.0952>. Taking inspiration from the program 'Flight', developed by Colin Pennycuick (Pennycuick (2008) "Modelling the flying bird". Amsterdam: Elsevier. ISBN 0-19-857721-4), flight performance is estimated based on basic morphological measurements such as body mass, wingspan and wing area. 'afpt' can be used to make predictions on how animals should adjust their flight behaviour and wingbeat kinematics to varying flight conditions.
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2023-06-16 |
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r-adklakedata
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Package for the access and distribution of Long-term lake datasets from lakes in the Adirondack Park, northern New York state. Includes a wide variety of physical, chemical, and biological parameters from 28 lakes. Data are from multiple collection organizations and have been harmonized in both time and space for ease of reuse.
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2023-06-16 |
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r-adaptmcmc
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Enables sampling from arbitrary distributions if the log density is known up to a constant; a common situation in the context of Bayesian inference. The implemented sampling algorithm was proposed by Vihola (2012) <DOI:10.1007/s11222-011-9269-5> and achieves often a high efficiency by tuning the proposal distributions to a user defined acceptance rate.
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2023-06-16 |
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r-abc.data
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Contains data which are used by functions of the 'abc' package.
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2023-06-16 |
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r-rstan
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User-facing R functions are provided to parse, compile, test, estimate, and analyze Stan models by accessing the header-only Stan library provided by the 'StanHeaders' package. The Stan project develops a probabilistic programming language that implements full Bayesian statistical inference via Markov Chain Monte Carlo, rough Bayesian inference via 'variational' approximation, and (optionally penalized) maximum likelihood estimation via optimization. In all three cases, automatic differentiation is used to quickly and accurately evaluate gradients without burdening the user with the need to derive the partial derivatives.
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2023-06-16 |
