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r-interactiveigraph
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An extension of the package 'igraph'. This package create possibly to work with 'igraph' objects interactively.
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2023-06-16 |
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r-kerasr
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Provides a consistent interface to the 'Keras' Deep Learning Library directly from within R. 'Keras' provides specifications for describing dense neural networks, convolution neural networks (CNN) and recurrent neural networks (RNN) running on top of either 'TensorFlow' or 'Theano'. Type conversions between Python and R are automatically handled correctly, even when the default choices would otherwise lead to errors. Includes complete R documentation and many working examples.
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2023-06-16 |
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r-intriniostockapi
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Download financial data from the free 'Intrinio Stock API' (<https://intrinio.com/>). 'Intrinio' offers a REST API which provides financial markets data including intra-day stock prices, historical stock prices, technical indicators, company fundamentals, and more. Complete documentation for the 'Intrinio Stock API' is available here: <https://intrinio.com/documentation/api/>. To access the 'Intrinio Stock API', simply create a free account <https://intrinio.com/>.
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2023-06-16 |
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r-intoo
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Contains attribute operators (%$% and %$%<-), convenience functions and functions for printing objects compactly but informatively. And partly supports nested matrices.
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2023-06-16 |
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r-interferenceci
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Computes large sample confidence intervals of Liu and Hudgens (2014), exact confidence intervals of Tchetgen Tchetgen and VanderWeele (2012), and exact confidence intervals of Rigdon and Hudgens (2014) for treatment effects on a binary outcome in two-stage randomized experiments with interference.
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2023-06-16 |
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r-jsonarr
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This package enables users to access MongoDB by running queries and returning their results in R data frames. Usually, data in MongoDB is only available in the form of a JSON document. jSonarR uses data processing and conversion capabilities in the jSonar Analytics Platform and the JSON Studio Gateway (http://www.jsonstudio.com), to convert it to a tabular format which is easy to use with existing R packages.
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2023-06-16 |
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r-iqlearn
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Estimate an optimal dynamic treatment regime using Interactive Q-learning.
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2023-06-16 |
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r-infra
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Takes a data frame containing latitude and longitude coordinates and downloads images from map servers to determine their file size as a proxy of infrastructure
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2023-06-16 |
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r-inference
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Collection of functions to extract inferential values (point estimates, confidence intervals, p-values, etc) of a fitted model object into a matrix-like object that can be used for table/report generation; transform point estimates via the delta method.
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2023-06-16 |
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r-jenkins
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Manage jobs and builds on your Jenkins CI server <https://jenkins.io/>. Create and edit projects, schedule builds, manage the queue, download build logs, and much more.
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2023-06-16 |
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r-indiantaxcalc
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Calculate Indian Income Tax liability for Financial years of Individual resident aged below 60 years,Senior Citizen,Super Senior Citizen, Firm, Local Authority, Any Non Resident Individual / Hindu Undivided Family / Association of Persons /Body of Individuals / Artificial Judicial Person, Co-operative Society.
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2023-06-16 |
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r-infdim
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This package contains functions to perform calculations of the infine-dimensional model (IDM) and to produce 95% confidence intervals around the model elements through bootstrapping.
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2023-06-16 |
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r-hail
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Read data from the City of Portland's 'HYDRA' <http://or.water.usgs.gov/precip/> rainfall datasets within R.
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2023-06-16 |
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r-guerry
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Maps of France in 1830, multivariate datasets from A.-M. Guerry and others, and statistical and graphic methods related to Guerry's "Moral Statistics of France". The goal is to facilitate the exploration and development of statistical and graphic methods for multivariate data in a geospatial context of historical interest.
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2023-06-16 |
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r-ffield
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Force field simulation of interaction of set of points. Very useful for placing text labels on graphs, such as scatterplots.
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2023-06-16 |
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r-hssvd
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A data mining tool for discovering subgroups of patients and genes that simultaneously display unusual levels of variability compared to other genes and patients. Based on sparse singular value decomposition (SSVD), the method can detect both mean and variance biclusters in the presence of heterogeneous residual variance.
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2023-06-16 |
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r-hdmd
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High Dimensional Molecular Data (HDMD) typically have many more variables or dimensions than observations or replicates (D>>N). This can cause many statistical procedures to fail, become intractable, or produce misleading results. This package provides several tools to reduce dimensionality and analyze biological data for meaningful interpretation of results. Factor Analysis (FA), Principal Components Analysis (PCA) and Discriminant Analysis (DA) are frequently used multivariate techniques. However, PCA methods prcomp and princomp do not reflect the proportion of total variation of each principal component. Loadings.variation displays the relative and cumulative contribution of variation for each component by accounting for all variability in data. When D>>N, the maximum likelihood method cannot be applied in FA and the the principal axes method must be used instead, as in factor.pa of the psych package. The factor.pa.ginv function in this package further allows for a singular covariance matrix by applying a general inverse method to estimate factor scores. Moreover, factor.pa.ginv removes and warns of any variables that are constant, which would otherwise create an invalid covariance matrix. Promax.only further allows users to define rotation parameters during factor estimation. Similar to the Euclidean distance, the Mahalanobis distance estimates the relationship among groups. pairwise.mahalanobis computes all such pairwise Mahalanobis distances among groups and is useful for quantifying the separation of groups in DA. Genetic sequences are composed of discrete alphabetic characters, which makes estimates of variability difficult. MolecularEntropy and MolecularMI calculate the entropy and mutual information to estimate variability and covariability, respectively, of DNA or Amino Acid sequences. Functional grouping of amino acids (Atchley et al 1999) is also available for entropy and mutual information estimation. Mutual information values can be normalized by NMI to account for the background distribution arising from the stochastic pairing of independent, random sites. Alternatively, discrete alphabetic sequences can be transformed into biologically informative metrics to be used in various multivariate procedures. FactorTransform converts amino acid sequences using the amino acid indices determined by Atchley et al 2005.
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2023-06-16 |
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r-fticrms
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This package was developed partially with funding from the NIH Training Program in Biomolecular Technology (2-T32-GM08799).
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2023-06-16 |
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r-es
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Implementation of the Edge Selection Algorithm
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2023-06-16 |
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r-hiv.lifetables
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The functions in this package produce a complete set of mortality rates as a function of a combination of HIV prevalence and either life expectancy at birth (e0), child mortality (5q0), or child mortality with adult mortality (45q15)
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2023-06-16 |
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r-hartools
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The goal of 'HARtools' is to provide a simple set of functions to read/parse, write and visualise HTTP Archive ('HAR') files in R.
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2023-06-16 |
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r-gwg
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Based on calculations of 758 women this package calculates positive predictive values (PPV) and negative predictive values (NPV) for inadequate and excessive gestational weight gain (GWG) for different prevalences for different BMI categories.
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2023-06-16 |
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r-guardianr
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Provides an interface to the Open Platform's Content API of the Guardian Media Group. It retrieves content from news outlets The Observer, The Guardian, and guardian.co.uk from 1999 to current day.
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2023-06-16 |
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r-graphicsqc
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Functions to generate graphics files, compare them with "model" files, and report the results, including visual and textual diffs of any differences.
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2023-06-16 |
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r-gpdtest
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This package computes the bootstrap goodness-of-fit test for the generalized Pareto distribution by Villasenor-Alva and Gonzalez-Estrada (2009). The null hypothesis includes heavy and non-heavy tailed gPd's. A function for fitting the gPd to data using the parameter estimation methods proposed in the same article is also provided.
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2023-06-16 |
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r-gethr
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Full access to the Geth command line interface for running full Ethereum nodes. With gethr it is possible to carry out different tasks such as mine ether, transfer funds, create contacts, explore block history, etc. The package also provides access to all the available APIs. The officially exposed by Ethereum blockchains (eth, shh, web3, net) and some provided directly by Geth (admin, debug, miner, personal, txpool). For more details on Ethereum, access the project website <https://www.ethereum.org/>. For more details on the Geth client, access the project website <https://github.com/ethereum/go-ethereum/wiki/geth/>.
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2023-06-16 |
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r-gadifpt
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In this package we consider Gaussian Diffusion processes and smooth thresholds. After evaluating the mean of the process to check the subthreshold regimen hypothesis, the FPT density function is reconstructed via the numerical quadrature of the integral equation in (Buonocore 1987); first passage times are also generated by the method in (Buonocore 2014) and results are compared. The timestep of the simulations can iteratively be refined. User should provide the functional form for the drift and the infinitesimal variance in the script 'userfunc.R' and for the threshold in the script 'userthresh.R'. All the parameters required by the implementation are to be set in the script 'userparam.R'. Example scripts for common drifts and thresholds are given.
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2023-06-16 |
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r-frambgrowth
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Generation of theoretical size distributions of framboidal or sunflower pyrite. The growth mechanisms used are surface and supply controlled and dependent or independent of size. The algorithms are fully described in the published work in Mineralogy and Petrology journal: "Theoretical growth of framboidal and sunflower pyrite using the R-package frambgrowth" The authors Merinero, R., and Cardenes, V. (2018). <DOI:10.1007/s00710-017-0535-x>.
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2023-06-16 |
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r-fastpseudo
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Computes pseudo-observations for survival analysis on right-censored data based on restricted mean survival time.
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2023-06-16 |
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r-exactmeta
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Perform exact fixed effect meta analysis for rare events data without the need of artificial continuity correction.
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2023-06-16 |
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r-ew
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Edgeworth Expansion calculation.
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2023-06-16 |
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r-imgw
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Download Polish meteorological and hydrological data from the Institute of Meteorology and Water Management - National Research Institute (<https://dane.imgw.pl/>). This package also allows for adding geographical coordinates for each observation.
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2023-06-16 |
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r-iabin
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In randomized-controlled trials, interim analyses are often planned for possible early trial termination to claim superiority or futility of a new therapy. Blinded data also have information about the potential treatment difference between the groups. We developed a blinded data monitoring tool that enables investigators to predict whether they observe such an unblinded interim analysis results that supports early termination of the trial. Investigators may skip some of the planned interim analyses if an early termination is unlikely. This tool will provide reference information about N: Sample size at interim analysis, and T: Total number of responders at interim analysis for decision on performing an interim analysis.
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2023-06-16 |
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r-hiest
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Uses likelihood to estimate ancestry and heterozygosity. Evaluates simple hybrid classifications (parentals, F1, F2, backcrosses). Estimates genomic clines.
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2023-06-16 |
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r-glmmboot
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Performs bootstrap resampling for most models that update() works for. There are two primary functions: bootstrap_model() performs block resampling if random effects are present, and case resampling if not; bootstrap_ci() converts output from bootstrap model runs into confidence intervals and p-values. By default, bootstrap_model() calls bootstrap_ci(). Package motivated by Humphrey and Swingley (2018) <arXiv:1805.08670>.
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2023-06-16 |
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r-gibbs.met
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This package provides two generic functions for performing Markov chain sampling in a naive way for a user-defined target distribution, which involves only continuous variables. The function "gibbs_met" performs Gibbs sampling with each 1-dimensional distribution sampled with Metropolis update using Gaussian proposal distribution centered at the previous state. The function "met_gaussian" updates the whole state with Metropolis method using independent Gaussian proposal distribution centered at the previous state. The sampling is carried out without considering any special tricks for improving efficiency. This package is aimed at only routine applications of MCMC in moderate-dimensional problems.
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2023-06-16 |
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r-fuzzyfdr
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Exact calculation of fuzzy decision rules for multiple testing. Choose to control FDR (false discovery rate) using the Benjamini and Hochberg method, or FWER (family wise error rate) using the Bonferroni method. Kulinsakaya and Lewin (2007).
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2023-06-16 |
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r-functools
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Extends functional programming in R by providing support to the usual higher order functional suspects (Map, Reduce, Filter, etc.).
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2023-06-16 |
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r-fasthica
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It implements HICA (Hierarchical Independent Component Analysis) algorithm. This approach, obtained through the integration between treelets and Independent Component Analysis, is able to provide a multi-scale non-orthogonal data-driven basis, whose elements have a phenomenological interpretation according to the problem under study.
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2023-06-16 |
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r-eyetracking
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Misc function for working with eyetracking data
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2023-06-16 |
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r-expert
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Expert opinion (or judgment) is a body of techniques to estimate the distribution of a random variable when data is scarce or unavailable. Opinions on the quantiles of the distribution are sought from experts in the field and aggregated into a final estimate. The package supports aggregation by means of the Cooke, Mendel-Sheridan and predefined weights models.
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2023-06-16 |
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r-events
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Stores, manipulates, aggregates and otherwise messes with event data from KEDS/TABARI or any other extraction tool with similar output
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2023-06-16 |
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r-imprprobest
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A minimum distance estimator is calculated for an imprecise probability model. The imprecise probability model consists of upper coherent previsions whose credal sets are given by a finite number of constraints on the expectations. The parameter set is finite. The estimator chooses that parameter such that the empirical measure lies next to the corresponding credal set with respect to the total variation norm.
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2023-06-16 |
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r-grpregoverlap
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Fit the regularization path of linear, logistic or Cox models with overlapping grouped covariates based on the latent group lasso approach. Latent group MCP/SCAD as well as bi-level selection methods, namely the group exponential lasso and the composite MCP are also available. This package serves as an extension of R package 'grpreg' (by Dr. Patrick Breheny <[email protected]>) for grouped variable selection involving overlaps between groups.
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2023-06-16 |
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r-grouped
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Regression models for grouped and coarse data, under the Coarsened At Random assumption.
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2023-06-16 |
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r-gibbsacov
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Gibbs sampler for one-way linear mixed-effects models (ANOVA, ANCOVA) with homoscedasticity of errors and uniform priors.
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2023-06-16 |
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r-flower
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Flowering is an important life history trait of flowering plants. It has been mainly analyzed with respect to flowering onset and duration of flowering. This tools provide some functions to compute the temporal distribution of an flowering individual related to other population members. fCV() measures the temporal variation in flowering. RIind() measures the rank order of flowering for individual plants within a population. SI(), SI2(), SI3(), and SI4() calculate flowering synchrony with different methods.
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2023-06-16 |
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r-fitdrc
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Fits Density Ratio Classes to elicited probability-quantile points or intervals.
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2023-06-16 |
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r-fgof
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Goodness-of-fit test with multiplier or parametric bootstrap.
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2023-06-16 |
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r-fast
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The Fourier Amplitude Sensitivity Test (FAST) is a method to determine global sensitivities of a model on parameter changes with relatively few model runs. This package implements this sensitivity analysis method.
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2023-06-16 |
