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r-irepro
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Calculates intraclass correlation coefficient (ICC) for assessing reproducibility of interval-censored data with two repeated measurements (Kovacic and Varnai (2014) <doi:10.1097/EDE.0000000000000139>). ICC is estimated by maximum likelihood from model with one fixed and one random effect (both intercepts). Help in model checking (normality of subjects' means and residuals) is provided.
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2023-06-16 |
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r-iosmooth
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Density, spectral density, and regression estimation using infinite order flat-top kernels.
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2023-06-16 |
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r-interventionaldbn
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This package allows a dynamic Bayesian network to be inferred from microarray timecourse data with interventions (inhibitors).
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2023-06-16 |
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r-intervcomp
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Performs hypothesis testing using the interval estimates (e.g., confidence intervals). The non-overlapping interval estimates indicates the statistical significance. References to these procedures can be found at Noguchi and Marmolejo-Ramos (2016) <doi:10.1080/00031305.2016.1200487>, Bonett and Seier (2003) <doi:10.1198/0003130032323>, and Lemm (2006) <doi:10.1300/J082v51n02_05>.
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2023-06-16 |
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r-insurancedata
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Insurance datasets, which are often used in claims severity and claims frequency modelling. It helps testing new regression models in those problems, such as GLM, GLMM, HGLM, non-linear mixed models etc. Most of the data sets are applied in the project "Mixed models in ratemaking" supported by grant NN 111461540 from Polish National Science Center.
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2023-06-16 |
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r-inferencesmr
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The InferenceSMR package provides functions to make inference about the standardized mortality ratio (SMR) when evaluating the effect of a screening program. The package is based on methods described in Sasieni (2003) and Talbot et al. (2011).
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2023-06-16 |
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r-ihs
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Density, distribution function, quantile function and random generation for the inverse hyperbolic sine distribution. This package also provides a function that can fit data to the inverse hyperbolic sine distribution using maximum likelihood estimation.
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2023-06-16 |
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r-iciter
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A minimal wrapper around the NIH's 'iCite' API (<https://icite.od.nih.gov/api>). Given a vector of pubmed IDs, this package returns a dataframe of the information yielded by the 'iCite' API. The primary metric yielded by 'iCite' is the paper's relative citation ratio, but the API also returns other meta-data from the paper, including author names, publication journal, publication year, paper title, doi, and a number of other citation metrics.
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2023-06-16 |
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r-icesadvice
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A collection of functions that facilitate computational steps related to advice for fisheries management, according to ICES guidelines. These include methods for calculating reference points and model diagnostics.
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2023-06-16 |
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r-ica
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Independent Component Analysis (ICA) using various algorithms: FastICA, Information-Maximization (Infomax), and Joint Approximate Diagonalization of Eigenmatrices (JADE).
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2023-06-16 |
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r-hypergate
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Given a high-dimensional dataset that typically represents a cytometry dataset, and a subset of the datapoints, this algorithm outputs an hyperrectangle so that datapoints within the hyperrectangle best correspond to the specified subset. In essence, this allows the conversion of clustering algorithms' outputs to gating strategies outputs.
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2023-06-16 |
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r-hyperbolicdist
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This package provides functions for the hyperbolic and related distributions. Density, distribution and quantile functions and random number generation are provided for the hyperbolic distribution, the generalized hyperbolic distribution, the generalized inverse Gaussian distribution and the skew-Laplace distribution. Additional functionality is provided for the hyperbolic distribution, including fitting of the hyperbolic to data.
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2023-06-16 |
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r-hw.pval
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HW.pval calculates plain and fully conditional root-mean-square, chi-square, and log likelihood-ratio P-values for the user-provided genotypic counts to be consistent with the Hardy-Weinberg equilibrium model. For further information on the Hardy-Weinberg equilibrium model and the pseudocode, refer to the paper "Testing Hardy-Weinberg equilibrium with a simple root-mean-square statistic" by Rachel Ward.
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2023-06-16 |
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r-httpcache
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In order to improve performance for HTTP API clients, 'httpcache' provides simple tools for caching and invalidating cache. It includes the HTTP verb functions GET, PUT, PATCH, POST, and DELETE, which are drop-in replacements for those in the 'httr' package. These functions are cache-aware and provide default settings for cache invalidation suitable for RESTful APIs; the package also enables custom cache-management strategies. Finally, 'httpcache' includes a basic logging framework to facilitate the measurement of HTTP request time and cache performance.
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2023-06-16 |
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r-hsaur2
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Functions, data sets, analyses and examples from the second edition of the book ''A Handbook of Statistical Analyses Using R'' (Brian S. Everitt and Torsten Hothorn, Chapman & Hall/CRC, 2008). The first chapter of the book, which is entitled ''An Introduction to R'', is completely included in this package, for all other chapters, a vignette containing all data analyses is available. In addition, the package contains Sweave code for producing slides for selected chapters (see HSAUR2/inst/slides).
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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-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-gsubfn
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The gsubfn function is like gsub but can take a replacement function or certain other objects instead of the replacement string. Matches and back references are input to the replacement function and replaced by the function output. gsubfn can be used to split strings based on content rather than delimiters and for quasi-perl-style string interpolation. The package also has facilities for translating formulas to functions and allowing such formulas in function calls instead of functions. This can be used with R functions such as apply, sapply, lapply, optim, integrate, xyplot, Filter and any other function that expects another function as an input argument or functions like cat or sql calls that may involve strings where substitution is desirable. There is also a facility for returning multiple objects from functions and a version of transform that allows the RHS to refer to LHS used in the same transform.
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2023-06-16 |
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r-gsg
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gsg (gam selection gradients) provides a unified approach to the regression analysis of selection from longitudinal data collected from natural populations.
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2023-06-16 |
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r-grapfa
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gRapfa is for modelling discrete longitudinal data using acyclic probabilistic finite automata (APFA). The package contains functions for constructing APFA models from a given data using penalized likelihood methods. For graphical display of APFA models, gRapfa depends on 'igraph package'. gRapfa also contains an interface function to Beagle software that implements an efficient model selection algorithm.
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2023-06-16 |
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r-gpltr
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Combining a generalized linear model with an additional tree part on the same scale. A four-step procedure is proposed to fit the model and test the joint effect of the selected tree part while adjusting on confounding factors. We also proposed an ensemble procedure based on the bagging to improve prediction accuracy and computed several scores of importance for variable selection.
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2023-06-16 |
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r-gmodels
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Various R programming tools for model fitting.
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2023-06-16 |
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r-globals
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Identifies global ("unknown" or "free") objects in R expressions by code inspection using various strategies, e.g. conservative or liberal. The objective of this package is to make it as simple as possible to identify global objects for the purpose of exporting them in distributed compute environments.
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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-gets
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Automated General-to-Specific (GETS) modelling of the mean and variance of a regression, and indicator saturation methods for detecting and testing for structural breaks in the mean.
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2023-06-16 |
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r-geozoo
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Geometric objects defined in 'geozoo' can be simulated or displayed in the R package 'tourr'.
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2023-06-16 |
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r-gentag
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Implement a coherent and flexible protocol for animal color tagging. 'GenTag' provides a simple computational routine with low CPU usage to create color sequences for animal tag. First, a single-color tag sequence is created from an algorithm selected by the user, followed by verification of the combination uniqueness. Three methods to produce color tag sequences are provided. Users can modify the main function core to allow a wide range of applications.
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2023-06-16 |
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r-genesysr
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Access data on plant genetic resources from genebanks around the world published on Genesys (<https://www.genesys-pgr.org>). Your use of data is subject to terms and conditions available at <https://www.genesys-pgr.org/content/legal/terms>.
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2023-06-16 |
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r-gd
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Geographical detectors for measuring spatial stratified heterogeneity, as described in Jinfeng Wang (2010) <doi:10.1080/13658810802443457> and Jinfeng Wang (2016) <doi:10.1016/j.ecolind.2016.02.052>. Includes the optimal discretization of continuous data, four primary functions of geographical detectors, comparison of size effects of spatial unit and the visualizations of results. The descriptions of the package, methods and case datasets refer to the citation information below.
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2023-06-16 |
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r-lazysql
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Helper functions to build SQL statements for dbGetQuery or dbSendQuery under program control. They are intended to increase speed of coding and to reduce coding errors. Arguments are carefully checked, in particular SQL identifiers such as names of tables or columns. More patterns will be added as required.
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2023-06-16 |
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r-lagsequential
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Lag-sequential analysis is a method of assessing of patterns (what tends to follow what?) in sequences of codes. The codes are typically for discrete behaviors or states. The functions in this package read a stream of codes, or a frequency transition matrix, and produce a variety of lag sequential statistics, including transitional frequencies, expected transitional frequencies, transitional probabilities, z values, adjusted residuals, Yule's Q values, likelihood ratio tests of stationarity across time and homogeneity across groups or segments, transformed kappas for unidirectional dependence, bidirectional dependence, parallel and nonparallel dominance, and significance levels based on both parametric and randomization tests. The methods are described in Bakeman & Quera (2011) <doi:10.1017/CBO9781139017343>, O'Connor (1999) <doi:10.3758/BF03200753>, Wampold & Margolin (1982) <doi:10.1037/0033-2909.92.3.755>, and Wampold (1995, ISBN:0-89391-919-5).
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2023-06-16 |
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r-kmconfband
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Computes and plots an exact nonparametric band for any user-specified level of confidence from a single-sample survfit object
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2023-06-16 |
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r-kfda
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Kernel Fisher Discriminant Analysis (KFDA) is performed using Kernel Principal Component Analysis (KPCA) and Fisher Discriminant Analysis (FDA). There are some similar packages. First, 'lfda' is a package that performs Local Fisher Discriminant Analysis (LFDA) and performs other functions. In particular, 'lfda' seems to be impossible to test because it needs the label information of the data in the function argument. Also, the 'ks' package has a limited dimension, which makes it difficult to analyze properly. This package is a simple and practical package for KFDA based on the paper of Yang, J., Jin, Z., Yang, J. Y., Zhang, D., and Frangi, A. F. (2004) <DOI:10.1016/j.patcog.2003.10.015>.
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2023-06-16 |
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r-kdist
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Density, distribution function, quantile function and random generation for the K-distribution. A plotting function that plots data on Weibull paper and another function to draw additional lines. See results from package in T Lamont-Smith (2018), submitted J. R. Stat. Soc.
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2023-06-16 |
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r-jeek
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Provides a fast and scalable joint estimator for integrating additional knowledge in learning multiple related sparse Gaussian Graphical Models (JEEK). The JEEK algorithm can be used to fast estimate multiple related precision matrices in a large-scale. For instance, it can identify multiple gene networks from multi-context gene expression datasets. By performing data-driven network inference from high-dimensional and heterogeneous data sets, this tool can help users effectively translate aggregated data into knowledge that take the form of graphs among entities. Please run demo(jeek) to learn the basic functions provided by this package. For further details, please read the original paper: Beilun Wang, Arshdeep Sekhon, Yanjun Qi "A Fast and Scalable Joint Estimator for Integrating Additional Knowledge in Learning Multiple Related Sparse Gaussian Graphical Models" (ICML 2018) <arXiv:1806.00548>.
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2023-06-16 |
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r-jdx
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Simplifies and extends data exchange between 'R' and 'Java'.
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2023-06-16 |
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r-itertools2
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A port of Python's excellent itertools module to R for efficient looping.
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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-infodecompute
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The main purpose of this package is to generate the structure of the analysis of variance (ANOVA) table of the two-phase experiments. The user only need to input the design and the relationships of the random and fixed factors using the Wilkinson-Rogers' syntax, this package can then quickly generate the structure of the ANOVA table with the coefficients of the variance components for the expected mean squares. Thus, the balanced incomplete block design and provides the efficiency factors of the fixed effects can also be studied and compared much easily.
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2023-06-16 |
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r-inbreedr
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A framework for analysing inbreeding and heterozygosity-fitness correlations (HFCs) based on microsatellite and SNP markers.
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2023-06-16 |
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r-imrmc
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Do Multi-Reader, Multi-Case (MRMC) analyses of data from imaging studies where clinicians (readers) evaluate patient images (cases). What does this mean? ... Many imaging studies are designed so that every reader reads every case in all modalities, a fully-crossed study. In this case, the data is cross-correlated, and we consider the readers and cases to be cross-correlated random effects. An MRMC analysis accounts for the variability and correlations from the readers and cases when estimating variances, confidence intervals, and p-values. The functions in this package can treat arbitrary study designs and studies with missing data, not just fully-crossed study designs. The initial package analyzes the reader-average area under the receiver operating characteristic (ROC) curve with U-statistics according to Gallas, Bandos, Samuelson, and Wagner 2009 <doi:10.1080/03610920802610084>. Additional functions analyze other endpoints with U-statistics (binary performance and score differences) following the work by Gallas, Pennello, and Myers 2007 <doi:10.1364/JOSAA.24.000B70>. Package development and documentation is at <https://github.com/DIDSR/iMRMC/tree/master>.
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2023-06-16 |
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r-immailgun
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Send emails using the 'mailgun' api. To use this package you will need an account from <https://www.mailgun.com> .
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2023-06-16 |
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r-imak
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This is an Automatic Item Generator for Psychological Assessment. Items created with the 'IMak' package should not be used in applied settings as part of the working protocol without ensuring first that the items meet the required psychometric quality standards (see Blum & Holling, 2018) <DOI:10.3389/fpsyg.2018.01286>.
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2023-06-16 |
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r-imageviewer
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Display a 2D-matrix data as a interactive zoomable gray-scale image viewer, providing tools for manual data inspection. The viewer window shows cursor guiding lines and a corresponding data slices for both axes at the current cursor position. A tool-bar allows adjusting image display brightness/contrast through WebGL filters and performing basic high-pass/low-pass filtering.
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2023-06-16 |
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r-igraphtosonia
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This program facilitates exporting igraph graphs to the SoNIA file format
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2023-06-16 |
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r-igasso
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A collection of statistical tests for genetic association studies.
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2023-06-16 |
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r-idx2r
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Convert files to and from IDX format to vectors, matrices and arrays. IDX is a very simple file format designed for storing vectors and multidimensional matrices in binary format. The format is described on the website from Yann LeCun <http://yann.lecun.com/exdb/mnist/>.
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2023-06-16 |
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r-icpsrdata
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Reproducible, programmatic retrieval of datasets from the Inter-university Consortium for Political and Social Research archive.
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2023-06-16 |
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r-ic10trainingdata
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Training datasets for iC10; which implements the classifier described in the paper 'Genome-driven integrated classification of breast cancer validated in over 7,500 samples' (Ali HR et al., Genome Biology 2014). It uses copy number and/or expression form breast cancer data, trains a pamr classifier (Tibshirani et al.) with the features available and predicts the iC10 group. Genomic annotation for the training dataset has been obtained from Mark Dunning's lluminaHumanv3.db package.
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2023-06-16 |
