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r-rspde
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Functions that compute rational approximations of fractional elliptic stochastic partial differential equations. The package also contains functions for common statistical usage of these approximations. The main reference for the methods is Bolin and Kirchner (2019) <arXiv:1711.04333>, which can be generated by the citation function in R.
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2025-03-25 |
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r-rspc
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Implementation of Nelson rules for control charts in 'R'. The 'Rspc' implements some Statistical Process Control methods, namely Levey-Jennings type of I (individuals) chart, Shewhart C (count) chart and Nelson rules (as described in Montgomery, D. C. (2013) Introduction to statistical quality control. Hoboken, NJ: Wiley.). Typical workflow is taking the time series, specify the control limits, and list of Nelson rules you want to evaluate. There are several options how to modify the rules (one sided limits, numerical parameters of rules, etc.). Package is also capable of calculating the control limits from the data (so far only for i-chart and c-chart are implemented).
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2025-03-25 |
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r-rsoi
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Downloads Southern Oscillation Index, Oceanic Nino Index, North Pacific Gyre Oscillation data, North Atlantic Oscillation and Arctic Oscillation. Data sources are described in the README file.
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2025-03-25 |
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r-rsocrata
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Provides easier interaction with 'Socrata' open data portals <http://dev.socrata.com>. Users can provide a 'Socrata' data set resource URL, or a 'Socrata' Open Data API (SoDA) web query, or a 'Socrata' "human-friendly" URL, returns an R data frame. Converts dates to 'POSIX' format and manages throttling by 'Socrata'. Users can upload data to 'Socrata' portals directly from R.
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2025-03-25 |
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r-rsmartlyio
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Aims at loading Facebook and Instagram advertising data from 'Smartly.io' into R. 'Smartly.io' is an online advertising service that enables advertisers to display commercial ads on social media networks (see <http://www.smartly.io/> for more information). The package offers an interface to query the 'Smartly.io' API and loads data directly into R for further data processing and data analysis.
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2025-03-25 |
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r-rsm
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Provides functions to generate response-surface designs, fit first- and second-order response-surface models, make surface plots, obtain the path of steepest ascent, and do canonical analysis. A good reference on these methods is Chapter 10 of Wu, C-F J and Hamada, M (2009) "Experiments: Planning, Analysis, and Parameter Design Optimization" ISBN 978-0-471-69946-0.
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2025-03-25 |
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r-rslurm
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Functions that simplify submitting R scripts to a Slurm workload manager, in part by automating the division of embarrassingly parallel calculations across cluster nodes.
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2025-03-25 |
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r-rslp
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Implements the "Stemming Algorithm for the Portuguese Language" <DOI:10.1109/SPIRE.2001.10024>.
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2025-03-25 |
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r-rskey
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Create custom keyboard shortcuts to examine code selected in the 'Rstudio' editor. F3 can for example yield 'str(selection)' and F7 open the source code of CRAN and base package functions on 'github'.
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2025-03-25 |
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r-rsitecatalyst
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Functions for interacting with the Adobe Analytics API V1.4 (<https://api.omniture.com/admin/1.4/rest/>).
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2025-03-25 |
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r-rsfa
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Slow Feature Analysis in R, ported to R based on the matlab versions SFA toolkit 1.0 by Pietro Berkes and SFA toolkit 2.8 by Wolfgang Konen for matlab.
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2025-03-25 |
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r-rsem
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A robust procedure is implemented to estimate means and covariance matrix of multiple variables with missing data using Huber weight and then to estimate a structural equation model.
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2025-03-25 |
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r-rseedcalc
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Estimate the percentage of seeds in a seedlot that contain stacks of genetically modified traits. Estimates are calculated using a multinomial group testing model with maximum likelihood estimation of the parameters.
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2025-03-25 |
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r-rse
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A Bayesian-weighted estimator and two unweighted estimators are developed to estimate the number of newly found rare species in additional ecological samples. Among these methods, the Bayesian-weighted estimator and an unweighted (Chao-derived) estimator are of high accuracy and recommended for practical applications. Technical details of the proposed estimators have been well described in the following paper: Shen TJ, Chen YH (2018) A Bayesian weighted approach to predicting the number of newly discovered rare species. Conservation Biology, In press.
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2025-03-25 |
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r-rsdmx
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Set of classes and methods to read data and metadata documents exchanged through the Statistical Data and Metadata Exchange (SDMX) framework, currently focusing on the SDMX XML standard format (SDMX-ML).
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2025-03-25 |
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r-rscala
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'Scala' <http://www.scala-lang.org/> is embedded in 'R' and callbacks from 'Scala' to 'R' are available. Support is provided to write 'R' packages that access 'Scala'. After installation, please run 'rscala::scalaConfig()'.
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2025-03-25 |
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r-rsca
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A statistical tool for multivariate modeling and clustering using stepwise cluster analysis. The modeling output of rSCA is constructed as a cluster tree to represent the complicated relationships between multiple dependent and independent variables. A free tool (named rSCA Tree Generator) for visualizing the cluster tree from rSCA is also released and it can be downloaded at <https://rscatree.weebly.com/>.
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2025-03-25 |
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r-rsaucelabs
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Retrieve, update, delete job information from <https://saucelabs.com/>. Poll the 'SauceLabs' services current status and access supported platforms. Send and retrieve files from 'SauceLabs' and manage tunnels associated with 'SauceConnect'.
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2025-03-25 |
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r-rsatscan
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SaTScan(TM) (http://www.satscan.org) is software for finding regions in Time, Space, or Time-Space that have excess risk, based on scan statistics, and uses Monte Carlo hypothesis testing to generate P-values for these regions. The rsatscan package provides functions for writing R data frames in SaTScan-readable formats, for setting SaTScan parameters, for running SaTScan in the OS, and for reading the files that SaTScan creates.
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2025-03-25 |
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r-rsarules
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Implements the Gibbs sampling algorithm to randomly sample association rules with one pre-chosen item as the consequent from a transaction dataset. The Gibbs sampling algorithm was proposed in G. Qian, C.R. Rao, X. Sun and Y. Wu (2016) <DOI:10.1073/pnas.1604553113>.
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2025-03-25 |
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r-rsampling
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Resampling Stats (http://www.resample.com) is an add-in for running randomization tests in Excel worksheets. The workflow is (1) to define a statistic of interest that can be calculated from a data table, (2) to randomize rows ad/or columns of a data table to simulate a null hypothesis and (3) and to score the value of the statistic from many randomizations. The relative frequency distribution of the statistic in the simulations is then used to infer the probability of the observed value be generated by the null process (probability of Type I error). This package intends to translate this logic for R for teaching purposes. Keeping the original workflow is favored over performance.
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2025-03-25 |
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r-rsadbe
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The package contains all the data sets related to the book written by the maintainer of the package.
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2025-03-25 |
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r-rrscale
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Non-linear transformations of data to better discover latent effects. Applies a sequence of three transformations (1) a Gaussianizing transformation, (2) a Z-score transformation, and (3) an outlier removal transformation.
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2025-03-25 |
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r-rrreg
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Univariate and multivariate methods to analyze randomized response (RR) survey designs (e.g., Warner, S. L. (1965). Randomized response: A survey technique for eliminating evasive answer bias. Journal of the American Statistical Association, 60, 63–69, <doi:10.2307/2283137>). Besides univariate estimates of true proportions, RR variables can be used for correlations, as dependent variable in a logistic regression (with or without random effects), or as predictors in a linear regression (Heck, D. W., & Moshagen, M. (2018). RRreg: An R package for correlation and regression analyses of randomized response data. Journal of Statistical Software, 85(2), 1–29, <doi:10.18637/jss.v085.i02>). For simulations and the estimation of statistical power, RR data can be generated according to several models. The implemented methods also allow to test the link between continuous covariates and dishonesty in cheating paradigms such as the coin-toss or dice-roll task (Moshagen, M., & Hilbig, B. E. (2017). The statistical analysis of cheating paradigms. Behavior Research Methods, 49, 724–732, <doi:10.3758/s13428-016-0729-x>).
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2025-03-25 |
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r-rrpp
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Linear model calculations are made for many random versions of data. Using residual randomization in a permutation procedure, sums of squares are calculated over many permutations to generate empirical probability distributions for evaluating model effects. This packaged is described by Collyer & Adams (2018) <doi:10.1111/2041-210X.13029>. Additionally, coefficients, statistics, fitted values, and residuals generated over many permutations can be used for various procedures including pairwise tests, prediction, classification, and model comparison. This package should provide most tools one could need for the analysis of high-dimensional data, especially in ecology and evolutionary biology, but certainly other fields, as well.
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2025-03-25 |
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r-rromeo
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Fetches information from the 'SHERPA/RoMEO' API <http://www.sherpa.ac.uk/romeo/apimanual.php> which indexes policies of journal regarding the archival of scientific manuscripts before and/or after peer-review as well as formatted manuscripts.
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2025-03-25 |
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r-rroad
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Computation of the International Roughness Index (IRI) given a longitudinal road profile. The IRI can be calculated for a single road segment or for a sequence of segments with a fixed length (e. g. 100m). For the latter, an overlap of the segments can be selected. The IRI and likewise the algorithms for its determination are defined in Sayers, Michael W; Gillespie, Thomas D; Queiroz, Cesar A.V. 1986. The International Road Roughness Experiment (IRRE) : establishing correlation and a calibration standard for measurements. World Bank technical paper; no. WTP 45. Washington, DC : The World Bank. (ISBN 0-8213-0589-1) available from <http://documents.worldbank.org/curated/en/326081468740204115>.
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2025-03-25 |
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r-rrna
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Functions for creating and manipulating RNA secondary structure plots.
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2025-03-25 |
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r-rrblup
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Software for genomic prediction with the RR-BLUP mixed model (Endelman 2011, <doi:10.3835/plantgenome2011.08.0024>). One application is to estimate marker effects by ridge regression; alternatively, BLUPs can be calculated based on an additive relationship matrix or a Gaussian kernel.
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2025-03-25 |
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r-rrate
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Replication Rate (RR) is the probability of replicating a statistically significant association in genome-wide association studies. This R-package provide the estimation method for replication rate which makes use of the summary statistics from the primary study. We can use the estimated RR to determine the sample size of the replication study, and to check the consistency between the results of the primary study and those of the replication study.
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2025-03-25 |
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r-rqcc
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Constructs robust quality control chart based on the median and Hodges-Lehmann estimators (location) and the median absolute deviation (MAD) and Shamos estimators (scale) which are unbiased with a sample of finite size. For more details, see Park, Kim and Wang (2019)<arXiv:1908.00462>. This work was partially supported by the National Research Foundation of Korea (NRF) grant funded by the Korea government (No. NRF-2017R1A2B4004169).
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2025-03-25 |
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r-rpushbullet
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An R interface to the Pushbullet messaging service which provides fast and efficient notifications (and file transfer) between computers, phones and tablets. An account has to be registered at the site <http://www.pushbullet.com> site to obtain a (free) API key.
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2025-03-25 |
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r-rpublica
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Client for accessing data journalism APIs from ProPublica <http://www.propublica.org/>.
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2025-03-25 |
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r-rpsychi
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The rpsychi offers a number of functions for psychiatry, psychiatric nursing, clinical psychology. Functions are primarily for statistical significance testing using published work. For example, you can conduct a factorial analysis of variance (ANOVA), which requires only the mean, standard deviation, and sample size for each cell, rather than the individual data. This package covers fundamental statistical tests such as t-test, chi-square test, analysis of variance, and multiple regression analysis. With some exceptions, you can obtain effect size and its confidence interval. These functions help you to obtain effect size from published work, and then to conduct a priori power analysis or meta-analysis, even if a researcher do not report effect size in a published work.
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2025-03-25 |
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r-rprobsup
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The A() function calculates the A statistic, a nonparametric measure of effect size for two independent groups that’s also known as the probability of superiority (Ruscio, 2008), along with its standard error and a confidence interval constructed using bootstrap methods (Ruscio & Mullen, 2012). Optional arguments can be specified to calculate variants of the A statistic developed for other research designs (e.g., related samples, more than two independent groups or related samples; Ruscio & Gera, 2013). <DOI: 10.1037/1082-989X.13.1.19>. <DOI: 10.1080/00273171.2012.658329>. <DOI: 10.1080/00273171.2012.738184>.
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2025-03-25 |
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r-rprintf
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Provides a set of functions to facilitate building formatted strings under various replacement rules: C-style formatting, variable-based formatting, and number-based formatting. C-style formatting is basically identical to built-in function 'sprintf'. Variable-based formatting allows users to put variable names in a formatted string which will be replaced by variable values. Number-based formatting allows users to use index numbers to represent the corresponding argument value to appear in the string.
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2025-03-25 |
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r-rprime
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'Eprime' is a set of programs for administering psychological experiments by computer. This package provides functions for loading, parsing, filtering and exporting data in the text files produced by 'Eprime' experiments.
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2025-03-25 |
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r-rppairwisedesign
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Using some association schemes to obtain a new series of resolvable partially pairwise balanced designs (RPPBD) and space-filling designs.
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2025-03-25 |
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r-rpoet
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Wrapper for the 'PoetryDB' API <http://poetrydb.org> that allows for interaction and data extraction from the database in an R interface. The 'PoetryDB' API is a database of poetry and poets implemented with 'MongoDB' to enable developers and poets to easily access one of the most comprehensive poetry databases currently available.
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2025-03-25 |
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r-rpnf
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A set of functions to analyze and print the development of a commodity using the Point and Figure (P&F) approach. A P&F processor can be used to calculate daily statistics for the time series. These statistics can be used for deeper investigations as well as to create plots. Plots can be generated as well known X/O Plots in plain text format, and additionally in a more graphical format.
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2025-03-25 |
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r-rpmm
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Recursively Partitioned Mixture Model for Beta and Gaussian Mixtures. This is a model-based clustering algorithm that returns a hierarchy of classes, similar to hierarchical clustering, but also similar to finite mixture models.
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2025-03-25 |
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r-rpmg
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Really Poor Man's Graphical User Interface, used to create interactive R analysis sessions with simple R commands.
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2025-03-25 |
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r-rplotengine
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Generate basic charts either by custom applications, or from a small script launched from the system console, or within the R console. Two ASCII text files are necessary: (1) The graph parameters file, which name is passed to the function 'rplotengine()'. The user can specify the titles, choose the type of the graph, graph output formats (e.g. png, eps), proportion of the X-axis and Y-axis, position of the legend, whether to show or not a grid at the background, etc. (2) The data to be plotted, which name is specified as a parameter ('data_filename') in the previous file. This data file has a tabulated format, with a single character (e.g. tab) between each column, and a headers line located in the first row. Optionally, the file could include data columns for showing confidence intervals.
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2025-03-25 |
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r-rpivottable
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Build powerful pivot tables (aka Pivot Grid, Pivot Chart, Cross-Tab) and dynamically slice & dice / drag 'n' drop your data. 'rpivotTable' is a wrapper of 'pivottable', a powerful open-source Pivot Table library implemented in 'JavaScript' by Nicolas Kruchten. Aligned to 'pivottable' v2.19.0.
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2025-03-25 |
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r-rpipedrive
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R interaction with 'pipedrive.com API'. All functions were created and documented according to <https://developers.pipedrive.com/docs/api/v1/>. Created with the objective of offering integration and even the development of 'APIs'. Making possible to create workflows and easily downloading databases for analysis.
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2025-03-25 |
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r-rpinterest
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Get information (boards, pins and users) from the Pinterest <http://www.pinterest.com> API.
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2025-03-25 |
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r-rphylip
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Rphylip provides an R interface for the PHYLIP package. All users of Rphylip will thus first have to install the PHYLIP phylogeny methods program package (Felsenstein 2013). See http://www.phylip.com for more information about installing PHYLIP.
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2025-03-25 |
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r-rpexe.rpext
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This reduced piecewise exponential survival software implements the likelihood ratio test and backward elimination procedure in Han, Schell, and Kim (2012 <doi:10.1080/19466315.2012.698945>, 2014 <doi:10.1002/sim.5915>), and Han et al. (2016 <doi:10.1111/biom.12590>). Inputs to the program can be either times when events/censoring occur or the vectors of total time on test and the number of events. Outputs of the programs are times and the corresponding p-values in the backward elimination. Details about the model and implementation are given in Han et al. 2014. This program can run in R version 3.2.2 and above.
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2025-03-25 |
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r-rpensemble
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Implements the methodology of "Cannings, T. I. and Samworth, R. J. (2017) Random-projection ensemble classification, J. Roy. Stat. Soc., Ser. B. (with discussion), 79, 959--1035". The random projection ensemble classifier is a general method for classification of high-dimensional data, based on careful combination of the results of applying an arbitrary base classifier to random projections of the feature vectors into a lower-dimensional space. The random projections are divided into non-overlapping blocks, and within each block the projection yielding the smallest estimate of the test error is selected. The random projection ensemble classifier then aggregates the results of applying the base classifier on the selected projections, with a data-driven voting threshold to determine the final assignment.
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2025-03-25 |
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r-rpclr
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This package implements the R-PCLR (Random-Penalized Conditional Logistic Regression) algorithm for obtaining variable importance. The algorithm is applicable for the analysis of high dimensional data from matched case-control studies.
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2025-03-25 |
