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r-venn
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Draws and displays Venn diagrams up to 7 sets, and any Boolean union of set intersections.
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2024-01-16 |
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r-vegperiod
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Collection of common methods to determine growing season length in a simple manner. Start and end dates of the vegetation periods are calculated solely based on daily mean temperatures and the day of the year.
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2024-01-16 |
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r-vegawidget
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'Vega' and 'Vega-Lite' parse text in 'JSON' notation to render chart-specifications into 'HTML'. This package is used to facilitate the rendering. It also provides a means to interact with signals, events, and datasets in a 'Vega' chart using 'JavaScript' or 'Shiny'.
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2024-01-16 |
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r-vegdata
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Handling of vegetation data from different sources ( Turboveg 2.0 <https://www.synbiosys.alterra.nl/turboveg/>; the German national repository <https://www.vegetweb.de> and others. Taxonomic harmonization (given appropriate taxonomic lists, e.g. the German taxonomic standard list "GermanSL", <https://germansl.infinitenature.org>).
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2024-01-16 |
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r-vegalite
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The 'Vega-Lite' 'JavaScript' framework provides a higher-level grammar for visual analysis, akin to 'ggplot' or 'Tableau', that generates complete 'Vega' specifications. Functions exist which enable building a valid 'spec' from scratch or importing a previously created 'spec' file. Functions also exist to export 'spec' files and to generate code which will enable plots to be embedded in properly configured web pages. The default behavior is to generate an 'htmlwidget'.
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2024-01-16 |
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r-vcdextra
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Provides additional data sets, methods and documentation to complement the 'vcd' package for Visualizing Categorical Data and the 'gnm' package for Generalized Nonlinear Models. In particular, 'vcdExtra' extends mosaic, assoc and sieve plots from 'vcd' to handle 'glm()' and 'gnm()' models and adds a 3D version in 'mosaic3d'. Additionally, methods are provided for comparing and visualizing lists of 'glm' and 'loglm' objects. This package is now a support package for the book, "Discrete Data Analysis with R" by Michael Friendly and David Meyer.
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2024-01-16 |
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r-vecsets
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The 'base' tools union() intersect(), etc., follow the algebraic definition that each element of a set must be unique. Since it's often helpful to compare all elements of two vectors, this toolset treats every element as unique for counting purposes. For ease of use, all functions in vecsets have an argument 'multiple' which, when set to FALSE, reverts them to the base::sets (alias for all the items) tools functionality.
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2024-01-16 |
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r-vec2dtransf
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Applies affine and similarity transformations on vector spatial data (sp objects). Transformations can be defined from control points or directly from parameters. If redundant control points are provided Least Squares is applied allowing to obtain residuals and RMSE.
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2024-01-16 |
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r-vdspcalibration
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Provides statistical methods for the design and analysis of a calibration study, which aims for calibrating measurements using two different methods. The package includes sample size calculation, sample selection, regression analysis with error-in measurements and change-point regression. The method is described in Tian, Durazo-Arvizu, Myers, et al. (2014) <DOI:10.1002/sim.6235>.
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2024-01-16 |
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r-vdjgermlines
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Contains variable, diversity, and joining sequences and accompanying functions that enable both the extraction of and comparison between immune V-D-J genomic segments from a variety of species. Sources include IMGT from MP Lefranc (2009) <doi:10.1093/nar/gkn838> and Vgenerepertoire from publication DN Olivieri (2014) <doi:10.1007/s00251-014-0784-3>.
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2024-01-16 |
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r-vcvcomp
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Comparison of variance - covariance patterns using relative principal component analysis (relative eigenanalysis), as described in Le Maitre and Mitteroecker (2019) <doi:10.1111/2041-210X.13253>. Also provides functions to compute group covariance matrices, distance matrices, and perform proportionality tests. A worked sample on the body shape of cichlid fishes is included, based on the dataset from Kerschbaumer et al. (2013) <doi:10.5061/dryad.fc02f>.
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2024-01-16 |
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r-vaultr
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Provides an interface to a 'HashiCorp' vault server over its http API (typically these are self-hosted; see <https://www.vaultproject.io>). This allows for secure storage and retrieval of secrets over a network, such as tokens, passwords and certificates. Authentication with vault is supported through several backends including user name/password and authentication via 'GitHub'.
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2024-01-16 |
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r-varimp
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Computes the random forest variable importance (VIMP) for the conditional inference random forest (cforest) of the 'party' package. Includes a function (varImp) that computes the VIMP for arbitrary measures from the 'measures' package. For calculating the VIMP regarding the measures accuracy and AUC two extra functions exist (varImpACC and varImpAUC).
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2024-01-16 |
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r-vcov
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Methods for faster extraction (about 5x faster in a few test cases) of variance-covariance matrices and standard errors from models. Methods in the 'stats' package tend to rely on the summary method, which may waste time computing other summary statistics which are summarily ignored.
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2024-01-16 |
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r-variancegamma
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Provides functions for the variance gamma distribution. Density, distribution and quantile functions. Functions for random number generation and fitting of the variance gamma to data. Also, functions for computing moments of the variance gamma distribution of any order about any location. In addition, there are functions for checking the validity of parameters and to interchange different sets of parameterizations for the variance gamma distribution.
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2024-01-16 |
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r-vcd
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Visualization techniques, data sets, summary and inference procedures aimed particularly at categorical data. Special emphasis is given to highly extensible grid graphics. The package was package was originally inspired by the book "Visualizing Categorical Data" by Michael Friendly and is now the main support package for a new book, "Discrete Data Analysis with R" by Michael Friendly and David Meyer (2015).
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2024-01-16 |
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r-varselrf
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Variable selection from random forests using both backwards variable elimination (for the selection of small sets of non-redundant variables) and selection based on the importance spectrum (somewhat similar to scree plots; for the selection of large, potentially highly-correlated variables). Main applications in high-dimensional data (e.g., microarray data, and other genomics and proteomics applications).
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2024-01-16 |
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r-varsel
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Feature selection using Sequential Forward Floating feature Selection and Jeffries-Matusita distance. It returns a suboptimal set of features to use for image classification. Reference: Dalponte, M., Oerka, H.O., Gobakken, T., Gianelle, D. & Naesset, E. (2013). Tree Species Classification in Boreal Forests With Hyperspectral Data. IEEE Transactions on Geoscience and Remote Sensing, 51, 2632-2645, <DOI:10.1109/TGRS.2012.2216272>.
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2024-01-16 |
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r-vars
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Estimation, lag selection, diagnostic testing, forecasting, causality analysis, forecast error variance decomposition and impulse response functions of VAR models and estimation of SVAR and SVEC models.
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2024-01-16 |
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r-variables
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Abstract descriptions of (yet) unobserved variables.
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2024-01-16 |
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r-vares
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Computes Value at risk and expected shortfall, two most popular measures of financial risk, for over one hundred parametric distributions, including all commonly known distributions. Also computed are the corresponding probability density function and cumulative distribution function. See Chan, Nadarajah and Afuecheta (2015) <doi:10.1080/03610918.2014.944658> for more details.
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2024-01-16 |
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r-varhandle
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Variables are the fundamental parts of each programming language but handling them efficiently might be frustrating for programmers. This package contains some functions to help user (especially data explorers) to make more sense of their variables and take the most out of variables and hardware resources. These functions are written and crafted since 2014 with years of experience in statistical data analysis on high-dimensional data, and for each of them there was a need. Functions in this package are supposed to be efficient and easy to use, hence they will be frequently updated to make them more convenient.
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2024-01-16 |
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r-vared
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Generating functions for both optimal and ordinary difference sequences, and the difference-based estimation functions.
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2024-01-16 |
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r-vardiag
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Interactive variogram diagnostics.
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2024-01-16 |
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r-var.etp
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A collection of the functions for estimation, hypothesis testing, prediction for stationary vector autoregressive models.
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2024-01-16 |
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r-valottery
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Historical results for the state of Virginia lottery draw games. Data were downloaded from https://www.valottery.com/.
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2024-01-16 |
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r-varbin
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Tool for easy and efficient discretization of continuous and categorical data. The package calculates the most optimal binning of a given explanatory variable with respect to a user-specified target variable. The purpose is to assign a unique Weight-of-Evidence value to each of the calculated binpoints in order to recode the original variable. The package allows users to impose certain restrictions on the functional form on the resulting binning while maximizing the overall information value in the original data. The package is well suited for logistic scoring models where input variables may be subject to restrictions such as linearity by e.g. regulatory authorities. An excellent source describing in detail the development of scorecards, and the role of Weight-of-Evidence coding in credit scoring is (Siddiqi 2006, ISBN: 978–0-471–75451–0). The package utilizes the discrete nature of decision trees and Isotonic Regression to accommodate the trade-off between flexible functional forms and maximum information value.
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2024-01-16 |
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r-valection
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A binding for the 'valection' program which offers various ways to sample the outputs of competing algorithms or parameterizations, and fairly assess their performance against each other. The 'valection' C library is required to use this package and can be downloaded from: <http://labs.oicr.on.ca/boutros-lab/software/valection>. Cooper CI, et al; Valection: Design Optimization for Validation and Verification Studies; Biorxiv 2018; <doi:10.1101/254839>.
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2024-01-16 |
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r-utility
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Construct and plot objective hierarchies and associated value and utility functions. Evaluate the values and utilities and visualize the results as colored objective hierarchies or tables. Visualize uncertainty by plotting median and quantile intervals within the nodes of objective hierarchies. Get numerical results of the evaluations in standard R data types for further processing.
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2024-01-16 |
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r-valaddin
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A set of basic tools to transform functions into functions with input validation checks, in a manner suitable for both programmatic and interactive use.
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2024-01-16 |
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r-vaersvax
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US VAERS vaccine data for 01/01/2018 - 06/14/2018. If you want to explore the full VAERS data for 1990 - Present (data, symptoms, and vaccines), then check out the 'vaers' package from the URL below. The URL and BugReports below correspond to the 'vaers' package, of which 'vaersvax' is a small subset (2018 only). 'vaers' is not hosted on CRAN due to the large size of the data set. To install the Suggested 'vaers' and 'vaersND' packages, use the following R code: 'devtools::install_git("<https://gitlab.com/iembry/vaers.git>", build_vignettes = TRUE)' and 'devtools::install_git("<https://gitlab.com/iembry/vaersND.git>", build_vignettes = TRUE)'. "The Vaccine Adverse Event Reporting System (VAERS) is a national early warning system to detect possible safety problems in U.S.-licensed vaccines. VAERS is co-managed by the Centers for Disease Control and Prevention (CDC) and the U.S. Food and Drug Administration (FDA)." For more information about the data, visit <https://vaers.hhs.gov/>. For information about vaccination/immunization hazards, visit <http://www.questionuniverse.com/rethink.html#vaccine>.
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2024-01-16 |
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r-vaersndvax
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Non-Domestic VAERS vaccine data for 01/01/2016 - 06/14/2016. If you want to explore the full VAERS data for 1990 - Present (data, symptoms, and vaccines), then check out the 'vaersND' package from the URL below. The URL and BugReports below correspond to the 'vaersND' package, of which 'vaersNDvax' is a small subset (2016 only). 'vaersND' is not hosted on CRAN due to the large size of the data set. To install the Suggested 'vaers' and 'vaersND' packages, use the following R code: 'devtools::install_git("https://gitlab.com/iembry/vaers.git", build_vignettes = TRUE)' and 'devtools::install_git("https://gitlab.com/iembry/vaersND.git", build_vignettes = TRUE)'. "VAERS is a national vaccine safety surveillance program co-sponsored by the US Centers for Disease Control and Prevention (CDC) and the US Food and Drug Administration (FDA). VAERS is a post-marketing safety surveillance program, collecting information about adverse events (possible side effects) that occur after the administration of vaccines licensed for use in the United States." For more information about the data, visit <https://vaers.hhs.gov/index>. For information about vaccination/immunization hazards, visit <http://www.questionuniverse.com/rethink.html/#vaccine>.
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2024-01-16 |
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r-usingr
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A collection of data sets to accompany the textbook "Using R for Introductory Statistics," second edition.
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2024-01-16 |
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r-usgas
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Provides an overview of the demand for natural gas in the US by state and country level. Data source: US Energy Information Administration <https://www.eia.gov/>.
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2024-01-16 |
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r-utc
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Three functions are provided: first function changes time from local to UTC, other changes from UTC to local and third returns difference between local and UTC. %h+% operator is also provided it adds hours to a time.
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2024-01-16 |
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r-ustatbookabsc
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A set of functions leading to multivariate response L1 regression. This includes functions on computing Euclidean inner products and norms, weighted least squares estimates on multivariate responses, function to compute fitted values and residuals. This package is a companion to the book "U-Statistics, M-estimation and Resampling", by Arup Bose and Snigdhansu Chatterjee, to appear in 2017 as part of the "Texts and Readings in Mathematics" (TRIM) series of Hindustan Book Agency and Springer-Verlag.
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2024-01-16 |
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r-ustyc
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Forms a query to submit for US Treasury yield curve data, posting this query to the US Treasury web site's data feed service. By default the download includes data yield data for 12 products from January 1, 1990, some of which are NA during this span. The caller can pass parameters to limit the query to a certain year or year and month, but the full download is not especially large. The download data from the service is in XML format. The package's main function transforms that XML data into a numeric data frame with treasury product items (constant maturity yields for 12 kinds of bills, notes, and bonds) as columns and dates as row names. The function returns a list which includes an item for this data frame as well as query-related values for reference and the update date from the service.
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2024-01-16 |
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r-usmapdata
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Provides a container for data used by the 'usmap' package. The data used by 'usmap' has been extracted into this package so that the file size of the 'usmap' package can be reduced greatly. The data in this package will be updated roughly once per year (plus bug fixes) as new shape files are provided by the US Census bureau.
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2024-01-16 |
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r-useful
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A set of little functions that have been found useful to do little odds and ends such as plotting the results of K-means clustering, substituting special text characters, viewing parts of a data.frame, constructing formulas from text and building design and response matrices.
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2024-01-16 |
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r-usmap
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Obtain United States map data frames of varying region types (e.g. county, state). The map data frames include Alaska and Hawaii conveniently placed to the bottom left, as they appear in most maps of the US. Convenience functions for plotting choropleths and working with FIPS codes are also provided.
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2024-01-16 |
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r-usa.state.boundaries
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Contains a WGS84 datum map of the USA, which includes all Commonwealth and State boundaries & also includes Puerto Rico and the U.S. Virgin Islands. This map is a reprojection of the NAD83 datum map from the USGS National Map. This package contains a subset of the data included in the 'USA.state.boundaries.data' package, which is available in a 'drat' repository. To install that data package, please follow the instructions at <https://gitlab.com/iembry/usa.state.boundaries.data>.
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2024-01-16 |
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r-urlchecker
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Provide the URL checking tools available in R 4.1+ as a package for earlier versions of R. Also uses concurrent requests so can be much faster than the serial versions.
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2024-01-16 |
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r-usethis
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Automate package and project setup tasks that are otherwise performed manually. This includes setting up unit testing, test coverage, continuous integration, Git, 'GitHub', licenses, 'Rcpp', 'RStudio' projects, and more.
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2024-01-16 |
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r-upsetr
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Creates visualizations of intersecting sets using a novel matrix design, along with visualizations of several common set, element and attribute related tasks (Conway 2017) <doi:10.1093/bioinformatics/btx364>.
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2024-01-16 |
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r-usedist
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Functions to re-arrange, extract, and work with distances.
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2024-01-16 |
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r-usdm
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This is a framework that aims to provide methods and tools for assessing the impact of different sources of uncertainties (e.g.positional uncertainty) on performance of species distribution models (SDMs).)
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2024-01-16 |
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r-usdata
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Demographic data on the United States at the county and state levels spanning multiple years.
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2024-01-16 |
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r-uroot
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Seasonal unit roots and seasonal stability tests. P-values based on response surface regressions are available for both tests. P-values based on bootstrap are available for seasonal unit root tests.
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2024-01-16 |
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r-universals
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Provides S3 generic methods and some default implementations for Bayesian analyses that generate Markov Chain Monte Carlo (MCMC) samples. The purpose of 'universals' is to reduce package dependencies and conflicts. The 'nlist' package implements many of the methods for its 'nlist' class.
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2024-01-16 |
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r-urlshortener
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Allows using two URL shortening services, which also provide expanding and analytic functions. Specifically developed for 'Bit.ly' (which requires OAuth 2.0) and 'is.gd' (no API key).
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2024-01-16 |
