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r-jsonarr
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public |
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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2025-04-22 |
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r-json64
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public |
Encode/Decode 'base64', with support for JSON format, using two functions: j_encode() and j_decode(). 'Base64' is a group of similar binary-to-text encoding schemes that represent binary data in an ASCII string format by translating it into a radix-64 representation, used when there is a need to encode binary data that needs to be stored and transferred over media that are designed to deal with textual data, ensuring that the data will remain intact and without modification during transport. <https://developer.mozilla.org/en-US/docs/Web/API/WindowBase64/Base64_encoding_and_decoding> On the other side, JSON (JavaScript Object Notation) is a lightweight data-interchange format. Easy to read, write, parse and generate. It is based on a subset of the JavaScript Programming Language. JSON is a text format that is completely language independent but uses conventions that are familiar to programmers of the C-family of languages, including C, C++, C#, Java, JavaScript, Perl, Python, and many others. JSON structure is built around name:value pairs and ordered list of values. <https://www.json.org> The first function, j_encode(), let you transform a data.frame or list to a 'base64' encoded JSON (or JSON string). The j_decode() function takes a 'base64' string (could be an encoded JSON) and transform it to a data.frame (or list, depending of the JSON structure).
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2025-04-22 |
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r-jrvfinance
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public |
Implements the basic financial analysis functions similar to (but not identical to) what is available in most spreadsheet software. This includes finding the IRR and NPV of regularly spaced cash flows and annuities. Bond pricing and YTM calculations are included. In addition, Black Scholes option pricing and Greeks are also provided.
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2025-04-22 |
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r-jrich
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These functions calculate the taxonomic measures presented in Miranda-Esquivel (2016). The package introduces Jack-knife resampling in evolutionary distinctiveness prioritization analysis, as a way to evaluate the support of the ranking in area prioritization, and the persistence of a given area in a conservation analysis. The algorithm is described in: Miranda-Esquivel, D (2016) <DOI:10.1007/978-3-319-22461-9_11>.
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2025-04-22 |
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r-jrc
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An 'httpuv' based bridge between R and 'JavaScript'. Provides an easy way to exchange commands and data between a web page and a currently running R session.
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2025-04-22 |
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r-jpen
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public |
A Joint PENalty Estimation of Covariance and Inverse Covariance Matrices.
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2025-04-22 |
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r-jose
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public |
Read and write JSON Web Keys (JWK, rfc7517), generate and verify JSON Web Signatures (JWS, rfc7515) and encode/decode JSON Web Tokens (JWT, rfc7519). These standards provide modern signing and encryption formats that are the basis for services like OAuth 2.0 or LetsEncrypt and are natively supported by browsers via the JavaScript WebCryptoAPI.
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2025-04-22 |
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r-josaplay
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public |
Josa in Korean is often determined by judging the previous word. When writing reports using Rmd, a function that prints the appropriate investigation for each case is helpful. The 'josaplay' package then evaluates the previous word to determine which josa is appropriate.
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2025-04-22 |
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r-josae
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public |
Implementation of some unit and area level EBLUP estimators as well as the estimators of their MSE also under heteroscedasticity. The package further documents the publications Breidenbach and Astrup (2012) <DOI:10.1007/s10342-012-0596-7>, Breidenbach et al. (2016) <DOI:10.1016/j.rse.2015.07.026> and Breidenbach et al. (2018 in press). The vignette further explains the use of the implemented functions.
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2025-04-22 |
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r-jointpm
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public |
A bivariate integration method to estimate risk caused by two extreme and dependent forcing variables.
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2025-04-22 |
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r-jointnmix
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public |
Fits univariate and joint N-mixture models for data on two unmarked site-associated species. Includes functions to estimate latent abundances through empirical Bayes methods.
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2025-04-22 |
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r-joint.cox
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public |
Perform likelihood estimation and dynamic prediction under joint frailty-copula models for tumour progression and death in meta-analysis. A penalized likelihood method is employed for estimating model parameters, where the baseline hazard functions are modeled by smoothing splines. The methods are applicable for meta-analytic data combining several studies. The methods can analyze data having information on both terminal event time (e.g., time-to-death) and non-terminal event time (e.g., time-to-tumour progression). See Emura et al. (2017) <doi:10.1177/0962280215604510> for likelihood estimation, and Emura et al. (2018) <doi:10.1177/0962280216688032> for dynamic prediction. More details on these methods can also be found in a book of Emura et al. (2019) <10.1007/978-981-13-3516-7>. Survival data from ovarian cancer patients are also available.
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2025-04-22 |
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r-johnson
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public |
RE.Johnson performs the Johnson Transformation to increase the normality.
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2025-04-22 |
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r-jmvcore
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public |
A framework for creating rich interactive analyses for the jamovi platform (see <https://www.jamovi.org> for more information).
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2025-04-22 |
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r-jmuoutlier
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public |
Performs a permutation test on the difference between two location parameters, a permutation correlation test, a permutation F-test, the Siegel-Tukey test, a ratio mean deviance test. Also performs some graphing techniques, such as for confidence intervals, vector addition, and Fourier analysis; and includes functions related to the Laplace (double exponential) and triangular distributions. Performs power calculations for the binomial test.
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2025-04-22 |
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r-jmisc
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Some handy function in R
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2025-04-22 |
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r-jmetrik
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public |
The main purpose of this package is to make it easy for userR's to interact with 'jMetrik' an open source application for psychometric analysis. For example it allows useR's to write data frames to file in a format that can be used by 'jMetrik'. It also allows useR's to read *.jmetrik files (e.g. output from an analysis) for follow-up analysis in R. The *.jmetrik format is a flat file that includes a multiline header and the data as comma separated values. The header includes metadata about the file and one row per variable with the following information in each row: variable name, data type, item scoring, special data codes, and variable label.
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2025-04-22 |
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r-jmdesign
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Performs power calculations for joint modeling of longitudinal and survival data with k-th order trajectories when the variance-covariance matrix, Sigma_theta, is unknown.
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2025-04-22 |
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r-jm
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Shared parameter models for the joint modeling of longitudinal and time-to-event data.
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2025-04-22 |
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r-jlctree
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Implements the tree-based approach to joint modeling of time-to-event and longitudinal data. This approach looks for a tree-based partitioning such that within each estimated latent class defined by a terminal node, the time-to-event and longitudinal responses display a lack of association. See Zhang and Simonoff (2018) <arXiv:1812.01774>.
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2025-04-22 |
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r-jjb
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Set of common functions used for manipulating colors, detecting and interacting with 'RStudio', modeling, formatting, determining users' operating system, feature scaling, and more!
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2025-04-22 |
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r-jiebard
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jiebaR is a package for Chinese text segmentation, keyword extraction and speech tagging. This package provides the data files required by jiebaR.
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2025-04-22 |
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r-jgl
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The Joint Graphical Lasso is a generalized method for estimating Gaussian graphical models/ sparse inverse covariance matrices/ biological networks on multiple classes of data. We solve JGL under two penalty functions: The Fused Graphical Lasso (FGL), which employs a fused penalty to encourage inverse covariance matrices to be similar across classes, and the Group Graphical Lasso (GGL), which encourages similar network structure between classes. FGL is recommended over GGL for most applications. Reference: Danaher P, Wang P, Witten DM. (2013) <doi:10.1111/rssb.12033>.
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2025-04-22 |
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r-jetpack
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Manage project dependencies from your DESCRIPTION file. Create a reproducible virtual environment with minimal additional files in your project. Provides tools to add, remove, and update dependencies as well as install existing dependencies with a single function.
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2025-04-22 |
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r-jenkins
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public |
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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2025-04-22 |
