This package contains convenience functions for working with spatial data across multiple UTM zones, raster-vector operations common in the analysis of conflict data, and converting degrees, minutes, and seconds latitude and longitude coordinates to decimal degrees.

Dump source code, documentation and vignettes of an R package into a single file. Supports installed packages, tar.gz archives, and package source directories. If the package is not installed, only its source is automatically downloaded from CRAN for processing. The output is a single plain text file or a character vector, which is useful to ingest complete package documentation and source into a large language model (LLM) or pass it further to other tools, such as ragnar <https://github.com/tidyverse/ragnar> to create a Retrieval-Augmented Generation (RAG) workflow.

Sends texts to the <https://www.receptiviti.com> API to be scored, and facilitates the creation of custom norms and local results databases.

Three methods to calculate R2 for models with correlated errors, including Phylogenetic GLS, Phylogenetic Logistic Regression, Linear Mixed Models (LMMs), and Generalized Linear Mixed Models (GLMMs). See details in Ives 2018 <doi:10.1093/sysbio/syy060>.

This package implements distance based probability models for ranking data. The supported distance metrics include Kendall distance, Spearman distance, Footrule distance, Hamming distance, Weighted-tau distance and Weighted Kendall distance. Phi-component model and mixture models are also supported.

Defines colour palettes and themes for Royal Statistical Society (RSS) publications, including Significance magazine. Palettes and themes are supported in both base R and ggplot2 graphics, and are intended to be used by authors submitting to RSS publications.

Predict fish year-class strength by calibration regression analysis of multiple recruitment index series.

Adds subtotal rows / sections (a la the SAS Proc Tabulate All option) to a Group By output by running a series of Group By functions with partial sets of the same variables and combining the results with the original. Can be used to add comprehensive information to a data report or to quickly aggregate Group By outputs used to gain a greater understanding of data.

The RBP curve is a visual tool to assess the performance of prediction models.

This holds r markdown and quarto templates for academic papers and slide decks. It also has templates to create research projects which contain academic papers as vignettes.

This package provides a user-friendly interface to NASA Exoplanets Archive API <https://exoplanetarchive.ipac.caltech.edu/>, enabling retrieval and analysis of exoplanetary and stellar data. Includes functions for querying, filtering, summarizing, and computing derived parameters from the Exoplanets catalog.

Add-in to the RJDemetra package on seasonal adjustments. It allows to produce dashboards to summarise models and quickly check the quality of the seasonal adjustment.

This package provides a client package that makes the KorAP web service API accessible from R. The corpus analysis platform KorAP has been developed as a scientific tool to make potentially large, stratified and multiply annotated corpora, such as the German Reference Corpus DeReKo or the Corpus of the Contemporary Romanian Language CoRoLa', accessible for linguists to let them verify hypotheses and to find interesting patterns in real language use. The RKorAPClient package provides access to KorAP and the corpora behind it for user-created R code, as a programmatic alternative to the KorAP web user-interface. You can learn more about KorAP and use it directly on DeReKo at <https://korap.ids-mannheim.de/>.

This package provides a research infrastructure to develop and evaluate collaborative filtering recommender algorithms. This includes a sparse representation for user-item matrices, many popular algorithms, top-N recommendations, and cross-validation. Hahsler (2022) <doi:10.48550/arXiv.2205.12371>.

This package provides an easy way to report the results of ROC analysis, including: 1. an ROC curve. 2. the value of Cutoff, AUC (Area Under Curve), ACC (accuracy), SEN (sensitivity), SPE (specificity), PLR (positive likelihood ratio), NLR (negative likelihood ratio), PPV (positive predictive value), NPV (negative predictive value), PPA (percentage of positive accordance), NPA (percentage of negative accordance), TPA (percentage of total accordance), KAPPA (kappa value).

The R equivalent of nodemon'. Watches specified directories for file changes and reruns a designated R script when changes are detected. It's designed to automate the process of reloading your R applications during development, similar to nodemon for Node.js'.

SurveyCTO is a platform for mobile data collection in offline settings. The rsurveycto R package uses the SurveyCTO REST API <https://docs.surveycto.com/05-exporting-and-publishing-data/05-api-access/01.api-access.html> to read datasets and forms from a SurveyCTO server into R as data.table's and to download file attachments. The package also has limited support to write datasets to a server.

R access to the FOAAS (F... Off As A Service) web service is provided.

Aims at loading Google Adwords data into R. Adwords is an online advertising service that enables advertisers to display advertising copy to web users (see <https://developers.google.com/adwords/> for more information). Therefore the package implements three main features. First, the package provides an authentication process for R with the Google Adwords API (see <https://developers.google.com/adwords/api/> for more information) via OAUTH2. Second, the package offers an interface to apply the Adwords query language in R and query the Adwords API with ad-hoc reports. Third, the received data are transformed into suitable data formats for further data processing and data analysis.

This package provides methods for multiway data analysis by means of Parafac and Tucker 3 models. Robust versions (Engelen and Hubert (2011) <doi:10.1016/j.aca.2011.04.043>) and versions for compositional data are also provided (Gallo (2015) <doi:10.1080/03610926.2013.798664>, Di Palma et al. (2018) <doi:10.1080/02664763.2017.1381669>). Several optimization methods alternative to ALS are available (Simonacci and Gallo (2019) <doi:10.1016/j.chemolab.2019.103822>, Simonacci and Gallo (2020) <doi:10.1007/s00500-019-04320-9>).

Placental epigenetic clock to estimate aging based on gestational age using DNA methylation levels, so called placental epigenetic clock (PlEC). We developed a PlEC for the 2024 Placental Clock DREAM Challenge (<https://www.synapse.org/Synapse:syn59520082/wiki/628063>). Our PlEC achieved the top performance based on an independent test set. PlEC can be used to identify accelerated/decelerated aging of placenta for understanding placental dysfunction-related conditions, e.g., great obstetrical syndromes including preeclampsia, fetal growth restriction, preterm labor, preterm premature rupture of the membranes, late spontaneous abortion, and placental abruption. Detailed methodologies and examples are documented in our vignette, available at <https://herdiantrisufriyana.github.io/rplec/doc/placental_aging_analysis.html>.

We generate random variables following general Marchenko-Pastur distribution and Tracy-Widom distribution. We compute limits and distributions of eigenvalues and generalized components of spiked covariance matrices. We give estimation of all population eigenvalues of spiked covariance matrix model. We give tests of population covariance matrix. We also perform matrix denoising for signal-plus-noise model.

Efficient algorithms for generating ensembles of robust, sparse and diverse models via robust multi-model subset selection (RMSS). The robust ensembles are generated by minimizing the sum of the least trimmed square loss of the models in the ensembles under constraints for the size of the models and the sharing of the predictors. Tuning parameters for the robustness, sparsity and diversity of the robust ensemble are selected by cross-validation.

Studies of resilience in older adults employ a single-arm design where everyone experiences the stressor. The simplistic approach of regressing change versus baseline yields biased estimates due to regression-to-the-mean. This package provides a method to correct the bias. It also allows covariates to be included. The method implemented in the package is described in Varadhan, R., Zhu, J., and Bandeen-Roche, K (2023), Biostatistics (To appear).