Runtime for serving containers that can execute R code on the AWS Lambda serverless compute service <https://aws.amazon.com/lambda/>. Provides the necessary functionality for handling the various endpoints required for accepting new input and sending responses.

Large language model agents as governed research instruments, built on LLMR'. The package supports designed conversations and factorial experiments with declared tools and budgets. Each run produces an inspectable record that can be archived and checked.

Implementation of the drift-diffusion mixed model for category learning as described in Paulon et al. (2021) <doi:10.1080/01621459.2020.1801448>.

Simulates outcomes of an updated version of the latent state reinforcement learning model originally described in Cochran and Cisler (2019) <doi:10.1371/journal.pcbi.1007331>. The package is designed to create results under all reasonable experiment setups, including different reinforcement schedules, number of cues, number of phases, and number of options per trial. Participants can be simulated using either fixed parameters or parameters drawn from a distribution.

This package provides a graph proposed by Rosenbaum is useful for checking some properties of various sorts of latent scale, this program generates commands to obtain the graph using dot from graphviz'.

This package provides functions to prepare, visualize, and analyse diachronic network data on local political actors, with a particular focus on the development of local party systems and identification of actor groups. Formalizes and automates a continuity diagram method that has been previously applied in research on Czech local politics, e.g. Bubenicek and Kubalek (2010, ISSN:1803-8220), Kubalek and Bubenicek (2012, ISSN:1803-8220), and Cmejrek, Bubenicek, and Copik (2010, ISBN:978-80-247-3061-5). The package also includes several example datasets derived from Czech municipal elections, compiled from official election results, field research, and previously published case studies on Czech local politics.

Linear model functions using permutation tests.

This package contains functions for a flexible varying-coefficient landmark model by incorporating multiple short-term events into the prediction of long-term survival probability. For more information about landmark prediction please see Li, W., Ning, J., Zhang, J., Li, Z., Savitz, S.I., Tahanan, A., Rahbar.M.H., (2023+). "Enhancing Long-term Survival Prediction with Multiple Short-term Events: Landmarking with A Flexible Varying Coefficient Model".

This package provides a statistical learning method that tries to find the best set of predictors and interactions between predictors for modeling binary or quantitative response data in a decision tree. Several search algorithms and ensembling techniques are implemented allowing for finetuning the method to the specific problem. Interactions with quantitative covariables can be properly taken into account by fitting local regression models. Moreover, a variable importance measure for assessing marginal and interaction effects is provided. Implements the procedures proposed by Lau et al. (2024, <doi:10.1007/s10994-023-06488-6>).

This package provides a simple progress bar showing estimated remaining time. Multiple forecast methods and user defined forecast method for the remaining time are supported.

This package provides a curated collection of Howard Phillips Lovecraft's complete stories, collected for the purpose of text analysis.

This package provides a system for accurately designing complex light regimes using LEDs. Takes calibration data and user-defined target irradiances and it tells you what intensities to use. For more details see Vong et al. (2025) <doi:10.1101/2025.06.06.658293>.

My PhD supervisor once told me that everyone doing newspaper analysis starts by writing code to read in files from the LexisNexis newspaper archive (retrieved e.g., from <https://www.lexisnexis.com/> or any of the partner sites). However, while this is a nice exercise I do recommend, not everyone has the time. This package takes files downloaded from the newspaper archive of LexisNexis', reads them into R and offers functions for further processing.

"Learning with Subset Stacking" is a supervised learning algorithm that is based on training many local estimators on subsets of a given dataset, and then passing their predictions to a global estimator. You can find the details about LESS in our manuscript at <arXiv:2112.06251>.

This package provides a toolbox for R arrays. Flexibly split, bind, reshape, modify, subset and name arrays.

Estimation of life expectancy and Life Years Lost (LYL, or lillies for short) for a given population, for example those with a given disease or condition. In addition, the package can be used to compare estimates from different populations, or to estimate confidence intervals. Technical details of the method are available in Plana-Ripoll et al. (2020) <doi:10.1371/journal.pone.0228073> and Andersen (2017) <doi:10.1002/sim.7357>.

Calculate mean statistics and leaf angle distribution type from measured leaf inclination angles. LAD distribution is fitted using a two-parameters (mu, nu) Beta distribution and compared with six theoretical LAD distributions. Additional information is provided in Chianucci and Cesaretti (2022) <doi:10.1101/2022.10.28.513998>.

This package provides a flexible and easy-to use interface for the soil vegetation atmosphere transport (SVAT) model LWF-BROOK90, written in Fortran. The model simulates daily transpiration, interception, soil and snow evaporation, streamflow and soil water fluxes through a soil profile covered with vegetation, as described in Hammel & Kennel (2001, ISBN:978-3-933506-16-0) and Federer et al. (2003) <doi:10.1175/1525-7541(2003)004%3C1276:SOAETS%3E2.0.CO;2>. A set of high-level functions for model set up, execution and parallelization provides easy access to plot-level SVAT simulations, as well as multi-run and large-scale applications.

Probabilistic multivariate time series forecasting using a variational sequence-to-sequence model with Lambda-style temporal aggregation. Provides transformations, uncertainty estimates, diagnostics, and publication-ready plots.

Datasets for the fourth edition of "Statistics: Unlocking the Power of Data" by Lock^5 Includes versions of datasets from earlier editions.

This package provides a LaTeX Letter class for rmarkdown', using the pandoc-letter template adapted for use with markdown'.

This package performs recursive partitioning of linear and nonlinear mixed effects models, specifically for longitudinal data. The package is an extension of the original longRPart package by Stewart and Abdolell (2013) <https://cran.r-project.org/package=longRPart>.

Parse various reflectance/transmittance/absorbance spectra file formats to extract spectral data and metadata, as described in Gruson, White & Maia (2019) <doi:10.21105/joss.01857>. Among other formats, it can import files from Avantes <https://www.avantes.com/>, CRAIC <https://www.microspectra.com/>, and OceanOptics'/'OceanInsight <https://www.oceanoptics.com/> brands.

An implementation of the Log Cumulative Probability Model (LCPM) and Proportional Probability Model (PPM) for which the Maximum Likelihood Estimates are determined using constrained optimization. This implementation accounts for the implicit constraints on the parameter space. Other features such as standard errors, z tests and p-values use standard methods adapted from the results based on constrained optimization.