Trajectories and Phylogenies Simulator

Generates stochastic time series and genealogies associated with a population dynamics model. Times series are simulated using the Gillespie exact and approximate algorithms and a new algorithm we introduce that uses both approaches to optimize the time execution of the simulations. Genealogies are simulated from a trajectory using a backwards-in-time based approach. Methods are described in Danesh G et al (2022) .

Power Analyses for Interaction Effects in Cross-Sectional Regressions

Power analysis for regression models which test the interaction of two or three independent variables on a single dependent variable. Includes options for correlated interacting variables and specifying variable reliability. Two-way interactions can include continuous, binary, or ordinal variables. Power analyses can be done either analytically or via simulation. Includes tools for simulating single data sets and visualizing power analysis results. The primary functions are power_interaction_r2() and power_interaction() for two-way interactions, and power_interaction_3way_r2() for three-way interactions. Please cite as: Baranger DAA, Finsaas MC, Goldstein BL, Vize CE, Lynam DR, Olino TM (2023). "Tutorial: Power analyses for interaction effects in cross-sectional regressions." .

Lexicons for Text Analysis

A collection of lexical hash tables, dictionaries, and word lists.

Random Survival Forest for Recurrent Events

Analyze recurrent events with right-censored data and the potential presence of a terminal event (that prevents further occurrences, like death). 'recofest' extends the random survival forest algorithm, adapting splitting rules and node estimators to handle complexities of recurrent events. The methodology is fully described in Murris, J., Bouaziz, O., Jakubczak, M., Katsahian, S., & Lavenu, A. (2024) (< https://hal.science/hal-04612431v1/document>).

Tools for Modelling of Animal Flight Performance

Allows estimation and modelling of flight costs in animal (vertebrate) flight, implementing the aerodynamic power model described in Klein Heerenbrink et al. (2015) . Taking inspiration from the program 'Flight', developed by Colin Pennycuick (Pennycuick (2008) "Modelling the flying bird". Amsterdam: Elsevier. ISBN 0-19-857721-4), flight performance is estimated based on basic morphological measurements such as body mass, wingspan and wing area. 'afpt' can be used to make predictions on how animals should adjust their flight behaviour and wingbeat kinematics to varying flight conditions.

Single Cell Transcriptomics-Level Cytokine Activity Prediction and Estimation

Generates cell-level cytokine activity estimates using relevant information from gene sets constructed with the 'CytoSig' and the 'Reactome' databases and scored using the modified 'Variance-adjusted Mahalanobis (VAM)' framework for single-cell RNA-sequencing (scRNA-seq) data. 'CytoSig' database is described in: Jiang at al., (2021) . 'Reactome' database is described in: Gillespie et al., (2021) . The 'VAM' method is outlined in: Frost (2020) .

Scale Mixture of Normal Distribution in Linear Mixed-Effects Model

Bayesian analysis of censored linear mixed-effects models that replace Gaussian assumptions with a flexible class of distributions, such as the scale mixture of normal family distributions, considering a damped exponential correlation structure which was employed to account for within-subject autocorrelation among irregularly observed measures. For more details, see Kelin Zhong, Fernanda L. Schumacher, Luis M. Castro, Victor H. Lachos (2025) .

sbioPN: Simulation of deterministic and stochastic spatial biochemical reaction networks using Petri Nets

sbioPN is a package suited to perform simulation of deterministic and stochastic systems of biochemical reaction networks with spatial effects. Models are defined using a subset of Petri Nets, in a way that is close at how chemical reactions are defined. For deterministic solutions, sbioPN creates the associated system of differential equations "on the fly", and solves it with a Runge Kutta Dormand Prince 45 explicit algorithm. For stochastic solutions, sbioPN offers two variants of Gillespie algorithm, or SSA. For hybrid deterministic/stochastic, it employs the Haseltine and Rawlings algorithm, that partitions the system in fast and slow reactions. sbioPN algorithms are developed in C to achieve adequate performance.

Road Condition Analysis

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>.

Simulation of deterministic and stochastic biochemical reaction networks using Petri Nets

bioPN is a package suited to perform simulation of deterministic and stochastic systems of biochemical reaction networks. Models are defined using a subset of Petri Nets, in a way that is close at how chemical reactions are defined. For deterministic solutions, bioPN creates the associated system of differential equations "on the fly", and solves it with a Runge Kutta Dormand Prince 45 explicit algorithm. For stochastic solutions, bioPN offers variants of Gillespie algorithm, or SSA. For hybrid deterministic/stochastic, it employs the Haseltine and Rawlings algorithm, that partitions the system in fast and slow reactions. bioPN algorithms are developed in C to achieve adequate performance.