Analysis of local adaptation on Medicago for French institute INRA

Replication of simulations and results from Chapelle, O., & Li, L. (2011). An empirical evaluation of Thompson sampling. Advances in neural information processing systems, 2249-2257.

Miscellaneous functions and simulation code that don't belong anywhere else.

🐟 R package for NetLogo experiments http://bergant.github.io/nlexperiment/

Integrated population models for interacting species

Solution to how many moves on average it take a randomly moving knight to return to the starting square

Simulaciones de epidemias 👾 en poblaciones con mezclas homogéneas 👪 utilizando modelos basados en agentes autónomos 🤖

R package dieroller

Simulate data and fit 2-species occupancy model à la Rota et al. (2016) w/ Unmarked

Supplemental material for Redfors, Björn, et al. "The win ratio approach for composite endpoints: practical guidance based on previous experience." European Heart Journal (2020). This repo contains R functions that approximate the sample size for a two-arm clinical trial based on a composite endpoint analyzed using the Win Ratio.

tibble friendly, cleverly impure functions to simulate stochastic processes

Simulation Study for the Bayes PCA method

Stochastic epidemiological branching simulation

Binding free energy calculation

Review: Data-driven methodology for detecting treatment effect heterogeneity

A tutorial on automating R simulation studies with clusters

Sample R code for paper "Design and analysis of cluster randomized trials with time-to-event outcomes under the additive hazards mixed model" by Blaha, Esserman and Li (Under Review).

Statistical model to simulate individual haemoglobin concentrations in human hosts as a function of observed egg counts quantifying hookworm infection. The model employs latent variables to reproduce an underlying worm burdens distribution in the population. The model after calibration is used to predict the prevalence of anaemia that can be att…

Statistical Quantification of Individual Differences: an simulation tool for understanding multi-level phenotypic data in linear mixed models