Extracting, Computing and Exploring the Parameters of Statistical Models using R
Extracting, Computing and Exploring the Parameters of Statistical Models using R - Published in JOSS (2020)
simstudy
simstudy: Illuminating research methods through data generation - Published in JOSS (2020)
A Short Introduction to PF
A Short Introduction to PF: A C++ Library for Particle Filtering - Published in JOSS (2020)
Multivariate Covariance Generalized Linear Models in Python
Multivariate Covariance Generalized Linear Models in Python: The mcglm library - Published in JOSS (2024)
brms
brms R package for Bayesian generalized multivariate non-linear multilevel models using Stan
mixedmodels.jl
A Julia package for fitting (statistical) mixed-effects models
speclet
A Bayesian hierarchical model to discover tissue-specific cancer driver genes and synthetic lethal interactions from CRISPR/Cas9 LoF screens.
r-pipeline-development-workshop
Workshop on pipeline development and model deployment onto Kubernetes via Docker using R.
prettyglm
prettyglm provides a set of functions which can easily create beautiful coefficient summaries which can readily be shared and explained.
https://github.com/abel-research/openlimbtt
An Open-Source, synthetic transtibial residual limb anatomic dataset
https://github.com/kukuster/ci_methods_analyser
Analyse efficacy of your own confidence interval (CI) methods
https://github.com/abel-research/openhands
An Open-Source, synthetic finger anatomic dataset
coevolve
coevolve R package for Bayesian generalized dynamic phylogenetic models using Stan
hookworm_anaemia_statistical_model
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 attributed to hookworm infection.
teaching
Teaching Materials for Dr. Waleed A. Yousef
QuasiGLM
Adjust Poisson and Binomial Generalised Linear Models to their quasi equivalents for dispersed data
