Modeling football outcomes | Bradley-Terry-Davidson model | Bivariate-Poisson model | Likelihood approach | Bayesian approach | Hamiltonian Monte Carlo (HMC) | Variational Inference Methods | Laplace Approximation | Installing the package | Bradley-Terry-Davidson model fit | Using btd_foot | Visualization tools | Goal-based models fit | Static fit | Changing default priors | Dynamic fit | Using btd_foot and stan_foot sequentially | Model estimates and visualization tools | Plotting and interpreting team-specific abilities | Model checking | Predictions and predictive accuracy | Posterior out-of-sample probabilities | Home-win posterior probabilities | Rank-league reconstruction | Model comparisons | Comparing Football Prediction Models using compare_foot | LOOIC and WAIC | Extensions in next versions | References

Example: bivariate Gaussian data | Example: fishery data | References

Pivotal algorithms: how they works, and why | piv_KMeans: k-means clustering via pivotal units | References