scorematchingad

Hyvärinen's score matching https://jmlr.org/papers/v6/hyvarinen05a.html is a useful estimation technique when the normalising constant for a probability distribution is difficult to compute. This package implements score matching estimators using automatic differentiation in the 'CppAD' library https://github.com/coin-or/CppAD and is designed for quickly implementing score matching estimators for new models. Also available is general robustification (Windham, 1995) https://www.jstor.org/stable/2346159. Already in the package are estimators for directional distributions (Mardia, Kent and Laha, 2016) doi:10.48550/arXiv.1604.08470 and the flexible Polynomially-Tilted Pairwise Interaction model for compositional data. The latter estimators perform well when there are zeros in the compositions (Scealy and Wood, 2023) doi:10.1080/01621459.2021.2016422, even many zeros (Scealy, Hingee, Kent, and Wood, 2024) doi:10.1007/s11222-024-10412-w.

Last 30 days

This package has been downloaded 163 times in the last 30 days. Now we're getting somewhere! Enough downloads to populate a lively group chat. The following heatmap shows the distribution of downloads per day. Yesterday, it was downloaded 15 times.

The following line graph shows the downloads per day. You can hover over the graph to see the exact number of downloads per day.

Last 365 days

This package has been downloaded 2,106 times in the last 365 days. That's enough downloads to impress a room full of undergrads. A commendable achievement indeed. The day with the most downloads was May 22, 2024 with 49 downloads.

The following line graph shows the downloads per day. You can hover over the graph to see the exact number of downloads per day.