mpath

Algorithms compute robust estimators for loss functions in the concave convex (CC) family by the iteratively reweighted convex optimization (IRCO), an extension of the iteratively reweighted least squares (IRLS). The IRCO reduces the weight of the observation that leads to a large loss; it also provides weights to help identify outliers. Applications include robust (penalized) generalized linear models and robust support vector machines. The package also contains penalized Poisson, negative binomial, zero-inflated Poisson, zero-inflated negative binomial regression models and robust models with non-convex loss functions. Wang et al. (2014) doi:10.1002/sim.6314, Wang et al. (2015) doi:10.1002/bimj.201400143, Wang et al. (2016) doi:10.1177/0962280214530608, Wang (2021) doi:10.1007/s11749-021-00770-2, Wang (2024) doi:10.1111/anzs.12409.

Last 30 days

This package has been downloaded 671 times in the last 30 days. Not bad! The download count is somewhere between 'small-town buzz' and 'moderate academic conference'. The following heatmap shows the distribution of downloads per day. Yesterday, it was downloaded 23 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 10,925 times in the last 365 days. The downloads are officially high enough to crash an underfunded departmental server. Quite an accomplishment! The day with the most downloads was Feb 12, 2025 with 169 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.