ExtremeRisks

A set of procedures for estimating risks related to extreme events via risk measures such as Expectile, Value-at-Risk, etc. is provided. Estimation methods for univariate independent observations and temporal dependent observations are available. The methodology is extended to the case of independent multidimensional observations. The statistical inference is performed through parametric and non-parametric estimators. Inferential procedures such as confidence intervals, confidence regions and hypothesis testing are obtained by exploiting the asymptotic theory. Adapts the methodologies derived in Padoan and Stupfler (2020) doi:10.48550/arXiv.2004.04078, Padoan and Stupfler (2020) doi:10.48550/arXiv.2007.08944, Daouia et al. (2018) doi:10.1111/rssb.12254, Drees (2000) doi:10.1214/aoap/1019487617, Drees (2003) doi:10.3150/bj/1066223272, de Haan and Ferreira (2006) doi:10.1007/0-387-34471-3, de Haan et al. (2016) doi:10.1007/s00780-015-0287-6.

Last 30 days

This package has been downloaded 152 times in the last 30 days. More than a random curiosity, but not quite a blockbuster. Still, it's gaining traction! The following heatmap shows the distribution of downloads per day. Yesterday, it was downloaded 5 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 2,257 times in the last 365 days. Now we’re talking! This work is officially 'heard of in academic circles', just like those wild research papers on synthetic bananas. The day with the most downloads was Sep 11, 2024 with 25 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.