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20112020
most citedA goodness-of-fit test for bivariate extreme-value copulas

95 citations · 252 across the 11 of their papers we have counts for

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8 papers · 1 filter

stat.ME2020★ 6 cited

Moving-Resting Process with Measurement Error in Animal Movement Modeling

Chaoran Hu, Mark Elbroch, Thomas Meyer +2

Statistical modeling of animal movement is of critical importance. The continuous trajectory of an animal's movements is only observed at discrete, often irregularly spaced time po…

stat.ME2018★ 5 cited

On estimation for Brownian motion governed by telegraph process with multiple off states

Vladimir Pozdnyakov, L. Mark Elbroch, Chaoran Hu +2

Brownian motion whose infinitesimal variance changes according to a three-state continuous time Markov Chain is studied. This Markov Chain can be viewed as a telegraph process with…

stat.ME2016★ 87 cited

Automated Threshold Selection for Extreme Value Analysis via Goodness-of-Fit Tests with Application to Batched Return Level Mapping

Brian Bader, Jun Yan, Xuebin Zhang

Threshold selection is a critical issue for extreme value analysis with threshold-based approaches. Under suitable conditions, exceedances over a high threshold have been shown to…

stat.ME2016★ 27 cited

Automated Selection of r for the r Largest Order Statistics Approach with Adjustment for Sequential Testing

Brian Bader, Jun Yan, Xuebin Zhang

The r largest order statistics approach is widely used in extreme value analysis because it may use more information from the data than just the block maxima. In practice, the choi…

stat.ME2012★ 11 cited

A two-step approach to model precipitation extremes in California based on max-stable and marginal point processes

Hongwei Shang, Jun Yan, Xuebin Zhang

In modeling spatial extremes, the dependence structure is classically inferred by assuming that block maxima derive from max-stable processes. Weather stations provide daily record…

stat.ME2012★ 6 cited

Goodness-of-fit testing based on a weighted bootstrap: A fast large-sample alternative to the parametric bootstrap

Ivan Kojadinovic, Jun Yan

The process comparing the empirical cumulative distribution function of the sample with a parametric estimate of the cumulative distribution function is known as the empirical proc…