Extreme value distributions

By Samuel Kotz, Saralees Nadarajah. 2013

1,254 citations recorded by the source corpus.

View Paper: https://www.semanticscholar.org/paper/095de22281c66c30c99c5c2b8159b9b88446c0ca

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Demography

In Finance

Citations in the corpus

A new high‐resolution Meteorological Reanalysis Italian Dataset: MERIDA (2019, methodology): “The estimation of the snow loads will be carried out using the generalized extreme values (GEV) analysis (Kotz and Nadarajah, 2000; Coles, 2001) following two different approaches, the block maxima (Coles, 2001) and the peak over threshold (POT: Coles, 2001) over the period 2000–2018.”
Meta-Recognition: The Theory and Practice of Recognition Score Analysis (2011, background): “The Extreme Value Theorem, also known as the FisherTippet Theorem[23] states:”
The Marshall-Olkin Fréchet Distribution (2013, background): “More information about the Fréchet distribution can be found in Kotz and Nadarajah (2000).”
Generalized Gumbel distribution (2010, background): “5, the second and higher moments do not exist [13].”
Exponentiated Pareto Distribution: Different Method of Estimations (2009, background): “…different parameters estimators for certain distributions; Balakrishnan and Basu (1995), Hossain and Zimmer (2003), Komori and Hirose (2004), Kotz and Nadarajah (2000), Kundu and Raqab (2005), Murthy et al. (2004), Nguyen (2004), Surles and Padgett (2005), Wingo (1993), Wu and Li (2003) and…”
On Six-Parameter Frechet Distribution: Properties and Applications (2016, background): “Further information about the Fréchet distribution and its applications were discussed in Kotz and Nadarajah (2000).”
Battle of extreme value distributions: A global survey on extreme daily rainfall (2013, methodology): “Finally, in the domain of attraction of the RW law belong distributions bounded from above [see e.g., Kotz and Nadarajah, 2000].”
Recent Advances in Open Set Recognition: A Survey (2018, methodology): “Based on the intuition that one can reject the large set of unknown unknown classes even under an assumption of incomplete class knowledge if the positive data for any known known classes is accurately modeled without overﬁt-ting, Jain et al. [19] invoked the EVT to model the positive training sampl”
Some Results for Beta Fréchet Distribution (2008, background): “The book of Kotz and Nadarajah (2000) demonstrates the applicability of the Fréchet distribution in several fields.”
A Survey of Stealth Malware Attacks, Mitigation Measures, and Steps Toward Autonomous Open World Solutions (2016, background): “They are also are directly derived from EVT and incorporate higherorder statistics which Gaussian distributions cannot (e.g., skew, curtosis).”
Sparse Representation-Based Open Set Recognition (2017, background): “n threshold between 0 and 1. B. Extreme Value Theory Extreme value theory is a branch of statistics analyzing the distribution of data of abnormally high or low values. It has been applied in Finance [20], Hydrology [21] and novelty detection problems [22], [23], [24]. In this section, we give a bri”
Posterior propriety in Bayesian extreme value analyses using reference priors (2015, neutral): “) is proportional to ˙ (n+1)ˇ(˘)exp ( Xn i=1 z 1=˘ i ) Yn i=1 z (1+1=˘) i ; (4.1) where z i= 1 + ˘(y i )=˙and ˙>0. If ˘>0 then ˙=˘<y 1 and if ˘<0 then ˙=˘>y n. 4.1 Prior densities Kotz and Nadarajah (2000, page 63) give the Fisher information matrix for the GEV distribution (1.2). U”
Global Production with Export Platforms (2016, neutral): “…index – defined in (4) – which aggregates the product-level prices that the firm (i, φ, Z, ) charges in market m, as pm(i, φ, Z, ) = κ 1 1−σ φ−1 (∑ k∈Z (γikwkτkm) −θ θk )−1/θ , (7) 12See Kotz and Nadarajah (2000), Chapter 1, for a description of the Fréchet and other extreme value distributions.”