Results 51 to 60 of about 19,957,777 (200)

Head/Tail Breaks: A New Classification Scheme for Data with a Heavy-Tailed Distribution [PDF]

The Professional Geographer, 2013
13 pages, 11 figures, 2 ...
openaire   +2 more sources

Models for Heavy-tailed Asset Returns [PDF]

Many of the concepts in theoretical and empirical finance developed over the past decades – including the classical portfolio theory, the Black- Scholes-Merton option pricing model or the RiskMetrics variance-covariance approach to VaR – rest upon the ...
Szymon Borak, Adam Misiorek, Rafał Weron   +2 more
core   +2 more sources

Transformation kernel density estimation of actuarial loss functions [PDF]

, 2013
[cat] Es presenta un estimador nucli transformat que és adequat per a distribucions de cua pesada. Utilitzant una transformació basada en la distribució de probabilitat Beta l’elecció del paràmetre de finestra és molt directa. Es presenta una aplicació a
Guillén, Montserrat, Nielsen, Jens Perch, Bolancé Losilla, Catalina   +2 more
core   +2 more sources

Graph Huber: a robust regression model for graph data

Xibei Gongye Daxue Xuebao
As it is increasingly prevalent that data contains noise or obeys heavy-tailed distribution, a robust regression model becomes one of focal and hot topics in many study fields.
SU Meihong, WANG Jiaxing, LI Yan, ZHANG Hai   +3 more
doaj   +1 more source

Heavy-Tailed Linear Regression and K-Means

Information
Most standard machine learning algorithms are formulated with the implicit assumption that empirical data are “well-behaved”. In this work, we consider heavy-tailed data whose underlying distribution does not necessarily possess finite moments.
Mario Sayde, Jihad Fahs, Ibrahim Abou-Faycal   +2 more
doaj   +1 more source

Characterizing the Heterogeneity of the OpenStreetMap Data and Community

ISPRS International Journal of Geo-Information, 2015
OpenStreetMap (OSM) constitutes an unprecedented, free, geographical information source contributed by millions of individuals, resulting in a database of great volume and heterogeneity.
Ding Ma, Mats Sandberg, Bin Jiang
doaj   +1 more source

New methods to define heavy-tailed distributions with applications to insurance data

Journal of Taibah University for Science, 2020
Heavy-tailed distributions play an important role in modelling data in actuarial and financial sciences. In this article, nine new methods are suggested to define new distributions suitable for modelling data with an heavy right tail.
Zubair Ahmad, Eisa Mahmoudi, G. G. Hamedani, Omid Kharazmi   +3 more
doaj   +1 more source

Transformations In Hazard Rate Estimation For Heavy-Tailed Data

IFAC Proceedings Volumes, 2013
Abstract A new estimate of the hazard rate function is proposed, specifically designed for situations when the underlying data are heavy tailed. The estimate is nonparametric in nature and is based on the concept that estimation bias is reduced both in body and in the tail through an appropriate transformation of the sample.
openaire   +1 more source

Inference for double Pareto lognormal queues with applications [PDF]

, 2008
In this article we describe a method for carrying out Bayesian inference for the double Pareto lognormal (dPlN) distribution which has recently been proposed as a model for heavy-tailed phenomena. We apply our approach to inference for the dPlN/M/1 and
Lillo Rodríguez, Rosa Elvira, Wilson, Simon P., Ramírez Cobo, Josefa, Wiper, Michael Peter   +3 more
core   +1 more source

A Robust TCPHD Filter for Multi-Sensor Multitarget Tracking Based on a Gaussian–Student’s t-Mixture Model

Remote Sensing
To realize multitarget trajectory tracking under non-Gaussian heavy-tailed noise, we propose a Gaussian–Student t-mixture distribution-based trajectory cardinality probability hypothesis density filter (GSTM-TCPHD).
Shaoming Wei, Yingbin Lin, Jun Wang, Yajun Zeng, Fangrui Qu, Xuan Zhou, Zhuotong Lu   +6 more
doaj   +1 more source