Results 31 to 40 of about 1,758,675 (318)

Two-stage data segmentation permitting multiscale change points, heavy tails and dependence [PDF]

open access: yesAnnals of the Institute of Statistical Mathematics, 2019
The segmentation of a time series into piecewise stationary segments is an important problem both in time series analysis and signal processing. In the presence of multiscale change points with both large jumps over short intervals and small jumps over ...
Haeran Cho, C. Kirch
semanticscholar   +1 more source

Heavy-Tailed Independent Component Analysis [PDF]

open access: yes2015 IEEE 56th Annual Symposium on Foundations of Computer Science, 2015
30 ...
Anderson, Joseph   +3 more
openaire   +2 more sources

A Note on Second Order Conditions in Extreme Value Theory: Linking General and Heavy Tail Conditions

open access: yesRevstat Statistical Journal, 2007
Second order conditions ruling the rate of convergence in any first order condition involving regular variation and assuring a unified extreme value limiting distribution function for the sequence of maximum values, linearly normalized, have appeared in
M. Isabel Fraga Alves   +3 more
doaj   +1 more source

Adaptive Models and Heavy Tails [PDF]

open access: yesSSRN Electronic Journal, 2016
This paper proposes a novel and flexible framework to estimate autoregressive models with time-varying parameters. Our setup nests various adaptive algorithms that are commonly used in the macroeconometric literature, such as learning-expectations and forgetting-factor algorithms.
Davide Delle Monache, Ivan Petrella
openaire   +5 more sources

Top Incomes, Heavy Tails, and Rank-Size Regressions

open access: yesEconometrics, 2018
In economics, rank-size regressions provide popular estimators of tail exponents of heavy-tailed distributions. We discuss the properties of this approach when the tail of the distribution is regularly varying rather than strictly Pareto.
Christian Schluter
doaj   +1 more source

Inhomogeneous phase-type distributions and heavy tails [PDF]

open access: yesJournal of Applied Probability, 2018
We extend the construction principle of phase-type (PH) distributions to allow for inhomogeneous transition rates and show that this naturally leads to direct probabilistic descriptions of certain transformations of PH distributions.
H. Albrecher, M. Bladt
semanticscholar   +1 more source

Heavy-tailed fractional Pearson diffusions [PDF]

open access: yesStochastic Processes and their Applications, 2017
We define heavy-tailed fractional reciprocal gamma and Fisher-Snedecor diffusions by a non-Markovian time change in the corresponding Pearson diffusions. Pearson diffusions are governed by the backward Kolmogorov equations with space-varying polynomial coefficients and are widely used in applications.
Leonenko, Nikolai   +3 more
openaire   +5 more sources

Minimum of heavy-tailed random variables is not heavy tailed

open access: yesAIMS Mathematics, 2023
<abstract><p>By constructing an appropriate example, we show that the class of heavy-tailed distributions is not closed under minimum. We provide two independent heavy-tailed random variables, such that their minimum is not heavy tailed. In addition, we establish a few properties of the distributions considered in the example.</p></
Leipus, Remigijus   +2 more
openaire   +3 more sources

A Review of More than One Hundred Pareto-Tail Index Estimators

open access: yesStatistica, 2021
Heavy-tailed distributions are often encountered in economics, finance, biology, telecommunications, geology, etc. The heaviness of a tail is measured by a tail index. Numerous methods for tail index estimation have been proposed. This paper reviews more
Igor Fedotenkov
doaj   +1 more source

Bandits With Heavy Tail

open access: yesIEEE Transactions on Information Theory, 2013
The stochastic multi-armed bandit problem is well understood when the reward distributions are sub-Gaussian. In this paper we examine the bandit problem under the weaker assumption that the distributions have moments of order 1+ , for some $ \in (0,1]$. Surprisingly, moments of order 2 (i.e., finite variance) are sufficient to obtain regret bounds of
S. Bubeck, N. Cesa-Bianchi, G. Lugosi
openaire   +2 more sources

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