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Linganisha mbinu

Pitia mbinu ulizochagua bega kwa bega; safu zinazotofautiana zinaangaziwa.

Nadharia ya Thamani Iliyokithiri (EVT)×Nadharia ya Anguko×
NyanjaFedhaSayansi ya Aktuaria
FamiliaRegression modelRegression model
Mwaka wa asili20012010
MwanzilishiColes (textbook treatment); McNeil, Frey & EmbrechtsFilip Lundberg; Harald Cramér
AinaTail / extreme-event modelStochastic risk process model
Chanzo asiliaColes, S. (2001). An Introduction to Statistical Modeling of Extreme Values. Springer. ISBN: 978-1852334598Asmussen, S., & Albrecher, H. (2010). Ruin Probabilities (2nd ed.). World Scientific. ISBN: 978-981-4282-52-9
Majina mbadalaEVT, generalized extreme value, generalized Pareto distribution, peaks over thresholdCollective Risk Theory, Cramér-Lundberg Theory, Probability of Ruin Analysis, Hasar Süreci Çöküş Teorisi
Zinazohusiana53
MuhtasariExtreme Value Theory is a statistical framework for modelling the rare events that live in the tail of a probability distribution. As developed in Coles (2001) and applied to risk by McNeil, Frey & Embrechts (2005), it offers two standard routes: the Generalized Extreme Value (GEV) distribution for block maxima and the Generalized Pareto Distribution (GPD), used in the peaks-over-threshold approach, for exceedances above a high threshold.Ruin Theory models the stochastic surplus process of an insurance company to quantify the probability that accumulated losses eventually exceed available capital. Introduced by Filip Lundberg in his 1903 doctoral thesis and rigorously unified by Harald Cramér in 1930, the classical Cramér-Lundberg model assumes premiums arrive at a constant rate, claims follow a compound Poisson process, and individual claim sizes are independent and identically distributed. It remains the foundational framework of collective risk theory in actuarial science.
ScholarGateSeti ya data
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  2. 2 Vyanzo
  3. PUBLISHED
  1. v1
  2. 1 Vyanzo
  3. PUBLISHED

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ScholarGateLinganisha mbinu: Extreme Value Theory · Ruin Theory. Imepatikana 2026-06-20 kutoka https://scholargate.app/sw/compare