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  2. Frequency of exceedance - Wikipedia

    en.wikipedia.org/wiki/Frequency_of_exceedance

    Thus, the mean time between peaks, including the residence time or mean time before the very first peak, is the inverse of the frequency of exceedance N −1 (y max). If the number of peaks exceeding y max grows as a Poisson process, then the probability that at time t there has not yet been any peak exceeding y max is e −N(y max)t. [6] Its ...

  3. Buffered probability of exceedance - Wikipedia

    en.wikipedia.org/wiki/Buffered_probability_of...

    The bPOE is the probability of a tail with known mean value . The figure shows the bPOE at threshold x {\displaystyle x} (marked in red) as the blue shaded area. Therefore, by definition, bPOE is equal to one minus the confidence level at which the Conditional Value at Risk (CVaR) is equal to x {\displaystyle x} .

  4. Generalized extreme value distribution - Wikipedia

    en.wikipedia.org/wiki/Generalized_extreme_value...

    In probability theory and statistics, the generalized extreme value (GEV) distribution [2] is a family of continuous probability distributions developed within extreme value theory to combine the Gumbel, Fréchet and Weibull families also known as type I, II and III extreme value distributions.

  5. File:High School Probability and Statistics Enrichment.pdf

    en.wikipedia.org/wiki/File:High_School...

    You are free: to share – to copy, distribute and transmit the work; to remix – to adapt the work; Under the following conditions: attribution – You must give appropriate credit, provide a link to the license, and indicate if changes were made.

  6. Extreme value theory - Wikipedia

    en.wikipedia.org/wiki/Extreme_value_theory

    Extreme value theory is used to model the risk of extreme, rare events, such as the 1755 Lisbon earthquake.. Extreme value theory or extreme value analysis (EVA) is the study of extremes in statistical distributions.

  7. Gumbel distribution - Wikipedia

    en.wikipedia.org/wiki/Gumbel_distribution

    Gumbel has also shown that the estimator r ⁄ (n+1) for the probability of an event — where r is the rank number of the observed value in the data series and n is the total number of observations — is an unbiased estimator of the cumulative probability around the mode of the distribution.

  8. Probability distribution fitting - Wikipedia

    en.wikipedia.org/wiki/Probability_distribution...

    An estimate of the uncertainty in the first and second case can be obtained with the binomial probability distribution using for example the probability of exceedance Pe (i.e. the chance that the event X is larger than a reference value Xr of X) and the probability of non-exceedance Pn (i.e. the chance that the event X is smaller than or equal ...

  9. Beneish M-score - Wikipedia

    en.wikipedia.org/wiki/Beneish_M-Score

    Beneish M-score is a probabilistic model, so it cannot detect companies that manipulate their earnings with 100% accuracy. Financial institutions were excluded from the sample in Beneish paper when calculating M-score since these institutions make money through different routes.

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