Publication

Heavy-tail Phenomena: Spatio-temporal Extremal Dependence

2014
Reports

Abstract

Heavy-tail phenomena are common in real-life data; the finance and insurance industries, telecommunications, and environment-related events offer typical examples of such phenomena. We focus on the particular topic of the extremogram, for which Davis and Mikosh (2009) present an empirical estimator. We propose the use of a semi-parametric model which allows extrapolation beyond the range of the data and flexible enough to cover any type of extremal dependence.

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2014
Reports

Abstract

Official source

Related concepts (17)

Semiparametric model

In statistics, a semiparametric model is a statistical model that has parametric and nonparametric components. A statistical model is a parameterized family of distributions: indexed by a parameter . A parametric model is a model in which the indexing parameter is a vector in -dimensional Euclidean space, for some nonnegative integer . Thus, is finite-dimensional, and . With a nonparametric model, the set of possible values of the parameter is a subset of some space , which is not necessarily finite-dimensional.

Parametric model

In statistics, a parametric model or parametric family or finite-dimensional model is a particular class of statistical models. Specifically, a parametric model is a family of probability distributions that has a finite number of parameters. A statistical model is a collection of probability distributions on some sample space. We assume that the collection, P, is indexed by some set Θ. The set Θ is called the parameter set or, more commonly, the parameter space.

Estimator

In statistics, an estimator is a rule for calculating an estimate of a given quantity based on observed data: thus the rule (the estimator), the quantity of interest (the estimand) and its result (the estimate) are distinguished. For example, the sample mean is a commonly used estimator of the population mean. There are point and interval estimators. The point estimators yield single-valued results. This is in contrast to an interval estimator, where the result would be a range of plausible values.

Related publications (1)

Heavy-tail Phenomena: Spatio-temporal Extremal Dependence

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