Results 41 to 50 of about 61,616 (135)

Bayesian threshold selection for extremal models using measures of surprise [PDF]

, 2014
Statistical extreme value theory is concerned with the use of asymptotically motivated models to describe the extreme values of a process. A number of commonly used models are valid for observed data that exceed some high threshold.
Fan, Y., Lee, J., Sisson, S. A.
core  

Divergence based Robust Estimation of the Tail Index through An Exponential Regression Model

, 2016
The extreme value theory is very popular in applied sciences including Finance, economics, hydrology and many other disciplines. In univariate extreme value theory, we model the data by a suitable distribution from the general max-domain of attraction ...
Ghosh, Abhik
core   +1 more source

Heavy tail robust estimation and inference for average treatment effects [PDF]

Econometric Reviews
We study the probability tail properties of Inverse probability weighting (IPW) estimators of the average treatment effect (ATE) when there is limited overlap between the covariate distributions of the treatment and control groups. Under unconfoundedness
Saraswata Chaudhuri, Jonathan B. Hill
semanticscholar   +1 more source

Extreme Value Inference for General Heterogeneous Data

Social Science Research Network
We extend extreme value statistics to independent data with possibly very different distributions. In particular, we present novel asymptotic normality results for the Hill estimator, which now estimates the extreme value index of the average ...
Yi He, J. Einmahl
semanticscholar   +1 more source

Test for Infinite Variance in Stock Returns [PDF]

, 2008
The existence of second order moment or the finite variance is a commonly used assumption in financial time series analysis. We examine the validation of this condition for main stock index return series by applying the extreme value theory.
YAN, Xian Ning
core   +1 more source

High-dimensional peaks-over-threshold inference

, 2017
Max-stable processes are increasingly widely used for modelling complex extreme events, but existing fitting methods are computationally demanding, limiting applications to a few dozen variables.
Davison, Anthony C., de Fondeville, Raphaël   +1 more
core   +1 more source

Inference for New Environmental Contours Using Extreme Value Analysis

Journal of Agricultural Biological and Environmental Statistics
Environmental contours are often used in engineering applications to describe risky combinations of variables according to some definition of an exceedance probability.
Emma S. Simpson, J. Tawn
semanticscholar   +1 more source

Likelihood Inference for Factor Copula Models with Asymmetric Tail Dependence

Entropy
For multivariate non-Gaussian involving copulas, likelihood inference is dominated by the data in the middle, and fitted models might not be very good for joint tail inference, such as assessing the strength of tail dependence.
Harry Joe, Xiaoting Li
semanticscholar   +1 more source

On Tail Index Estimation based on Multivariate Data

, 2014
This article is devoted to the study of tail index estimation based on i.i.d. multivariate observations, drawn from a standard heavy-tailed distribution, i.e. of which 1-d Pareto-like marginals share the same tail index.
Clémençon, Stéphan, Dematteo, Antoine
core   +1 more source

Asymptotic and bootstrap inference for inequality and poverty measures [PDF]

A random sample drawn from a population would appear to offer an ideal opportunity to use the bootstrap in order to perform accurate inference, since the observations of the sample are IID.
Emmanuel Flachaire, Russell Davidson
core