Fast Tail Index Estimation for Power Law Distributions in R

06/18/2020

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Power law distributions, in particular Pareto distributions, describe data across diverse areas of study. We have developed a package in R to estimate the tail index for such datasets focusing on speed (in particular with large datasets), keeping in mind ease of use, as well as accuracy. In this document, we provide a user guide to our package along with the results obtained highlighting the speed advantages of our package.

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Fast Tail Index Estimation for Power Law Distributions in R

The nonlinear distribution of employment across municipalities

On a minimum distance procedure for threshold selection in tail analysis

On a property of the inequality curve λ(p)

Scaling Properties of Human Brain Functional Networks

Maximum-likelihood fits of piece-wise Pareto distributions with finite and non-zero core

R package for producing beamplots as a preferred alternative to the h index when assessing single researchers (based on downloads from Web of Science)

SEIR-Campus: Modeling Infectious Diseases on University Campuses

Fast Tail Index Estimation for Power Law Distributions in R

Related Research

The nonlinear distribution of employment across municipalities

On a minimum distance procedure for threshold selection in tail analysis

On a property of the inequality curve λ(p)

Scaling Properties of Human Brain Functional Networks

Maximum-likelihood fits of piece-wise Pareto distributions with finite and non-zero core

R package for producing beamplots as a preferred alternative to the h index when assessing single researchers (based on downloads from Web of Science)

SEIR-Campus: Modeling Infectious Diseases on University Campuses