Finite sample behaviour of classical and quantile regression estimators for the Pareto distribution

Frederico Caeiro; Ana P. Martins; Inês J. Sequeira

doi:10.1063/1.4912753

Finite sample behaviour of classical and quantile regression estimators for the Pareto distribution

Frederico Caeiro, Ana P. Martins, Inês J. Sequeira

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

4 Citations (Scopus)

Abstract

The Pareto distribution is a well known and important model in Statistics. It has been used to study large incomes, city population size, size of losses, stock price fluctuations, number of citations received by papers and other similar phenomena. In this work we compare the finite sample performance of several estimation methods, namely the Moment, Maximum Likelihood and Quantile Regression methods. The comparison will be made through a Monte-Carlo simulation study.

Original language	English
Title of host publication	Proceedings of the International Conference on Numerical Analysis and Applied Mathematics 2014, ICNAAM 2014
Publisher	AIP - American Institute of Physics
Volume	1648
ISBN (Electronic)	978-0-7354-1287-3
DOIs	https://doi.org/10.1063/1.4912753
Publication status	Published - 10 Mar 2015
Event	International Conference on Numerical Analysis and Applied Mathematics 2014, ICNAAM 2014 - Rhodes, Greece Duration: 22 Sept 2014 → 28 Sept 2014

Conference

Conference	International Conference on Numerical Analysis and Applied Mathematics 2014, ICNAAM 2014
Country/Territory	Greece
City	Rhodes
Period	22/09/14 → 28/09/14

Keywords

Maximum likelihood estimator
Moment estimator
Monte-Carlo method
Pareto distribution
Quantile regression estimator

Access to Document

10.1063/1.4912753Licence: Unspecified

Cite this

@inproceedings{c724f9ce2f21441fbcf247bb87b38b79,

title = "Finite sample behaviour of classical and quantile regression estimators for the Pareto distribution",

abstract = "The Pareto distribution is a well known and important model in Statistics. It has been used to study large incomes, city population size, size of losses, stock price fluctuations, number of citations received by papers and other similar phenomena. In this work we compare the finite sample performance of several estimation methods, namely the Moment, Maximum Likelihood and Quantile Regression methods. The comparison will be made through a Monte-Carlo simulation study.",

keywords = "Maximum likelihood estimator, Moment estimator, Monte-Carlo method, Pareto distribution, Quantile regression estimator",

author = "Frederico Caeiro and Martins, {Ana P.} and Sequeira, {In{\^e}s J.}",

note = "sem pdf conforme despacho; International Conference on Numerical Analysis and Applied Mathematics 2014, ICNAAM 2014 ; Conference date: 22-09-2014 Through 28-09-2014",

year = "2015",

month = mar,

day = "10",

doi = "10.1063/1.4912753",

language = "English",

volume = "1648",

booktitle = "Proceedings of the International Conference on Numerical Analysis and Applied Mathematics 2014, ICNAAM 2014",

publisher = "AIP - American Institute of Physics",

address = "United States",

}

Caeiro, F, Martins, AP & Sequeira, IJ 2015, Finite sample behaviour of classical and quantile regression estimators for the Pareto distribution. in Proceedings of the International Conference on Numerical Analysis and Applied Mathematics 2014, ICNAAM 2014. vol. 1648, 540007, AIP - American Institute of Physics, International Conference on Numerical Analysis and Applied Mathematics 2014, ICNAAM 2014, Rhodes, Greece, 22/09/14. https://doi.org/10.1063/1.4912753

Finite sample behaviour of classical and quantile regression estimators for the Pareto distribution. / Caeiro, Frederico; Martins, Ana P.; Sequeira, Inês J.
Proceedings of the International Conference on Numerical Analysis and Applied Mathematics 2014, ICNAAM 2014. Vol. 1648 AIP - American Institute of Physics, 2015. 540007.

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

TY - GEN

T1 - Finite sample behaviour of classical and quantile regression estimators for the Pareto distribution

AU - Caeiro, Frederico

AU - Martins, Ana P.

AU - Sequeira, Inês J.

N1 - sem pdf conforme despacho

PY - 2015/3/10

Y1 - 2015/3/10

N2 - The Pareto distribution is a well known and important model in Statistics. It has been used to study large incomes, city population size, size of losses, stock price fluctuations, number of citations received by papers and other similar phenomena. In this work we compare the finite sample performance of several estimation methods, namely the Moment, Maximum Likelihood and Quantile Regression methods. The comparison will be made through a Monte-Carlo simulation study.

AB - The Pareto distribution is a well known and important model in Statistics. It has been used to study large incomes, city population size, size of losses, stock price fluctuations, number of citations received by papers and other similar phenomena. In this work we compare the finite sample performance of several estimation methods, namely the Moment, Maximum Likelihood and Quantile Regression methods. The comparison will be made through a Monte-Carlo simulation study.

KW - Maximum likelihood estimator

KW - Moment estimator

KW - Monte-Carlo method

KW - Pareto distribution

KW - Quantile regression estimator

UR - http://www.scopus.com/inward/record.url?scp=84939648344&partnerID=8YFLogxK

U2 - 10.1063/1.4912753

DO - 10.1063/1.4912753

M3 - Conference contribution

AN - SCOPUS:84939648344

VL - 1648

BT - Proceedings of the International Conference on Numerical Analysis and Applied Mathematics 2014, ICNAAM 2014

PB - AIP - American Institute of Physics

T2 - International Conference on Numerical Analysis and Applied Mathematics 2014, ICNAAM 2014

Y2 - 22 September 2014 through 28 September 2014

ER -

Finite sample behaviour of classical and quantile regression estimators for the Pareto distribution

Abstract

Conference

Keywords

Access to Document

Other files and links

Fingerprint

Cite this