Externally studentized normal midrange distribution

ABSTRACT The distribution of externally studentized midrange was created based on the original studentization procedures of Student and was inspired in the distribution of the externally studentized range. The large use of the externally studentized range in multiple comparisons was also a motivatio...

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Main Authors: Ben Dêivide de Oliveira Batista, Daniel Furtado Ferreira, Lucas Monteiro Chaves
Format: Article
Language:English
Published: Universidade Federal de Lavras
Series:Ciência e Agrotecnologia
Subjects:
R.
Online Access:http://www.scielo.br/scielo.php?script=sci_arttext&pid=S1413-70542017000400378&lng=en&tlng=en
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spelling doaj-18b693502df147f4a83e858b8282a9982020-11-24T23:07:59ZengUniversidade Federal de LavrasCiência e Agrotecnologia1981-182941437838910.1590/1413-70542017414047716S1413-70542017000400378Externally studentized normal midrange distributionBen Dêivide de Oliveira BatistaDaniel Furtado FerreiraLucas Monteiro ChavesABSTRACT The distribution of externally studentized midrange was created based on the original studentization procedures of Student and was inspired in the distribution of the externally studentized range. The large use of the externally studentized range in multiple comparisons was also a motivation for developing this new distribution. This work aimed to derive analytic equations to distribution of the externally studentized midrange, obtaining the cumulative distribution, probability density and quantile functions and generating random values. This is a new distribution that the authors could not find any report in the literature. A second objective was to build an R package for obtaining numerically the probability density, cumulative distribution and quantile functions and make it available to the scientific community. The algorithms were proposed and implemented using Gauss-Legendre quadrature and the Newton-Raphson method in R software, resulting in the SMR package, available for download in the CRAN site. The implemented routines showed high accuracy proved by using Monte Carlo simulations and by comparing results with different number of quadrature points. Regarding to the precision to obtain the quantiles for cases where the degrees of freedom are close to 1 and the percentiles are close to 100%, it is recommended to use more than 64 quadrature points.http://www.scielo.br/scielo.php?script=sci_arttext&pid=S1413-70542017000400378&lng=en&tlng=enDistribution functiondensity functionGauss-Legendre quadratureNewton-Raphson methodR.
collection DOAJ
language English
format Article
sources DOAJ
author Ben Dêivide de Oliveira Batista
Daniel Furtado Ferreira
Lucas Monteiro Chaves
spellingShingle Ben Dêivide de Oliveira Batista
Daniel Furtado Ferreira
Lucas Monteiro Chaves
Externally studentized normal midrange distribution
Ciência e Agrotecnologia
Distribution function
density function
Gauss-Legendre quadrature
Newton-Raphson method
R.
author_facet Ben Dêivide de Oliveira Batista
Daniel Furtado Ferreira
Lucas Monteiro Chaves
author_sort Ben Dêivide de Oliveira Batista
title Externally studentized normal midrange distribution
title_short Externally studentized normal midrange distribution
title_full Externally studentized normal midrange distribution
title_fullStr Externally studentized normal midrange distribution
title_full_unstemmed Externally studentized normal midrange distribution
title_sort externally studentized normal midrange distribution
publisher Universidade Federal de Lavras
series Ciência e Agrotecnologia
issn 1981-1829
description ABSTRACT The distribution of externally studentized midrange was created based on the original studentization procedures of Student and was inspired in the distribution of the externally studentized range. The large use of the externally studentized range in multiple comparisons was also a motivation for developing this new distribution. This work aimed to derive analytic equations to distribution of the externally studentized midrange, obtaining the cumulative distribution, probability density and quantile functions and generating random values. This is a new distribution that the authors could not find any report in the literature. A second objective was to build an R package for obtaining numerically the probability density, cumulative distribution and quantile functions and make it available to the scientific community. The algorithms were proposed and implemented using Gauss-Legendre quadrature and the Newton-Raphson method in R software, resulting in the SMR package, available for download in the CRAN site. The implemented routines showed high accuracy proved by using Monte Carlo simulations and by comparing results with different number of quadrature points. Regarding to the precision to obtain the quantiles for cases where the degrees of freedom are close to 1 and the percentiles are close to 100%, it is recommended to use more than 64 quadrature points.
topic Distribution function
density function
Gauss-Legendre quadrature
Newton-Raphson method
R.
url http://www.scielo.br/scielo.php?script=sci_arttext&pid=S1413-70542017000400378&lng=en&tlng=en
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