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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Universidade Federal de Lavras
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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 |
work_keys_str_mv |
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