Equalden.HD-package: Package Equalden.HD
In Equalden.HD: Testing the Equality of a High Dimensional Set of Densities
Description
Details
Value
Acknowledgements
Author(s)
References
Description
This package implements three different methods to test the null hypothesis that a large number k of
samples have a common density. The sample size can be as small as 2. These methods are particularly
well suited to the low sample size, high dimensional setting (n << k). The first method, proposed by
Zhan and Hart (2012), was developed to test the null hypothesis when the samples are independent of
each other. The other tests, proposed by Cousido-Rocha et al. (2018), are adaptations of the test in Zhan
and Hart (2012) for the setting in which the samples are weakly dependent. The standarized version of
each test statistic and its p-value are computed among other things.
Details
Package: Equalden.HD
Version: 1.2
Maintainer: Marta Cousido Rocha martacousido@uvigo.es
License: GPL-2
Value
Equalden.test.HD: Performs the k-sample test proposed in Zhan and Hart (2012) for the setting of low sample size, large
dimension and independent samples, and its adaptions to dependent samples proposed in Cousido-Rocha
et. al (2018).
Acknowledgements
This work has received financial support of the Call 2015 Grants for
PhD contracts for training of doctors of the Ministry of Economy and Competitiveness,
co-financed by the European Social Fund (Ref. BES-2015-074958).
The authors acknowledge support from MTM2014-55966-P project, Ministry of Economy and
Competitiveness, and MTM2017-89422-P project, Ministry of Economy, Industry
and Competitiveness, State Research Agency, and Regional Development Fund, UE.
The authors also acknowledge the financial support provided by the SiDOR research group
through the grant Competitive Reference Group, 2016-2019 (ED431C 2016/040),
funded by the “Conseller<c3><ad>a de Cultura, Educaci<c3><b3>n e Ordenaci<c3><b3>n Universitaria.
Xunta de Galicia”. Jos<c3><a9> Carlos Soage was supported by Red Tecnol<c3><b3>gica de
Matem<c3><a1>tica Industrial (Red TMATI), Cons. de Cultura, Educaci<c3><b3>n e OU, Xunta de Galicia
(ED341D R2016/051) and by Grupos de Referencia Competitiva, Consolidaci<c3><b3>n y
Estructuraci<c3><b3>n de Unidades de Investigaci<c3><b3>n Competitivas del SUG, Cons. de Cultura,
Educaci<c3><b3>n e OU, Xunta de Galicia (GRC ED431C 2016/040).
Author(s)
Cousido Rocha, Marta.
Soage Gonz<c3><a1>lez, Jos<c3><a9> Carlos.
de U<c3><b1>a-<c3><81>lvarez, Jacobo.
D. Hart, Jeffrey.
References
Cousido-Rocha, M., de U<c3><b1>a-<c3><81>lvarez, J., and Hart, J.(2018). Testing equality of a large number of densities under mixing conditions. Preprint.
Zhan, D., Hart, J. (2012). Testing equality of a large number of densities. Biometrika, 99, 1-17.
Equalden.HD documentation built on May 2, 2019, 11:33 a.m.
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Description Details Value Acknowledgements Author(s) References
Description
This package implements three different methods to test the null hypothesis that a large number k of samples have a common density. The sample size can be as small as 2. These methods are particularly well suited to the low sample size, high dimensional setting (n << k). The first method, proposed by Zhan and Hart (2012), was developed to test the null hypothesis when the samples are independent of each other. The other tests, proposed by Cousido-Rocha et al. (2018), are adaptations of the test in Zhan and Hart (2012) for the setting in which the samples are weakly dependent. The standarized version of each test statistic and its p-value are computed among other things.
Details
Package: Equalden.HD
Version: 1.2
Maintainer: Marta Cousido Rocha martacousido@uvigo.es
License: GPL-2
Value
Equalden.test.HD: Performs the k-sample test proposed in Zhan and Hart (2012) for the setting of low sample size, large dimension and independent samples, and its adaptions to dependent samples proposed in Cousido-Rocha et. al (2018).
Acknowledgements
This work has received financial support of the Call 2015 Grants for PhD contracts for training of doctors of the Ministry of Economy and Competitiveness, co-financed by the European Social Fund (Ref. BES-2015-074958). The authors acknowledge support from MTM2014-55966-P project, Ministry of Economy and Competitiveness, and MTM2017-89422-P project, Ministry of Economy, Industry and Competitiveness, State Research Agency, and Regional Development Fund, UE. The authors also acknowledge the financial support provided by the SiDOR research group through the grant Competitive Reference Group, 2016-2019 (ED431C 2016/040), funded by the “Conseller<c3><ad>a de Cultura, Educaci<c3><b3>n e Ordenaci<c3><b3>n Universitaria. Xunta de Galicia”. Jos<c3><a9> Carlos Soage was supported by Red Tecnol<c3><b3>gica de Matem<c3><a1>tica Industrial (Red TMATI), Cons. de Cultura, Educaci<c3><b3>n e OU, Xunta de Galicia (ED341D R2016/051) and by Grupos de Referencia Competitiva, Consolidaci<c3><b3>n y Estructuraci<c3><b3>n de Unidades de Investigaci<c3><b3>n Competitivas del SUG, Cons. de Cultura, Educaci<c3><b3>n e OU, Xunta de Galicia (GRC ED431C 2016/040).
Author(s)
Cousido Rocha, Marta.
Soage Gonz<c3><a1>lez, Jos<c3><a9> Carlos.
de U<c3><b1>a-<c3><81>lvarez, Jacobo.
D. Hart, Jeffrey.
References
Cousido-Rocha, M., de U<c3><b1>a-<c3><81>lvarez, J., and Hart, J.(2018). Testing equality of a large number of densities under mixing conditions. Preprint.
Zhan, D., Hart, J. (2012). Testing equality of a large number of densities. Biometrika, 99, 1-17.
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