Robust Procedures for Estimating and Testing in the Framework of Divergence Measures

The scope of the contributions to this book will be to present new and original research papers based on MPHIE, MHD, and MDPDE, as well as test statistics based on these estimators from a theoretical and applied point of view in different statistical problems with special emphasis on robustness. Man...

Full description

Saved in:
Bibliographic Details
HerausgeberIn:
Sonstige:
Year of Publication:2021
Language:English
Physical Description:1 electronic resource (333 p.)
Tags: Add Tag
No Tags, Be the first to tag this record!
id 993546054204498
ctrlnum (CKB)5400000000044731
(oapen)https://directory.doabooks.org/handle/20.500.12854/76875
(EXLCZ)995400000000044731
collection bib_alma
record_format marc
spelling Pardo, Leandro edt
Robust Procedures for Estimating and Testing in the Framework of Divergence Measures
Basel, Switzerland MDPI - Multidisciplinary Digital Publishing Institute 2021
1 electronic resource (333 p.)
text txt rdacontent
computer c rdamedia
online resource cr rdacarrier
The scope of the contributions to this book will be to present new and original research papers based on MPHIE, MHD, and MDPDE, as well as test statistics based on these estimators from a theoretical and applied point of view in different statistical problems with special emphasis on robustness. Manuscripts given solutions to different statistical problems as model selection criteria based on divergence measures or in statistics for high-dimensional data with divergence measures as loss function are considered. Reviews making emphasis in the most recent state-of-the art in relation to the solution of statistical problems base on divergence measures are also presented.
English
Research & information: general bicssc
classification
Bayes error rate
Henze-Penrose divergence
Friedman-Rafsky test statistic
convergence rates
bias and variance trade-off
concentration bounds
minimal spanning trees
composite likelihood
composite minimum density power divergence estimators
model selection
minimum pseudodistance estimation
Robustness
estimation of α
monitoring
numerical minimization
S-estimation
Tukey's biweight
integer-valued time series
one-parameter exponential family
minimum density power divergence estimator
density power divergence
robust change point test
Galton-Watson branching processes with immigration
Hellinger integrals
power divergences
Kullback-Leibler information distance/divergence
relative entropy
Renyi divergences
epidemiology
COVID-19 pandemic
Bayesian decision making
INARCH(1) model
GLM model
Bhattacharyya coefficient/distance
time series of counts
INGARCH model
SPC
CUSUM monitoring
MDPDE
contingency tables
disparity
mixed-scale data
pearson residuals
residual adjustment function
robustness
statistical distances
Hellinger distance
large deviations
divergence measures
rare event probabilities
3-0365-1460-0
3-0365-1459-7
Martin, Nirian edt
Pardo, Leandro oth
Martin, Nirian oth
language English
format eBook
author2 Martin, Nirian
Pardo, Leandro
Martin, Nirian
author_facet Martin, Nirian
Pardo, Leandro
Martin, Nirian
author2_variant l p lp
n m nm
author2_role HerausgeberIn
Sonstige
Sonstige
title Robust Procedures for Estimating and Testing in the Framework of Divergence Measures
spellingShingle Robust Procedures for Estimating and Testing in the Framework of Divergence Measures
title_full Robust Procedures for Estimating and Testing in the Framework of Divergence Measures
title_fullStr Robust Procedures for Estimating and Testing in the Framework of Divergence Measures
title_full_unstemmed Robust Procedures for Estimating and Testing in the Framework of Divergence Measures
title_auth Robust Procedures for Estimating and Testing in the Framework of Divergence Measures
title_new Robust Procedures for Estimating and Testing in the Framework of Divergence Measures
title_sort robust procedures for estimating and testing in the framework of divergence measures
publisher MDPI - Multidisciplinary Digital Publishing Institute
publishDate 2021
physical 1 electronic resource (333 p.)
isbn 3-0365-1460-0
3-0365-1459-7
illustrated Not Illustrated
work_keys_str_mv AT pardoleandro robustproceduresforestimatingandtestingintheframeworkofdivergencemeasures
AT martinnirian robustproceduresforestimatingandtestingintheframeworkofdivergencemeasures
status_str n
ids_txt_mv (CKB)5400000000044731
(oapen)https://directory.doabooks.org/handle/20.500.12854/76875
(EXLCZ)995400000000044731
carrierType_str_mv cr
is_hierarchy_title Robust Procedures for Estimating and Testing in the Framework of Divergence Measures
author2_original_writing_str_mv noLinkedField
noLinkedField
noLinkedField
_version_ 1787548734708514816
fullrecord <?xml version="1.0" encoding="UTF-8"?><collection xmlns="http://www.loc.gov/MARC21/slim"><record><leader>03631nam-a2200925z--4500</leader><controlfield tag="001">993546054204498</controlfield><controlfield tag="005">20231214133131.0</controlfield><controlfield tag="006">m o d </controlfield><controlfield tag="007">cr|mn|---annan</controlfield><controlfield tag="008">202201s2021 xx |||||o ||| 0|eng d</controlfield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(CKB)5400000000044731</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(oapen)https://directory.doabooks.org/handle/20.500.12854/76875</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(EXLCZ)995400000000044731</subfield></datafield><datafield tag="041" ind1="0" ind2=" "><subfield code="a">eng</subfield></datafield><datafield tag="100" ind1="1" ind2=" "><subfield code="a">Pardo, Leandro</subfield><subfield code="4">edt</subfield></datafield><datafield tag="245" ind1="1" ind2="0"><subfield code="a">Robust Procedures for Estimating and Testing in the Framework of Divergence Measures</subfield></datafield><datafield tag="260" ind1=" " ind2=" "><subfield code="a">Basel, Switzerland</subfield><subfield code="b">MDPI - Multidisciplinary Digital Publishing Institute</subfield><subfield code="c">2021</subfield></datafield><datafield tag="300" ind1=" " ind2=" "><subfield code="a">1 electronic resource (333 p.)</subfield></datafield><datafield tag="336" ind1=" " ind2=" "><subfield code="a">text</subfield><subfield code="b">txt</subfield><subfield code="2">rdacontent</subfield></datafield><datafield tag="337" ind1=" " ind2=" "><subfield code="a">computer</subfield><subfield code="b">c</subfield><subfield code="2">rdamedia</subfield></datafield><datafield tag="338" ind1=" " ind2=" "><subfield code="a">online resource</subfield><subfield code="b">cr</subfield><subfield code="2">rdacarrier</subfield></datafield><datafield tag="520" ind1=" " ind2=" "><subfield code="a">The scope of the contributions to this book will be to present new and original research papers based on MPHIE, MHD, and MDPDE, as well as test statistics based on these estimators from a theoretical and applied point of view in different statistical problems with special emphasis on robustness. Manuscripts given solutions to different statistical problems as model selection criteria based on divergence measures or in statistics for high-dimensional data with divergence measures as loss function are considered. Reviews making emphasis in the most recent state-of-the art in relation to the solution of statistical problems base on divergence measures are also presented.</subfield></datafield><datafield tag="546" ind1=" " ind2=" "><subfield code="a">English</subfield></datafield><datafield tag="650" ind1=" " ind2="7"><subfield code="a">Research &amp; information: general</subfield><subfield code="2">bicssc</subfield></datafield><datafield tag="653" ind1=" " ind2=" "><subfield code="a">classification</subfield></datafield><datafield tag="653" ind1=" " ind2=" "><subfield code="a">Bayes error rate</subfield></datafield><datafield tag="653" ind1=" " ind2=" "><subfield code="a">Henze-Penrose divergence</subfield></datafield><datafield tag="653" ind1=" " ind2=" "><subfield code="a">Friedman-Rafsky test statistic</subfield></datafield><datafield tag="653" ind1=" " ind2=" "><subfield code="a">convergence rates</subfield></datafield><datafield tag="653" ind1=" " ind2=" "><subfield code="a">bias and variance trade-off</subfield></datafield><datafield tag="653" ind1=" " ind2=" "><subfield code="a">concentration bounds</subfield></datafield><datafield tag="653" ind1=" " ind2=" "><subfield code="a">minimal spanning trees</subfield></datafield><datafield tag="653" ind1=" " ind2=" "><subfield code="a">composite likelihood</subfield></datafield><datafield tag="653" ind1=" " ind2=" "><subfield code="a">composite minimum density power divergence estimators</subfield></datafield><datafield tag="653" ind1=" " ind2=" "><subfield code="a">model selection</subfield></datafield><datafield tag="653" ind1=" " ind2=" "><subfield code="a">minimum pseudodistance estimation</subfield></datafield><datafield tag="653" ind1=" " ind2=" "><subfield code="a">Robustness</subfield></datafield><datafield tag="653" ind1=" " ind2=" "><subfield code="a">estimation of α</subfield></datafield><datafield tag="653" ind1=" " ind2=" "><subfield code="a">monitoring</subfield></datafield><datafield tag="653" ind1=" " ind2=" "><subfield code="a">numerical minimization</subfield></datafield><datafield tag="653" ind1=" " ind2=" "><subfield code="a">S-estimation</subfield></datafield><datafield tag="653" ind1=" " ind2=" "><subfield code="a">Tukey's biweight</subfield></datafield><datafield tag="653" ind1=" " ind2=" "><subfield code="a">integer-valued time series</subfield></datafield><datafield tag="653" ind1=" " ind2=" "><subfield code="a">one-parameter exponential family</subfield></datafield><datafield tag="653" ind1=" " ind2=" "><subfield code="a">minimum density power divergence estimator</subfield></datafield><datafield tag="653" ind1=" " ind2=" "><subfield code="a">density power divergence</subfield></datafield><datafield tag="653" ind1=" " ind2=" "><subfield code="a">robust change point test</subfield></datafield><datafield tag="653" ind1=" " ind2=" "><subfield code="a">Galton-Watson branching processes with immigration</subfield></datafield><datafield tag="653" ind1=" " ind2=" "><subfield code="a">Hellinger integrals</subfield></datafield><datafield tag="653" ind1=" " ind2=" "><subfield code="a">power divergences</subfield></datafield><datafield tag="653" ind1=" " ind2=" "><subfield code="a">Kullback-Leibler information distance/divergence</subfield></datafield><datafield tag="653" ind1=" " ind2=" "><subfield code="a">relative entropy</subfield></datafield><datafield tag="653" ind1=" " ind2=" "><subfield code="a">Renyi divergences</subfield></datafield><datafield tag="653" ind1=" " ind2=" "><subfield code="a">epidemiology</subfield></datafield><datafield tag="653" ind1=" " ind2=" "><subfield code="a">COVID-19 pandemic</subfield></datafield><datafield tag="653" ind1=" " ind2=" "><subfield code="a">Bayesian decision making</subfield></datafield><datafield tag="653" ind1=" " ind2=" "><subfield code="a">INARCH(1) model</subfield></datafield><datafield tag="653" ind1=" " ind2=" "><subfield code="a">GLM model</subfield></datafield><datafield tag="653" ind1=" " ind2=" "><subfield code="a">Bhattacharyya coefficient/distance</subfield></datafield><datafield tag="653" ind1=" " ind2=" "><subfield code="a">time series of counts</subfield></datafield><datafield tag="653" ind1=" " ind2=" "><subfield code="a">INGARCH model</subfield></datafield><datafield tag="653" ind1=" " ind2=" "><subfield code="a">SPC</subfield></datafield><datafield tag="653" ind1=" " ind2=" "><subfield code="a">CUSUM monitoring</subfield></datafield><datafield tag="653" ind1=" " ind2=" "><subfield code="a">MDPDE</subfield></datafield><datafield tag="653" ind1=" " ind2=" "><subfield code="a">contingency tables</subfield></datafield><datafield tag="653" ind1=" " ind2=" "><subfield code="a">disparity</subfield></datafield><datafield tag="653" ind1=" " ind2=" "><subfield code="a">mixed-scale data</subfield></datafield><datafield tag="653" ind1=" " ind2=" "><subfield code="a">pearson residuals</subfield></datafield><datafield tag="653" ind1=" " ind2=" "><subfield code="a">residual adjustment function</subfield></datafield><datafield tag="653" ind1=" " ind2=" "><subfield code="a">robustness</subfield></datafield><datafield tag="653" ind1=" " ind2=" "><subfield code="a">statistical distances</subfield></datafield><datafield tag="653" ind1=" " ind2=" "><subfield code="a">Hellinger distance</subfield></datafield><datafield tag="653" ind1=" " ind2=" "><subfield code="a">large deviations</subfield></datafield><datafield tag="653" ind1=" " ind2=" "><subfield code="a">divergence measures</subfield></datafield><datafield tag="653" ind1=" " ind2=" "><subfield code="a">rare event probabilities</subfield></datafield><datafield tag="776" ind1=" " ind2=" "><subfield code="z">3-0365-1460-0</subfield></datafield><datafield tag="776" ind1=" " ind2=" "><subfield code="z">3-0365-1459-7</subfield></datafield><datafield tag="700" ind1="1" ind2=" "><subfield code="a">Martin, Nirian</subfield><subfield code="4">edt</subfield></datafield><datafield tag="700" ind1="1" ind2=" "><subfield code="a">Pardo, Leandro</subfield><subfield code="4">oth</subfield></datafield><datafield tag="700" ind1="1" ind2=" "><subfield code="a">Martin, Nirian</subfield><subfield code="4">oth</subfield></datafield><datafield tag="906" ind1=" " ind2=" "><subfield code="a">BOOK</subfield></datafield><datafield tag="ADM" ind1=" " ind2=" "><subfield code="b">2023-12-15 05:43:35 Europe/Vienna</subfield><subfield code="f">system</subfield><subfield code="c">marc21</subfield><subfield code="a">2022-04-04 09:22:53 Europe/Vienna</subfield><subfield code="g">false</subfield></datafield><datafield tag="AVE" ind1=" " ind2=" "><subfield code="i">DOAB Directory of Open Access Books</subfield><subfield code="P">DOAB Directory of Open Access Books</subfield><subfield code="x">https://eu02.alma.exlibrisgroup.com/view/uresolver/43ACC_OEAW/openurl?u.ignore_date_coverage=true&amp;portfolio_pid=5338128820004498&amp;Force_direct=true</subfield><subfield code="Z">5338128820004498</subfield><subfield code="b">Available</subfield><subfield code="8">5338128820004498</subfield></datafield></record></collection>