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  • Search: subject:"sparse contingency tables"
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Year of publication
Subject
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sparse contingency tables 4 Chi-Squared test 3 Theorie 3 independence test 3 local likelihood 3 local polynomial smoothers 3 nonparametric estimation 3 Išsklaidytos dažnių lentelės 2 Loglinear models 2 Logtiesiniai modeliai 2 Mathematics 2 Schätztheorie 2 Semiparametric smoothing 2 Semiparametrinis glodinimas 2 Sparse contingency tables 2 Statistischer Test 2 Theory 2 Arbeitsmarkt 1 Arbeitsmarktsegmentation 1 Atstitiktiniai Markovo laukai 1 Atstitiktinis Markovo laukas 1 Estimation theory 1 High-dimensional sparse contingency tables 1 Labor market 1 Labor matching map 1 Labour market segmentation 1 Markov field 1 Markov fields 1 Matching 1 Poisson models 1 Qualitative Methode 1 Qualitative method 1 Qualitatives Verfahren 1 Rasch models 1 Regional and occupational associations 1 Smoothing models 1 Spain 1 Spanien 1 Spanish labor market 1 Statistical test 1
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Online availability
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Free 4 Undetermined 2
Type of publication
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Book / Working Paper 5 Article 2
Type of publication (narrower categories)
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Thesis 2 Working Paper 2 Arbeitspapier 1 Article in journal 1 Aufsatz in Zeitschrift 1 Graue Literatur 1 Non-commercial literature 1
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Language
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English 5 Lithuanian 1 Undetermined 1
Author
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Abberger, Klaus 3 Bloznelis, Mindaugas 2 Dučinskas, Kęstutis 2 Eidukevičius, Rimantas 2 Kubilius, Kęstutis 2 Meilūnas, Mečislavas 2 Radavičius, Marijus 2 Rudzkis, Rimantas 2 Saulis, Leonas 2 Židanavičiūtė, Jurgita 2 Alvarez de Toledo, Pablo 1 Joe, Harry 1 Maydeu-Olivares, Alberto 1 Núñez, Fernando 1 Usabiaga Ibáñez, Carlos 1
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Institution
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Vilnius Gediminas Technical University 2 Zentrum für Finanzen und Ökonometrie, Fachbereich Wirtschaftswissenschaften 1
Published in...
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CoFE Discussion Paper 2 CoFE discussion papers 1 Economic modelling 1 Psychometrika 1
Source
All
BASE 2 ECONIS (ZBW) 2 RePEc 2 EconStor 1
Showing 1 - 7 of 7
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Matching in segmented labor markets : an analytical proposal based on high-dimensional contingency tables
Alvarez de Toledo, Pablo; Núñez, Fernando; Usabiaga … - In: Economic modelling 93 (2020), pp. 175-186
Persistent link: https://www.econbiz.de/10012430102
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Kategorinių požymių priklausomybių struktūros statistinė analizė ir jos taikymas genetikoje
Židanavičiūtė, Jurgita - 2010
Disertacijoje nagrinėjami kai kurie kategorinių požymių statistinės analizėsuždaviniai – ryšių struktūros bei modelio parinkimo ir jo parametrų įvertinimouždaviniai. Disertacijos tikslas – pasiūlyti ryšių struktūros tarp kategoriniųpožymių įvertinimo metodą tuo atveju,...
Persistent link: https://www.econbiz.de/10009478998
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Dependence Structure Analysis of Categorical Variables With Applications in Genetics
Židanavičiūtė, Jurgita - 2010
The dissertation considers some problems in the statistical analysis of categoricalvariables – the dependence structure between categorical variablesand the problems of selecting and assessing the models for this structure. Theaim of this dissertation is to propose the method to estimate...
Persistent link: https://www.econbiz.de/10009478999
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Smoothing ordered sparse contingency tables and the x2 test
Abberger, Klaus - 2002
To estimate cell probabilities for ordered sparse contingency tables several smoothing techniques have been …
Persistent link: https://www.econbiz.de/10011543900
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Smoothing ordered sparse contingency tables and the Chi-Squared test
Abberger, Klaus - 2002
To estimate cell probabilities for ordered sparse contingency tables several smooth- ing techniques have been …
Persistent link: https://www.econbiz.de/10010324053
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A General Family of Limited Information Goodness-of-Fit Statistics for Multinomial Data
Joe, Harry; Maydeu-Olivares, Alberto - In: Psychometrika 75 (2010) 3, pp. 393-419
Persistent link: https://www.econbiz.de/10008674007
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Smoothing ordered sparse contingency tables and the Chi-Squared test
Abberger, Klaus - Zentrum für Finanzen und Ökonometrie, Fachbereich … - 2002
To estimate cell probabilities for ordered sparse contingency tables several smooth- ing techniques have been …
Persistent link: https://www.econbiz.de/10005741213
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