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Master's Dissertation
DOI
10.11606/D.45.2007.tde-14062007-103802
Document
Author
Full name
Cátia Petri
E-mail
Institute/School/College
Knowledge Area
Date of Defense
Published
São Paulo, 2007
Supervisor
Committee
Pereira, Carlos Alberto de Braganca (President)
Mazzon, Jose Afonso
Wechsler, Sergio
Title in Portuguese
Relação entre níveis de significância Bayesiano e freqüentista: e-value e p-value em tabelas de contingência
Keywords in Portuguese
integração numérica
otimização numérica
verossimilhança
Abstract in Portuguese
O FBST (Full Bayesian Significance Test) é um procedimento para testar hipóteses precisas, apresentado por Pereira e Stern (1999), e baseado no cálculo da probabilidade posterior do conjunto tangente ao conjunto que define a hipótese nula. Este procedimento é uma alternativa Bayesiana aos testes de significância usuais. Neste trabalho, estudamos a relação entre os resultados do FBST e de um teste freqüentista, o TRVG (Teste da Razão de Verossimilhanças Generalizado), através de alguns problemas clássicos de testes de hipóteses. Apresentamos, também, todos os procedimentos computacionais utilizados para a resolução automática dos dois testes para grandes amostras, necessária ao estudo da relação entre os testes.
Title in English
Relationship between Bayesian and frequentist significance tests: e-value and p-value in contingency tables
Keywords in English
likelihood
numerical integration
numerical optimization
Abstract in English
FBST (Full Bayesian Significance Test) is a procedure to test precise hypotheses, presented by Pereira and Stern (1999), which is based on the calculus of the posterior probability of the set tangent to the set that defines the null hypothesis. This procedure is a Bayesian alternative to the usual significance tests. In the present work we study the relation between the FBST's results and those of a frequentist test, GLRT (Generalised Likelihood Ratio Test) through some classical problems in hypotesis testing. We also present all computer procedures that compose the automatic solutions for applying FBST and GLRT on big samples what was necessary for studying the relation between both tests.
 
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TeseCatiaPetri.pdf (1.17 Mbytes)
Publishing Date
2007-09-27
 
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