• JoomlaWorks Simple Image Rotator
  • JoomlaWorks Simple Image Rotator
  • JoomlaWorks Simple Image Rotator
  • JoomlaWorks Simple Image Rotator
  • JoomlaWorks Simple Image Rotator
  • JoomlaWorks Simple Image Rotator
  • JoomlaWorks Simple Image Rotator
  • JoomlaWorks Simple Image Rotator
  • JoomlaWorks Simple Image Rotator
  • JoomlaWorks Simple Image Rotator
 
  Bookmark and Share
 
 
Master's Dissertation
DOI
https://doi.org/10.11606/D.45.2010.tde-16032015-181446
Document
Author
Full name
Thiago Feitosa Campos
E-mail
Institute/School/College
Knowledge Area
Date of Defense
Published
São Paulo, 2010
Supervisor
Committee
Branco, Marcia D Elia (President)
Garcia, Nancy Lopes
Machado, Fabio Prates
Title in Portuguese
Simulação perfeita da distribuição normal multivariada truncada
Keywords in Portuguese
Amostrador perfeito
CFTP
Distribuição multivariada truncada
Abstract in Portuguese
No presente trabalho apresentamos o algoritmo de simulacão perfeita CFTP, proposto em Propp & Wilson (1996). Seguindo o trabalho de Philippe & Robert (2003) implementamos o CFTP gerando amostras da distribuicão normal bivariada truncada no quadrante positivo. O algoritmo proposto e comparado com o amostrador de Gibbs e o método de rejeição. Finalmente, apresentamos sugestões para a implementação do CFTP para gerar amostras da distribuição normal truncada em dimensões maiores que dois e a geração de amostras em conjuntos diferente do quadrante positivo.
Title in English
Perfect simulation of the multivariate truncated normal distribution
Keywords in English
CFTP
Perfect sampler
Truncated multivariate distribution
Abstract in English
This project will display the CFTP perfect simulation algorithm presented at Propp & Wilson (1996). According to Philippe & Robert (2003) will be implemented the CFTP providing samples of the bivariate normal distribution truncated at the positive quadrant. The proposed algorithm is compared to the samples generated by Gibbs Sampler and by the rejection sampling ( or acceptance rejection method or "accept-reject algorithm"). Finally, suggestions to the implementation of CFTP in order to produce truncated normal distribution samples at bigger dimensions than two and the provide a diferent set of samples from the positive quadrant.
 
WARNING - Viewing this document is conditioned on your acceptance of the following terms of use:
This document is only for private use for research and teaching activities. Reproduction for commercial use is forbidden. This rights cover the whole data about this document as well as its contents. Any uses or copies of this document in whole or in part must include the author's name.
dissertacao.pdf (1.39 Mbytes)
Publishing Date
2015-03-18
 
WARNING: Learn what derived works are clicking here.
All rights of the thesis/dissertation are from the authors
CeTI-SC/STI
Digital Library of Theses and Dissertations of USP. Copyright © 2001-2024. All rights reserved.