Zobrazeno 1 - 10
of 47
pro vyhledávání: '"Thiago G. Ramires"'
Autor:
Thiago G. Ramires, Luiz R. Nakamura, Ana J. Righetto, Andréa C. Konrath, Carlos A. B. Pereira
Publikováno v:
Stats, Vol 4, Iss 4, Pp 916-930 (2021)
A method for statistical analysis of multimodal and/or highly distorted data is presented. The new methodology combines different clustering methods with the GAMLSS (generalized additive models for location, scale, and shape) framework, and is theref
Externí odkaz:
https://doaj.org/article/e18053fe1685454ea055a50ed91a0cc8
Autor:
Fernanda V. Roquim, Thiago G. Ramires, Luiz R. Nakamura, Ana J. Righetto, Renato R. Lima, Rayne A. Gomes
Publikováno v:
Semina: Ciências Exatas e Tecnológicas, Vol 42, Iss 2 (2021)
Generalized additive models for location, scale and shape (GAMLSS) are a very flexible statistical modeling framework, being an important generalization of the well-known generalized linear models and generalized additive models. Their main advantage
Externí odkaz:
https://doaj.org/article/e46893a8c70d4fe79bf3546d95777a97
Autor:
Thiago G. Ramires, Luiz R. Nakamura, Ana J. Righetto, Renan J. Carvalho, Lucas A. Vieira, Carlos A. B. Pereira
Publikováno v:
Entropy, Vol 23, Iss 4, p 469 (2021)
This paper presents a discussion regarding regression models, especially those belonging to the location class. Our main motivation is that, with simple distributions having simple interpretations, in some cases, one gets better results than the ones
Externí odkaz:
https://doaj.org/article/4c287ee33e274fb5a1c349107d59a122
Publikováno v:
Cadernos de Saúde Pública, Vol 34, Iss 1 (2018)
Renal insufficiency is a serious medical and public health problem worldwide. Recently, although many surveys have been developed to identify factors related to the lifetime of patients with renal insufficiency, controversial results from several stu
Externí odkaz:
https://doaj.org/article/8c235cb7505743b494f9e835aa9b10d2
Publikováno v:
Journal of Statistical Theory and Applications (JSTA), Vol 16, Iss 3 (2017)
First we introduce and study some general mathematical properties of a new generator of continuous distributions with two extra shape parameters called the odd generalized half-Cauchy family. A second goal, we introduce the new log-generalized odd ha
Externí odkaz:
https://doaj.org/article/dab44dcbd1db4765b470d37720ad099e
Publikováno v:
Statistics, Optimization and Information Computing
Repositório Institucional da USP (Biblioteca Digital da Produção Intelectual)
Universidade de São Paulo (USP)
instacron:USP
Repositório Institucional da USP (Biblioteca Digital da Produção Intelectual)
Universidade de São Paulo (USP)
instacron:USP
This study introduces a generalization of the odd power Cauchy family by adding one more shape parameter togain more flexibility modeling the complex data structures. The linear representations for the density, moments, quantile,and generating functi
Autor:
Morad Alizadeh, G.G. Hamedani, Haitham M. Yousof, Thiago G. Ramires, Indranil Ghosh, S. M. A. Jahanshahi
Publikováno v:
Journal of Data Science. 15:723-740
Publikováno v:
Journal of Data Science. 16:677-706
Autor:
Dimitrios Stasinopoulos, Robert A. Rigby, Thiago G. Ramires, Ana Julia Righetto, Josmar Mazucheli, Luiz Ricardo Nakamura, Rodrigo R. Pescim
Publikováno v:
Journal of Data Science. :96-110
One of the key features in regression models consists in selecting appropriate characteristics that explain the behavior of the response variable, in which stepwise-based procedures occupy a prominent position. In this paper we performed several simu
Autor:
Thiago G. Ramires, Ana Julia Righetto, Tábata Bergonci, Luiz Ricardo Nakamura, Elesandro Bornhofen
Publikováno v:
Repositório Institucional da USP (Biblioteca Digital da Produção Intelectual)
Universidade de São Paulo (USP)
instacron:USP
Universidade de São Paulo (USP)
instacron:USP
Different countries around the globe have different levels of vulnerability to risks because of several factors, e.g. degree of development, governance, infrastructure, among others. The probability of occurrence of certain risks as drought and unfav