Zobrazeno 1 - 10
of 174
pro vyhledávání: '"Wagner, Hugo"'
This article describes the R package htmcglm implemented for performing hypothesis tests on regression and dispersion parameters of multivariate covariance generalized linear models (McGLMs). McGLMs provide a general statistical modeling framework fo
Externí odkaz:
http://arxiv.org/abs/2208.01568
Autor:
de Freitas, Lineu Alberto Cavazani, Carlos, Ligia de Oliveira, Campos, Antônio Carlos Ligocki, Bonat, Wagner Hugo
Clinical trials are common in medical research where multiple non-Gaussian responses and time-dependent observations are frequent. The analysis of data from these studies requires statistical modeling techniques that take these characteristics into a
Externí odkaz:
http://arxiv.org/abs/2208.00027
Autor:
da Silva, Guilherme Parreira, Laureano, Henrique Aparecido, Petterle, Ricardo Rasmussen, Júnior, Paulo Justiniano Ribeiro, Bonat, Wagner Hugo
Researchers are often interested in understanding the relationship between a set of covariates and a set of response variables. To achieve this goal, the use of regression analysis, either linear or generalized linear models, is largely applied. Howe
Externí odkaz:
http://arxiv.org/abs/2205.10486
Autor:
Guilherme Parreira da Silva, Henrique Aparecido Laureano, Ricardo Rasmussen Petterle, Paulo Justiniano Ribeiro Júnior, Wagner Hugo Bonat
Publikováno v:
Austrian Journal of Statistics, Vol 53, Iss 1 (2024)
Univariate regression models have rich literature for counting data. However, this is not the case for multivariate count data. Therefore, we present the Multivariate Generalized Linear Mixed Models framework that deals with a multivariate set of res
Externí odkaz:
https://doaj.org/article/967f2bbcb5564896a2e8677f84387e4e
We propose a model-based geostatistical approach to deal with regionalized compositions. We combine the additive-log-ratio transformation with multivariate geostatistical models whose covariance matrix is adapted to take into account the correlation
Externí odkaz:
http://arxiv.org/abs/1606.06522
Autor:
Bonat, Wagner Hugo, Jørgensen, Bent
We propose a general framework for non-normal multivariate data analysis called multivariate covariance generalized linear models (McGLMs), designed to handle multivariate response variables, along with a wide range of temporal and spatial correlatio
Externí odkaz:
http://arxiv.org/abs/1504.01551
Generalized linear mixed models (GLMM) encompass large class of statistical models, with a vast range of applications areas. GLMM extends the linear mixed models allowing for different types of response variable. Three most common data types are cont
Externí odkaz:
http://arxiv.org/abs/1401.2957
Publikováno v:
Journal of Agricultural, Biological, and Environmental Statistics, 2019 Jun 01. 24(2), 346-368.
Externí odkaz:
https://www.jstor.org/stable/48702921
Autor:
Zeviani, Walmes Marques, Ribeiro Jr., Paulo Justiniano, Bonat, Wagner Hugo, Shimakura, Silvia Emiko, Muniz, Joel Augusti
Event counts are response variables with non-negative integer values representing the number of times that an event occurs within a fixed domain such as a time interval, a geographical area or a cell of a contingency table. Analysis of counts by Gaus
Externí odkaz:
http://arxiv.org/abs/1312.2423