Dirichlet negative multinomial regression for overdispersed correlated count data
نویسندگان
چکیده
منابع مشابه
Dirichlet negative multinomial regression for overdispersed correlated count data
A generic random effects formulation for the Dirichlet negative multinomial distribution is developed together with a convenient regression parameterization. A simulation study indicates that, even when somewhat misspecified, regression models based on the Dirichlet negative multinomial distribution have smaller median absolute error than generalized estimating equations, with a particularly pr...
متن کاملQuantile regression for overdispersed count data: a hierarchical method
Generalized Poisson regression is commonly applied to overdispersed count data, and focused on modelling the conditional mean of the response. However, conditional mean regression models may be sensitive to response outliers and provide no information on other conditional distribution features of the response. We consider instead a hierarchical approach to quantile regression of overdispersed c...
متن کاملOn Hinde-Demetrio Regression Models for Overdispersed Count Data
In this paper we introduce the Hinde-Demétrio (HD) regression models for analyzing overdispersed count data and, mainly, investigate the e¤ect of dispersion parameter. The HD distributions are discrete additive exponential dispersion models (depending on canonical and dispersion parameters) with a third real index parameter p and have been characterized by its unit variance function + p. For p ...
متن کاملDeep Dirichlet Multinomial Regression
Dirichlet Multinomial Regression (DMR) and other supervised topic models can incorporate arbitrary document-level features to inform topic priors. However, their ability to model corpora are limited by the representation and selection of these features – a choice the topic modeler must make. Instead, we seek models that can learn the feature representations upon which to condition topic selecti...
متن کاملEstimation of Count Data using Bivariate Negative Binomial Regression Models
Abstract Negative binomial regression model (NBR) is a popular approach for modeling overdispersed count data with covariates. Several parameterizations have been performed for NBR, and the two well-known models, negative binomial-1 regression model (NBR-1) and negative binomial-2 regression model (NBR-2), have been applied. Another parameterization of NBR is negative binomial-P regression mode...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: Biostatistics
سال: 2012
ISSN: 1465-4644,1468-4357
DOI: 10.1093/biostatistics/kxs050