Common approaches to monotonic regression focus on the case of a unidimensional covariate and continuous dependent … based on AIC-type measures. The method is applied to several data sets. -- monotonic regression ; additive models …

In this paper we consider regression models for count data allowing for overdispersion in a Bayesian framework. Besides … autoregressive prior based on Pettitt et al. (2002). Apart from the Poisson regression model, the negative binomial and the … generalized Poisson regression model are addressed. Further, zero-inflated models combined with the Poisson and generalized …

(2004b) show that by data augmentation via the introduction of two sequences of latent variables a Poisson regression model … can be transformed into a normal linear model. We show how this methodology can be extended to spatial Poisson regression …

strategies for therapy and research. In order to increase our understanding we developed a segmented regression model which …

Parameter estimates of logistic and Cox regression models are biased for finite samples. In a simulation study we …

for such general mixed hazard regression models is derived using penalized likelihood for regression coefficients and … application to leukemia survival data in Northwest England. -- extended Cox model ; structured hazard regression ; mixed models …