This research aims to analyze the comparison of Poisson and Binomial Negative modeling causative factors gum abscess incidence in West Java. The methods used are Regression Negative. Predictors this habit eating sweet foods (X1), consumption sugary drinks (X2), never going a dental medical personnel (X3). results study obtained AIC values negative binomial models smaller than regression model. ...

Clinicians need to predict the number of involved nodes in breast cancer patients in order to ascertain severity, prognosis, and design subsequent treatment. The distribution of involved nodes often displays over-dispersion-a larger variability than expected. Until now, the negative binomial model has been used to describe this distribution assuming that over-dispersion is only due to unobserve...

Abstract One-parameter link functions play a fundamental role in regression via generalized linear modelling. This paper develops the general theory for two -parameter links very large class of vector models by using total derivatives applied to composite log-likelihood within Fisher scoring/iteratively reweighted least squares algorithm. We solve four-decade old problem with an interesting his...

BACKGROUND Dengue fever (DF) is a growing public health problem in Vietnam. The disease burden in Vietnam has been increasing for decades. In Hanoi, in contrast to many other regions, extrinsic drivers such as weather have not been proved to be predictive of disease frequency, which limits the usefulness of such factors in an early warning system. AIMS The purpose of this research was to revi...

Characterizing the information carried by neural populations in the brain requires accurate statistical models of neural spike responses. The negative-binomial distribution provides a convenient model for over-dispersed spike counts, that is, responses with greater-than-Poisson variability. Here we describe a powerful data-augmentation framework for fully Bayesian inference in neural models wit...