Research from all publishers Recent studies have introduced innovative probabilistic frameworks and regression models that address the complexities inherent in count data.

Count data with means <2 are often assumed to follow a Poisson distribution. However, in many cases these kinds of data, such as number of young fledged, are more appropriately considered to be ...

Course Topics"Logistic and Poisson Regression," Wednesday, November 5: The fourth LISA mini course focuses on appropriate model building for categorical response data, specifically binary and count ...

Joint mean-covariance regression modeling with unconstrained parametrization for continuous longitudinal data has provided statisticians and practitioners with a powerful analytical device. How to ...

Model the data as a log-linear model with (the Poisson variance function) and where Yij= number of epileptic seizures in interval j tij= length of interval j The correlations between the counts are ...

The model is formulated in an hierarchical Bayesian framework and fitted using MCMC simulations. The model borrows strength over time and space as well as from auxiliary claimant counts series.

DTSA 5011 Modern Regression Analysis in R Specialization: Statistical Modeling for Data Science Applications Instructor: Brian Zaharatos, Director, Professional Master’s Degree in Applied Mathematics ...