There is hardly any literature on modelling nonlinear dynamic relations involving nonnormal time series data. This is a serious lacuna because nonnormal data are far more abundant than normal ones, ...

This paper presents an EM algorithm for semiparametric likelihood analysis of linear, generalized linear, and nonlinear regression models with measurement errors in explanatory variables. A structural ...

Although epistasis is an important phenomenon in the genetics and evolution of complex traits, epistatic effects are hard to estimate. The main problem is due to the overparameterized epistatic ...

In a recent study posted to the bioRxiv* pre-print server, researchers developed a maximum likelihood (ML) model to capture severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) evolutionary ...