Maximum likelihood estimation (MLE) underpins a wide array of regression models by selecting parameter values that maximise the probability of observed data under assumed distributions. In classical ...
It is a right-skewed count variable that is heavily overdispersed relative to the Poisson benchmark, which means ordinary ...
Title Comparing maximum likelihood and Bayesian methods for fitting Hidden Markov Models to multi-state capture recapture data of invasive Silver Carp in the Illinois River ...
A new likelihood-based framework estimates count-model parameters directly from aggregated summaries such as binned ...
Some results have been hidden because they may be inaccessible to you
Show inaccessible results