There are three SAS procedures that enable you to do maximum likelihood estimation of parameters in an arbitrary model with a likelihood function that you define: PROC MODEL, PROC NLP, and PROC IML.

Bayesian estimation and maximum likelihood methods represent two central paradigms in modern statistical inference. Bayesian estimation incorporates prior beliefs through Bayes’ theorem, updating ...

We present a maximum-likelihood method for parameter estimation in terahertz time-domain spectroscopy. We derive the likelihood function for a parameterized frequency response function, given a pair ...

This is a preview. Log in through your library . Abstract We focus on a class of non-standard problems involving non-parametric estimation of a monotone function that is characterized by n1/3 rate of ...

This is a preview. Log in through your library . Abstract In a linear (or affine) functional model the principal parameter is a subspace (respectively an affine subspace) in a finite dimensional inner ...