Maximum likelihood estimation of the parameters of a statistical model involves maximizing the likelihood or, equivalently, the log likelihood with respect to the parameters. The parameter values at ...

Parameter estimation and optimisation in fuel cells are critical in developing robust and predictive models necessary for improving their efficiency, longevity, and overall performance. At the heart ...

Two-dimensional (2-D) polynomial phase signals occur in different areas of image processing. When the degree of the polynomial is two they are called chirp signals. In this paper, we consider the ...

Nonlinear estimation algorithms are required for obtaining estimates of the parameters of a regression model with innovations having an ARMA structure. The three estimation methods employed by the ...

This study demonstrated the equivalence between the Rasch testlet model and the three-level one-parameter testlet model and explored the Markov Chain Monte Carlo (MCMC) method for model parameter ...

The purpose of this paper is to present a comprehensive simulation study on the finite sample properties of minimum distance and maximum likelihood estimators for bivariate and multivariate parametric ...