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 ...

Estimation techniques in computer vision applications must estimate accurate model parameters despite small-scale noise in the data, occasional large-scale measurement errors (outliers), and ...

The following data are taken from Lawless (1982, p.193) and represent the number of days it took rats painted with a carcinogen to develop carcinoma. The last 2 observations are censored data from a ...

Muhammad Sumair, Tauseef Aized, Syed Asad Raza Gardezi, Muhammad Mahmood Aslam Bhutta, Syed Ubaid ur Rehman, Syed Muhammad Sohail Rehman Energy Exploration & Exploitation, Vol. 39, No. 5 (September ...

As a follow-on course to "Linear Kalman Filter Deep Dive", this course derives the steps of the extended Kalman filter and the sigma-point Kalman filter for estimating the state of nonlinear dynamic ...

This paper is devoted to the parameterization of correlations in the Vasicek credit portfolio model. First, we analytically approximate standard errors for value-at-risk and expected shortfall based ...