Theory of parameter estimation

Theory of Parameter Estimation

0. Introduction and summary. The analysis of data from the gravitational-wave detectors that are currently under construction in several countries will be a challenging problem. The reason is that gravitational-vawe signals are expected to be extremely weak and often very rare. Therefore it will be of great importance to implement optimal statistical methods to extract all possible information ...

Elimination Theory for Nonlinear Parameter Estimation

Estimation of a four-parameter item response theory model.

We explore the justification and formulation of a four-parameter item response theory model (4PM) and employ a Bayesian approach to recover successfully parameter estimates for items and respondents. For data generated using a 4PM item response model, overall fit is improved when using the 4PM rather than the 3PM or the 2PM. Furthermore, although estimated trait scores under the various models ...

Parameter Estimation of the Cauchy Distribution in Information Theory Approach

As we know the Cauchy distribution plays an important role in Probability Theory and Statistics. In this paper, we investigate the estimation of the location and the scale parameter. Both the one-dimensional problem and the multidimensional problem are studied for large sample. In the one-dimensional case, we give two algorithms for the estimation. The first one is an iterative method for which...

Parameter Estimation of Loranz Chaotic Dynamic System Using Bees Algorithm

An important problem in nonlinear science is the unknown parameters estimation in Loranz chaotic system. Clearly, the parameter estimation for chaotic systems is a multidimensional continuous optimization problem, where the optimization goal is to minimize mean squared errors (MSEs) between real and estimated responses for a number of given samples. The Bees algorithm (BA) is a new member of me...