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 ...

Experimental data and mathematical models are beginning to take equal billing in systems biology. Experimental observations without a framework in which to link them offer researchers only limited ...

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 ...

Precision measurement has been long pursued due to its vital importance in physics and other sciences. Quantum mechanics supplies this task with two new elements. On one hand, quantum mechanics ...

The Annals of Statistics, Vol. 15, No. 4 (Dec., 1987), pp. 1651-1666 (16 pages) We consider the problem of estimating parameter matrices which occur in the noncentral ...

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 ...

A new method for measuring three different properties of light, at the same time, has been developed using an ...

Some of the models used to forecast everything from financial trends to animal populations in an ecosystem are incorrect, ...

Problems of maximum likelihood estimation are discussed for shape and scale parameters from certain decreasing hazard rate distributions, typically either mixed-exponential or "work-hardened." ...