Estimation of gillnet selectivity curve by maximum likelihood method

Estimation of Gillnet Selectivity Curve by Maximum Likelihood Method

Maximum likelihood estimation of survival curve parameters.

A maximum likelihood procedure is presented for the estimation of the parameters in a survival curve which is used in the quantitative investigation of cytological damage resulting from ionizing radiation. This estimation procedure is developed under the assumption that the observations are distributed as independent Poisson random variables. In addition, a weighted least squares procedure, whi...

Nonparametric Maximum Likelihood Estimation by the Method of Sieves

Maximum likelihood estimation often fails when the parameter takes values in an infinite dimensional space. For example, the maximum likelihood method cannot be applied to the completely nonparametric estimation of a density function from an iid sample; the maximum of the likelihood is not attained by any density. In this example, as in many other examples, the parameter space (positive functio...

Approximate Maximum Likelihood Method for Frequency Estimation

A frequency can be estimated by few Discrete Fourier Transform (DFT) coefficients, see Rife and Vincent (1970), Quinn (1994, 1997). This approach is computationally efficient. However, the statistical efficiency of the estimator depends on the location of the frequency. In this paper, we explain this approach from a point of view of an Approximate Maximum Likelihood (AML) method. Then we enhanc...

Maximum Likelihood Estimation of Parameters in Generalized Functional Linear Model

Sometimes, in practice, data are a function of another variable, which is called functional data. If the scalar response variable is categorical or discrete, and the covariates are functional, then a generalized functional linear model is used to analyze this type of data. In this paper, a truncated generalized functional linear model is studied and a maximum likelihood approach is used to esti...