Improved estimators for dispersion models with dispersion covariates

In this paper we discuss improved estimators for the regression and the dispersion parameters in an extended class of dispersion models (J{\o}rgensen, 1996). This class extends the regular dispersion models by letting the dispersion parameter vary throughout the observations, and contains the dispersion models as particular case. General formulae for the second-order bias are obtained explicitly in dispersion models with dispersion covariates, which generalize previous results by Botter and Cordeiro (1998), Cordeiro and McCullagh (1991), Cordeiro and Vasconcellos (1999), and Paula (1992). The practical use of the formulae is that we can derive closed-form expressions for the second-order biases of the maximum likelihood estimators of the regression and dispersion parameters when the information matrix has a closed-form. Various expressions for the second-order biases are given for special models. The formulae have advantages for numerical purposes because they require only a supplementary weighted linear regression. We also compare these bias-corrected estimators with two different estimators which are also bias-free to the second-order that are based on bootstrap methods. These estimators are compared by simulation

Statistical multifragmentation model with discretized energy and the generalized Fermi breakup. I. Formulation of the model

The Generalized Fermi Breakup recently demonstrated to be formally equivalent to the Statistical Multifragmentation Model, if the contribution of excited states are included in the state densities of the former, is implemented. Since this treatment requires the application of the Statistical Multifragmentation Model repeatedly on the hot fragments until they have decayed to their ground states, it becomes extremely computational demanding, making its application to the systems of interest extremely difficult. Based on exact recursion formulae previously developed by Chase and Mekjian to calculate the statistical weights very efficiently, we present an implementation which is efficient enough to allow it to be applied to large systems at high excitation energies. Comparison with the GEMINI++ sequential decay code shows that the predictions obtained with our treatment are fairly similar to those obtained with this more traditional model.Comment: 8 pages, 6 figure

Finite size effects in isobaric ratios

The properties of isobaric ratios, between nuclei produced in the same reaction, are investigated using the canonical and grand-canonical statistical ensembles. Although the grand-canonical for- mulae furnish a means to correlate the ratios with the liquid drop parameters, finite size effects make it difficult to obtain their actual values from fitting nuclear collision data.Comment: 4 pages, 2 figure