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

Effects of geometric constraints on the nuclear multifragmentation process

We include in statistical model calculations the facts that in the nuclear multifragmentation process the fragments are produced within a given volume and have a finite size. The corrections associated with these constraints affect the partition modes and, as a consequence, other observables in the process. In particular, we find that the favored fragmenting modes strongly suppress the collective flow energy, leading to much lower values compared to what is obtained from unconstrained calculations. This leads, for a given total excitation energy, to a nontrivial correlation between the breakup temperature and the collective expansion velocity. In particular we find that, under some conditions, the temperature of the fragmenting system may increase as a function of this expansion velocity, contrary to what it might be expected.Comment: 16 pages, 5 figure

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

Paradeduction in Axiomatic Formal Systems

The concept of paradeduction is presented in order to justify that we can overlook contradictory information taking into account only what is consistent. Besides that, paradeduction is used to show that there is a way to transform any logic, introduced as an axiomatic formal system, into a paraconsistent one