The new class of Kummer beta generalized distributions

Ng and Kotz (1995) introduced a distribution that provides greater flexibility to extremes. We define and study a new class of distributions called the Kummer beta generalized family to extend the normal, Weibull, gamma and Gumbel distributions, among several other well-known distributions. Some special models are discussed. The ordinary moments of any distribution in the new family can be expressed as linear functions of probability weighted moments of the baseline distribution. We examine the asymptotic distributions of the extreme values. We derive the density function of the order statistics, mean absolute deviations and entropies. We use maximum likelihood estimation to fit the distributions in the new class and illustrate its potentiality with an application to a real data set.

Levels of Selenomonas species in generalized aggressive periodontitis

Goncalves LFH, Fermiano D, Feres M, Figueiredo LC, Teles FRP, Mayer MPA, Faveri M. Levels of Selenomonas species in generalized aggressive periodontitis. J Periodont Res 2012; 47: 711718. (c) 2012 John Wiley & Sons A/S Background and Objective: To compare the levels of Selenomonas sputigena and uncultivated/unrecognized Selenomonas species in subgingival biofilms from periodontally healthy subjects and from subjects with generalized aggressive periodontitis. Material and Methods: Fifteen periodontally healthy subjects and 15 subjects with generalized aggressive periodontitis were recruited and their clinical periodontal parameters were evaluated. Nine subgingival plaque samples were collected from each subject and all were individually analyzed for the levels of 10 bacterial taxa, including cultured and uncultivated/unrecognized microorganisms, using the RNA-oligonucleotide quantification technique. Between-group differences in the levels of the test taxa were determined using the MannWhitney U-test. Results: Subjects with generalized aggressive periodontitis showed significantly higher mean counts of Porphyromonas gingivalis, S. sputigena and the Mitsuokella sp. Human Oral Taxon (HOT) 131 (previously described as Selenomonas sp. oral clone CS002), while higher mean counts of Actinomyces gerencseriae and Streptococcus sanguinis were found in periodontally healthy subjects (p < 0.01). Selenomonas sp. HOT 146 was only detected in the generalized aggressive periodontitis group. In the generalized aggressive periodontitis group, the levels of P.gingivalis and S.sputigena were higher in deep sites (probing depth = 5 mm) than in shallow sites (probing depth = 3 mm) (p < 0.01). Furthermore, in subjects with generalized aggressive periodontitis, sites with probing depth of = 3 mm harbored higher levels of these two species than sites with the same probing depth in periodontally healthy subjects. There were positive correlations between probing depth and the levels of P.gingivalis (r = 0.77; p < 0.01), S.sputigena (r = 0.60; p < 0.01) and Selenomonas dianae (previously described as Selenomonas sp. oral clone EW076) (r = 0.42, p < 0.05). Conclusion: S. sputigena and Mitsuokella sp. HOT 131 may be associated with the pathogenesis of generalized aggressive periodontitis, and their role in the onset and progression of this infection should be investigated further.

Thermodynamics of Ising model with infinite-range interactions by generalized canonical ensemble

In this work we present the idea of how generalized ensembles can be used to simplify the operational study of non-additive physical systems. As alternative of the usual methods of direct integration or mean-field theory, we show how the solution of the Ising model with infinite-range interactions is obtained by using a generalized canonical ensemble. We describe how the thermodynamical properties of this model in the presence of an external magnetic field are founded by simple parametric equations. Without impairing the usual interpretation, we obtain an identical critical behaviour as observed in traditional approaches.

On Wald Residuals in Generalized Linear Models

A rigorous asymptotic theory for Wald residuals in generalized linear models is not yet available. The authors provide matrix formulae of order O(n(-1)), where n is the sample size, for the first two moments of these residuals. The formulae can be applied to many regression models widely used in practice. The authors suggest adjusted Wald residuals to these models with approximately zero mean and unit variance. The expressions were used to analyze a real dataset. Some simulation results indicate that the adjusted Wald residuals are better approximated by the standard normal distribution than the Wald residuals.