Nesting patterns among Neotropical species assemblages: can reserves in urban areas be failing to protect anurans?

Nestedness among species assemblages implies that sites of lower species richness are subsets of richer sites in a regional species pool. This nestedness is a reflection of a non-random process of species loss as a consequence of factors that promote the disaggregation of assemblages. The impoverishment of assemblage diversity is more often observed in fragmented landscapes. This non-random process has important implications for conservation. We recorded 95 species of anurans across 22 protected areas, of which 11 sites were in an urban matrix and 11 were in a non-urban matrix. We found that sites in the urban matrix had lower richness and high values of nestedness with no spatial autocorrelation among geographic distances and species composition. Thus, species were non-randomly distributed across the landscape and a nested pattern was documented from non-urban matrix sites to urban matrix sites. The impoverishment of assemblages toward the urban matrix sites may suggest that protected areas in an urban matrix are less suitable for anuran conservation than those in a non-urban matrix sites. Both the ecological revitalization of protected areas in urban matrix and protection of non-urban forested sites are needed for the conservation of Neotropical anurans.     

On bartlett and bartlett-type corrections francisco cribari-neto

This paper reviews the literature on Bartlett and Bartlett-type corrections. It focuses on the corrections to the likelihood ratio, score and Wald test statistics. Three different Bartlett-type corrections which are equivalent to order n-1, n being the sample size, are compared through simulation. One of the forms displayed superior behavior both in terms of size and power. We also use Monte Carlo simulation to examine the effect of independent variables and the impact of the number of nuisance parameters on the finite-sample behavior of some asymptotic econometric criteria in regression models.     

On the Marshall–Olkin extended Weibull distribution

We study some mathematical properties of the Marshall–Olkin extended Weibull distribution introduced by Marshall and Olkin (Biometrika 84:641–652, 1997). We provide explicit expressions for the moments, generating and quantile functions, mean deviations, Bonferroni and Lorenz curves, reliability and Rényi entropy. We determine the moments of the order statistics. We also discuss the estimation of the model parameters by maximum likelihood and obtain the observed information matrix. We provide an application to real data which illustrates the usefulness of the model.     

Bias Correction in Generalized Nonlinear Models with Dispersion Covariates

We derive general formulae for the second-order biases of maximum likelihood estimates of the parameters in generalized nonlinear models with dispersion covariates. This result generalizes previous work by Botter and Cordeiro (1998 Botter , D. A. , Cordeiro , G. M. ( 1998 ). Improved estimates for generalized linear models with dispersion covariates . J. Statist. Comput. Simul. 62 : 91 – 104 .[Taylor & Francis Online], [Web of Science ®] , [Google Scholar]) and Cordeiro and McCullagh (1991 Cordeiro , G. M. , McCullagh , P. ( 1991 ). Bias correction in generalized linear models . J. Roy Statist. Soc. B 53 : 629 – 643 . [Google Scholar]). The practical use of such bias corrections is illustrated in a simulation study.     

Asymptotic Skewness in Exponential Family Nonlinear Models

In this article, we give an asymptotic formula of order n ^?1/2, where n is the sample size, for the skewness of the distributions of the maximum likelihood estimates of the pa-ra-meters in exponencial family nonlinear models. We generalize the result by Cordeiro and Cordeiro (2001 Cordeiro , H. H. , Cordeiro , G. M. ( 2001 ). Skewness for parameters in generalized linear models . Commun. Statist. Theor. Meth. 30 : 1317 – 1334 .[Taylor & Francis Online], [Web of Science ®] , [Google Scholar]). The formula is given in matrix notation and is very suitable for computer implementation and to obtain closed form expressions for a great variety of models. Some special cases and two applications are discussed.