Influence diagnostics in heteroscedastic and/or autoregressive nonlinear elliptical models for correlated data

In this paper, we propose nonlinear elliptical models for correlated data with heteroscedastic and/or autoregressive structures. Our aim is to extend the models proposed by Russo et al. [22] by considering a more sophisticated scale structure to deal with variations in data dispersion and/or a possible autocorrelation among measurements taken throughout the same experimental unit. Moreover, to avoid the possible influence of outlying observations or to take into account the non-normal symmetric tails of the data, we assume elliptical contours for the joint distribution of random effects and errors, which allows us to attribute different weights to the observations. We propose an iterative algorithm to obtain the maximum-likelihood estimates for the parameters and derive the local influence curvatures for some specific perturbation schemes. The motivation for this work comes from a pharmacokinetic indomethacin data set, which was analysed previously by Bocheng and Xuping [1] under normality.

Amycolatopsis granulosa sp nov., Amycolatopsis ruanii sp nov and Amycolatopsis thermalba sp nov., thermophilic actinomycetes isolated from arid soils

The taxonomic positions of three thermophilic actinomycetes isolated from arid soil samples were established by using a polyphasic approach. The organisms had chemical and morphological features that were consistent with their classification in the genus Amycolatopsis. 16S rRNA gene sequence data supported the classification of the isolates in the genus Amycolatopsis and showed that they formed distinct branches in the Amycolatopsis methanolica subclade. DNA-DNA relatedness studies between the isolates and their phylogenetic neighbours showed that they belonged to distinct genomic species. The three isolates were readily distinguished from one another and from the type strains of species classified in the A. methanolica subclade based on a combination of phenotypic properties and by genomic fingerprinting. Consequently, it is proposed that the three isolates be classified in the genus Amycolatopsis as representatives of Amycolatopsis granulosa sp. nov. (type strain GY307(T)=NCIMB 14709(T)=NRRL B-24844(T)), Amycolatopsis ruanii sp. nov. (type strain NMG112(T)=NCIMB 14711(T)=NRRL B-24848(T)) and Amycolatopsis thermalba sp. nov. (type strain SF45(T)=NCIMB 14705(T)=NRRL B-24845(T)).