Influence diagnostics for elliptical semiparametric mixed models

In this paper we extend semiparametric mixed linear models with normal errors to elliptical errors in order to permit distributions with heavier and lighter tails than the normal ones. Penalized likelihood equations are applied to derive the maximum penalized likelihood estimates (MPLEs) which appear to be robust against outlying observations in the sense of the Mahalanobis distance. A reweighed iterative process based on the back-fitting method is proposed for the parameter estimation and the local influence curvatures are derived under some usual perturbation schemes to study the sensitivity of the MPLEs. Two motivating examples preliminarily analyzed under normal errors are reanalyzed considering some appropriate elliptical errors. The local influence approach is used to compare the sensitivity of the model estimates.

Assessment of variance components in nonlinear mixed-effects elliptical models

The issue of assessing variance components is essential in deciding on the inclusion of random effects in the context of mixed models. In this work we discuss this problem by supposing nonlinear elliptical models for correlated data by using the score-type test proposed in Silvapulle and Silvapulle (1995). Being asymptotically equivalent to the likelihood ratio test and only requiring the estimation under the null hypothesis, this test provides a fairly easy computable alternative for assessing one-sided hypotheses in the context of the marginal model. Taking into account the possible non-normal distribution, we assume that the joint distribution of the response variable and the random effects lies in the elliptical class, which includes light-tailed and heavy-tailed distributions such as Student-t, power exponential, logistic, generalized Student-t, generalized logistic, contaminated normal, and the normal itself, among others. We compare the sensitivity of the score-type test under normal, Student-t and power exponential models for the kinetics data set discussed in Vonesh and Carter (1992) and fitted using the model presented in Russo et al. (2009). Also, a simulation study is performed to analyze the consequences of the kurtosis misspecification.

A mixed model QTL analysis for sugarcane multiple-harvest-location trial data

Sugarcane-breeding programs take at least 12 years to develop new commercial cultivars. Molecular markers offer a possibility to study the genetic architecture of quantitative traits in sugarcane, and they may be used in marker-assisted selection to speed up artificial selection. Although the performance of sugarcane progenies in breeding programs are commonly evaluated across a range of locations and harvest years, many of the QTL detection methods ignore two- and three-way interactions between QTL, harvest, and location. In this work, a strategy for QTL detection in multi-harvest-location trial data, based on interval mapping and mixed models, is proposed and applied to map QTL effects on a segregating progeny from a biparental cross of pre-commercial Brazilian cultivars, evaluated at two locations and three consecutive harvest years for cane yield (tonnes per hectare), sugar yield (tonnes per hectare), fiber percent, and sucrose content. In the mixed model, we have included appropriate (co)variance structures for modeling heterogeneity and correlation of genetic effects and non-genetic residual effects. Forty-six QTLs were found: 13 QTLs for cane yield, 14 for sugar yield, 11 for fiber percent, and 8 for sucrose content. In addition, QTL by harvest, QTL by location, and QTL by harvest by location interaction effects were significant for all evaluated traits (30 QTLs showed some interaction, and 16 none). Our results contribute to a better understanding of the genetic architecture of complex traits related to biomass production and sucrose content in sugarcane.

Competing regression models for longitudinal data

The choice of an appropriate family of linear models for the analysis of longitudinal data is often a matter of concern for practitioners. To attenuate such difficulties, we discuss some issues that emerge when analyzing this type of data via a practical example involving pretestposttest longitudinal data. In particular, we consider log-normal linear mixed models (LNLMM), generalized linear mixed models (GLMM), and models based on generalized estimating equations (GEE). We show how some special features of the data, like a nonconstant coefficient of variation, may be handled in the three approaches and evaluate their performance with respect to the magnitude of standard errors of interpretable and comparable parameters. We also show how different diagnostic tools may be employed to identify outliers and comment on available software. We conclude by noting that the results are similar, but that GEE-based models may be preferable when the goal is to compare the marginal expected responses.

Phylogeny and cryptic diversity in geckos (Phyllopezus; Phyllodactylidae; Gekkota) from South America's open biomes

The gecko genus Phyllopezus occurs across South America's open biomes: Cerrado, Seasonally Dry Tropical Forests (SDTF, including Caatinga), and Chaco. We generated a multi-gene dataset and estimated phylogenetic relationships among described Phyllopezus taxa and related species. We included exemplars from both described Phyllopezus pollicaris subspecies, P. p. pollicaris and P. p. przewalskii. Phylogenies from the concatenated data as well as species trees constructed from individual gene trees were largely congruent. All phylogeny reconstruction methods showed Bogertia lutzae as the sister species of Phyllopezus maranjonensis, rendering Phyllopezus paraphyletic. We synonymized the monotypic genus Bogertia with Phyllopezus to maintain a taxonomy that is isomorphic with phylogenetic history. We recovered multiple, deeply divergent, cryptic lineages within P. pollicaris. These cryptic lineages possessed mtDNA distances equivalent to distances among other gekkotan sister taxa. Described P. pollicaris subspecies are not reciprocally monophyletic and current subspecific taxonomy does not accurately reflect evolutionary relationships among cryptic lineages. We highlight the conservation significance of these results in light of the ongoing habitat loss in South America's open biomes. (C) 2011 Elsevier Inc. All rights reserved.

Phylogenetic relationships of rock-wallabies, Petrogale (Marsupialia: Macropodidae) and their biogeographic history within Australia

The rock-wallaby genus Petrogale comprises a group of habitat-specialist macropodids endemic to Australia. Their restriction to rocky outcrops, with infrequent interpopulation dispersal, has been suggested as the cause of their recent and rapid diversification. Molecular phylogenetic relationships within and among species of Petrogale were analysed using mitochondrial (cytochrome oxidase c subunit 1, cytochrome b. NADH dehydrogenase subunit 2) and nuclear (omega-globin intron, breast and ovarian cancer susceptibility gene) sequence data with representatives that encompassed the morphological and chromosomal variation within the genus, including for the first time both Petrogale concinna and Petrogale purpureicollis. Four distinct lineages were identified, (1) the brachyotis group, (2) Petrogale persephone, (3) Petrogale xanthopus and (4) the lateralis-penicillata group. Three of these lineages include taxa with the ancestral karyotype (2n = 22). Paraphyletic relationships within the brachyotis group indicate the need for a focused phylogeographic study. There was support for P. purpureicollis being reinstated as a full species and P. concinna being placed within Petrogale rather than in the monotypic genus Peradorcas. Bayesian analyses of divergence times suggest that episodes of diversification commenced in the late Miocene-Pliocene and continued throughout the Pleistocene. Ancestral state reconstructions suggest that Petrogale originated in a mesic environment and dispersed into more arid environments, events that correlate with the timing of radiations in other arid zone vertebrate taxa across Australia. Crown Copyright (C) 2011 Published by Elsevier Inc. All rights reserved.

Influence Assessment in an Heteroscedastic Errors-in-Variables Model

The main goal of this article is to consider influence assessment in models with error-prone observations and variances of the measurement errors changing across observations. The techniques enable to identify potential influential elements and also to quantify the effects of perturbations in these elements on some results of interest. The approach is illustrated with data from the WHO MONICA Project on cardiovascular disease.

Strategies in identifying individuals in a segregant population of common bean and implications of genotype x environment interaction in the success of selection

The objective of this study was to compare the BLUP selection method with different selection strategies in F-2:4 and assess the efficiency of this method on the early choice of the best common bean (Phaseolus vulgaris) lines. Fifty-one F-2:4 progenies were produced from a cross between the CVIII8511 x RP-26 lines. A randomized block design was used with 20 replications and one-plant field plots. Character data on plant architecture and grain yield were obtained and then the sum of the standardized variables was estimated for simultaneous selection of both traits. Analysis was carried out by mixed models (BLUP) and the least squares method to compare different selection strategies, like mass selection, stratified mass selection and between and within progeny selection. The progenies selected by BLUP were assessed in advanced generations, always selecting the greatest and smallest sum of the standardized variables. Analyses by the least squares method and BLUP procedure ranked the progenies in the same way. The coincidence of the individuals identified by BLUP and between and within progeny selection was high and of the greatest magnitude when BLUP was compared with mass selection. Although BLUP is the best estimator of genotypic value, its efficiency in the response to long term selection is not different from any of the other methods, because it is also unable to predict the future effect of the progenies x environments interaction. It was inferred that selection success will always depend on the most accurate possible progeny assessment and using alternatives to reduce the progenies x environments interaction effect.

The importance of plant life form on spatial associations along a subtropical coastal dune gradient

Questions Does the spatial association between isolated adult trees and understorey plants change along a gradient of sand dunes? Does this association depend on the life form of the understorey plant? Location Coastal sand dunes, southeast Brazil. Methods We recorded the occurrence of understorey plant species in 100 paired 0.25 m2 plots under adult trees and in adjacent treeless sites along an environmental gradient from beach to inland. Occurrence probabilities were modelled as a function of the fixed variables of the presence of a neighbour, distance from the seashore and life form, and a random variable, the block (i.e. the pair of plots). Generalized linear mixed models (GLMM) were fitted in a backward step-wise procedure using Akaike's information criterion (AIC) for model selection. Results The occurrence of understorey plants was affected by the presence of an adult tree neighbour, but the effect varied with the life form of the understorey species. Positive spatial association was found between isolated adult neighbour and young trees, whereas a negative association was found for shrubs. Moreover, a neutral association was found for lianas, whereas for herbs the effect of the presence of an adult neighbour ranged from neutral to negative, depended on the subgroup considered. The strength of the negative association with forbs increased with distance from the seashore. However, for the other life forms, the associational pattern with adult trees did not change along the gradient. Conclusions For most of the understorey life forms there is no evidence that the spatial association between isolated adult trees and understorey plants changes with the distance from the seashore, as predicted by the stress gradient hypothesis, a common hypothesis in the literature about facilitation in plant communities. Furthermore, the positive spatial association between isolated adult trees and young trees identified along the entire gradient studied indicates a positive feedback that explains the transition from open vegetation to forest in subtropical coastal dune environments.

Trypanosoma (Megatrypanum) melophagium in the Sheep Ked Melophagus ovinus from Organic Farms in Croatia: Phylogenetic Inferences Support Restriction to Sheep and Sheep Keds and Close Relationship with Trypanosomes from Other Ruminant Species

Trypanosoma (Megatrypanum) melophagium is a parasite of sheep transmitted by sheep keds, the sheep-restricted ectoparasite Melophagus ovinus (Diptera: Hippoboscidae). Sheep keds were 100% prevalent in sheep from five organic farms in Croatia, Southeastern Europe, whereas trypanosomes morphologically compatible with T. melophagium were 86% prevalent in the guts of the sheep keds. Multilocus phylogenetic analyses using sequences of small subunit rRNA, glycosomal glyceraldehyde-3-phosphate dehydrogenase, spliced leader, and internal transcribed spacer 1 of the rDNA distinguished T. melophagium from all allied trypanosomes from other ruminant species and placed the trypanosome in the subgenus Megatrypanum. Trypanosomes from sheep keds from Croatia and Scotland, the only available isolates for comparison, shared identical sequences. All biologic and phylogenetic inferences support the restriction of T. melophagium to sheep and, especially, to the sheep keds. The comparison of trypanosomes from sheep, cattle, and deer from the same country, which was never achieved before this work, strongly supported the host-restricted specificity of trypanosomes of the subgenus Megatrypanum. Our findings indicate that with the expansion of organic farms, both sheep keds and T. melophagium may re-emerge as parasitic infections of sheep.

Coupled Boltzmann calculation of mixed axion/neutralino cold dark matter production in the early universe

We calculate the relic abundance of mixed axion/neutralino cold dark matter which arises in R-parity conserving supersymmetric (SUSY) models wherein the strong CP problem is solved by the Peccei-Quinn (PQ) mechanism with a concommitant axion/saxion/axino supermultiplet. By numerically solving the coupled Boltzmann equations, we include the combined effects of 1. thermal axino production with cascade decays to a neutralino LSP, 2. thermal saxion production and production via coherent oscillations along with cascade decays and entropy injection, 3. thermal neutralino production and re-annihilation after both axino and saxion decays, 4. gravitino production and decay and 5. axion production both thermally and via oscillations. For SUSY models with too high a standard neutralino thermal abundance, we find the combined effect of SUSY PQ particles is not enough to lower the neutralino abundance down to its measured value, while at the same time respecting bounds on late-decaying neutral particles from BBN. However, models with a standard neutralino underabundance can now be allowed with either neutralino or axion domination of dark matter, and furthermore, these models can allow the PQ breaking scale f(a) to be pushed up into the 10(14) - 10(15) GeV range, which is where it is typically expected to be in string theory models.

Cation Distribution and Local Order in Mixed Sodium Metaphosphate Glasses

Two structural properties in mixed alkali metal phosphate glasses that seem to be crucial to the development of the mixed ion effect in dc conductivity were systematically analyzed in Na mixed metaphosphates: the local order around the mobile species, and their distribution and mixing in the glass network. The set of glasses considered here, Na1-xMxPO3 with M = Li, Ag, K, Rb, and Cs and 0 <= x <= 1, encompass a broad degree of size mismatch between the mixed cation species. A comprehensive solid-state nuclear magnetic resonance study was carried out using P-31 MAS, Na-23 triple quantum MAS, Rb-87 QCPMG, P-31-Na-23 REDOR, Na-23-Li-7 and Li-7-Li-6 SEDOR, and Na-23 spin echo decay. It was observed that the arrangement of P atoms around Na in the mixed glasses was indistinguishable from that observed in the NaPO3 glass. However, systematic distortions in the local structure of the 0 environments around Na were observed, related to the presence of the second cation. The average Na-O distances show an expansion/compression When Na+ ions are replaced by cations with respectively smaller/bigger radii. The behavior of the nuclear electric quadrupole coupling. constants indicates that this expansion reduces the local symmetry, while the compression produces the opposite effect These effects become marginally small when the site mismatch between the cations is small, as in Na-Ag mixed glasses. The present study confirms the intimate mixing of cation species at the atomic scale, but clear deviations from random mixing were detected in systems with larger alkali metal ions (Cs-Na, K-Na, Rb-Na). In contrast, no deviations from the statistical ion mixture were found in the systems Ag-Na and Li-Na, where mixed cations are either of radii comparable to (Ag+) or smaller than (Li+) Na+. The set of results supports two fundamental structural features of the models proposed to explain the mixed ion effect: the. structural specificity of the sites occupied by each cation species and their mixing at the atomic scale.

MATHEMATICAL MODELS AND POLYHEDRAL STUDIES FOR INTEGRAL SHEET METAL DESIGN

We deal with the optimization of the production of branched sheet metal products. New forming techniques for sheet metal give rise to a wide variety of possible profiles and possible ways of production. In particular, we show how the problem of producing a given profile geometry can be modeled as a discrete optimization problem. We provide a theoretical analysis of the model in order to improve its solution time. In this context we give the complete convex hull description of some substructures of the underlying polyhedron. Moreover, we introduce a new class of facet-defining inequalities that represent connectivity constraints for the profile and show how these inequalities can be separated in polynomial time. Finally, we present numerical results for various test instances, both real-world and academic examples.

A Poisson mixed model with nonnormal random effect distribution

In this paper, we propose a random intercept Poisson model in which the random effect is assumed to follow a generalized log-gamma (GLG) distribution. This random effect accommodates (or captures) the overdispersion in the counts and induces within-cluster correlation. We derive the first two moments for the marginal distribution as well as the intraclass correlation. Even though numerical integration methods are, in general, required for deriving the marginal models, we obtain the multivariate negative binomial model from a particular parameter setting of the hierarchical model. An iterative process is derived for obtaining the maximum likelihood estimates for the parameters in the multivariate negative binomial model. Residual analysis is proposed and two applications with real data are given for illustration. (C) 2011 Elsevier B.V. All rights reserved.

A general class of zero-or-one inflated beta regression models

This paper proposes a general class of regression models for continuous proportions when the data contain zeros or ones. The proposed class of models assumes that the response variable has a mixed continuous-discrete distribution with probability mass at zero or one. The beta distribution is used to describe the continuous component of the model, since its density has a wide range of different shapes depending on the values of the two parameters that index the distribution. We use a suitable parameterization of the beta law in terms of its mean and a precision parameter. The parameters of the mixture distribution are modeled as functions of regression parameters. We provide inference, diagnostic, and model selection tools for this class of models. A practical application that employs real data is presented. (C) 2011 Elsevier B.V. All rights reserved.