949 resultados para Maximum likelihood estimator (MLE)


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The taxonomic position of a streptomycete isolated from soil collected from Cockle Park Experimental Farm, Northumberland, UK, was determined by using a polyphasic approach. The organism had chemical and morphological features consistent with its classification in the genus Streptomyces. 16S rRNA gene sequence analysis supported classification of the strain in the genus Streptomyces and showed that it formed a distinct phyletic line loosely associated with members of the Streptomyces yeochonensis Glade. It was related most closely to Streptomyces paucisporeus 1413(T) (98.6%16S rRNA gene sequence similarity), but could be distinguished from the latter based on the low level of DNA DNA relatedness (40%). It was readily distinguished from the type strains of all species assigned to the S. yeochonensis clade based on a combination of phenotypic properties. Strain BK168(T) (=KACC 20908(T)=NCIMB 14704(T)) should therefore be classified as the type strain of a novel species of the genus Streptomyces, for which the name Streptomyces cocklensis sp. nov. is proposed. The organism produces the antibiotic dioxamycin.

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It is thought that speciation in phytophagous insects is often due to colonization of novel host plants, because radiations of plant and insect lineages are typically asynchronous. Recent phylogenetic comparisons have supported this model of diversification for both insect herbivores and specialized pollinators. An exceptional case where contemporaneous plant-insect diversification might be expected is the obligate mutualism between fig trees (Ficus species, Moraceae) and their pollinating wasps (Agaonidae, Hymenoptera). The ubiquity and ecological significance of this mutualism in tropical and subtropical ecosystems has long intrigued biologists, but the systematic challenge posed by >750 interacting species pairs has hindered progress toward understanding its evolutionary history. In particular, taxon sampling and analytical tools have been insufficient for large-scale cophylogenetic analyses. Here, we sampled nearly 200 interacting pairs of fig and wasp species from across the globe. Two supermatrices were assembled: on an average, wasps had sequences from 77% of 6 genes (5.6 kb), figs had sequences from 60% of 5 genes (5.5 kb), and overall 850 new DNA sequences were generated for this study. We also developed a new analytical tool, Jane 2, for event-based phylogenetic reconciliation analysis of very large data sets. Separate Bayesian phylogenetic analyses for figs and fig wasps under relaxed molecular clock assumptions indicate Cretaceous diversification of crown groups and contemporaneous divergence for nearly half of all fig and pollinator lineages. Event-based cophylogenetic analyses further support the codiversification hypothesis. Biogeographic analyses indicate that the present-day distribution of fig and pollinator lineages is consistent with a Eurasian origin and subsequent dispersal, rather than with Gondwanan vicariance. Overall, our findings indicate that the fig-pollinator mutualism represents an extreme case among plant-insect interactions of coordinated dispersal and long-term codiversification.

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We study a five-parameter lifetime distribution called the McDonald extended exponential model to generalize the exponential, generalized exponential, Kumaraswamy exponential and beta exponential distributions, among others. We obtain explicit expressions for the moments and incomplete moments, quantile and generating functions, mean deviations, Bonferroni and Lorenz curves and Gini concentration index. The method of maximum likelihood and a Bayesian procedure are adopted for estimating the model parameters. The applicability of the new model is illustrated by means of a real data set.

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Accurate estimates of the penetrance rate of autosomal dominant conditions are important, among other issues, for optimizing recurrence risks in genetic counseling. The present work on penetrance rate estimation from pedigree data considers the following situations: 1) estimation of the penetrance rate K (brief review of the method); 2) construction of exact credible intervals for K estimates; 3) specificity and heterogeneity issues; 4) penetrance rate estimates obtained through molecular testing of families; 5) lack of information about the phenotype of the pedigree generator; 6) genealogies containing grouped parent-offspring information; 7) ascertainment issues responsible for the inflation of K estimates.

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The taxonomic positions of two thermophilic actinomycetes isolated from an arid Australian soil sample were established based on an investigation using a polyphasic taxonomic approach. The organisms had chemical and morphological properties typical of members of the genus Amycolatopsis and formed distinct phyletic lines in the Amycolatopsis methanolica 16S rRNA subclade. The two organisms were distinguished from one another and from the type strains of related species of the genus Amycolatopsis using a range of phenotypic properties. Based on the combined genotypic and phenotypic data, it is proposed that the two isolates be classified in the genus Amycolatopsis as Amycolatopsis thermophila sp. nov. (type strain GY088(T)=NCIMB 14699(T)=NRRL B-24836(T)) and Amycolatopsis viridis sp. nov. (type strain GY115(T)=NCIMB 14700(T)= NRRL B-24837(T)).

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The beta-Birnbaum-Saunders (Cordeiro and Lemonte, 2011) and Birnbaum-Saunders (Birnbaum and Saunders, 1969a) distributions have been used quite effectively to model failure times for materials subject to fatigue and lifetime data. We define the log-beta-Birnbaum-Saunders distribution by the logarithm of the beta-Birnbaum-Saunders distribution. Explicit expressions for its generating function and moments are derived. We propose a new log-beta-Birnbaum-Saunders regression model that can be applied to censored data and be used more effectively in survival analysis. We obtain the maximum likelihood estimates of the model parameters for censored data and investigate influence diagnostics. The new location-scale regression model is modified for the possibility that long-term survivors may be presented in the data. Its usefulness is illustrated by means of two real data sets. (C) 2011 Elsevier B.V. All rights reserved.

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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.

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Spatial linear models have been applied in numerous fields such as agriculture, geoscience and environmental sciences, among many others. Spatial dependence structure modelling, using a geostatistical approach, is an indispensable tool to estimate the parameters that define this structure. However, this estimation may be greatly affected by the presence of atypical observations in the sampled data. The purpose of this paper is to use diagnostic techniques to assess the sensitivity of the maximum-likelihood estimators, covariance functions and linear predictor to small perturbations in the data and/or the spatial linear model assumptions. The methodology is illustrated with two real data sets. The results allowed us to conclude that the presence of atypical values in the sample data have a strong influence on thematic maps, changing the spatial dependence structure.

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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)).

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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.

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A total of 46,089 individual monthly test-day (TD) milk yields (10 test-days), from 7,331 complete first lactations of Holstein cattle were analyzed. A standard multivariate analysis (MV), reduced rank analyses fitting the first 2, 3, and 4 genetic principal components (PC2, PC3, PC4), and analyses that fitted a factor analytic structure considering 2, 3, and 4 factors (FAS2, FAS3, FAS4), were carried out. The models included the random animal genetic effect and fixed effects of the contemporary groups (herd-year-month of test-day), age of cow (linear and quadratic effects), and days in milk (linear effect). The residual covariance matrix was assumed to have full rank. Moreover, 2 random regression models were applied. Variance components were estimated by restricted maximum likelihood method. The heritability estimates ranged from 0.11 to 0.24. The genetic correlation estimates between TD obtained with the PC2 model were higher than those obtained with the MV model, especially on adjacent test-days at the end of lactation close to unity. The results indicate that for the data considered in this study, only 2 principal components are required to summarize the bulk of genetic variation among the 10 traits.

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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.

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Documenting the Neotropical amphibian diversity has become a major challenge facing the threat of global climate change and the pace of environmental alteration. Recent molecular phylogenetic studies have revealed that the actual number of species in South American tropical forests is largely underestimated, but also that many lineages are millions of years old. The genera Phyzelaphryne (1 sp.) and Adelophryne (6 spp.), which compose the subfamily Phyzelaphryninae, include poorly documented, secretive, and minute frogs with an unusual distribution pattern that encompasses the biotic disjunction between Amazonia and the Atlantic forest. We generated >5.8 kb sequence data from six markers for all seven nominal species of the subfamily as well as for newly discovered populations in order to (1) test the monophyly of Phyzelaphryninae, Adelophryne and Phyzelaphryne, (2) estimate species diversity within the subfamily, and (3) investigate their historical biogeography and diversification. Phylogenetic reconstruction confirmed the monophyly of each group and revealed deep subdivisions within Adelophryne and Phyzelaphryne, with three major clades in Adelophryne located in northern Amazonia, northern Atlantic forest and southern Atlantic forest. Our results suggest that the actual number of species in Phyzelaphryninae is, at least, twice the currently recognized species diversity, with almost every geographically isolated population representing an anciently divergent candidate species. Such results highlight the challenges for conservation, especially in the northern Atlantic forest where it is still degraded at a fast pace. Molecular dating revealed that Phyzelaphryninae originated in Amazonia and dispersed during early Miocene to the Atlantic forest. The two Atlantic forest clades of Adelophryne started to diversify some 7 Ma minimum, while the northern Amazonian Adelophryne diversified much earlier, some 13 Ma minimum. This striking biogeographic pattern coincides with major events that have shaped the face of the South American continent, as we know it today. (C) 2012 Elsevier Inc. All rights reserved.

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Sphaerospermopsis torques-reginae (Komarek) Werner, Laughinghouse IV, Fiore & Sant'Anna comb. nov. was originally described as Anabaena torques-reginae Komarek from planktonic populations of Cuban eutrophic environments, characterized by twisted trichomes with spherical akinetes adjacent to the heterocytes. Recently, using molecular analyses, all planktonic Anabaena Bory ex Bornet & Flahault morphospecies were transferred into the genus Dolichospermum (Ralfs ex Bornet & Flahault) Wacklin el al., including Dolichospermum torques-reginae (Komarek) Wacklin et al. However, by a polyphasic characterization of strains of Anabaena reniformis Lemmermann and Aphanizomenon aphanizomenoides (Forti) Horecka & Komarek (=Anabaena aphanizomenoides Forti), these planktonic species were reclassified into Sphaerospermopsis Zapomelova et al. Our study's main objective was to characterize morphologically and molecularly cyanobacterial populations identified as Dolichospermum torques-reginae, observed in different aquatic ecosystems in South America. The 16S rRNA gene of two Dolichospermum torques-reginae strains (ITEP-024 and ITEP-026) was sequenced and phylogenetically analyzed for the first time. The morphological and phylogenetic analyses demonstrated the affiliation of the studied populations with the genus Sphaerospermopsis and, consequently, were denominated as Sphaerospermopsis torques-reginae. Furthermore, geographic distribution, ecology, and toxicity of the species are discussed. It was observed in different aquatic environments, natural and artificial, tropical and subtropical in Brazil, temperate in Argentina, and tropical in Colombia, suggesting a wide distribution in South America. It normally occurred in dense freshwater blooms, although it was also found in water with low salinity. Sphaerospermopsis torques-reginae toxic blooms have been reported in tropical water bodies in northeastern Brazil.

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This paper reports measurements of atmospheric neutrino and antineutrino interactions in the MINOS Far Detector, based on 2553 live-days (37.9 kton-years) of data. A total of 2072 candidate events are observed. These are separated into 905 contained-vertex muons and 466 neutrino-induced rock-muons, both produced by charged-current nu(mu) and (nu) over bar (mu) interactions, and 701 contained-vertex showers, composed mainly of charged-current nu(e) and (nu) over bar (e) interactions and neutral-current interactions. The curvature of muon tracks in the magnetic field of the MINOS Far Detector is used to select separate samples of nu(mu) and (nu) over bar (mu) events. The observed ratio of (nu) over bar (mu) to v(mu) events is compared with the Monte Carlo ( MC) simulation, giving a double ratio of R((nu) over bar/nu)data/R(nu) over bar/nu MC = 1.03 +/- 0.08(stat) +/- 0.08(syst). The v(mu) and (nu) over bar (mu) data are separated into bins of L/E resolution, based on the reconstructed energy and direction of each event, and a maximum likelihood fit to the observed L/E distributions is used to determine the atmospheric neutrino oscillation parameters. This fit returns 90% confidence limits of |Delta m(2)| = (1.9 +/- 0.4) x 10(-3) eV(2) and sin(2)2 theta > 0.86. The fit is extended to incorporate separate nu(mu) and (nu) over bar mu oscillation parameters, returning 90% confidence limits of |Delta m(2)| - |Delta(m) over bar (2)| = 0.6(-0.8)(+2.4) x 10(-3) eV(2) on the difference between the squared-mass splittings for neutrinos and antineutrinos.