997 resultados para Partitioned Likelihood Support


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In simultaneous analyses of multiple data partitions, the trees relevant when measuring support for a clade are the optimal tree, and the best tree lacking the clade (i.e., the most reasonable alternative). The parsimony-based method of partitioned branch support (PBS) forces each data set to arbitrate between the two relevant trees. This value is the amount each data set contributes to clade support in the combined analysis, and can be very different to support apparent in separate analyses. The approach used in PBS can also be employed in likelihood: a simultaneous analysis of all data retrieves the maximum likelihood tree, and the best tree without the clade of interest is also found. Each data set is fitted to the two trees and the log-likelihood difference calculated, giving partitioned likelihood support (PLS) for each data set. These calculations can be performed regardless of the complexity of the ML model adopted. The significance of PLS can be evaluated using a variety of resampling methods, such as the Kishino-Hasegawa test, the Shimodiara-Hasegawa test, or likelihood weights, although the appropriateness and assumptions of these tests remains debated.

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Partitioned Bremer support (PBS) is a valuable means of assessing congruence in combined data sets, but some aspects require clarification. When more than one equally parsimonious tree is found during the constrained search for trees lacking the node of interest, averaging PBS for each data set across these trees can conceal conflict, and PBS should ideally be examined for each constrained tree. Similarly, when multiple most parsimonious trees (MPTs) are generated during analysis of the combined data, PBS is usually calculated on the consensus tree. However, extra information can be obtained if PBS is calculated on each of the MPTs or even suboptimal trees. (C) 2002 The Willi Hennig Society. Published by Elsevier Science (USA). All rights reserved.

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The phylogenetic relationships and historical biogeography of 10 currently described rainforest skinks in the genus Saproscincus were investigated using mitochondrial protein-coding ND4 and ribosomal RNA 16S genes. A robust phylogeny is inferred using both maximum likelihood and Bayesian analysis, with all inter-specific nodes strongly supported when datasets are combined. The phylogeny supports the recognition of two major lineages (northern and southern), each of which comprises two divergent clades. Both northern and southern lineages have comparably divergent representatives in mid-east Queensland (MEQ), providing further molecular evidence for the importance of two major biogeographic breaks, the St. Lawrence gap and Burdekin gap separating MEQ from southern and northern counterparts respectively. Vicariance associated with the fragmentation and contraction of temperate rainforest during the mid-late Miocene epoch underpins the deep divergence between morphologically conservative lineages in at least three instances. In contrast, one species, Saproseincus oriarus, shows very low sequence divergence but distinct morphological and ecological differentiation from its allopatric sister clade within Saproseincus mustelinus. These results suggest that while vicariance has played a prominent role in diversification and historical biogeography of Saproscincus, divergent selection may also be important. (C) 2004 Elsevier Inc. All rights reserved.

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Agapophytinae subf.n. is a highly diverse lineage of Australasian Therevidae, comprising eight described and two new genera: Agapophytus Guerin-Meneville, Acupalpa Krober, Acraspisa Krober, Belonalys Krober, Bonjeania Irwin & Lyneborg, Parapsilocephala Krober, Acatopygia Krober, Laxotela Winterton & Irwin, Pipinnipons gen.n. and Patanothrix gen.n. A genus-level cladistic analysis of the subfamily was undertaken using sixty-eight adult morphological characters and c. 1000 base pairs of the elongation factor-1 alpha (EF-1 alpha) protein coding gene. The morphological data partition produced three most parsimonious cladograms, whereas the molecular data partition gave a single most parsimonious cladogram, which did not match any of the cladograms found in the morphological analysis. The level of congruence between the data partitions was determined using the partition homogeneity test (HTF) and Wilcoxon signed ranks rest. Despite being significantly incongruent in at least one of the incongruence tests, the partitions were combined in a simultaneous analysis. The combined data yielded a single cladogram that was better supported than that of the individual partitions analysed separately. The relative contributions of the data partitions to support for individual nodes on the combined cladogram were investigated using Partitioned Bremer Support. The level of support for many nodes on the combined cladogram was non-additive and often greater than the sum of support for the respective nodes on individual partitions. This synergistic interaction between incongruent data partitions indicates a common phylogenetic signal in both partitions. It also suggests that criteria for partition combination based solely on incongruence may be misleading. The phylogenetic relationships of the genera are discussed using the combined data. A key to genera of Agapophytinae is presented, with genera diagnosed and figured. Two new genera are described: Patanothrix with a new species (Pat. skevingtoni) and Pat. wilsoni (Mann) transferred from Parapsilocephala, and Pipinnipons with a new species (Pip. kroeberi). Pipinnipons fascipennis (Krober) is transferred from Squamopygin Krober and Pip. imitans (Mann) is transferred from Agapophytus. Agapophytus bicolor (Krober) is transferred from Parapsilocephala. Agapophytus varipennis Mann is synonymised with Aga, queenslandi Krober and Aga. flavicornis Mann is synonymised with Aga. pallidicornis (Krober).

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The aim of many genetic studies is to locate the genomic regions (called quantitative trait loci, QTLs) that contribute to variation in a quantitative trait (such as body weight). Confidence intervals for the locations of QTLs are particularly important for the design of further experiments to identify the gene or genes responsible for the effect. Likelihood support intervals are the most widely used method to obtain confidence intervals for QTL location, but the non-parametric bootstrap has also been recommended. Through extensive computer simulation, we show that bootstrap confidence intervals are poorly behaved and so should not be used in this context. The profile likelihood (or LOD curve) for QTL location has a tendency to peak at genetic markers, and so the distribution of the maximum likelihood estimate (MLE) of QTL location has the unusual feature of point masses at genetic markers; this contributes to the poor behavior of the bootstrap. Likelihood support intervals and approximate Bayes credible intervals, on the other hand, are shown to behave appropriately.

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Phylogenetic analyses of chloroplast DNA sequences, morphology, and combined data have provided consistent support for many of the major branches within the angiosperm, clade Dipsacales. Here we use sequences from three mitochondrial loci to test the existing broad scale phylogeny and in an attempt to resolve several relationships that have remained uncertain. Parsimony, maximum likelihood, and Bayesian analyses of a combined mitochondrial data set recover trees broadly consistent with previous studies, although resolution and support are lower than in the largest chloroplast analyses. Combining chloroplast and mitochondrial data results in a generally well-resolved and very strongly supported topology but the previously recognized problem areas remain. To investigate why these relationships have been difficult to resolve we conducted a series of experiments using different data partitions and heterogeneous substitution models. Usually more complex modeling schemes are favored regardless of the partitions recognized but model choice had little effect on topology or support values. In contrast there are consistent but weakly supported differences in the topologies recovered from coding and non-coding matrices. These conflicts directly correspond to relationships that were poorly resolved in analyses of the full combined chloroplast-mitochondrial data set. We suggest incongruent signal has contributed to our inability to confidently resolve these problem areas. (c) 2007 Elsevier Inc. All rights reserved.

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The development of mixed-criticality virtualized multicore systems poses new challenges that are being subject of active research work. There is an additional complexity: it is now required to identify a set of partitions, and allocate applications to partitions. In this job, a number of issues have to be considered, such as the criticality level of the application, security and dependability requirements, operating system used by the application, time requirements granularity, specific hardware needs, etc. MultiPARTES [6] toolset relies on Model Driven Engineering (MDE) [12], which is a suitable approach in this setting. In this paper, it is described the support provided for automatic system partitioning generation and toolset extensibility.

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Hemichordates were traditionally allied to the chordates, but recent molecular analyses have suggested that hemichordates are a sister group to the echinoderms, a relationship that has important consequences for the interpretation of the evolution of deuterostome body plans. However, the molecular phylogenetic analyses to date have not provided robust support for the hemichordate + echinoderm clade. We use a maximum likelihood framework, including the parametric bootstrap, to reanalyze DNA data from complete mitochondrial genomes and nuclear 18S rRNA. This approach provides the first statistically significant support for the hemichordate + echinoderm clade from molecular data. This grouping implies that the ancestral deuterostome had features that included an adult with a pharynx and a dorsal nerve cord and an indirectly developing dipleurula-like larva.

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Paper/Poster presented in Work in Progress Session, 28th GI/ITG International Conference on Architecture of Computing Systems (ARCS 2015). 24 to 26, Mar, 2015. Porto, Portugal.

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This paper extends previous research and discussion on the use of multivariate continuous data, which are about to become more prevalent in forensic science. As an illustrative example, attention is drawn here on the area of comparative handwriting examinations. Multivariate continuous data can be obtained in this field by analysing the contour shape of loop characters through Fourier analysis. This methodology, based on existing research in this area, allows one describe in detail the morphology of character contours throughout a set of variables. This paper uses data collected from female and male writers to conduct a comparative analysis of likelihood ratio based evidence assessment procedures in both, evaluative and investigative proceedings. While the use of likelihood ratios in the former situation is now rather well established (typically, in order to discriminate between propositions of authorship of a given individual versus another, unknown individual), focus on the investigative setting still remains rather beyond considerations in practice. This paper seeks to highlight that investigative settings, too, can represent an area of application for which the likelihood ratio can offer a logical support. As an example, the inference of gender of the writer of an incriminated handwritten text is forwarded, analysed and discussed in this paper. The more general viewpoint according to which likelihood ratio analyses can be helpful for investigative proceedings is supported here through various simulations. These offer a characterisation of the robustness of the proposed likelihood ratio methodology.

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Background Individual signs and symptoms are of limited value for the diagnosis of influenza. Objective To develop a decision tree for the diagnosis of influenza based on a classification and regression tree (CART) analysis. Methods Data from two previous similar cohort studies were assembled into a single dataset. The data were randomly divided into a development set (70%) and a validation set (30%). We used CART analysis to develop three models that maximize the number of patients who do not require diagnostic testing prior to treatment decisions. The validation set was used to evaluate overfitting of the model to the training set. Results Model 1 has seven terminal nodes based on temperature, the onset of symptoms and the presence of chills, cough and myalgia. Model 2 was a simpler tree with only two splits based on temperature and the presence of chills. Model 3 was developed with temperature as a dichotomous variable (≥38°C) and had only two splits based on the presence of fever and myalgia. The area under the receiver operating characteristic curves (AUROCC) for the development and validation sets, respectively, were 0.82 and 0.80 for Model 1, 0.75 and 0.76 for Model 2 and 0.76 and 0.77 for Model 3. Model 2 classified 67% of patients in the validation group into a high- or low-risk group compared with only 38% for Model 1 and 54% for Model 3. Conclusions A simple decision tree (Model 2) classified two-thirds of patients as low or high risk and had an AUROCC of 0.76. After further validation in an independent population, this CART model could support clinical decision making regarding influenza, with low-risk patients requiring no further evaluation for influenza and high-risk patients being candidates for empiric symptomatic or drug therapy.

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Land cover classification is a key research field in remote sensing and land change science as thematic maps derived from remotely sensed data have become the basis for analyzing many socio-ecological issues. However, land cover classification remains a difficult task and it is especially challenging in heterogeneous tropical landscapes where nonetheless such maps are of great importance. The present study aims to establish an efficient classification approach to accurately map all broad land cover classes in a large, heterogeneous tropical area of Bolivia, as a basis for further studies (e.g., land cover-land use change). Specifically, we compare the performance of parametric (maximum likelihood), non-parametric (k-nearest neighbour and four different support vector machines - SVM), and hybrid classifiers, using both hard and soft (fuzzy) accuracy assessments. In addition, we test whether the inclusion of a textural index (homogeneity) in the classifications improves their performance. We classified Landsat imagery for two dates corresponding to dry and wet seasons and found that non-parametric, and particularly SVM classifiers, outperformed both parametric and hybrid classifiers. We also found that the use of the homogeneity index along with reflectance bands significantly increased the overall accuracy of all the classifications, but particularly of SVM algorithms. We observed that improvements in producer’s and user’s accuracies through the inclusion of the homogeneity index were different depending on land cover classes. Earlygrowth/degraded forests, pastures, grasslands and savanna were the classes most improved, especially with the SVM radial basis function and SVM sigmoid classifiers, though with both classifiers all land cover classes were mapped with producer’s and user’s accuracies of around 90%. Our approach seems very well suited to accurately map land cover in tropical regions, thus having the potential to contribute to conservation initiatives, climate change mitigation schemes such as REDD+, and rural development policies.

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Background and aims Recent studies have adopted a broad definition of Sapindaceae that includes taxa traditionally placed in Aceraceae and Hippocastanaceae, achieving monophyly but yielding a family difficult to characterize and for which no obvious morphological synapomorphy exists. This expanded circumscription was necessitated by the finding that the monotypic, temperate Asian genus Xanthoceras, historically placed in Sapindaceae tribe Harpullieae, is basal within the group. Here we seek to clarify the relationships of Xanthoceras based on phylogenetic analyses using a dataset encompassing nearly 3/4 of sapindaceous genera, comparing the results with information from morphology and biogeography, in particular with respect to the other taxa placed in Harpullieae. We then re-examine the appropriateness of maintaining the current broad, morphologically heterogeneous definition of Sapindaceae and explore the advantages of an alternative family circumscription. Methods Using 243 samples representing 104 of the 142 currently recognized genera of Sapindaceae s. lat. (including all in Harpullieae), sequence data were analyzed for nuclear (ITS) and plastid (matK, rpoB, trnD-trnT, trnK-matK, trnL-trnF and trnS-trnG) markers, adopting the methodology of a recent family-wide study, performing single-gene and total evidence analyses based on maximum likelihood (ML) and maximum parsimony (MP) criteria, and applying heuristic searches developed for large datasets, viz, a new strategy implemented in RAxML (for ML) and the parsimony ratchet (for MP). Bootstrap analyses were performed for each method to test for congruence between markers. Key results Our findings support earlier suggestions that Harpullieae are polyphyletic: Xanthoceras is confirmed as sister to all other sampled taxa of Sapindaceae s. lat.; the remaining members belong to three other clades within Sapindaceae s. lat., two of which correspond respectively to the groups traditionally treated as Aceraceae and Hippocastanaceae, together forming a clade sister to the largely tropical Sapindaceae s. str., which is monophyletic and morphologically coherent provided Xanthoceras is excluded. Conclusion To overcome the difficulties of a broadly circumscribed Sapindaceae, we resurrect the historically recognized temperate families Aceraceae and Hippocastanaceae, and describe a new family, Xanthoceraceae, thus adopting a monophyletic and easily characterized circumscription of Sapindaceae nearly identical to that used for over a century.

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This paper studies whether firms' use of R&D subsidies and R&D tax incentives is correlated to two sources of underinvestment in R&D, financing constraints and appropriability. We find that financially constrained SMEs are less likely to use R&D tax credits and more likely to obtain subsidies. SMEs using legal methods to protect their intellectual property are more likely to use tax incentives. Results are ambiguous for large firms. For both having previous experience in R&D increases the likelihood of using tax incentives, while it reduces the likelihood of using exclusively subsidies, suggesting that the latter induce entry into R&D. Results imply that direct funding and tax credits do not have the same ability to address each source of R&D underinvestment, and that on average subsidies may be better suited than tax credits at least for SMEs. From a policy perspective these tools may be complements rather than substitutes.