954 resultados para Multivariate polynomial
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This paper aims to find relations between the socioeconomic characteristics, activity participation, land use patterns and travel behavior of the residents in the Sao Paulo Metropolitan Area (SPMA) by using Exploratory Multivariate Data Analysis (EMDA) techniques. The variables influencing travel pattern choices are investigated using: (a) Cluster Analysis (CA), grouping and characterizing the Traffic Zones (17), proposing the independent variable called Origin Cluster and, (b) Decision Tree (DT) to find a priori unknown relations among socioeconomic characteristics, land use attributes of the origin TZ and destination choices. The analysis was based on the origin-destination home-interview survey carried out in SPMA in 1997. The DT application revealed the variables of greatest influence on the travel pattern choice. The most important independent variable considered by DT is car ownership, followed by the Use of Transportation ""credits"" for Transit tariff, and, finally, activity participation variables and Origin Cluster. With these results, it was possible to analyze the influence of a family income, car ownership, position of the individual in the family, use of transportation ""credits"" for transit tariff (mainly for travel mode sequence choice), activities participation (activity sequence choice) and Origin Cluster (destination/travel distance choice). (c) 2010 Elsevier Ltd. All rights reserved.
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This paper presents a family of algorithms for approximate inference in credal networks (that is, models based on directed acyclic graphs and set-valued probabilities) that contain only binary variables. Such networks can represent incomplete or vague beliefs, lack of data, and disagreements among experts; they can also encode models based on belief functions and possibilistic measures. All algorithms for approximate inference in this paper rely on exact inferences in credal networks based on polytrees with binary variables, as these inferences have polynomial complexity. We are inspired by approximate algorithms for Bayesian networks; thus the Loopy 2U algorithm resembles Loopy Belief Propagation, while the Iterated Partial Evaluation and Structured Variational 2U algorithms are, respectively, based on Localized Partial Evaluation and variational techniques. (C) 2007 Elsevier Inc. All rights reserved.
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Purpose - This paper seeks to identify collaboration elements and evaluate their intensity in the Brazilian supermarket retail chain, especially the manufacturer-retailer channel. Design/methodology/approach - A structured questionnaire was elaborated and applied to 125 representatives from suppliers of large supermarket chains. Statistical methods including multivariate analysis were employed. Variables were grouped and composed into five indicators (joint actions, information sharing, interpersonal integration, gains and cost sharing, and strategic integration) to assess the degree of collaboration. Findings - The analyses showed that the interviewees considered interpersonal integration to be of greater importance to collaboration intensity than the other integration factors, such as gain or cost sharing or even strategic integration. Research limitations/implications - The research was conducted solely from the point of view of the industries that supply the large retail networks. The interviews were not conducted in pairs; that is, there was no application of one questionnaire to the retail network and another to the partner industry. Practical implications - Companies should invest in conducting periodic meetings with their partners to increase collaboration intensity, and should carry out technical visits to learn about their partners` logistic reality and thus make better operational decisions. Originality/value - The paper reveals which indicators produce greater collaboration intensity, and thus those that are more relevant to more efficient logistics management.
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Starting from the Durbin algorithm in polynomial space with an inner product defined by the signal autocorrelation matrix, an isometric transformation is defined that maps this vector space into another one where the Levinson algorithm is performed. Alternatively, for iterative algorithms such as discrete all-pole (DAP), an efficient implementation of a Gohberg-Semencul (GS) relation is developed for the inversion of the autocorrelation matrix which considers its centrosymmetry. In the solution of the autocorrelation equations, the Levinson algorithm is found to be less complex operationally than the procedures based on GS inversion for up to a minimum of five iterations at various linear prediction (LP) orders.
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In order to provide adequate multivariate measures of information flow between neural structures, modified expressions of partial directed coherence (PDC) and directed transfer function (DTF), two popular multivariate connectivity measures employed in neuroscience, are introduced and their formal relationship to mutual information rates are proved.
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Functional magnetic resonance imaging (fMRI) has become an important tool in Neuroscience due to its noninvasive and high spatial resolution properties compared to other methods like PET or EEG. Characterization of the neural connectivity has been the aim of several cognitive researches, as the interactions among cortical areas lie at the heart of many brain dysfunctions and mental disorders. Several methods like correlation analysis, structural equation modeling, and dynamic causal models have been proposed to quantify connectivity strength. An important concept related to connectivity modeling is Granger causality, which is one of the most popular definitions for the measure of directional dependence between time series. In this article, we propose the application of the partial directed coherence (PDC) for the connectivity analysis of multisubject fMRI data using multivariate bootstrap. PDC is a frequency domain counterpart of Granger causality and has become a very prominent tool in EEG studies. The achieved frequency decomposition of connectivity is useful in separating interactions from neural modules from those originating in scanner noise, breath, and heart beating. Real fMRI dataset of six subjects executing a language processing protocol was used for the analysis of connectivity. Hum Brain Mapp 30:452-461, 2009. (C) 2007 Wiley-Liss, Inc.
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BACKGROUND: Guidelines for red blood cell (RBC) transfusions exist; however, transfusion practices vary among centers. This study aimed to analyze transfusion practices and the impact of patients and institutional characteristics on the indications of RBC transfusions in preterm infants. STUDY DESIGN AND METHODS: RBC transfusion practices were investigated in a multicenter prospective cohort of preterm infants with a birth weight of less than 1500 g born at eight public university neonatal intensive care units of the Brazilian Network on Neonatal Research. Variables associated with any RBC transfusions were analyzed by logistic regression analysis. RESULTS: Of 952 very-low-birth-weight infants, 532 (55.9%) received at least one RBC transfusion. The percentages of transfused neonates were 48.9, 54.5, 56.0, 61.2, 56.3, 47.8, 75.4, and 44.7%, respectively, for Centers 1 through 8. The number of transfusions during the first 28 days of life was higher in Center 4 and 7 than in other centers. After 28 days, the number of transfusions decreased, except for Center 7. Multivariate logistic regression analysis showed higher likelihood of transfusion in infants with late onset sepsis (odds ratio [OR], 2.8; 95% confidence interval [CI], 1.8-4.4), intraventricular hemorrhage (OR, 9.4; 95% CI, 3.3-26.8), intubation at birth (OR, 1.7; 95% CI, 1.0-2.8), need for umbilical catheter (OR, 2.4; 95% CI, 1.3-4.4), days on mechanical ventilation (OR, 1.1; 95% CI, 1.0-1.2), oxygen therapy (OR, 1.1; 95% CI, 1.0-1.1), parenteral nutrition (OR, 1.1; 95% CI, 1.0-1.1), and birth center (p < 0.001). CONCLUSIONS: The need of RBC transfusions in very-low-birth-weight preterm infants was associated with clinical conditions and birth center. The distribution of the number of transfusions during hospital stay may be used as a measure of neonatal care quality.
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Survival models involving frailties are commonly applied in studies where correlated event time data arise due to natural or artificial clustering. In this paper we present an application of such models in the animal breeding field. Specifically, a mixed survival model with a multivariate correlated frailty term is proposed for the analysis of data from over 3611 Brazilian Nellore cattle. The primary aim is to evaluate parental genetic effects on the trait length in days that their progeny need to gain a commercially specified standard weight gain. This trait is not measured directly but can be estimated from growth data. Results point to the importance of genetic effects and suggest that these models constitute a valuable data analysis tool for beef cattle breeding.
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For the first time, we introduce and study some mathematical properties of the Kumaraswamy Weibull distribution that is a quite flexible model in analyzing positive data. It contains as special sub-models the exponentiated Weibull, exponentiated Rayleigh, exponentiated exponential, Weibull and also the new Kumaraswamy exponential distribution. We provide explicit expressions for the moments and moment generating function. We examine the asymptotic distributions of the extreme values. Explicit expressions are derived for the mean deviations, Bonferroni and Lorenz curves, reliability and Renyi entropy. The moments of the order statistics are calculated. We also discuss the estimation of the parameters by maximum likelihood. We obtain the expected information matrix. We provide applications involving two real data sets on failure times. Finally, some multivariate generalizations of the Kumaraswamy Weibull distribution are discussed. (C) 2010 The Franklin Institute. Published by Elsevier Ltd. All rights reserved.
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Core collections are of strategic importance as they allow the use of a small part of a germplasm collection that is representative of the total collection. The objective of this study was to develop a soybean core collection of the USDA Soybean Germplasm Collection by comparing the results of random, proportional, logarithmic, multivariate proportional and multivariate logarithmic sampling strategies. All but the random sampling strategy used stratification of the entire collection based on passport data and maturity group classification. The multivariate proportional and multivariate logarithmic strategies made further use of qualitative and quantitative trait data to select diverse accessions within each stratum. The 18 quantitative trait data distribution parameters were calculated for each core and for the entire collection for pairwise comparison to validate the sampling strategies. All strategies were adequate for assembling a core collection. The random core collection best represented the entire collection in statistical terms. Proportional and logarithmic strategies did not maximize statistical representation but were better in selecting maximum variability. Multivariate proportional and multivariate logarithmic strategies produced the best core collections as measured by maximum variability conservation. The soybean core collection was established using the multivariate proportional selection strategy. (C) 2010 Elsevier B.V. All rights reserved.
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Germplasm molecular and phenotypic characterization is instrumental to its utilization and to genetic variability incorporation into rice breeding programmes. The diversity within 192 Japanese rice accessions was analysed for 22 agro-morphological traits and 24 single sequence repeat markers. A total of 181 alleles were detected, 38 of which were exclusive. The number of alleles/marker ranged from 2 to 16, with an average of 7.54 alleles/locus and the H(e) value ranged from 0.01 to 0.82, with an average of 0.46. The accessions showed diversity at molecular and phenotypic level and few showed also good agronomic performance. Tocher`s method applied on a total-dissimilarity matrix was used to determine cluster formation of 13 diversity groups. Most of the accessions (81%) were clustered within a group, whereas eight accessions (Kyuushuu, Eika Ine, Ishiwari Mochi, Col/Fukui/1965, Ookuma Nishiki, Suzume Shirazu, Iwate Ryoon and Toga) did not cluster with other accessions.
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The mechanisms involved in the control of growth in chickens are too complex to be explained only under univariate analysis because all related traits are biologically correlated. Therefore, we evaluated broiler chicken performance under a multivariate approach, using the canonical discriminant analysis. A total of 1920 chicks from eight treatments, defined as the combination of four broiler chicken strains (Arbor Acres, AgRoss 308, Cobb 500 and RX) from both sexes, were housed in 48 pens. Average feed intake, average live weight, feed conversion and carcass, breast and leg weights were obtained for days 1 to 42. Canonical discriminant analysis was implemented by SAS((R)) CANDISC procedure and differences between treatments were obtained by the F-test (P < 0.05) over the squared Mahalanobis` distances. Multivariate performance from all treatments could be easily visualised because one graph was obtained from two first canonical variables, which explained 96.49% of total variation, using a SAS((R)) CONELIP macro. A clear distinction between sexes was found, where males were better than females. Also between strains, Arbor Acres, AgRoss 308 and Cobb 500 (commercial) were better than RX (experimental), Evaluation of broiler chicken performance was facilitated by the fact that the six original traits were reduced to only two canonical variables. Average live weight and carcass weight (first canonical variable) were the most important traits to discriminate treatments. The contrast between average feed intake and average live weight plus feed conversion (second canonical variable) were used to classify them. We suggest analysing performance data sets using canonical discriminant analysis.
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The citriculture in Brazil, as well as in other important regions in the world, is based on very few mandarin cultivars. This fact leads to a short harvest period and higher prices for off-season fruit. The `Okitsu` Satsuma (Citrus unshiu Marc.) is among the earliest ripening mandarin cultivars and it is considered to be tolerant to, citrus canker (Xanthomonas citri subsp. citri Schaad et al.) and to citrus variegated chlorosis (Xylella fastidiosa Wells et al.). Despite having regular fruit quality under hot climate conditions, the early fruit maturation and absence of seeds of `Okitsu` fruits are well suited for the local market in the summer(December through March), when the availability of citrus fruits for fresh consumption is limited. Yet, only a few studies have been conducted in Brazil on rootstocks for `Okitsu`. Consequently, a field trial was carried out in Bebeclouro, Sao Paulo State, to evaluate the horticultural performance of `Okitsu` Satsuma mandarin budded onto 12 rootstocks: the citrandarin `Changsha` mandarin (Citrus reticulata Blanco) x Poncirus trifoliata `English Small`: the hybrid Rangpur lime (Citrus limonia Osbeck) x `Swingle` citrumelo (P. trifoliata (L.) Raf. x Citrus paradisi Macfad.); the trifoliates (P. trifoliata (L) Raf)`Rubidoux`,`FCAV` and `Flying Dragon`(P. trifoliata var. monstrosa); the mandarins `Sun Chu Sha Kat`(C. reticulata Blanco) and `Sunki`(Citrus sunki (Hayata) Hort. ex. Tanaka); the Rangpur limes (C. limonia Osbeck) `Cravo Limeira` and `Cravo FCAV`;`Carrizo` citrange (Citrus sinensis x P. trifoliata), `Swingle` citrumelo (P. trifoliata x C. paradisi), and `Orlando` tangelo (C. paradisi x Citrus tangerina cv. `Dancy`). The experimental grove was planted in 2001, using a 6 m x 3 m spacing, in a randomized block design. No supplementary irrigation was applied. Fruit yield, canopy volume, and fruit quality were assessed for each rootstock. A cluster multivariate analysis identified three different rootstock pairs with similar effects on plant growth, yield and fruit quality of `Okitsu` mandarin. The `Flying Dragon `trifoliate had a unique effect over the `Okitsu` trees performance, inducing lower canopy volume and higher yield efficiency and fruit quality, and might be suitable for high-density plantings. The `Cravo Limeira` and `Cravo FCAV` Rangpur limes induced early-ripening of fruits, with low fruit quality. `Sun Chu Sha Kat` and `Sunki` mandarins and the `Orlando` tangelo conferred lower yield efficiency and less content of soluble solids for the latter rootstock. (C) 2009 Elsevier B.V. All rights reserved.
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Despite its outstanding position, the Brazilian citriculture is established on a very limited pool of varieties that limits its expansion and restricts the fruit availability throughout the year. This situation determines the urgent necessity of developing alternative scion and rootstock cultivars, with good performance under local conditions. `Folha Murcha` sweet orange (Citrus sinensis (L.) Osbeck) is a late-harvest cultivar, suitable both for the juice processing industry and the fresh fruit market, being described as tolerant to citrus canker (Xanthomonas citri subsp. citri Schaad et al.), and less affected by citrus variegated chlorosis (Xylella fastidiosa Wells et al.). A study was conducted in Bebedouro, Sao Paulo State, Brazil, to evaluate the horticultural performance of `Folha Murcha` sweet orange budded onto 12 rootstocks: the citrandarin `Changsha` mandarin (Citrus reticulata Blanco) x Poncirus trifoliata `English Small`: the hybrid `Rangpur` lime (Citrus limonia Osbeck) x `Swingle` citrumelo (P. trifoliata (L.) Raf x Citrus paradisi Macfad.); the trifoliates (P. trifoliata (L.) Raf.)`Rubidoux`, `FCAV`, and `Flying Dragon` (P. trifoliata var. monstrosa); the `Sun Chu Sha Kat` mandarin (C. reticulata Blanco); the `Sunki` mandarin (Citrus sunki (Hayata) Hart. ex. Tanaka); the `Rangpur` limes (C. limonia Osbeck) `Cravo Limeira` and `Cravo FCAV`; `Carrizo` citrange (C. sinensis x P. trifoliata), `Swingle` citrumelo (P. trifoliata x C. paradisi), and `Orlando` tangelo (C. paradisi x Citrus tangerina cv. `Dancy`). The experimental grove was planted in 2001, using a 7 m x 4 m spacing, in a randomized block design, with five replications and two plants per plot. No supplementary irrigation was applied. Fruit yield, canopy volume, tree tolerance to drought and to citrus variegated chlorosis, and fruit quality were assessed for each rootstock. Trees grafted onto the `Flying Dragon` trifoliate were smaller in size, but had largest yield efficiency when compared to those grafted onto other rootstocks. Lower alternate bearing index was observed on trees budded onto `Cravo FCAV` `Rangpur` lime. Both `Rangpur` lime rootstocks and the `Sunki` mandarin induced higher tree tolerance to drought. The `Flying Dragon` trifoliate induced better fruit quality and higher tolerance to citrus variegated chlorosis (CVC) to `Folha Murcha` trees. A cluster multivariate analysis identified three groups of rootstocks with similar effects on `Folha Murcha` tree performance. Among the 12 evaluated rootstocks, the `Flying Dragon` trifoliate has a unique effect on plant growth, tolerance to drought and CVC, fruit yield and fruit quality of `Folha Murcha` trees, and may be better suited for high-density plantings. (C) 2011 Elsevier B.V. All rights reserved.
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Beneficial bacteria interact with plants by colonizing the rhizosphere and roots followed by further spread through the inner tissues, resulting in endophytic colonization. The major factors contributing to these interactions are not always well understood for most bacterial and plant species. It is believed that specific bacterial functions are required for plant colonization, but also from the plant side specific features are needed, such as plant genotype (cultivar) and developmental stage. Via multivariate analysis we present a quantification of the roles of these components on the composition of root-associated and endophytic bacterial communities in potato plants, by weighing the effects of bacterial inoculation, plant genotype and developmental stage. Spontaneous rifampicin resistant mutants of two bacterial endophytes, Paenibacillus sp. strain E119 and Methylobacterium mesophilicum strain SR1.6/6, were introduced into potato plants of three different cultivars (Eersteling, Robijn and Karnico). Densities of both strains in, or attached to potato plants were measured by selective plating, while the effects of bacterial inoculation, plant genotype and developmental stage on the composition of bacterial, Alphaproteobacterial and Paenibacillus species were determined by PCR-denaturing gradient gel-electrophoresis (DGGE). Multivariate analyses revealed that the composition of bacterial communities was mainly driven by cultivar type and plant developmental stage, while Alphaproteobacterial and Paenibacillus communities were mainly influenced by bacterial inoculation. These results are important for better understanding the effects of bacterial inoculations to plants and their possible effects on the indigenous bacterial communities in relation with other plant factors such as genotype and growth stage.