Multivariate models for correlated count data

In this study, we deal with the problem of overdispersion beyond extra zeros for a collection of counts that can be correlated. Poisson, negative binomial, zero-inflated Poisson and zero-inflated negative binomial distributions have been considered. First, we propose a multivariate count model in which all counts follow the same distribution and are correlated. Then we extend this model in a sense that correlated counts may follow different distributions. To accommodate correlation among counts, we have considered correlated random effects for each individual in the mean structure, thus inducing dependency among common observations to an individual. The method is applied to real data to investigate variation in food resources use in a species of marsupial in a locality of the Brazilian Cerrado biome. © 2013 Copyright Taylor and Francis Group, LLC.

Choosing between Cox proportional hazards and logistic models for interval-censored data via bootstrap

This work develops a new methodology in order to discriminate models for interval-censored data based on bootstrap residual simulation by observing the deviance difference from one model in relation to another, according to Hinde (1992). Generally, this sort of data can generate a large number of tied observations and, in this case, survival time can be regarded as discrete. Therefore, the Cox proportional hazards model for grouped data (Prentice & Gloeckler, 1978) and the logistic model (Lawless, 1982) can befitted by means of generalized linear models. Whitehead (1989) considered censoring to be an indicative variable with a binomial distribution and fitted the Cox proportional hazards model using complementary log-log as a link function. In addition, a logistic model can be fitted using logit as a link function. The proposed methodology arises as an alternative to the score tests developed by Colosimo et al. (2000), where such models can be obtained for discrete binary data as particular cases from the Aranda-Ordaz distribution asymmetric family. These tests are thus developed with a basis on link functions to generate such a fit. The example that motivates this study was the dataset from an experiment carried out on a flax cultivar planted on four substrata susceptible to the pathogen Fusarium oxysoprum. The response variable, which is the time until blighting, was observed in intervals during 52 days. The results were compared with the model fit and the AIC values.

Electric load forecasting using a fuzzy ART&ARTMAP neural network

This work presents a neural network based on the ART architecture ( adaptive resonance theory), named fuzzy ART& ARTMAP neural network, applied to the electric load-forecasting problem. The neural networks based on the ARTarchitecture have two fundamental characteristics that are extremely important for the network performance ( stability and plasticity), which allow the implementation of continuous training. The fuzzy ART& ARTMAP neural network aims to reduce the imprecision of the forecasting results by a mechanism that separate the analog and binary data, processing them separately. Therefore, this represents a reduction on the processing time and improved quality of the results, when compared to the Back-Propagation neural network, and better to the classical forecasting techniques (ARIMA of Box and Jenkins methods). Finished the training, the fuzzy ART& ARTMAP neural network is capable to forecast electrical loads 24 h in advance. To validate the methodology, data from a Brazilian electric company is used. (C) 2004 Elsevier B.V. All rights reserved.

Variabilidade genética intrapopulacional em Myracrodruon urundeuva Fr. All. por marcador AFLP

Levels of genetic variability for in situ and ex situ genetic conservation were estimated in a population of Myracrodruon urundeuva using the PCR (polymerase chain reaction) technique with the AFLP (Amplified fragment-length polymorphism) genetic marker. Seeds for progeny tests were collected from 30 open-pollination trees (matrices) at Paulo de Faria Ecological Station - SP. From this genetic material, three progeny tests were installed on the Teaching and Research Farm of Ilha Solteira Faculty of Engineering - University of São Paulo State (UNESP), which is located in Selvlria - MS, Brazil. The analysis by genetic marker was conducted with three combinations of different starters EcoRl-Msel, resulting in a total number of 137 polymorphic bands, thus forming a table of binary data. These data were used for the analysis of genetic divergence and distance between progenies. High levels of genetic divergence were observed among families. Based on the Analysis of Molecular Variance (AMOVA), it was shown that 16.2% of genetic diversity is found among progenies and 83.8% within progenies, which suggests deviances of random matings. The grouping of progenies, based on genetic distances, suggests that progenies deriving from trees which are close to each other tend to be more similar. This, in turn, indicates that the population originating the seeds may be genetically structured.

Detection of cavitated approximal surfaces using cone beam CT and intraoral receptors

Objectives: The aim of this study was to compare cone beam CT (CBCT) in a small field of view (FOV) with a solid-state sensor and a photostimulable phosphor plate system for detection of cavitated approximal surfaces. Methods: 257 non-filled approximal surfaces from human permanent premolars and molars were recorded by two intraoral digital receptors, a storage phosphor plate (Digora Optime, Soredex) and a solid-state CMOS sensor (Digora Toto, Soredex), and scanned in a cone beam CT unit (3D Accuitomo FPD80, Morita) with a FOV of 4 cm and a voxel size of 0.08 mm. Image sections were carried out in the axial and mesiodistal tooth planes. Six observers recorded surface cavitation in all images. Validation of the true absence or presence of surface cavitation was performed by inspecting the surfaces under strong light with the naked eye. Differences in sensitivity, specificity and agreement were estimated by analysing the binary data in a generalized linear model using an identity link function. Results: A significantly higher sensitivity was obtained by all observers with CBCT (p,0.001), which was not compromised by a lower specificity. Therefore, a significantly higher overall agreement was obtained with CBCT (p,0.001). There were no significant differences between the Digora Optime phosphor plate system and the Digora Toto CMOS sensor for any parameter. Conclusions: CBCT was much more accurate in the detection of surface cavitation in approximal surfaces than intraoral receptors. The differences are interpreted as clinically significant. A CBCT examination performed for other reasons should also be assessed for approximal surface cavities in teeth without restorations. © 2013 The British Institute of Radiology.

Resistência da seringueira ao mal das folhas e modelagem no patossistema Hevea sp. – Microcyclus ulei através dos parâmetros monocíclicos

Pós-graduação em Ciência Florestal - FCA

Análise dinâmica de contingências de sistemas de energia elétrica por redes neurais baseadas na teoria da ressonância adaptativa

Pós-graduação em Engenharia Elétrica - FEIS

Caracterização da diversidade genética de Stryphnodendron adstringens (Mart.) Coville por marcador molecular AFLP e transferência de microssatélites

Pós-graduação em Agronomia (Horticultura) - FCA

Abordagem multivariada, perfil composicional e construção de curva de calibração para predição do teor de óleo em Jatropha curcas L

Pós-graduação em Agronomia (Genética e Melhoramento de Plantas) - FCAV

Modelos lineares generalizados mistos e equações de estimação generalizadas para dados binário aplicados em anestesiologia veterinária

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Variações sazonais dos níveis plasmáticos do esteroide sexual 17β-estradiol (e2) em fêmeas de matrinxã (brycon amazonicus)

Pós-graduação em Ciência e Tecnologia Animal - FEIS

Modelos lineares generalizados bayesianos para dados longitudinais

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

Exploração e análise de dados coletados pelo sistema integrado de monitoramento ambiental utilizando técnicas de visual analytics

Pós-graduação em Ciências Cartográficas - FCT

Multivariate analysis of stable isotope data in the traceability process for birds

A análise isotópica tem se mostrado uma ferramenta de suma importância ao processo de rastreabilidade, no entanto, existem divergências nas análises estatísticas dos resultados, uma vez que os dados são dependentes e advindos de vários elementos químicos tais como Carbono, Hidrogênio, Oxigênio, Nitrogênio e Enxofre (CHON'S). Com o intuito de estabelecer a análise propícia para os dados de rastreabilidade em aves pela técnica de isótopos estáveis e avaliar a necessidade da análise conjunta das variáveis, foram usados dados de carbono-13 e de nitrogênio-15 de ovos (albúmen + gema) de poedeiras e músculo peitoral de frangos de corte, os quais foram submetidos à análise estatística univariada (Anova e complementada pelo teste de Tukey) e multivariada (Manova e Discriminante). Os dados foram analisados no software Minitab 16, e os resultados, consolidados na teoria, confirmam a necessidade de análise multivariada, mostrando também que a análise discriminante esclarece as dúvidas apresentadas nos resultados de outros métodos de análise comparados nesta pesquisa.

Determination of disease biomarkers in Eucalyptus by comprehensive two-dimensional gas chromatography and multivariate data analysis

In this paper is reported the use of the chromatographic profiles of volatiles to determine disease markers in plants - in this case, leaves of Eucalyptus globulus contaminated by the necrotroph fungus Teratosphaeria nubilosa. The volatile fraction was isolated by headspace solid phase microextraction (HS-SPME) and analyzed by comprehensive two-dimensional gas chromatography-fast quadrupole mass spectrometry (GC. ×. GC-qMS). For the correlation between the metabolic profile described by the chromatograms and the presence of the infection, unfolded-partial least squares discriminant analysis (U-PLS-DA) with orthogonal signal correction (OSC) were employed. The proposed method was checked to be independent of factors such as the age of the harvested plants. The manipulation of the mathematical model obtained also resulted in graphic representations similar to real chromatograms, which allowed the tentative identification of more than 40 compounds potentially useful as disease biomarkers for this plant/pathogen pair. The proposed methodology can be considered as highly reliable, since the diagnosis is based on the whole chromatographic profile rather than in the detection of a single analyte. © 2013 Elsevier B.V..