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Técnicas não-paramétricas e paramétricas usadas na análise de sobrevivência de Chrysoperla externa (Neuroptera: Chrysopidae) / Non-Parametric and Parametric Techniques used in the survival analysis of Chrysoperla externa (Neuroptera: Chrysopidae)Miranda, Marconi Silva 13 March 2012 (has links)
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Previous issue date: 2012-03-13 / In survival analysis, the response variable is the time of occurrence of an event of interest, denominated failure time. Another characteristic of the survival analysis is to incorporate to the study incomplete sample data, in which for a
determined reason the occurrence of the event was not verified, being these data defined as censured. The objective of this paper was to compare the use of the parametric and non-parametric techniques to estimate the survival time of C. externa (Neuroptera: Chrysopidae), predator insect which feed on other insects as well as mite, under the effect of three commercial products nim-based: Neempro (10 g of
azadirachtina L-1), Organic neem (3,3 g of Azadirachtina L-1) and Natuneem (1,5 g of azadirachtina L-1). With this objective the survival functions for the different concentrations of each product, through the non-parametric method of Kaplan-Meier
were estimated and compared by the logrank test and by parametric techniques, using the Weibull and log-normal exponential tests. Besides that, a study in order to select the most parsimonious model was done, using for that the likelihood ratio test (LRT) as well as the Akaike information criterion (AIC). The estimates of the selected parametric model were used to determine the survival functions in the
concentrations of the three products, with the purpose of comparing with the nonparametric estimator Kaplan-Meier. Once the best model was defined the median survival time of C. externa was calculated in the tested concentrations of the
products. Taking into consideration the conditions described in this experiment, one can conclude that the concentrations of the nim-based products have influence in the survival of C. externa. The higher the concentration of the used products, the lower was the survival time and among the evaluated products, Neempro was the one which presented the least lethal to the natural predator. / Em análise de sobrevivência, a variável resposta é o tempo de ocorrência de um evento de interesse, denominado tempo de falha. Outra característica da análise de sobrevivência é incorporar ao estudo dados amostrais incompletos, que por algum motivo a ocorrência do evento não foi verificada, dados estes definidos como censurados. O objetivo deste trabalho foi comparar o uso das técnicas paramétricas e não-paramétricas para estimar o tempo de sobrevivência de C. externa (Neuroptera: Chrysopidae), inseto predador que se alimenta de outros insetos e ácaros, sob efeito de três produtos comerciais à base de nim: Neempro (10 g de azadirachtina L-1), Organic neem (3,3 g de Azadirachtina L-1) e Natuneem (1,5 g de azadiractina L-1). Com esse objetivo foram estimadas as funções de sobrevivência para as diferentes
concentrações de cada produto, por meio do método não-paramétrico de Kaplan-Meier, e comparadas pelo teste logrank e por meio das técnicas paramétricas, utilizando os modelos exponencial, de Weibull e log-normal. Foi realizado ainda, um
estudo com a finalidade de selecionar o modelo mais parcimonioso, utilizando para isto o teste da razão de verossimilhança (TRV) e o critério de informação de Akaike
(AIC). As estimativas do modelo paramétrico selecionado foram usadas para determinar as funções de sobrevivência nas concentrações dos três produtos, com o objetivo de comparar com o estimador não-paramétrico de Kaplan-Meier. Definido o
melhor modelo foi calculado o tempo mediano de sobrevivência do C. externa nas concentrações testadas dos produtos. Levando em consideração as condições descritas neste experimento, pode-se concluir que as concentrações dos produtos a base de nim possuem influencia na sobrevivência de C. externa. Quanto maior foi a concentração dos produtos utilizados, menor foi o tempo de sobrevivência e entre os
produtos avaliados o Neempro foi o que apresentou ser o menos letal ao predador natural.
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Variational Bayesian Learning and its ApplicationsZhao, Hui January 2013 (has links)
This dissertation is devoted to studying a fast and analytic approximation method, called the variational Bayesian (VB) method, and aims to give insight into its general applicability and usefulness, and explore its applications to various real-world problems. This work has three main foci: 1) The general applicability and properties; 2) Diagnostics for VB approximations; 3) Variational applications.
Generally, the variational inference has been developed in the context of the exponential family, which is open to further development. First, it usually consider the cases in the context of the conjugate exponential family. Second, the variational inferences are developed only with respect to natural parameters, which are often not the parameters of immediate interest. Moreover, the full factorization, which assumes all terms to be independent of one another, is the most commonly used scheme in the most of the variational applications. We show that VB inferences can be extended to a more general situation. We propose a special parameterization for a parametric family, and also propose a factorization scheme with a more general dependency structure than is traditional in VB. Based on these new frameworks, we develop a variational formalism, in which VB has a fast implementation, and not be limited to the conjugate exponential setting. We also investigate its local convergence property, the effects of choosing different priors, and the effects of choosing different factorization scheme.
The essence of the VB method relies on making simplifying assumptions about the posterior dependence of a problem. By definition, the general posterior dependence structure is distorted. In addition, in the various applications, we observe that the posterior variances are often underestimated. We aim to develop diagnostics test to assess VB approximations, and these methods are expected to be quick and easy to use, and to require no sophisticated tuning expertise. We propose three methods to compute the actual posterior covariance matrix by only using the knowledge obtained from VB approximations: 1) To look at the joint posterior distribution and attempt to find an optimal affine transformation that links the VB and true posteriors; 2) Based on a marginal posterior density approximation to work in specific low dimensional directions to estimate true posterior variances and correlations; 3) Based on a stepwise conditional approach, to construct and solve a set of system of equations that lead to estimates of the true posterior variances and correlations. A key computation in the above methods is to calculate a uni-variate marginal or conditional variance. We propose a novel way, called the VB Adjusted Independent Metropolis-Hastings (VBAIMH) method, to compute these quantities. It uses an independent Metropolis-Hastings (IMH) algorithm with proposal distributions configured by VB approximations. The variance of the target distribution is obtained by monitoring the acceptance rate of the generated chain.
One major question associated with the VB method is how well the approximations can work. We particularly study the mean structure approximations, and show how it is possible using VB approximations to approach model selection tasks such as determining the dimensionality of a model, or variable selection.
We also consider the variational application in Bayesian nonparametric modeling, especially for the Dirichlet process (DP). The posterior inference for DP has been extensively studied in the context of MCMC methods. This work presents a a full variational solution for DP with non-conjugate settings. Our solution uses a truncated stick-breaking representation. We propose an empirical method to determine the number of distinct components in a finite dimensional DP. The posterior predictive distribution for DP is often not available in a closed form. We show how to use the variational techniques to approximate this quantity.
As a concrete application study, we work through the VB method on regime-switching lognormal models and present solutions to quantify both the uncertainty in the parameters and model specification. Through a series numerical comparison studies with likelihood based methods and MCMC methods on the simulated and real data sets, we show that the VB method can recover exactly the model structure, gives the reasonable point estimates, and is very computationally efficient.
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Análise de sobrevivência do tomateiro a Phytophthora infestans / Analysis of the survival of the tomato plant Phytophthora infestansAraujo, Maria Nilsa Martins de 05 September 2008 (has links)
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Previous issue date: 2008-09-05 / Coordenação de Aperfeiçoamento de Pessoal de Nível Superior / Reburning caused by Phytophthora infestansis is characterized as an aggressive disease of great destructive impact, capable of limiting or even hindering the economic cultivation of the tomato plant under conditions of high humidity and low temperatures. In view of the problems reburning can cause to tomato plant crops, this work aimed to: 1) fit models to describe the progress of the disease and form groups of tomato accesses with similar curves; 2) estimate data referring to the number of days to reach 5% severity of the disease, by means of inverse regression; 3) fit survival curves by means of the Kaplan-Meier estimator for the access groups and compare them by means of the Logrank test;4)fit survival curves by means of probabilistic models and compare these curves with Kaplan Meir´s non-parametric technique. Using tomato reburning real data, it was possible to fit the exponential model (Y = y0 exp (rX)) to
describe the disease s progress. The means of the parameter estimates were submitted to grouping analysis using the centroid method, generating 10 access groups. Time up to 5% of the disease was calculated via inverse regression. Non-parametric techniques were used to estimate survival function by means of the Kaplan-Meier´s estimator to compare the survival curves by the Logrank test .The survival function was also fit using the probabilistic models, exponential Weibull and Log-normal, respectively, which were compared by means of the verisimilitude ratio test (VRT), considering the generalized Gamma model, as a general case for these models. The methodology applied allowed fitting the exponential model to describe tomato plant reburning progress and to regroup the accesses studied in the 10 groups. The access BGH-6 obtained a smaller disease progress than the others, thus characterizing its higher resistance to the disease; An inverse regression allowed time estimation up to the occurrence of 5% of the severity of the tomato plant reburning. The Kaplan-Meier ´s non-parametric technique allowed estimating the survival curves of the tomato plant accesses belonging to the groups 1, 2, 4, 6 and 8. Utilizing the Logrank test, it could be
concluded that most two-by-two comparisons were significant (p<0.05), except in the comparisons of groups 2x4, 4x8 and 6x8. The use of the probabilistic models, exponential Weibull and Log-normal allowed estimating the survival curves of groups 2, 4, 6 and 8, except for group 4, to which the Weibull model was not adequate. Comparing the probabilistic models with the non-parametric technique, the curves of
the probabilistic models of groups 2 and 4 presented satisfactory results, compared to the curve estimated by Kaplan-Meier. / A requeima causada por Phytophthora infestans caracteriza-se por ser uma doença agressiva e de grande impacto destrutivo, podendo limitar ou até mesmo impedir o cultivo econômico do tomateiro sob condições de alta umidade e baixas temperaturas. Diante dos problemas que a requeima pode provocar às lavouras de tomate, este trabalho teve por objetivos: 1) ajustar modelos para descrever o progresso da doença e formar grupos de acessos de tomateiro com curvas semelhantes; 2) estimar dados referentes ao número de dias até atingir 5% de severidade da doença, por meio de regressão inversa; 3) ajustar curvas de sobrevivência por meio do estimador de Kaplan-Meier para grupos de acessos e compará-las mediante o uso do teste Logrank; 4) ajustar curvas de sobrevivência por meio de modelos probabilísticos e compará-las com a técnica não-paramétrica de Kaplan-Meier. Utilizando dados reais sobre a requeima do tomateiro, foi possível ajustar o modelo exponencial (Y = y0 exp (rX)) para descrever o progresso da doença. As médias das estimativas dos parâmetros foram submetidas à análise de agrupamento pelo método Centróide, o que gerou 10 grupos de acessos, sendo o tempo até a incidência de 5% da doença calculado via regressão inversa. Foram utilizadas técnicas não-paramétricas para estimar a função de sobrevivência por meio
do estimador de Kaplan-Meier e para comparar as curvas de sobrevivência pelo teste Logrank. Foi também ajustada a função de sobrevivência, empregando-se os modelos probabilísticos Exponencial, Weibull e Log-normal, os quais foram comparados por meio do Teste da Razão da Verossimilhança (TRV), considerando-se o modelo Gama generalizado por ser caso geral para esses modelos. A metodologia utilizada permitiu ajustar o modelo Exponencial para descrever o progresso da requeima do tomateiro e agrupar os acessos estudados em 10 grupos. O acesso BGH-6 sofreu um progresso de doença menor que os demais, caracterizando-se, assim, sua maior resistência à enfermidade. A regressão inversa possibilitou estimar o tempo até a ocorrência de 5% da severidade da requeima do tomateiro. Pela técnica não-paramétrica de Kaplan-Meier, foi possível estimar as curvas de sobrevivência dos acessos de tomateiro pertencentes aos grupos 1, 2, 4, 6 e 8. Utilizando o teste Logrank, pode-se concluir que a maioria das comparações duas a duas foi significativa (p<0,05), exceto nas comparações dos grupos 2x4, 4x8 e 6x8. O uso dos modelos probabilísticos Exponencial, Weibull e Log-normal possibilitou a estimação das curvas de sobrevivência nos grupos 2, 4, 6 e 8, exceto no grupo 4, em que o modelo Weibull não foi adequado. Comparando os modelos probabilísticos com a técnica não-paramétrica, as curvas dos modelos probabilísticos dos grupos 2 e 4 apresentaram ajustes satisfatórios com relação à curva estimada por Kaplan-Meier.
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