941 resultados para Cadeias de Markov. Algoritmos gen
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Welsch (Projektbearbeiter): Frisch-fröhliches Gedicht anläßlich der Niederschlagung der badischen revolutionären Aufstände vom April und September 1848 mit Hilfe von Bundestruppen des VIII. Armeekorps (württembergisches, hessisches und nassauisches Militär)
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Welsch (Projektbearbeiter): Weder die Preußische Nationalversammlung noch das Ministerium Camphausen, weder das Militär, noch der Berliner Magistrat treten für die Rechte, das Wohl und die Freiheit des Volkes ein; dies kann nur das Volk selbst tun. "Alles ist faul, oberfaul - nur das Volk in seinem gesunden Kerne nicht. Verlaßt euch auf euch selbst! Stehet oder fallet Alle für einen Mann!"
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Robert Eisler
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Julius Böhmer
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David Kaufmann
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David Kaufmann
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Von Dr. Günther Enderlein
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Bibliograph. Nachweis: Harms I,224
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Gelegenheitsschrift zur Wahl und Krönung von Matthias zum Römisch-Deutschen Kaiser
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Gelegenheitsschrift zur Wahl und Krönung von Matthias zum Römisch-Deutschen Kaiser
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Gelegenheitsschrift zur Wahl und Krönung von Matthias zum Römisch-Deutschen Kaiser
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Gelegenheitsschrift zur Wahl und Krönung von Matthias zum Römisch-Deutschen Kaiser
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The discrete-time Markov chain is commonly used in describing changes of health states for chronic diseases in a longitudinal study. Statistical inferences on comparing treatment effects or on finding determinants of disease progression usually require estimation of transition probabilities. In many situations when the outcome data have some missing observations or the variable of interest (called a latent variable) can not be measured directly, the estimation of transition probabilities becomes more complicated. In the latter case, a surrogate variable that is easier to access and can gauge the characteristics of the latent one is usually used for data analysis. ^ This dissertation research proposes methods to analyze longitudinal data (1) that have categorical outcome with missing observations or (2) that use complete or incomplete surrogate observations to analyze the categorical latent outcome. For (1), different missing mechanisms were considered for empirical studies using methods that include EM algorithm, Monte Carlo EM and a procedure that is not a data augmentation method. For (2), the hidden Markov model with the forward-backward procedure was applied for parameter estimation. This method was also extended to cover the computation of standard errors. The proposed methods were demonstrated by the Schizophrenia example. The relevance of public health, the strength and limitations, and possible future research were also discussed. ^
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The tobacco-specific nitrosamine 4-(methylnitrosamino)-1-(3-pyridyl)-1-butanone (NNK) is an obvious carcinogen for lung cancer. Since CBMN (Cytokinesis-blocked micronucleus) has been found to be extremely sensitive to NNK-induced genetic damage, it is a potential important factor to predict the lung cancer risk. However, the association between lung cancer and NNK-induced genetic damage measured by CBMN assay has not been rigorously examined. ^ This research develops a methodology to model the chromosomal changes under NNK-induced genetic damage in a logistic regression framework in order to predict the occurrence of lung cancer. Since these chromosomal changes were usually not observed very long due to laboratory cost and time, a resampling technique was applied to generate the Markov chain of the normal and the damaged cell for each individual. A joint likelihood between the resampled Markov chains and the logistic regression model including transition probabilities of this chain as covariates was established. The Maximum likelihood estimation was applied to carry on the statistical test for comparison. The ability of this approach to increase discriminating power to predict lung cancer was compared to a baseline "non-genetic" model. ^ Our method offered an option to understand the association between the dynamic cell information and lung cancer. Our study indicated the extent of DNA damage/non-damage using the CBMN assay provides critical information that impacts public health studies of lung cancer risk. This novel statistical method could simultaneously estimate the process of DNA damage/non-damage and its relationship with lung cancer for each individual.^