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Développement d'une nouvelle technique de pointé automatique pour les données de sismique réfraction / Development of a new adaptive algorithm for automatic picking of seismic refraction dataKhalaf, Amin 15 February 2016 (has links)
Un pointé précis des temps de premières arrivées sismiques joue un rôle important dans de nombreuses études d’imagerie sismique. Un nouvel algorithme adaptif est développé combinant trois approches associant l’utilisation de fenêtres multiples imbriquées, l’estimation des propriétés statistiques d’ordre supérieur et le critère d’information d’Akaike. L’algorithme a l’avantage d’intégrer plusieurs propriétés (l’énergie, la gaussianité, et la stationnarité) dévoilant la présence des premières arrivées. Tandis que les incertitudes de pointés ont, dans certains cas, d’importance équivalente aux pointés eux-mêmes, l’algorithme fournit aussi automatiquement une estimation sur leur incertitudes. La précision et la fiabilité de cet algorithme sont évaluées en comparant les résultats issus de ce dernier avec ceux provenant d’un pointé manuel, ainsi que d’autres pointeurs automatiques. Cet algorithme est simple à mettre en œuvre et ne nécessite pas de grandes performances informatiques. Cependant, la présence de bruit dans les données peut en dégrader la performance. Une double sommation dans le domaine temporel est alors proposée afin d’améliorer la détectabilité des premières arrivées. Ce processus est fondé sur un principe clé : la ressemblance locale entre les traces stackées. Les résultats montrent l’intérêt qu’il y a à appliquer cette sommation avant de réaliser le pointé automatique. / Accurate picking of first arrival times plays an important role in many seismic studies, particularly in seismic tomography and reservoirs or aquifers monitoring. A new adaptive algorithm has been developed based on combining three picking methods (Multi-Nested Windows, Higher Order Statistics and Akaike Information Criterion). It exploits the benefits of integrating three properties (energy, gaussianity, and stationarity), which reveal the presence of first arrivals. Since time uncertainties estimating is of crucial importance for seismic tomography, the developed algorithm provides automatically the associated errors of picked arrival times. The comparison of resulting arrival times with those picked manually, and with other algorithms of automatic picking, demonstrates the reliable performance of this algorithm. It is nearly a parameter-free algorithm, which is straightforward to implement and demands low computational resources. However, high noise level in the seismic records declines the efficiency of the developed algorithm. To improve the signal-to-noise ratio of first arrivals, and thereby to increase their detectability, double stacking in the time domain has been proposed. This approach is based on the key principle of the local similarity of stacked traces. The results demonstrate the feasibility of applying the double stacking before the automatic picking.
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Lag length selection for vector error correction modelsSharp, Gary David January 2010 (has links)
This thesis investigates the problem of model identification in a Vector Autoregressive framework. The study reviews the existing research, conducts an extensive simulation based analysis of thirteen information theoretic criterion (IC), one of which is a novel derivation. The simulation exercise considers the evaluation of seven alternative error restricted vector autoregressive models with four different lag lengths. Alternative sample sizes and parameterisations are also evaluated and compared to results in the existing literature. The results of the comparative analysis provide strong support for the efficiency based criterion of Akaike and in particular the selection capability of the novel criterion, referred to as a modified corrected Akaike information criterion, demonstrates useful finite sample properties.
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Information Content in Data Sets: A Review of Methods for Interrogation and Model ComparisonBanks, H. Thomas, Joyner, Michele L. 01 January 2018 (has links)
In this reviewwe discuss methodology to ascertain the amount of information in given data sets with respect to determination of model parameters with desired levels of uncertainty.We do this in the context of least squares (ordinary,weighted, iterative reweightedweighted or "generalized", etc.) based inverse problem formulations. The ideas are illustrated with several examples of interest in the biological and environmental sciences.
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Change Point Analysis for Lognormal Distribution Based on Schwarz Information CriterionCooper, Richard 12 August 2020 (has links)
No description available.
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Model selectionHildebrand, Annelize 11 1900 (has links)
In developing an understanding of real-world problems,
researchers develop mathematical and statistical models. Various
model selection methods exist which can be used to obtain a
mathematical model that best describes the real-world situation
in some or other sense. These methods aim to assess the merits
of competing models by concentrating on a particular criterion.
Each selection method is associated with its own criterion and
is named accordingly. The better known ones include Akaike's
Information Criterion, Mallows' Cp and cross-validation, to name
a few. The value of the criterion is calculated for each model
and the model corresponding to the minimum value of the criterion
is then selected as the "best" model. / Mathematical Sciences / M. Sc. (Statistics)
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Model selectionHildebrand, Annelize 11 1900 (has links)
In developing an understanding of real-world problems,
researchers develop mathematical and statistical models. Various
model selection methods exist which can be used to obtain a
mathematical model that best describes the real-world situation
in some or other sense. These methods aim to assess the merits
of competing models by concentrating on a particular criterion.
Each selection method is associated with its own criterion and
is named accordingly. The better known ones include Akaike's
Information Criterion, Mallows' Cp and cross-validation, to name
a few. The value of the criterion is calculated for each model
and the model corresponding to the minimum value of the criterion
is then selected as the "best" model. / Mathematical Sciences / M. Sc. (Statistics)
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Crystallographic Image Processing with Unambiguous 2D Bravais Lattice Identification on the Basis of a Geometric Akaike Information CriterionBilyeu, Taylor Thomas 02 July 2013 (has links)
Crystallographic image processing (CIP) is a technique first used to aid in the structure determination of periodic organic complexes imaged with a high-resolution transmission electron microscope (TEM). The technique has subsequently been utilized for TEM images of inorganic crystals, scanning TEM images, and even scanning probe microscope (SPM) images of two-dimensional periodic arrays. We have written software specialized for use on such SPM images. A key step in the CIP process requires that an experimental image be classified as one of only 17 possible mathematical plane symmetry groups. The current methods used for making this symmetry determination are not entirely objective, and there is no generally accepted method for measuring or quantifying deviations from ideal symmetry. Here, we discuss the crystallographic symmetries present in real images and the general techniques of CIP, with emphasis on the current methods for symmetry determination in an experimental 2D periodic image. The geometric Akaike information criterion (AIC) is introduced as a viable statistical criterion for both quantifying deviations from ideal symmetry and determining which 2D Bravais lattice best fits the experimental data from an image being processed with CIP. By objectively determining the statistically favored 2D Bravais lattice, the determination of plane symmetry in the CIP procedure can be greatly improved. As examples, we examine scanning tunneling microscope images of 2D molecular arrays of the following compounds: cobalt phthalocyanine on Au (111) substrate; nominal cobalt phthalocyanine on Ag (111); tetraphenoxyphthalocyanine on highly oriented pyrolitic graphite; hexaazatriphenylene-hexacarbonitrile on Ag (111). We show that the geometric AIC procedure can unambiguously determine which 2D Bravais lattice fits the experimental data for a variety of different lattice types. In some cases, the geometric AIC procedure can be used to determine which plane symmetry group best fits the experimental data, when traditional CIP methods fail to do so.
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Algoritmos genéticos em inferência de redes gênicasJiménez, Ray Dueñas January 2014 (has links)
Orientador: Prof. Dr. David Correa Martins Júnior / Dissertação (mestrado) - Universidade Federal do ABC, Programa de Pós-Graduação em Ciência da Computação, 2014.
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Risk factor modeling of Hedge Funds' strategies / Risk factor modeling of Hedge Funds' strategiesRadosavčević, Aleksa January 2017 (has links)
This thesis aims to identify main driving market risk factors of different strategies implemented by hedge funds by looking at correlation coefficients, implementing Principal Component Analysis and analyzing "loadings" for first three principal components, which explain the largest portion of the variation of hedge funds' returns. In the next step, a stepwise regression through iteration process includes and excludes market risk factors for each strategy, searching for the combination of risk factors which will offer a model with the best "fit", based on The Akaike Information Criterion - AIC and Bayesian Information Criterion - BIC. Lastly, to avoid counterfeit results and overcome model uncertainty issues a Bayesian Model Average - BMA approach was taken. Key words: Hedge Funds, hedge funds' strategies, market risk, principal component analysis, stepwise regression, Akaike Information Criterion, Bayesian Information Criterion, Bayesian Model Averaging Author's e-mail: aleksaradosavcevic@gmail.com Supervisor's e-mail: mp.princ@seznam.cz
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Biomassa de epífitas vasculares em floresta de restinga na Mata Atlântica / Biomass of vascular epiphytes in seasonally flooded coastal forest (restinga) in the Atlantic ForestBakker, Yvonne Vanessa, 1975- 27 August 2018 (has links)
Orientador: Simone Aparecida Vieira / Dissertação (mestrado) - Universidade Estadual de Campinas, Instituto de Biologia / Made available in DSpace on 2018-08-27T10:19:45Z (GMT). No. of bitstreams: 1
Bakker_YvonneVanessa_M.pdf: 1853475 bytes, checksum: 2ff87ee7761a486f4b4ef47d5be567c8 (MD5)
Previous issue date: 2015 / Resumo: A Mata Atlântica é um dos principais biomas do mundo sendo considerada um dos 25 hotspots de biodiversidade. Dentre os ecossistemas associados à Mata Atlântica, a Floresta de Restinga foi quase totalmente dizimada, restando apenas 0,5% de sua área original. A Restinga se caracteriza por ocorrer nos cordões arenosos ao longo da costa onde o solo é distrófico e sujeito a inundações sazonais. Entre as comunidades que ocorrem nas florestas de restinga, destacam-se as epífitas vasculares que, por não terem contato com o solo, possuem adaptações ecológicas que garantem a aquisição de nutrientes via deposição seca e úmida. Para avaliar o papel das epífitas vasculares no funcionamento das Florestas de Restinga realizou-se o levantamento quantitativo da biomassa das epífitas vasculares em uma área de um hectare de Floresta de Restinga, no Núcleo Picinguaba do Parque Estadual da Serra do Mar (PESM), no litoral norte paulista, município de Ubatuba. Para tanto, foi coletado todo o material epifítico presente em 23 forófitos com DAP entre 4,9 e 41,7 cm, previamente selecionados. Cada forófito foi dividido por zonas ecológicas (copa, galhos e tronco), buscando amostrar os indivíduos arbóreos com diferentes (a) arquitetura de copa (A, para palmeiras; B para copa pequena e C, para copa grande) e (b) índice de cobertura por epífitas (ICE) que classifica os indivíduos arbóreos de acordo com o porte e a biomassa das epífitas. Esse material foi então separado e determinado o peso seco por grupos de epífitas: Arácea (Araceae, Gesneriaceae e Piperaceae), Bromeliacea, Orchidaceae e Miscelânia (Cactaceae, Pteridófitas, raízes, e solo aéreo). A zona ecológica que apresentou maior biomassa epifítica foi o tronco, com 54% do total, seguida pelos galhos com 45% do total. A biomassa epifítica variou de 0,01 kg a 28,9 kg por forófito. A biomassa epifítica total de um hectare de floresta, foi estimada em 2,32 Mg ha-1 representando apenas 1,34% de toda biomassa viva acima do solo, no entanto sua contribuição é de 18% da biomassa fotossintetizante da floresta e de mais de 10 Mg ha-1 de biomassa fresca evidenciando a importante contribuição do componente para o funcionamento do ecossistema. A estimativa de biomassa através do modelo alométrico desenvolvido neste estudo, utilizando-se como variáveis preditoras o índice de cobertura por epífitas e o DAP do forófito, representa um importante avanço nos estudos que envolvem a quantificação da biomassa de epífitas vasculares, sendo de fácil utilização e passível de aplicação em diferentes fitofisionomias, permitindo a comparação entre estudos distintos / Abstract: The Atlantic Forest is one of the most important biomes of the world and is considered one of the 25 hotspots of biodiversity. Among the ecosystems associated with the Atlantic Forest, one of the more endangered is the Restinga Forest with only 0,5% of its original area preserved. Restinga is the seasonally flooded coastal forest that occurs in sandy ridges along the coast where the soil is extremely poor in nutrients, very acid and subject to seasonal flooding. Among the communities that occur in Restinga forest, we highlight the vascular epiphytes that by not depending on soil nutrients, may play an important role in nutrient dynamics in these systems. To evaluate the role of vascular epiphytes in Restinga Forests, this study proceeded a quantitative survey of the biomass of vascular epiphytes in an area of one hectare of Restinga forest, in Picinguaba at the Serra do Mar State Park (PESM), Ubatuba, north coast of São Paulo State. On 23 phorophytes with diameter at breast height (DBH) ? 4.8 cm, previously selected, was all the epiphytic material collected, divided by ecological zones (canopy, branches and trunk). The trees were sample trees with different (a) canopy architecture (A, to palm trees; B, to small crown; and C, for large crown) and (b) coverage ratio by epiphytes (ICE), which classifies individual trees according to the size and biomass of epiphytes. This material was separate and determined the dry weight per epiphytes groups: Arácea (Araceae, Gesneriaceae and Piperaceae), Bromeliacea, Orchidaceae and Miscellany (Cactaceae, Pteridophytes, roots, organic matter). The ecological zone with the highest biomass epiphytic was the trunk, with 54% of the total, followed by branches with 45%. An allometric model for the estimation of epiphytes biomass as a function of the host tree DBH, ICE and dry weight of epiphytes was develop based in the information collected. From this model, biomass of vascular epiphytes was estimate in 2,32 Mg ha-1 for 1ha of Restinga forest. The epiphytic biomass per host tree varied from 0.01 kg to 28.9 kg. The total epiphytic biomass represent only 1.34% of all living biomass above ground (AGB), but its contribution is 18% of the photosynthetic biomass of the forest and more than 10 Mg ha-1 of wet biomass, showing the importance of this component to the functioning of the ecosystem. The estimate of biomass through allometric model developed in this study, using as predictors the epiphyte coverage index and the DAP of the host tree, represents an important advance in studies involving the quantification of biomass of vascular epiphytes, being easy to use and applicable in different vegetation types, allowing comparison between different studies / Mestrado / Ecologia / Mestra em Ecologia
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