11 resultados para Maclaurin Series


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Dissertação apresentada como requisito parcial para obtenção do grau de Mestre em Estatística e Gestão de Informação

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The section at Cristo Rei shows sandy beds with intercalated clayey lenses (IVb division from the Lisbon Miocene series) that correspond to a major regression event dated from between ca. 17.6 and 17 Ma. They also correspond to a distal position (relatively to the typical fluviatile facies in Lisbon), nearer the basin's axis. Geologic data and paleontological analysis (plant fossils, fishes, crocodilians, land mammals) allow the reconstruction of environments that were represented in the concerned area: estuary with channels and ox-bows; upstream, areas occupied by brackish waters where Gryphaea griphoides banks developped; still farther upstream, freshwaters sided by humid forests and low mountain subtropical forests under warm temperate and rainy conditions, as well as not far away, seasonally dry environments (low density tree or shrub cover, or steppe).

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In the Lusitanian Basin (Central Portugal), the Middle-Upper Liassic series are characterized by an expressive marly limestone accumulation, sediments that were deposited on a homoclinal carbonate ramp. These series belong to the Vale das Fontes, Lemede, S. Gião (and the lateral equivalents Prado and Cabo Carvoeiro Formations) and, partially, to the Póvoa da Lomba Formations. These units, in great part controlled by an accurate ammonite biostratigraphic scale, are organized into two secondorder transgressive-regressive sequences. The first one (SP) is dated of early Pliensbachian/lowermost early Toarcian age; the second (ST) is dated of early Toarcian to early Aalenian.

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With an example taken from a late-Hauterivian series of the Lusitanian Basin (Portugal), we will demonstrate the sedimentary record of orbital pattern variations and, consequently, climate variations in an inner platform environment with patterns and isolation changes, allows us to establish 4 major orders of periodicity related to orbital components:- The large cycles ob bed thickness variation, constituted by 31-32 beds, recording the 400 ky eccentricity cycle component;- The medium cycles, represented by byndles of 8-9 beds, related to the 100 ky eccentricity cycle component; - The small cycles, of 3-5 beds, recording the 41 ky obliquity components;- The very small cycles, of 2 beds, related to the 22 ky and 26 ky precession components. The mean duration of each bed is around 11.8 ky, a number very close to that of the precession hemi-cycle. Climatic control on qualitative production is confirmed by the close relation between the bed thickness variations, the insolation variability and the variation of micritized elements concentrations.

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Thesis submitted in the fulfillment of the requirements for the Degree of Master in Biomedical Engineering

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The last three decades have seen quite dramatic changes the way we modeled time dependent data. Linear processes have been in the center stage in modeling time series. As far as the second order properties are concerned, the theory and the methodology are very adequate.However, there are more and more evidences that linear models are not sufficiently flexible and rich enough for modeling purposes and that failure to account for non-linearities can be very misleading and have undesired consequences.

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Dissertation submitted in the fufillment of the requirements for the Degree of Master in Biomedical Engineering

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The continued increase in availability of economic data in recent years and, more importantly, the possibility to construct larger frequency time series, have fostered the use (and development) of statistical and econometric techniques to treat them more accurately. This paper presents an exposition of structural time series models by which a time series can be decomposed as the sum of a trend, seasonal and irregular components. In addition to a detailled analysis of univariate speci fications we also address the SUTSE multivariate case and the issue of cointegration. Finally, the recursive estimation and smoothing by means of the Kalman filter algorithm is described taking into account its different stages, from initialisation to parameter s estimation.

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This study analyses financial data using the result characterization of a self-organized neural network model. The goal was prototyping a tool that may help an economist or a market analyst to analyse stock market series. To reach this goal, the tool shows economic dependencies and statistics measures over stock market series. The neural network SOM (self-organizing maps) model was used to ex-tract behavioural patterns of the data analysed. Based on this model, it was de-veloped an application to analyse financial data. This application uses a portfo-lio of correlated markets or inverse-correlated markets as input. After the anal-ysis with SOM, the result is represented by micro clusters that are organized by its behaviour tendency. During the study appeared the need of a better analysis for SOM algo-rithm results. This problem was solved with a cluster solution technique, which groups the micro clusters from SOM U-Matrix analyses. The study showed that the correlation and inverse-correlation markets projects multiple clusters of data. These clusters represent multiple trend states that may be useful for technical professionals.

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The real convergence hypothesis has spurred a myriad of empirical tests and approaches in the economic literature. This Work Project intends to test for real output and growth convergence in all N(N-1)/2 possible pairs of output and output growth gaps of 14 Eurozone countries. This paper follows a time-series approach, as it tests for the presence of unit roots and persistence changes in the above mentioned pairs of output gaps, as well as for the existence of growth convergence with autoregressive models. Overall, significantly greater evidence has been found to support growth convergence rather than output convergence in our sample.