18 resultados para principal component regression


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The main objective of this survey was to perform descriptive analysis of crime evolution in Portugal between 1995 and 2013. The main focus of this survey was to analyse spatial crime evolution patterns in Portuguese NUTS III regions. Most important crime types have been included into analysis. The main idea was to uncover relation between local patterns and global crime evolution; to define regions which have contributed to global crime evolution of some specific crime types and to define how they have contributed. There were many statistical reports and scientific papers which have analysed some particular crime types, but one global spatial-temporal analysis has not been found. Principal Component Analysis and multidimensional descriptive data analysis technique STATIS have been the base of the analysis. The results of this survey has shown that strong spatial and temporal crime patterns exist. It was possible to describe global crime evolution patterns and to define crime evolution patterns in NUTS III regions. It was possible to define three to four groups of crimes where each group shows similar spatial crime dynamics.

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This paper studies the effects of monetary policy on mutual fund risk taking using a sample of Portuguese fixed-income mutual funds in the 2000-2012 period. Firstly I estimate time-varying measures of risk exposure (betas) for the individual funds, for the benchmark portfolio, as well as for a representative equally-weighted portfolio, through 24-month rolling regressions of a two-factor model with two systematic risk factors: interest rate risk (TERM) and default risk (DEF). Next, in the second phase, using the estimated betas, I try to understand what portion of the risk exposure is in excess of the benchmark (active risk) and how it relates to monetary policy proxies (one-month rate, Taylor residual, real rate and first principal component of a cross-section of government yields and rates). Using this methodology, I provide empirical evidence that Portuguese fixed-income mutual funds respond to accommodative monetary policy by significantly increasing exposure, in excess of their benchmarks, to default risk rate and slightly to interest risk rate as well. I also find that the increase in funds’ risk exposure to gain a boost in return (search-for-yield) is more pronounced following the 2007-2009 global financial crisis, indicating that the current historic low interest rates may incentivize excessive risk taking. My results suggest that monetary policy affects the risk appetite of non-bank financial intermediaries.

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Continuous cell lines that proliferate in chemically defined and simple media have been highly regarded as suitable alternatives for vaccine production. One such cell line is the AG1.CR.pIX avian cell line developed by PROBIOGEN. This cell line can be cultivated in a fully scalable suspension culture and adapted to grow in chemically defined, calf serum free, medium [1]–[5]. The medium composition and cultivation strategy are important factors for reaching high virus titers. In this project, a series of computational methods was used to simulate the cell’s response to different environments. The study is based on the metabolic model of the central metabolism proposed in [1]. In a first step, Metabolic Flux Analysis (MFA) was used along with measured uptake and secretion fluxes to estimate intracellular flux values. The network and data were found to be consistent. In a second step, Flux Balance Analysis (FBA) was performed to access the cell’s biological objective. The objective that resulted in the best predicted results fit to the experimental data was the minimization of oxidative phosphorylation. Employing this objective, in the next step Flux Variability Analysis (FVA) was used to characterize the flux solution space. Furthermore, various scenarios, where a reaction deletion (elimination of the compound from the media) was simulated, were performed and the flux solution space for each scenario was calculated. Growth restrictions caused by essential and non-essential amino acids were accurately predicted. Fluxes related to the essential amino acids uptake and catabolism, the lipid synthesis and ATP production via TCA were found to be essential to exponential growth. Finally, the data gathered during the previous steps were analyzed using principal component analysis (PCA), in order to assess potential changes in the physiological state of the cell. Three metabolic states were found, which correspond to zero, partial and maximum biomass growth rate. Elimination of non-essential amino acids or pyruvate from the media showed no impact on the cell’s assumed normal metabolic state.