954 resultados para Multivariate polynomial
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Storm- and tsunami-deposits are generated by similar depositional mechanisms making their discrimination hard to establish using classic sedimentologic methods. Here we propose an original approach to identify tsunami-induced deposits by combining numerical simulation and rock magnetism. To test our method, we investigate the tsunami deposit of the Boca do Rio estuary generated by the 1755 earthquake in Lisbon which is well described in the literature. We first test the 1755 tsunami scenario using a numerical inundation model to provide physical parameters for the tsunami wave. Then we use concentration (MS. SIRM) and grain size (chi(ARM), ARM, B1/2, ARM/SIRM) sensitive magnetic proxies coupled with SEM microscopy to unravel the magnetic mineralogy of the tsunami-induced deposit and its associated depositional mechanisms. In order to study the connection between the tsunami deposit and the different sedimentologic units present in the estuary, magnetic data were processed by multivariate statistical analyses. Our numerical simulation show a large inundation of the estuary with flow depths varying from 0.5 to 6 m and run up of similar to 7 m. Magnetic data show a dominance of paramagnetic minerals (quartz) mixed with lesser amount of ferromagnetic minerals, namely titanomagnetite and titanohematite both of a detrital origin and reworked from the underlying units. Multivariate statistical analyses indicate a better connection between the tsunami-induced deposit and a mixture of Units C and D. All these results point to a scenario where the energy released by the tsunami wave was strong enough to overtop and erode important amount of sand from the littoral dune and mixed it with reworked materials from underlying layers at least 1 m in depth. The method tested here represents an original and promising tool to identify tsunami-induced deposits in similar embayed beach environments.
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This paper analyzes the risk-return trade-off in European equities considering both temporal and cross-sectional dimensions. In our analysis, we introduce not only the market portfolio but also 15 industry portfolios comprising the entire market. Several bivariate GARCH models are estimated to obtain the covariance matrix between excess market returns and the industrial portfolios and the existence of a risk-return trade-off is analyzed through a cross-sectional approach using the information in all portfolios. It is obtained evidence for a positive and significant risk-return trade-off in the European market. This conclusion is robust for different GARCH specifications and is even more evident after controlling for the main financial crisis during the sample period.
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This work focuses on the appraisal of public and environmental projects and, more specifically, on the calculation of the social discount rate (SDR) for this kind of very long-term investment projects. As a rule, we can state that the instantaneous discount rate must be equal to the hazard rate of the public good or to the mortality rate of the population that the project is intended to. The hazard can be due to technical failures of the system, but, in this paper, we are going to consider different independent variables that can cause the hazard. That is, we are going to consider a multivariate hazard rate. In our empirical application, the Spanish forest surface will be the system and the forest fire will be the fail that can be caused by several factors. The aim of this work is to integrate the different variables that produce the fail in the calculation of the SDR from a multivariate hazard rate approach.
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Preliminary version
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We are concerned with providing more empirical evidence on forecast failure, developing forecast models, and examining the impact of events such as audit reports. A joint consideration of classic financial ratios and relevant external indicators leads us to build a basic prediction model focused in non-financial Galician SMEs. Explanatory variables are relevant financial indicators from the viewpoint of the financial logic and financial failure theory. The paper explores three mathematical models: discriminant analysis, Logit, and linear multivariate regression. We conclude that, even though they both offer high explanatory and predictive abilities, Logit and MDA models should be used and interpreted jointly.
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INTRODUCTION: In Mexico, breast cancer (BC) is one of the main causes of cancer deaths in women, with increasing incidence and mortality in recent years. Therefore, the aim of the study is identify possible risk factors related to BC. METHODS: An epidemiological study of hospital cases of BC and controls with cervical uterine cancer (CUCA) was carried out at eight third level concentration hospitals in Mexico City. The total of 353 incident cases of BC and 630 controls with CUCA were identified among women younger than 75 years who had been residents of the metropolitan area of Mexico City for at least one year. Diagnosis was confirmed histologically in both groups. Variables were analyzed according to biological and statistical plausibility criteria. Univariate, bivariate and multivariate analyses were carried out. Cases and controls were stratified according to the menopausal hormonal status (pre and post menopause). RESULTS: The factors associated with BC were: higher socioeconomic level (OR= 2.77; 95%CI = 1.77 - 4.35); early menarche (OR= 1.32; 95%CI= 0.88 - 2.00); old age at first pregnancy (>31 years: OR= 5.49; 95%CI= 2.16 - 13.98) and a family history of BC (OR= 4.76; 95% CI= 2.10 - 10.79). In contrast, an increase in the duration of the breastfeeding period was a protective factor (>25 months: OR= 0.38; 95%CI= 0.20 - 0.70). CONCLUSIONS: This study contributes to the identification of risk factors for BC described in the international literature, in the population of Mexican women. Breastfeeding appears to play an important role in protecting women from BC. Because of changes in women`s lifestyles, lactation is decreasing in Mexico, and young women tend not to breastfeed or to shorten the duration of lactation.
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OBJECTIVE: To identify the association between food group consumption frequency and serum lipoprotein levels among adults. METHODS: The observations were made during a cross-sectional survey of a representative sample of men and women over 20 years old living in Cotia county, S. Paulo, Brazil. Data on food frequency consumption, serum lipids, and other covariates were available for 1,045 adults. Multivariate analyses adjusted by age, gender, body mass index, waist-to-hip ratio, educational level, family income, physical activity, smoking, and alcohol consumption were performed. RESULTS: Consumption of processed meat, chicken, red meat, eggs and dairy foods were each positively and significantly correlated with LDL-C, whereas the intake of vegetables and fruits showed an inverse correlation. Daily consumption of processed meat, chicken, red meat, eggs, and dairy foods were associated with 16.6 mg/dl, 14.5 mg/dl, 11.1 mg/dl, 5.8 mg/dl, and 4.6 mg/dl increase in blood LDL-C, respectively. Increases of daily consumption of fruit and vegetables were associated with 5.2 mg/dl and 5.5 mg/dl decreases in LDL-C, respectively. Alcohol beverage consumption showed a significant positive correlation with HDL-C. CONCLUSIONS: Dietary habits in the study population seem to contribute substantially to the variation in blood LDL and HDL concentrations. Substantially CHD risk reduction could be achieved with dietary changes.
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Mestrado em Intervenção Sócio-Organizacional na Saúde - Área de especialização: Políticas de Gestão e Administração dos Serviços de Saúde.
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OBJECTIVE: Selecting controls is one of the most difficult tasks in the design of case-control studies. Hospital controls may be inadequate and random controls drawn from the base population may be unavailable. The aim was to assess the use of hospital visitors as controls in a case-control study on the association of organochlorinated compounds and other risk factors for breast cancer conducted in the main hospital of the "Instituto Nacional de Câncer" -- INCA (National Cancer Institute) in Rio de Janeiro (Brazil). METHODS: The study included 177 incident cases and 377 controls recruited among female visitors. Three different models of control group composition were compared: Model 1, with all selected visitors; Model 2, excluding women visiting relatives with breast cancer; and Model 3, excluding all women visiting relatives with any type of cancer. Odds ratios (OR) and 95% confidence intervals were calculated to test the associations. RESULTS: Age-adjusted OR for breast cancer associated with risk factors other than family history of cancer, except smoking and breast size, were similar in the three models. Regarding family history of all cancers, except for breast cancer, there was a decreased risk in Models 1 and 2, while in Model 3 there was an increased risk, but not statistically significant. Family history of breast cancer was a risk factor in Models 2 and 3, but no association was found in Model 1. In multivariate analysis a significant risk of breast cancer was found when there was a family history of breast cancer in Models 2 and 3 but not in Model 1. CONCLUSIONS: These results indicate that while investigating risk factors unrelated to family history of cancer, the use of hospital visitors as controls may be a valid and feasible alternative.
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In this paper we present a methodology which enables the graphical representation, in a bi-dimensional Euclidean space, of atmospheric pollutants emissions in European countries. This approach relies on the use of Multidimensional Unfolding (MDU), an exploratory multivariate data analysis technique. This technique illustrates both the relationships between the emitted gases and the gases and their geographical origins. The main contribution of this work concerns the evaluation of MDU solutions. We use simulated data to define thresholds for the model fitting measures, allowing the MDU output quality evaluation. The quality assessment of the model adjustment is thus carried out as a step before interpretation of the gas types and geographical origins results. The MDU maps analysis generates useful insights, with an immediate substantive result and enables the formulation of hypotheses for further analysis and modeling.
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O documento em anexo encontra-se na versão post-print (versão corrigida pelo editor).
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Storm- and tsunami-deposits are generated by similar depositional mechanisms making their discrimination hard to establish using classic sedimentologic methods. Here we propose an original approach to identify tsunami-induced deposits by combining numerical simulation and rock magnetism. To test our method, we investigate the tsunami deposit of the Boca do Rio estuary generated by the 1755 earthquake in Lisbon which is well described in the literature. We first test the 1755 tsunami scenario using a numerical inundation model to provide physical parameters for the tsunami wave. Then we use concentration (MS. SIRM) and grain size (chi(ARM), ARM, B1/2, ARM/SIRM) sensitive magnetic proxies coupled with SEM microscopy to unravel the magnetic mineralogy of the tsunami-induced deposit and its associated depositional mechanisms. In order to study the connection between the tsunami deposit and the different sedimentologic units present in the estuary, magnetic data were processed by multivariate statistical analyses. Our numerical simulation show a large inundation of the estuary with flow depths varying from 0.5 to 6 m and run up of similar to 7 m. Magnetic data show a dominance of paramagnetic minerals (quartz) mixed with lesser amount of ferromagnetic minerals, namely titanomagnetite and titanohematite both of a detrital origin and reworked from the underlying units. Multivariate statistical analyses indicate a better connection between the tsunami-induced deposit and a mixture of Units C and D. All these results point to a scenario where the energy released by the tsunami wave was strong enough to overtop and erode important amount of sand from the littoral dune and mixed it with reworked materials from underlying layers at least 1 m in depth. The method tested here represents an original and promising tool to identify tsunami-induced deposits in similar embayed beach environments.
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Este estudo teve como objetivos verificar a validade fatorial e a validade interna da versão brasileira do Exercise Motivation Inventory-2 (EMI-2) e comparar os principais motivos para prática de exercício tendo em conta os contextos de academia e personal training. Um total de 588 praticantes de exercício da cidade de Pelotas/RS/Brasil (405 de academia e 183 de personal training) preencheram o EMI-2, o qual é constituído por 51 itens, agrupados em 14 motivos (fatores) para prática de exercício físico. A validade fatorial do EMI-2 foi testada através da realização de análises fatoriais confirmatórias e a validade interna através do alfa de Cronbach. Para a verificar o efeito do contexto nos motivos foi utilizada a MANOVA e calculado o tamanho do efeito. Os resultados obtidos dão suporte à estrutura original do EMI-2 com 14 fatores, nesta amostra. Verificou-se um efeito multivariado significativo do contexto sobre os motivos de prática [Wilks’ λ = 0.912, F (14, 573.000) = 3.9, p < 0.001, η² = 0.088]. Os motivos de “Prazer”, “Força e resistência”, “Desafio”, “Socialização”, “Competição” e “Reconhecimento Social” foram significativamente superiores no contexto de academia e os motivos de “Agilidade” e “Prevenção de Doenças” foram significativamente superiores no contexto de personal training.
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OBJECTIVE: To identify factors associated to poor glycemic control among diabetic patients seen at primary health care centers. METHODS: A cross-sectional study was carried out in a sample of 372 diabetic patients attending 32 primary health care centers in southern Brazil. Data on three hierarchical levels of health unit infrastructure, medical care and patient characteristics were collected. RESULTS: The frequency of poor glycemic control was 50.5%. Multivariate analysis (multilevel method) showed that patients with body mass indexes below 27 kg/m², patients on oral hypoglycemic agents or insulin, and patients diagnosed as diabetic over five years prior to the interview were more likely to present poor glycemic control when compared to their counterparts. CONCLUSIONS: Given the hierarchical data structuring, all associations found suggest that factors associated to hyperglycemia are related to patient-level characteristics.
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OBJECTIVE: To assess the effects of individual, household and healthcare system factors on poor children's use of vaccination after the reform of the Colombian health system. METHODS: A household survey was carried out in a random sample of insured poor population in Bogota, in 1999. The conceptual and analytical framework was based on the Andersen's Behavioral Model of Health Services Utilization. It considers two units of analysis for studying vaccination use and its determinants: the insured poor population, including the children and their families characteristics; and the health care system. Statistical analysis were carried out by chi-square test with 95% confidence intervals, multivariate regression models and Cronbach's alpha coefficient. RESULTS: The logistic regression analysis showed that vaccination use was related not only to population characteristics such as family size (OR=4.3), living area (OR=1.7), child's age (OR=0.7) and head-of-household's years of schooling (OR=0.5), but also strongly related to health care system features, such as having a regular health provider (OR=6.0) and information on providers' schedules and requirements for obtaining care services (OR=2.1). CONCLUSIONS: The low vaccination use and the relevant relationships to health care delivery systems characteristics show that there are barriers in the healthcare system, which should be assessed and eliminated. Non-availability of regular healthcare and deficient information to the population are factors that can limit service utilization.