934 resultados para Non linear regression


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This paper presents and implements a number of tests for non-linear dependence and a test for chaos using transactions prices on three LIFFE futures contracts: the Short Sterling interest rate contract, the Long Gilt government bond contract, and the FTSE 100 stock index futures contract. While previous studies of high frequency futures market data use only those transactions which involve a price change, we use all of the transaction prices on these contracts whether they involve a price change or not. Our results indicate irrefutable evidence of non-linearity in two of the three contracts, although we find no evidence of a chaotic process in any of the series. We are also able to provide some indications of the effect of the duration of the trading day on the degree of non-linearity of the underlying contract. The trading day for the Long Gilt contract was extended in August 1994, and prior to this date there is no evidence of any structure in the return series. However, after the extension of the trading day we do find evidence of a non-linear return structure.

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A number of tests for non-linear dependence in time series are presented and implemented on a set of 10 daily sterling exchange rates covering the entire post Bretton-Woods era until the present day. Irrefutable evidence of non-linearity is shown in many of the series, but most of this dependence can apparently be explained by reference to the GARCH family of models. It is suggested that the literature in this area has reached an impasse, with the presence of ARCH effects clearly demonstrated in a large number of papers, but with the tests for non-linearity which are currently available being unable to classify any additional non-linear structure.

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Preparing for episodes with risks of anomalous weather a month to a year ahead is an important challenge for governments, non-governmental organisations, and private companies and is dependent on the availability of reliable forecasts. The majority of operational seasonal forecasts are made using process-based dynamical models, which are complex, computationally challenging and prone to biases. Empirical forecast approaches built on statistical models to represent physical processes offer an alternative to dynamical systems and can provide either a benchmark for comparison or independent supplementary forecasts. Here, we present a simple empirical system based on multiple linear regression for producing probabilistic forecasts of seasonal surface air temperature and precipitation across the globe. The global CO2-equivalent concentration is taken as the primary predictor; subsequent predictors, including large-scale modes of variability in the climate system and local-scale information, are selected on the basis of their physical relationship with the predictand. The focus given to the climate change signal as a source of skill and the probabilistic nature of the forecasts produced constitute a novel approach to global empirical prediction. Hindcasts for the period 1961–2013 are validated against observations using deterministic (correlation of seasonal means) and probabilistic (continuous rank probability skill scores) metrics. Good skill is found in many regions, particularly for surface air temperature and most notably in much of Europe during the spring and summer seasons. For precipitation, skill is generally limited to regions with known El Niño–Southern Oscillation (ENSO) teleconnections. The system is used in a quasi-operational framework to generate empirical seasonal forecasts on a monthly basis.

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Although the sunspot-number series have existed since the mid-19th century, they are still the subject of intense debate, with the largest uncertainty being related to the "calibration" of the visual acuity of individual observers in the past. Daisy-chain regression methods are applied to inter-calibrate the observers which may lead to significant bias and error accumulation. Here we present a novel method to calibrate the visual acuity of the key observers to the reference data set of Royal Greenwich Observatory sunspot groups for the period 1900-1976, using the statistics of the active-day fraction. For each observer we independently evaluate their observational thresholds [S_S] defined such that the observer is assumed to miss all of the groups with an area smaller than S_S and report all the groups larger than S_S. Next, using a Monte-Carlo method we construct, from the reference data set, a correction matrix for each observer. The correction matrices are significantly non-linear and cannot be approximated by a linear regression or proportionality. We emphasize that corrections based on a linear proportionality between annually averaged data lead to serious biases and distortions of the data. The correction matrices are applied to the original sunspot group records for each day, and finally the composite corrected series is produced for the period since 1748. The corrected series displays secular minima around 1800 (Dalton minimum) and 1900 (Gleissberg minimum), as well as the Modern grand maximum of activity in the second half of the 20th century. The uniqueness of the grand maximum is confirmed for the last 250 years. It is shown that the adoption of a linear relationship between the data of Wolf and Wolfer results in grossly inflated group numbers in the 18th and 19th centuries in some reconstructions.

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Objective: To describe the results of a nutritional intervention programme among Japanese-Brazilians according to gender. Design: A non-controlled experimental study. Setting: The research included three points of clinical, nutritional and physical activity evaluation: at baseline (in 2005), after the first year and at the end of the second year (in 2007). The paired Student t test and multiple linear regression analysis were used to evaluate changes in the subjects` profile (clinical, nutritional and physical activity variables). Subjects: Japanese-Brazilians (n 575) of both genders, aged over 30 years. Results: We verified statistically significant reductions in body weight (0.9 kg), waist circumference (2.9 cm), blood pressure, fasting blood glucose (>3 mg/dl) and total cholesterol (>20 mg/dl) and its fractions, in both genders. We also found reductions in intake of energy (among men), protein (among women) and fat (both genders) and increases in intake of total fibre (among women) and carbohydrate (among men). Conclusions: The intervention programme indicated meaningful benefits for the intervention subjects, with changes in their habits that led to a `healthier` lifestyle positively impacting their nutritional and metabolic profile.

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Previous studies found students who both work and attend school undergo a partial sleep deprivation that accumulates across the week. The aim of the present study was to obtain information using a questionnaire on a number of variables (e.g., socio-demographics, lifestyle, work timing, and sleep-wake habits) considered to impact on sleep duration of working (n = 51) and non-working (n = 41) high-school students aged 14-21 yrs old attending evening classes (19:00-22:30h) at a public school in the city of Sao Paulo, Brazil. Data were collected for working days and days off. Multiple linear regression analyses were performed to assess the factors associated with sleep duration on weekdays and weekends. Work, sex, age, smoking, consumption of alcohol and caffeine, and physical activity were considered control variables. Significant predictors of sleep duration were: work (p < 0.01), daily work duration (8-10h/day; p < 0.01), sex (p = 0.04), age 18-21 yrs (0.01), smoking (p = 0.02) and drinking habits (p = 0.03), irregular physical exercise (p < 0.01), ease of falling asleep (p = 0.04), and the sleep-wake cycle variables of napping (p < 0.01), nocturnal awakenings (p < 0.01), and mid-sleep regularity (p < 0.01). The results confirm the hypotheses that young students who work and attend school showed a reduction in night-time sleep duration. Sleep deprivation across the week, particularly in students working 8-10h/day, is manifested through a sleep rebound (i.e., extended sleep duration) on Saturdays. However, the different roles played by socio-demographic and lifestyle variables have proven to be factors that intervene with nocturnal sleep duration. The variables related to the sleep-wake cyclenaps and night awakeningsproved to be associated with a slight reduction in night-time sleep, while regularity in sleep and wake-up schedules was shown to be associated with more extended sleep duration, with a distinct expression along the week and the weekend. Having to attend school and work, coupled with other socio-demographic and lifestyle factors, creates an unfavorable scenario for satisfactory sleep duration.

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In this paper, the laminar fluid flow of Newtonian and non-Newtonian of aqueous solutions in a tubular membrane is numerically studied. The mathematical formulation, with associated initial and boundary conditions for cylindrical coordinates, comprises the mass conservation, momentum conservation and mass transfer equations. These equations are discretized by using the finite-difference technique on a staggered grid system. Comparisons of the three upwinding schemes for discretization of the non-linear (convective) terms are presented. The effects of several physical parameters on the concentration profile are investigated. The numerical results compare favorably with experimental data and the analytical solutions. (C) 2011 Elsevier Inc. All rights reserved.

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In interval-censored survival data, the event of interest is not observed exactly but is only known to occur within some time interval. Such data appear very frequently. In this paper, we are concerned only with parametric forms, and so a location-scale regression model based on the exponentiated Weibull distribution is proposed for modeling interval-censored data. We show that the proposed log-exponentiated Weibull regression model for interval-censored data represents a parametric family of models that include other regression models that are broadly used in lifetime data analysis. Assuming the use of interval-censored data, we employ a frequentist analysis, a jackknife estimator, a parametric bootstrap and a Bayesian analysis for the parameters of the proposed model. We derive the appropriate matrices for assessing local influences on the parameter estimates under different perturbation schemes and present some ways to assess global influences. Furthermore, for different parameter settings, sample sizes and censoring percentages, various simulations are performed; in addition, the empirical distribution of some modified residuals are displayed and compared with the standard normal distribution. These studies suggest that the residual analysis usually performed in normal linear regression models can be straightforwardly extended to a modified deviance residual in log-exponentiated Weibull regression models for interval-censored data. (C) 2009 Elsevier B.V. All rights reserved.

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In this article, we compare three residuals based on the deviance component in generalised log-gamma regression models with censored observations. For different parameter settings, sample sizes and censoring percentages, various simulation studies are performed and the empirical distribution of each residual is displayed and compared with the standard normal distribution. For all cases studied, the empirical distributions of the proposed residuals are in general symmetric around zero, but only a martingale-type residual presented negligible kurtosis for the majority of the cases studied. These studies suggest that the residual analysis usually performed in normal linear regression models can be straightforwardly extended for the martingale-type residual in generalised log-gamma regression models with censored data. A lifetime data set is analysed under log-gamma regression models and a model checking based on the martingale-type residual is performed.

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We consider the issue of assessing influence of observations in the class of Birnbaum-Saunders nonlinear regression models, which is useful in lifetime data analysis. Our results generalize those in Galea et al. [8] which are confined to Birnbaum-Saunders linear regression models. Some influence methods, such as the local influence, total local influence of an individual and generalized leverage are discussed. Additionally, the normal curvatures for studying local influence are derived under some perturbation schemes. We also give an application to a real fatigue data set.

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This paper derives the second-order biases Of maximum likelihood estimates from a multivariate normal model where the mean vector and the covariance matrix have parameters in common. We show that the second order bias can always be obtained by means of ordinary weighted least-squares regressions. We conduct simulation studies which indicate that the bias correction scheme yields nearly unbiased estimators. (C) 2009 Elsevier B.V. All rights reserved.

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Background: The relationship between CETP and postprandial hyperlipemia is still unclear. We verified the effects of varying activities of plasma CETP on postprandial lipemia and precocious atherosclerosis in asymptomatic adult women. Methods: Twenty-eight women, selected from a healthy population sample (n = 148) were classified according to three CETP levels, all statistically different: CETP deficiency (CETPd <= 4.5%, n = 8), high activity (CETPi >= 23.8, n = 6) and controls (CTL, CETP >= 4.6% and <= 23.7%, n = 14). After a 12 h fast they underwent an oral fat tolerance test (40 g of fat/m(2) of body surface area) for 8 hours. TG, TG-rich-lipoproteins (TRL), cholesterol and TRL-TG measurements (AUC, AUIC, AR, RR and late peaks) and comparisons were performed on all time points. Lipases and phospholipids transfer protein (PLTP) were determined. Correlation between carotid atherosclerosis (c-IMT) and postprandial parameters was determined. CETP TaqIB and I405V and ApoE-epsilon 3/epsilon 2/epsilon 4 polymorphisms were examined. To elucidate the regulation of increased lipemia in CETPd a multiple linear regression analysis was performed. Results: In the CETPi and CTL groups, CETP activity was respectively 9 and 5.3 higher compared to the CETPd group. Concentrations of all HDL fractions and ApoA-I were higher in the CETPd group and clearance was delayed, as demonstrated by modified lipemia parameters (AUC, AUIC, RR, AR and late peaks and meal response patterns). LPL or HL deficiencies were not observed. No genetic determinants of CETP deficiency or of postprandial lipemia were found. Correlations with c-IMT in the CETPd group indicated postprandial pro-atherogenic associations. In CETPd the regression multivariate analysis (model A) showed that CETP was largely and negatively predicted by VLDL-C lipemia (R(2) = 92%) and much less by TG, LDL-C, ApoAI, phospholipids and non-HDL-C. CETP (model B) influenced mainly the increment in ApoB-100 containing lipoproteins (R(2) = 85% negatively) and phospholipids (R(2) = 13%), at the 6(th)h point. Conclusion: The moderate CETP deficiency phenotype included a paradoxically high HDL-C and its sub fractions (as earlier described), positive associations with c-IMT, a postprandial VLDL-C increment predicting negatively CETP activity and CETP activity regulating inversely the increment in ApoB100-containing lipoproteins. We hypothesize that the enrichment of TG content in triglyceride-rich ApoB-containing lipoproteins and in TG rich remnants increases lipoproteins` competition to active lipolysis sites, reducing their catabolism and resulting on postprandial lipemia with atherogenic consequences.

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As contribuições deste artigo são duas. A primeira, um método de avaliação de regressões não lineares para a previsão de retornos intradiários de ações no mercado brasileiro é discutido e aplicado, com o objetivo de maximizar o retorno de um portfólio simulado de compras e vendas. A segunda, regressões usando funções-núcleo associadas ao particionamento da amostra por vizinhos mais próximos são realizadas. Algumas variáveis independentes utilizadas são indicadores técnicos, cujos parâmetros são otimizados dentro da amostra de estimação. Os resultados alcançados são positivos e superam, em uma análise quartil a quartil, os resultados produzidos por um modelo benchmark de autorregressão linear

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The main purpose of this study is identify and select the assessment indicators for Brand Equity (BE), in the fuels segment. Within this perspective, we have chosen to assess the influences based on the following attributes: Brand Loyalty (Lealdade à Marca ( LM), Brand Recognition (Conhecimento da Marca ( CM), Perceived Quality (Qualidade Percebida ( QP) and Brand Associations (Associações à Marca ( AM), through perception of consumers in Rio de Janeiro and São Paulo States. Based on deep interviews in the qualitative phase and in surveys, in the quantitative phase, we began the data analysis through Multiple Linear Regression, according to Atilgan et al. (2005) model and Ha (1996). In the first model, the (CM) was considered non-explanatory to (BE¿, and we¿ve chosen to remove it from the following study model. In the final model, besides remaining variables, demographic variables were included, such as: Family Income (Renda Familiar ( RF) and Federation State (Estado da Federação ( EF), as independent variables. The main relevant findings, through perception of consumers, indicated that the (BE) of company analyzed was better ranked in Rio de Janeiro than in São Paulo and, as for the income, higher level classes tend to have less understanding on the value of (BE) of Petrobras BR. The study finish with mentions the contribution of the research and management implication, as well as limitations and suggestions to further researchers.

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When a company desires to invest in a project, it must obtain resources needed to make the investment. The alternatives are using firm s internal resources or obtain external resources through contracts of debt and issuance of shares. Decisions involving the composition of internal resources, debt and shares in the total resources used to finance the activities of a company related to the choice of its capital structure. Although there are studies in the area of finance on the debt determinants of firms, the issue of capital structure is still controversial. This work sought to identify the predominant factors that determine the capital structure of Brazilian share capital, non-financial firms. This work was used a quantitative approach, with application of the statistical technique of multiple linear regression on data in panel. Estimates were made by the method of ordinary least squares with model of fixed effects. About 116 companies were selected to participate in this research. The period considered is from 2003 to 2007. The variables and hypotheses tested in this study were built based on theories of capital structure and in empirical researches. Results indicate that the variables, such as risk, size, and composition of assets and firms growth influence their indebtedness. The profitability variable was not relevant to the composition of indebtedness of the companies analyzed. However, analyzing only the long-term debt, comes to the conclusion that the relevant variables are the size of firms and, especially, the composition of its assets (tangibility).This sense, the smaller the size of the undertaking or the greater the representation of fixed assets in total assets, the greater its propensity to long-term debt. Furthermore, this research could not identify a predominant theory to explain the capital structure of Brazilian