1000 resultados para Censured data


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The present work aims to study the macroeconomic factors influence in credit risk for installment autoloans operations. The study is based on 4.887 credit operations surveyed in the Credit Risk Information System (SCR) hold by the Brazilian Central Bank. Using Survival Analysis applied to interval censured data, we achieved a model to estimate the hazard function and we propose a method for calculating the probability of default in a twelve month period. Our results indicate a strong time dependence for the hazard function by a polynomial approximation in all estimated models. The model with the best Akaike Information Criteria estimate a positive effect of 0,07% for males over de basic hazard function, and 0,011% for the increasing of ten base points on the operation annual interest rate, toward, for each R$ 1.000,00 on the installment, the hazard function suffer a negative effect of 0,28% , and an estimated elevation of 0,0069% for the same amount added to operation contracted value. For de macroeconomics factors, we find statistically significant effects for the unemployment rate (-0,12%) , for the one lag of the unemployment rate (0,12%), for the first difference of the industrial product index(-0,008%), for one lag of inflation rate (-0,13%) and for the exchange rate (-0,23%). We do not find statistic significant results for all other tested variables.

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In Brazil, due to the breeding season for Thoroughbred, the reproductive data are normally truncate, since the breeders try to get animals that were born at the beginning of the breeding season in order to take their competitive advantages (more developed, mature and trained animals) compared to animals born later in the same breeding season. To analyze these data suitable methods should be used. Then, this paper aims to compare three methodologies: the method of maximum restricted likelihood, using MTDFREML, bayesian analysis without censured data by software MTGSAM and bayesian analysis with censured data by software LMCD, to evaluate age at first conception in thoroughbred mares, in order to verify its impact on the choice of stallions during selection. The database contained 3509 records for age at first conception (months) for thoroughbred mares. The heritability estimates were 0.23, 0.30 and 0.0926 (log scale), for MTDF, MTGSAM and LMCD, respectively. Considering all animals in the pedigree (6713), ranking correlations varied from 0.91 to 0.99. When only stallions were considered (656), those varied from 0.48 to 0.99 (considering different percentages of selected males) between evalua-tion methods. The highest changes in the general classification were observed when LMCD was compared to the other two methods. As the linear censured model is the most suitable for trait analysis with censured data, it was observed that censure information would lead to the choice of different animals during the selection process, when compared to the two other methodologies.

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Recent data indicate that levels of overweight and obesity are increasing at an alarming rate throughout the world. At a population level (and commonly to assess individual health risk), the prevalence of overweight and obesity is calculated using cut-offs of the Body Mass Index (BMI) derived from height and weight. Similarly, the BMI is also used to classify individuals and to provide a notional indication of potential health risk. It is likely that epidemiologic surveys that are reliant on BMI as a measure of adiposity will overestimate the number of individuals in the overweight (and slightly obese) categories. This tendency to misclassify individuals may be more pronounced in athletic populations or groups in which the proportion of more active individuals is higher. This differential is most pronounced in sports where it is advantageous to have a high BMI (but not necessarily high fatness). To illustrate this point we calculated the BMIs of international professional rugby players from the four teams involved in the semi-finals of the 2003 Rugby Union World Cup. According to the World Health Organisation (WHO) cut-offs for BMI, approximately 65% of the players were classified as overweight and approximately 25% as obese. These findings demonstrate that a high BMI is commonplace (and a potentially desirable attribute for sport performance) in professional rugby players. An unanswered question is what proportion of the wider population, classified as overweight (or obese) according to the BMI, is misclassified according to both fatness and health risk? It is evident that being overweight should not be an obstacle to a physically active lifestyle. Similarly, a reliance on BMI alone may misclassify a number of individuals who might otherwise have been automatically considered fat and/or unfit.

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In this paper, a singularly perturbed ordinary differential equation with non-smooth data is considered. The numerical method is generated by means of a Petrov-Galerkin finite element method with the piecewise-exponential test function and the piecewise-linear trial function. At the discontinuous point of the coefficient, a special technique is used. The method is shown to be first-order accurate and singular perturbation parameter uniform convergence. Finally, numerical results are presented, which are in agreement with theoretical results.