939 resultados para monitoring process mean and variance


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(Relief influence on tree species richness in secondary forest fragments of Atlantic Forest, SE, Brazil). The aim of this work was to explore the relationship between tree species richness and morphological characteristics of relief at the Ibiuna Plateau (SE Brazil). We sampled 61 plots of 0.30 ha, systematically established in 20 fragments of secondary forest (2-274 ha) and in three areas within a continuous secondary forest site, Morro Grande Reserve (9,400 ha). At each plot, 100 trees with diameter at breast height > 5 cm were sampled by the point centered quarter method, and total richness and richness per dispersal and succession class were obtained. The relief was characterized by the mean and variance of slope, elevation, aspect and slope location. There was no significant relationship between relief heterogeneity and tree species richness. Relief parameters generally did not affect tree richness, but elevation was particularly important especially in the continuous forest. Despite the limited range of altitudinal variation (150 m), species richness increases with elevation. The highest areas were also those with the largest forest cover and the lowest disturbance degree, which should contribute to the greater richness of those sites. Our results suggest an indirect influence of relief, due to the fact that deforestation is less intense in higher regions, rather than a direct influence of abiotic factors related to the altitudinal gradient.

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In this article, we present a generalization of the Bayesian methodology introduced by Cepeda and Gamerman (2001) for modeling variance heterogeneity in normal regression models where we have orthogonality between mean and variance parameters to the general case considering both linear and highly nonlinear regression models. Under the Bayesian paradigm, we use MCMC methods to simulate samples for the joint posterior distribution. We illustrate this algorithm considering a simulated data set and also considering a real data set related to school attendance rate for children in Colombia. Finally, we present some extensions of the proposed MCMC algorithm.

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In this paper, we compare the performance of two statistical approaches for the analysis of data obtained from the social research area. In the first approach, we use normal models with joint regression modelling for the mean and for the variance heterogeneity. In the second approach, we use hierarchical models. In the first case, individual and social variables are included in the regression modelling for the mean and for the variance, as explanatory variables, while in the second case, the variance at level 1 of the hierarchical model depends on the individuals (age of the individuals), and in the level 2 of the hierarchical model, the variance is assumed to change according to socioeconomic stratum. Applying these methodologies, we analyze a Colombian tallness data set to find differences that can be explained by socioeconomic conditions. We also present some theoretical and empirical results concerning the two models. From this comparative study, we conclude that it is better to jointly modelling the mean and variance heterogeneity in all cases. We also observe that the convergence of the Gibbs sampling chain used in the Markov Chain Monte Carlo method for the jointly modeling the mean and variance heterogeneity is quickly achieved.

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For many learning tasks the duration of the data collection can be greater than the time scale for changes of the underlying data distribution. The question we ask is how to include the information that data are aging. Ad hoc methods to achieve this include the use of validity windows that prevent the learning machine from making inferences based on old data. This introduces the problem of how to define the size of validity windows. In this brief, a new adaptive Bayesian inspired algorithm is presented for learning drifting concepts. It uses the analogy of validity windows in an adaptive Bayesian way to incorporate changes in the data distribution over time. We apply a theoretical approach based on information geometry to the classification problem and measure its performance in simulations. The uncertainty about the appropriate size of the memory windows is dealt with in a Bayesian manner by integrating over the distribution of the adaptive window size. Thus, the posterior distribution of the weights may develop algebraic tails. The learning algorithm results from tracking the mean and variance of the posterior distribution of the weights. It was found that the algebraic tails of this posterior distribution give the learning algorithm the ability to cope with an evolving environment by permitting the escape from local traps.

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O objetivo do presente trabalho é verificar se, ao levar-se em consideração momentos de ordem superior (assimetria e curtose) na alocação de uma carteira de carry trade, há ganhos em relação à alocação tradicional que prioriza somente os dois primeiros momentos (média e variância). A hipótese da pesquisa é que moedas de carry trade apresentam retornos com distribuição não-Normal, e os momentos de ordem superior desta têm uma dinâmica, a qual pode ser modelada através de um modelo da família GARCH, neste caso IC-GARCHSK. Este modelo consiste em uma equação para cada momento condicional dos componentes independentes, explicitamente: o retorno, a variância, a assimetria, e a curtose. Outra hipótese é que um investidor com uma função utilidade do tipo CARA (constant absolute risk aversion), pode tê-la aproximada por uma expansão de Taylor de 4ª ordem. A estratégia do trabalho é modelar a dinâmica dos momentos da série dos logartimos neperianos dos retornos diários de algumas moedas de carry trade através do modelo IC-GARCHSK, e estimar a alocação ótima da carteira dinamicamente, de tal forma que se maximize a função utilidade do investidor. Os resultados mostram que há ganhos sim, ao levar-se em consideração os momentos de ordem superior, uma vez que o custo de oportunidade desta foi menor que o de uma carteira construída somente utilizando como critérios média e variância.

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Com o objetivo de mostrar uma aplicação dos modelos da família GARCH a taxas de câmbio, foram utilizadas técnicas estatísticas englobando análise multivariada de componentes principais e análise de séries temporais com modelagem de média e variância (volatilidade), primeiro e segundo momentos respectivamente. A utilização de análise de componentes principais auxilia na redução da dimensão dos dados levando a estimação de um menor número de modelos, sem contudo perder informação do conjunto original desses dados. Já o uso dos modelos GARCH justifica-se pela presença de heterocedasticidade na variância dos retornos das séries de taxas de câmbio. Com base nos modelos estimados foram simuladas novas séries diárias, via método de Monte Carlo (MC), as quais serviram de base para a estimativa de intervalos de confiança para cenários futuros de taxas de câmbio. Para a aplicação proposta foram selecionadas taxas de câmbio com maior market share de acordo com estudo do BIS, divulgado a cada três anos.

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Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

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Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

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Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

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In this paper we proposed a new two-parameters lifetime distribution with increasing failure rate. The new distribution arises on a latent complementary risk problem base. The properties of the proposed distribution are discussed, including a formal proof of its probability density function and explicit algebraic formulae for its reliability and failure rate functions, quantiles and moments, including the mean and variance. A simple EM-type algorithm for iteratively computing maximum likelihood estimates is presented. The Fisher information matrix is derived analytically in order to obtaining the asymptotic covariance matrix. The methodology is illustrated on a real data set. © 2010 Elsevier B.V. All rights reserved.

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Pós-graduação em Agronomia (Agricultura) - FCA

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The work consists of analyzing the risk management of investments by applying statistical concepts, economic and mathematical models considering the assets on the market on renowned financial institution. The assessment of these risks becomes increasingly interesting in view of minimizing your losses thus maximizing your chances of gains in both markets boom as extreme uncertainty, even with the sudden changes of scenery. Introducing concepts of investment funds, as well as the classification of the types of funds as funds management and equity, its guidelines, the concept of market investment funds. The types of assets comprising the investment funds, their taxation rules beyond the incidents that market widely used by investors and skilled people, both physical and legal, who keep their resources in this modality. With the historical data collected yields of investment funds of the Bank of Brazil, is an accomplished inflation adjustment and calculated the mean and variance for the verification of the model of Markowitz efficient frontier, a method used as investment analysis. This scan is used Matlab to obtain the set (or border) efficient portfolios. Once verified such data, there will be a critique of the Markowitz model as a quadratic programming and more coherent risk measures currently studied as VaR and CVaR minimizing the expected error, approaching our studies of current research. It is found that such studies have much to be explored, since there are many discussions about how effectively measure risk investments such as its characteristic and behavior, using a time series and volatility

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Antarctic fur seals (Arctocephalus gazella) in the South Shetland Islands are recovering from 19th-century exploitation more slowly than the main population at South Georgia. To document demographic changes associated with the recovery in the South Shetlands, we monitored fur seal abundance and reproduction in the vicinity of Elephant Island during austral summers from 1986/1987 through 1994/1995. Total births, mean and variance of birth dates, and average daily mortality rates were estimated from daily live pup counts at North Cove (NC) and North Annex (NA) colonies on Seal Island. Sightings of leopard seals (Hydrurga leptonyx) and incidents of leopard seal predation on fur seal pups were recorded opportunistically during daily fur seal research at both sites. High mortality of fur seal pups, attributed to predation by leopard seals frequently observed at NC, caused pup numbers to decline rapidly between January and March (i.e., prior to weaning) each year and probably caused a long-term decline in the size of that colony. The NA colony, where leopard seals were never observed, increased in size during the study. Pup mortality from causes other than leopard seal predation appeared to be similar at the two sites. The number of pups counted at four locations in the Elephant Island vicinity increased slowly, at an annual rate of 3.8%, compared to rates as high as 11% at other locations in the South Shetland Islands. Several lines of circumstantial evidence are consistent with the hypothesis that leopard seal predators limit the growth of the fur seal population in the Elephant Island area and perhaps in the broader population in the South Shetland Islands. The sustained growth of this fur seal population over many decades rules out certain predator–prey models, allowing inference about the interaction between leopard seals and fur seals even though it is less thoroughly studied than predator–prey systems of terrestrial vertebrates of the northern hemisphere. Top-down forces should be included in hypotheses for future research on the factors shaping the recovery of the fur seal population in the South Shetland Islands.

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Aim Estimates of geographic range size derived from natural history museum specimens are probably biased for many species. We aim to determine how bias in these estimates relates to range size. Location We conducted computer simulations based on herbarium specimen records from localities ranging from the southern United States to northern Argentina. Methods We used theory on the sampling distribution of the mean and variance to develop working hypotheses about how range size, defined as area of occupancy (AOO), was related to the inter-specific distribution of: (1) mean collection effort per area across the range of a species (MC); (2) variance in collection effort per area across the range of a species (VC); and (3) proportional bias in AOO estimates (PBias: the difference between the expected value of the estimate of AOO and true AOO, divided by true AOO). We tested predictions from these hypotheses using computer simulations based on a dataset of more than 29,000 herbarium specimen records documenting occurrences of 377 plant species in the tribe Bignonieae (Bignoniaceae). Results The working hypotheses predicted that the mean of the inter-specific distribution of MC, VC and PBias were independent of AOO, but that the respective variance and skewness decreased with increasing AOO. Computer simulations supported all but one prediction: the variance of the inter-specific distribution of VC did not decrease with increasing AOO. Main conclusions Our results suggest that, despite an invariant mean, the dispersion and symmetry of the inter-specific distribution of PBias decreases as AOO increases. As AOO increased, range size was less severely underestimated for a large proportion of simulated species. However, as AOO increased, range size estimates having extremely low bias were less common.

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The number of record-breaking events expected to occur in a strictly stationary time-series depends only on the number of values in the time-series, regardless of distribution. This holds whether the events are record-breaking highs or lows and whether we count from past to present or present to past. However, these symmetries are broken in distinct ways by trends in the mean and variance. We define indices that capture this information and use them to detect weak trends from multiple time-series. Here, we use these methods to answer the following questions: (1) Is there a variability trend among globally distributed surface temperature time-series? We find a significant decreasing variability over the past century for the Global Historical Climatology Network (GHCN). This corresponds to about a 10% change in the standard deviation of inter-annual monthly mean temperature distributions. (2) How are record-breaking high and low surface temperatures in the United States affected by time period? We investigate the United States Historical Climatology Network (USHCN) and find that the ratio of record-breaking highs to lows in 2006 increases as the time-series extend further into the past. When we consider the ratio as it evolves with respect to a fixed start year, we find it is strongly correlated with the ensemble mean. We also compare the ratios for USHCN and GHCN (minus USHCN stations). We find the ratios grow monotonically in the GHCN data set, but not in the USHCN data set. (3) Do we detect either mean or variance trends in annual precipitation within the United States? We find that the total annual and monthly precipitation in the United States (USHCN) has increased over the past century. Evidence for a trend in variance is inconclusive.