982 resultados para Statistics of extremes
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Includes bibliography: p. [349]-371 and index.
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The existence of juxtaposed regions of distinct cultures in spite of the fact that people's beliefs have a tendency to become more similar to each other's as the individuals interact repeatedly is a puzzling phenomenon in the social sciences. Here we study an extreme version of the frequency-dependent bias model of social influence in which an individual adopts the opinion shared by the majority of the members of its extended neighborhood, which includes the individual itself. This is a variant of the majority-vote model in which the individual retains its opinion in case there is a tie among the neighbors' opinions. We assume that the individuals are fixed in the sites of a square lattice of linear size L and that they interact with their nearest neighbors only. Within a mean-field framework, we derive the equations of motion for the density of individuals adopting a particular opinion in the single-site and pair approximations. Although the single-site approximation predicts a single opinion domain that takes over the entire lattice, the pair approximation yields a qualitatively correct picture with the coexistence of different opinion domains and a strong dependence on the initial conditions. Extensive Monte Carlo simulations indicate the existence of a rich distribution of opinion domains or clusters, the number of which grows with L(2) whereas the size of the largest cluster grows with ln L(2). The analysis of the sizes of the opinion domains shows that they obey a power-law distribution for not too large sizes but that they are exponentially distributed in the limit of very large clusters. In addition, similarly to other well-known social influence model-Axelrod's model-we found that these opinion domains are unstable to the effect of a thermal-like noise.
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We present a novel maximum-likelihood-based algorithm for estimating the distribution of alignment scores from the scores of unrelated sequences in a database search. Using a new method for measuring the accuracy of p-values, we show that our maximum-likelihood-based algorithm is more accurate than existing regression-based and lookup table methods. We explore a more sophisticated way of modeling and estimating the score distributions (using a two-component mixture model and expectation maximization), but conclude that this does not improve significantly over simply ignoring scores with small E-values during estimation. Finally, we measure the classification accuracy of p-values estimated in different ways and observe that inaccurate p-values can, somewhat paradoxically, lead to higher classification accuracy. We explain this paradox and argue that statistical accuracy, not classification accuracy, should be the primary criterion in comparisons of similarity search methods that return p-values that adjust for target sequence length.
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1975
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One of the main implications of the efficient market hypothesis (EMH) is that expected future returns on financial assets are not predictable if investors are risk neutral. In this paper we argue that financial time series offer more information than that this hypothesis seems to supply. In particular we postulate that runs of very large returns can be predictable for small time periods. In order to prove this we propose a TAR(3,1)-GARCH(1,1) model that is able to describe two different types of extreme events: a first type generated by large uncertainty regimes where runs of extremes are not predictable and a second type where extremes come from isolated dread/joy events. This model is new in the literature in nonlinear processes. Its novelty resides on two features of the model that make it different from previous TAR methodologies. The regimes are motivated by the occurrence of extreme values and the threshold variable is defined by the shock affecting the process in the preceding period. In this way this model is able to uncover dependence and clustering of extremes in high as well as in low volatility periods. This model is tested with data from General Motors stocks prices corresponding to two crises that had a substantial impact in financial markets worldwide; the Black Monday of October 1987 and September 11th, 2001. By analyzing the periods around these crises we find evidence of statistical significance of our model and thereby of predictability of extremes for September 11th but not for Black Monday. These findings support the hypotheses of a big negative event producing runs of negative returns in the first case, and of the burst of a worldwide stock market bubble in the second example. JEL classification: C12; C15; C22; C51 Keywords and Phrases: asymmetries, crises, extreme values, hypothesis testing, leverage effect, nonlinearities, threshold models
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A statistical evaluation of the population dynamics of Panstrongylus geniculatus is based on a cohort experiment conducted under controlled laboratory conditions. Animals were fed on hen every 15 days. Egg incubation took 21 days; mean duration of 1st, 2nd, 3rd, 4th, and 5th instar nymphs was 25, 30, 58, 62, and 67 days, respectively; mean nymphal development time was 39 weeks and adult longevity was 72 weeks. Females reproduced during 30 weeks, producing an average of 61.6 eggs for female on its lifetime; the average number of eggs/female/week was 2.1. Total number of eggs produced by the cohort was 1379. Average hatch for the cohort was 88.9%; it was not affected by age of the mother. Age specific survival and reproduction tables were constructed. The following population parameters were evaluated, generation time was 36.1 weeks; net reproduction rate was 89.4; intrinsic rate of natural increase was 0.125; instantaneous birth and death rates were 0.163 and 0.039 respectively; finite rate of increase was 1.13; total reproductive value was 1196 and stable age distribution was 31.2% eggs, 64.7% nymphs and 4.1% adults. Finally the population characteristics of P. geniculatus lead to the conclusion that this species is a K strategist.
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Statistics of Scientific Procedures on Living Animals NI 2005
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This publication is an historical recording of the most requested statistics on vital events and is a source of information that can be used in further analysis.
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This publication is an historical recording of the most requested statistics on vital events and is a source of information that can be used in further analysis.
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This publication is an historical recording of the most requested statistics on vital events and is a source of information that can be used in further analysis.
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This publication is an historical recording of the most requested statistics on vital events and is a source of information that can be used in further analysis.