16 resultados para binomial

em QUB Research Portal - Research Directory and Institutional Repository for Queen's University Belfast


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In this article, we extend the earlier work of Freeland and McCabe [Journal of time Series Analysis (2004) Vol. 25, pp. 701–722] and develop a general framework for maximum likelihood (ML) analysis of higher-order integer-valued autoregressive processes. Our exposition includes the case where the innovation sequence has a Poisson distribution and the thinning is binomial. A recursive representation of the transition probability of the model is proposed. Based on this transition probability, we derive expressions for the score function and the Fisher information matrix, which form the basis for ML estimation and inference. Similar to the results in Freeland and McCabe (2004), we show that the score function and the Fisher information matrix can be neatly represented as conditional expectations. Using the INAR(2) speci?cation with binomial thinning and Poisson innovations, we examine both the asymptotic e?ciency and ?nite sample properties of the ML estimator in relation to the widely used conditional least
squares (CLS) and Yule–Walker (YW) estimators. We conclude that, if the Poisson assumption can be justi?ed, there are substantial gains to be had from using ML especially when the thinning parameters are large.

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Aim To examine the effect of climate change on the occurrence and distribution of Pipistrellus nathusii (Nathusius' pipistrelle) in the United Kingdom (UK).Location We modelled habitat and climatic associations of P. nathusii in the UK and applied this model to the species' historical range in continental Europe.Methods A binomial logistic regression model was constructed relating the occurrence of P. nathusii to climate and habitat characteristics using historical species occurrence records (1940-2006) and CORINE land cover data. This model was applied to historical and projected climate data to examine changes in suitable range (1940-2080) of this species. We tested the predictive ability of the model with known records in the UK after 2006 and applied the model to the species' known range in Europe.Results The distribution of P. nathusii was related positively to the area of water bodies, woodland and small areas of urbanization, and negatively related to the area of peat/heathland. Species records were associated with higher minimum temperatures, low seasonal variation in temperature and intermediate rainfall. We found that suitable areas have existed in the UK since the 1940s and that these have expanded. The model had high predictive power when applied to new records after 2006, with a correct classification rate of 70%, estimated by receiver operating characteristic analysis. Based on climate projections, our model suggests a potential twofold increase in the area suitable for P. nathusii in the UK by 2050. The single most influential climate variable contributing to range increase was the projected increase in minimum temperature. When applied to Europe, the model predictions had best predictive capability of known records in western areas of the species' range, where P. nathusii is present during the winter.Main conclusions We show that a mobile, migratory species has adapted its range in response to recent climate change on a continental scale. We believe this may be the first study to demonstrate a case of range change linked to contemporary climate change in a mammal species in Europe.

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The maintenance of biodiversity is a fundamental theme of the Marine Strategy Framework Directive. Appropriate indicators to monitor change in biodiversity, along with associated targets representing "good environmental status" (GES), are required to be in place by July 2012. A method for selecting species-specific metrics to fulfil various specified indicator roles is proposed for demersal fish communities. Available data frequently do not extend far enough back in time to allow GES to be defined empirically. In such situations, trends-based targets offer a pragmatic solution. A method is proposed for setting indicator-level targets for the number of species-specific metrics required to meet their trends-based metric-level targets. This is based on demonstrating significant departures from the binomial distribution. The procedure is trialled using North Sea demersal fish survey data. Although fisheries management in the North Sea has improved in recent decades, management goals to stop further decline in biodiversity, and to initiate recovery, are yet to be met.

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We predicted that the probability of egg occurrence of salamander Salamandrina perspicillata depended on stream features and predation by native crayfish Austropotamobius fulcisianus and the introduced trout Salmo trutta. We assessed the presence of S. perspicillata at 54 sites within a natural reserve of southern Tuscany, Italy. Generalized linear models with binomial errors were constructed using egg presence/absence and altitude, stream mean size and slope, electrical conductivity, water pH and temperature, and a predation factor, defined according to the presence/absence of crayfish and trout. Some competing models also included an autocovariate term, which estimated how much the response variable at any one sampling point reflected response values at surrounding points. The resulting models were compared using Akaike's information criterion. Model selection led to a subset of 14 models with Delta AIC(c) <7 (i.e., models ranging from substantial support to considerably less support), and all but one of these included an effect of predation. Models with the autocovariate term had considerably more support than those without the term. According to multimodel inference, the presence of trout and crayfish reduced the probability of egg occurrence from a mean level of 0.90 (SE limits: 0.98-0.55) to 0.12 (SE limits: 0.34-0.04). The presence of crayfish alone had no detectable effects (SE limits: 0.86-0.39). The results suggest that introduced trout have a detrimental effect on the reproductive output of S. perspicillata and confirm the fundamental importance of distinguishing the roles of endogenous and exogenous forces that act on population distribution.

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Global amphibian declines are a major element of the current biodiversity crisis. Monitoring changes in the distribution and abundance of target species is a basic component in conservation decision making and requires robust and repeatable sampling. For EU member states, surveillance of designated species, including the common frog Rana temporaria, is a formal requirement of the 'EC Habitats & Species Directive'. We deployed established methods for estimating frog population density at local water bodies and extrapolated these to the national and ecoregion scale. Spawn occurred at 49.4% of water bodies and 70.1% of independent 500-m survey squares. Using spawn mat area, we estimated the number of adult breeding females and subsequently the total population assuming a sex ratio of 1:1. A negative binomial model suggested that mean frog density was 23.5 frogsha [95% confidence interval (CI) 14.9-44.0] equating to 196M frogs (95%CI 124M-367M) throughout Ireland. A total of 86% of frogs bred in drainage ditches, which were a notably common feature of the landscape. The recorded distribution of the species did not change significantly between the last Article 17 reporting period (1993-2006) and the current period (2007-2011) throughout the Republic of Ireland. Recording effort was markedly lower in Northern Ireland, which led to an apparent decline in the recorded distribution. We highlight the need to coordinate biological surveys between adjacent political jurisdictions that share a common ecoregion to avoid apparent disparities in the quality of distributional information. Power analysis suggested that a reduced sample of 40-50 survey squares is sufficient to detect a 30% decline (consistent with the International Union for Conservation of Nature Category of 'Vulnerable') at 80% power providing guidance for minimizing future survey effort. Our results provin assessments for R. temporaria and other clump-spawning amphibians. 2013 The Zoological Society of London.

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Some studies suggest that there are urban-rural variations in cancer incidence but whether these simply reflect urban-rural socioeconomic variation is unclear. We investigated whether there were urban-rural variations in the incidence of 18 cancers, after adjusting for socioeconomic status. Cancers diagnosed between 1995 and 2007 were extracted from the population-based National Cancer Registry Ireland and Northern Ireland Cancer Registry and categorised by urban-rural status, based on population density of area of residence at diagnosis (rural 15 people per hectare). Relative risks (RR) were calculated by negative binomial regression, adjusting for age, country and three area-based markers of socioeconomic status. Risks were significantly higher in both sexes in urban than rural residents with head and neck (males RR urban vs. rural = 1.53, 95 % CI 1.42-1.64; females RR = 1.29, 95 % CI 1.15-1.45), esophageal (males 1.21, 1.11-1.31; females 1.21, 1.08-1.35), stomach (males 1.36, 1.27-1.46; females 1.19, 1.08-1.30), colorectal (males 1.14, 1.09-1.18; females 1.04, 1.00-1.09), lung (males 1.54, 1.47-1.61; females 1.74, 1.65-1.84), non-melanoma skin (males 1.13, 1.10-1.17; females 1.23, 1.19-1.27) and bladder (males 1.30, 1.21-1.39; females 1.31, 1.17-1.46) cancers. Risks of breast, cervical, kidney and brain cancer were significantly higher in females in urban areas. Prostate cancer risk was higher in rural areas (0.94, 0.90-0.97). Other cancers showed no significant urban-rural differences. After adjusting for socioeconomic variation, urban-rural differences were evident for 12 of 18 cancers. Variations in healthcare utilization and known risk factors likely explain some of the observed associations. Explanations for others are unclear and, in the interests of equity, warrant further investigation. © 2014 The New York Academy of Medicine.

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Background
It is not clear whether the availability of tobacco affects the likelihood of smoking cessation. We examined whether the proximity to a tobacco store and
the number of stores were associated with smoking cessation, and compared results for proximity variables based on walking and straight-line (as the crow flies) distance.

Methods
The study population consisted of 8751 baseline smokers from the Finnish Public Sector study in 1997–2005. Smoking intensity (cigarettes/day) was
determined at baseline and smoking cessation was determined from a follow-up survey in 2008–2009. Proximity was measured using straight-line and walking
distance from home to the nearest tobacco store, and another exposure variable was the number of stores within 0.50 km from home. We calculated associations
with log-binomial regression models, adjusting for individual-level and area-level confounders.

Results
Of the participants, 3482 (39.8%) quit smoking during the follow-up (mean follow-up 5.5 years, SD 2.3 years). Among men who were moderate/heavy smokers at baseline and lived <0.50 km walking distance from the nearest tobacco store, the likelihood of smoking cessation was 27% (95% CI 12% to 40%) lower compared with those living ≥0.50 km from a store. Having even one store within 0.50 km walking distance from home decreased cessation in men who were moderate/heavy smokers by 37% (95% CI 19% to 51%). No decrease was found for men who were light smokers at baseline or for women.

Conclusions
Living within walking distance of a tobacco store reduced the likelihood of smoking cessation among men who were moderate/heavy smokers.

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Estimates probit, logit, Poisson, negative binomial, and beta regression models, returning their marginal effects, odds ratios, or incidence rate ratios as an output.

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Energy consumption and total cost of ownership are daunting challenges for Datacenters, because they scale disproportionately with performance. Datacenters running financial analytics may incur extremely high operational costs in order to meet performance and latency requirements of their hosted applications. Recently, ARM-based microservers have emerged as a viable alternative to high-end servers, promising scalable performance via scale-out approaches and low energy consumption. In this paper, we investigate the viability of ARM-based microservers for option pricing, using the Monte Carlo and Binomial Tree kernels. We compare an ARM-based microserver against a state-of-the-art x86 server. We define application-related but platform-independent energy and performance metrics to compare those platforms fairly in the context of datacenters for financial analytics and give insight on the particular requirements of option pricing. Our experiments show that through scaling out energyefficient compute nodes within a 2U rack-mounted unit, an ARM-based microserver consumes as little as about 60% of the energy per option pricing compared to an x86 server, despite having significantly slower cores. We also find that the ARM microserver scales enough to meet a high fraction of market throughput demand, while consuming up to 30% less energy than an Intel server

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Aims: Systematic review of mortality in childhood-/adolescent-diagnosed Type 1 diabetes and examination of factors explaining the mortality variation between studies. 
Methods: Relevant studies were identified from systematic searches of MEDLINE and EMBASE. Observed and expected numbers of deaths were extracted, and standardised mortality ratios (SMRs) and 95 % confidence intervals (CIs) were calculated. Negative binomial regression was used to investigate association between mortality and study/country characteristics.
Results: Thirteen relevant publications with mortality data were identified describing 23 independent studies. SMRs varied markedly ranging from 0 to 854 (chi-squared = 70.68,df = 21, p<0.0001). Significant associations were observed between SMR and mid-year of follow-up [incidence rate ratio (IRR) 0.95, 95 % CI 0.91–0.99 equivalent to a 5 % decrease per year], between SMR and infant mortality rate (IRR 1.07, 95 % CI 1.02–1.12, a 7 % increase for each death per 1,000 live births) and, after omitting an outlier, between SMR and health expenditure as a percentage of gross domestic product (GDP) (IRR 0.79, 95 % CI 0.68–0.93, a 21 % decrease for each one percent increase in GDP). No relationship was detected between SMR and a country’s childhood diabetes incidence rate or GDP.
Conclusions: Excess mortality in childhood-/adolescent diagnosed Type 1 diabetes is apparent across countries worldwide. Excesses were less marked in more recent studies and in countries with lower infant mortality and higher health expenditure.

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The purpose of this research is to reveal (1) which English binomials Japanese learners of English have productive knowledge of and (2) what strategies they use to produce English binomials when they do not know the binomials. One hundred and three Japanese learners of English with intermediate proficiency level completed an online survey of 44 binomials. The participants were given the first word of a binomial and asked to type a word following “and”. The target word was provided by more than 75% of participants for 19 of the 44 binomials, meaning that learners have productive knowledge for certain binomials. An analysis of errors suggested that the participants relied heavily on semantic relationships between items in binomials.However, the use of a semantic strategy for producing the second words often leads to non-binomial expressions. From these results we suggest that giving more input to learners, as well as teaching the “Me first” principle (Cooper & Ross, 1975) explicitly would help the learners to develop more accurate and effective strategies for uncertain or unfamiliar binomials.

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Aim: Our primary aim is to understand how assemblages of rare (restricted range) and common (widespread) species are correlated with each other among different taxa. We tested the proposition that marine species richness patterns of rare and common species differ, both within a taxon in their contribution to the richness pattern of the full assemblage and among taxa in the strength of their correlations with each other. Location The UK intertidal zone. Methods: We used high-resolution marine datasets for UK intertidal macroalgae, molluscs and crustaceans each with more than 400 species. We estimated the relative contribution of rare and common species, treating rarity and commonness as a continuous spectrum, to spatial patterns in richness using spatial crosscorrelations. Correlation strength and significance was estimated both within and between taxa. Results: Common species drove richness patterns within taxa, but rare species contributed more when species were placed on an equal footing via scaling by binomial variance. Between taxa, relatively small sub-assemblages (fewer than 60 species) of common species produced the maximum correlation with each other, regardless of taxon pairing. Cross-correlations between rare species were generally weak, with maximum correlation occurring between small sub-assemblages in only one case. Cross-correlations between common and rare species of different taxa were consistently weak or absent. Main conclusions: Common species in the three marine assemblages were congruent in their richness patterns, but rare species were generally not. The contrast between the stronger correlations among common species and the weak or absent correlations among rare species indicates a decoupling of the processes driving common and rare species richness patterns. The internal structure of richness patterns of these marine taxa is similar to that observed for terrestrial taxa.