1,720,984 research outputs found
kth-order Markov extremal models for assessing heatwave risks
Get PDFHeatwaves are defined as a set of hot days and nights that cause a marked short-term increase in mortality. Obtaining accurate estimates of the probability of an event lasting many days is important. Previous studies of temporal dependence of extremes have assumed either a first-order Markov model or a particularly strong form of extremal dependence, known as asymptotic dependence. Neither of these assumptions is appropriate for the heatwaves that we observe for our data. A first-order Markov assumption does not capture whether the previous temperature values have been increasing or decreasing and asymptotic dependence does not allow for asymptotic independence, a broad class of extremal dependence exhibited by many processes including all non-trivial Gaussian processes. This paper provides a kth-order Markov model framework that can encompass both asymptotic dependence and asymptotic independence structures. It uses a conditional approach developed for multivariate extremes coupled with copula methods for time series. We provide novel methods for the selection of the order of the Markov process that are based upon only the structure of the extreme events. Under this new framework, the observed daily maximum temperatures at Orleans, in central France, are found to be well modelled by an asymptotically independent third-order extremal Markov model. We estimate extremal quantities, such as the probability of a heatwave event lasting as long as the devastating European 2003 heatwave event. Critically our method enables the first reliable assessment of the sensitivity of such estimates to the choice of the order of the Markov process
Spatial joint probability for flood and coastal risk management and strategic assessments : Method report - SC140002/R1
No full textThis report outlines the process and methodology of generating and selecting reasonable worst case scenarios used to inform the evidence base for the 2016 update to the National Risk Assessment of inland flooding risks. The method uses carefully collated historical river flow and rainfall data from the Heffernan and Tawn joint probability model (previously recommended in the Environment Agency research project SC060088 which investigated the spatial coherence of flood risk) to create a large number of extreme but statistically plausible events. A set of extreme events defined at river flow and sub-daily rainfall gauges across England and Wales were developed into inland flood scenarios based on the statistical simulations. The likelihood associated with each of the new scenarios can be assessed in terms of a hydrological proxy for the aggregate severity of the event, based on the average of the extreme flow or rainfall values over the network of gaugesas well as a simplified measure of exposure. Although this is a very simple metric chosen as a proxy to indicate the relative severity of each event, this approach was considered a reasonable basis to inform and support the development of the scenarios through a blend of statistical analysis and expert judgement. The hydrometeorological plausibility of each event was also considered within this process, based on qualitative analysis of the large-scale climatological and meteorological drivers for flooding in the British Isles. A number of events were selected for consideration to provide example scenarios of extreme rainfall and river flow events that would cause flooding. One example joint fluvial–coastal scenario was also selected. A narrative accompanying each scenario gives an overview of the hydrometeorological conditions under which these events may occur, accompanied by historical context comparing the scenario to past flooding events. To calculate the consequences of flooding, hazard modelling for each scenario was conducted to create a hazard footprint using 2D hydrodynamic modelling. The hazard footprints generated were then usedin impact analysis by the Health and Safety Laboratory to convert receptor data to relevant metrics for flood risk assessment. The metrics give an indication of flood severity for each of the selected scenarios. The methods described here were used to inform evidence base for flooding risks in the National Risk Assessment2016
Extreme value theory with oceanographic applications
No full textSIGLEAvailable from British Library Document Supply Centre- DSC:DX83746 / BLDSC - British Library Document Supply CentreGBUnited Kingdo
Modelling heatwaves in central France : a case-study in extremal dependence
Get PDFHeatwaves are phenomena that have large social and economic consequences. Understanding and estimating the frequency of such events are of great importance to climate scientists and decision makers. Heatwaves are a type of extreme event which are by definition rare and as such there are few data in the historical record to help planners. Extreme value theory is a general framework from which inference can be drawn from extreme events. When modelling heatwaves it is important to take into account the intensity and duration of events above a critical level as well as the interaction between both factors. Most previous methods assume that the duration distribution is independent of the critical level that is used to define a heatwave: a shortcoming that can lead to incorrect inferences. The paper characterizes a novel method for analysing the temporal dependence of heatwaves with reference to observed temperatures from Orleans in central France. This method enables estimation of the probabilities for heatwave events irrespectively of whether the duration distribution is independent of the critical level. The methods are demonstrated by estimating the probability of an event more severe than the 2003 European heatwave or an event that causes a specified increase in mortality
Volatility model selection for extremes of financial time series
No full textAlthough both widely used in the financial industry, there is quite often very little justification why GARCH or stochastic volatility is preferred over the other in practice. Most of the relevant literature focuses on the comparison of the fit of various volatility models to a particular data set, which sometimes may be inconclusive due to the statistical similarities of both processes. With an ever growing interest among the financial industry in the risk of extreme price movements, it is natural to consider the selection between both models from an extreme value perspective. By studying the dependence structure of the extreme values of a given series, we are able to clearly distinguish GARCH and stochastic volatility models and to test statistically which one better captures the observed tail behaviour. We illustrate the performance of the method using some stock market returns and find that different volatility models may give a better fit to the upper or lower tails
Extended generalised Pareto models for tail estimation
No full textThe most popular approach in extreme value statistics is the modelling of threshold exceedances using the asymptotically motivated generalised Pareto distribution. This approach involves the selection of a high threshold above which the model fits the data well. Sometimes, few observations of a measurement process might be recorded in applications and so selecting a high quantile of the sample as the threshold leads to almost no exceedances. In this paper we propose extensions of the generalised Pareto distribution that incorporate an additional shape parameter while keeping the tail behaviour unaffected. The inclusion of this parameter offers additional structure for the main body of the distribution, improves the stability of the modified scale, tail index and return level estimates to threshold choice and allows a lower threshold to be selected. We illustrate the benefits of the proposed models with a simulation study and two case studies
Going Beyond Counting First Authors in Author Co-citation Analysis
Get PDFThe present study examines one of the fundamental aspects of author co-citation analysis (ACA) - the way co-citation
counts are defined. Co-citation counting provides the data on which all subsequent statistical analyses and mappings
are based, and we compare ACA results based on two different types of co-citation counting - the traditional type that
only counts the first one among a cited work's authors on the one hand and a non-traditional type that takes into
account the first 5 authors of a cited work on the other hand. Results indicate that the picture produced through this non-traditional author co-citation counting contains more coherent author groups and is therefore considerably clearer. However, this picture represents fewer specialties in the research field being studied than that produced through the traditional first-author co-citation counting when the same number of top-ranked authors is selected and analyzed. Reasons for these effects are discussed
Variations on the Author
Get PDF“Variations on the Author” discusses two of Eduardo Coutinho’s recent films (Um Dia na Vida, from 2010, and Últimas Conversas, posthumously released in 2015) and their contribution to the general question of documentary authorship. The director’s filmography is characterized by a consistent yet self-effacing form of authorial self-inscription: Coutinho often features as an interviewer that rather than express opinions propels discourses; an interviewer that is good at listening. This mode of self-inscription characterizes him as an author who is not expressive but who is nonetheless markedly present on the screen. In Um Dia na Vida, however, Coutinho is completely absent form the image, while Últimas Conversas, on the contrary, includes a confessional prologue that moves the director from the margins to the center of his films. This article examines the ways in which these works stand out in the filmography of a director who offers new insights into the notion of cinematic authorship
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