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Temporal Dependence (temporal + dependence)
Selected AbstractsCopulas and Temporal DependenceECONOMETRICA, Issue 1 2010Brendan K. Beare An emerging literature in time series econometrics concerns the modeling of potentially nonlinear temporal dependence in stationary Markov chains using copula functions. We obtain sufficient conditions for a geometric rate of mixing in models of this kind. Geometric , -mixing is established under a rather strong sufficient condition that rules out asymmetry and tail dependence in the copula function. Geometric , -mixing is obtained under a weaker condition that permits both asymmetry and tail dependence. We verify one or both of these conditions for a range of parametric copula functions that are popular in applied work. [source] A simulation tool for designing nutrient monitoring programmes for eutrophication assessments,ENVIRONMETRICS, Issue 1 2010Janet Heffernan Abstract This paper describes a simulation tool to aid the design of nutrient monitoring programmes in coastal waters. The tool is developed by using time series of water quality data from a Smart Buoy, an in situ monitoring device. The tool models the seasonality and temporal dependence in the data and then filters out these features to leave a white noise series. New data sets are then simulated by sampling from the white noise series and re-introducing the modelled seasonality and temporal dependence. Simulating many independent realisations allows us to study the performance of different monitoring designs and assessment methods. We illustrate the approach using total oxidised nitrogen (TOxN) and chlorophyll data from Liverpool Bay, U.K. We consider assessments of whether the underlying mean concentrations of these water quality variables are sufficiently low; i.e. below specified assessment concentrations. We show that for TOxN, even when mean concentrations are at background, daily data from a Smart Buoy or multi-annual sampling from a research vessel would be needed to obtain adequate power. Copyright © 2009 Crown Copyright [source] North Atlantic Oscillation timing of long- and short-distance migrationJOURNAL OF ANIMAL ECOLOGY, Issue 6 2002Mads C. Forchhammer Summary 1The timing of migration is associated with survival and reproductive risks of migrating species. Hence, variation in factors influencing this timing, such as climate, may have significant life history consequences for migrating species. 2Using an autoregressive phenological model, we analysed and contrasted the effects of climate (the North Atlantic Oscillation, NAO) and temporal dependence on the long-term (1928,77) dynamics of springtime arrival in three long-distance (83 populations) and three short-distance (52 populations) migratory bird species breeding throughout Norway. 3Following high NAO winters both long- and short-distance migrants arrived earlier than after low NAO winters. For long-distance migrants, the effect of high NAO winters was probably indirect through improved forage conditions in winter quarters, whereas the effect on short-distance migrants may be related both to improved forage and weather conditions during their northward spring migration. The NAO explained on average 13% (0,46%) and 18% (0,43%) of the interannual variation in arrival dates of long- and short-distance migrants, respectively. 4For both migrant types, long-term variability in springtime arrival increased with increasing strength of the influence of the NAO on timing of migration. In contrast, the strength of temporal dependence was unrelated to variability in long-term springtime arrival. [source] Forecasting the conditional covariance matrix of a portfolio under long-run temporal dependenceJOURNAL OF FORECASTING, Issue 6 2006Trino-Manuel Ñíguez Abstract Long-range persistence in volatility is widely modelled and forecast in terms of the so-called fractional integrated models. These models are mostly applied in the univariate framework, since the extension to the multivariate context of assets portfolios, while relevant, is not straightforward. We discuss and apply a procedure which is able to forecast the multivariate volatility of a portfolio including assets with long memory. The main advantage of this model is that it is feasible enough to be applied on large-scale portfolios, solving the problem of dealing with extremely complex likelihood functions which typically arises in this context. An application of this procedure to a portfolio of five daily exchange rate series shows that the out-of-sample forecasts for the multivariate volatility are improved under several loss functions when the long-range dependence property of the portfolio assets is explicitly accounted for.,,Copyright © 2006 John Wiley & Sons, Ltd. [source] Spatial risk assessment for extreme river flowsJOURNAL OF THE ROYAL STATISTICAL SOCIETY: SERIES C (APPLIED STATISTICS), Issue 5 2009Caroline Keef Summary., The UK has in recent years experienced a series of fluvial flooding events which have simultaneously affected communities over different parts of the country. For the co-ordination of flood mitigation activities and for the insurance and reinsurance industries, knowledge of the spatial characteristics of fluvial flooding is important. Past research into the spatiotemporal risk of fluvial flooding has largely been restricted to empirical estimates of risk measures. A weakness with such an approach is that there is no basis for extrapolation of these estimates to rarer events, which is required as empirical evidence suggests that larger events tend to be more localized in space. We adopt a model-based approach using the methods of Heffernan and Tawn. However, the large proportion of missing data over a network of sites makes direct application of this method highly inefficient. We therefore propose an extension of the Heffernan and Tawn method which accounts for missing values. Furthermore, as the risk measures are spatiotemporal an extension of the Heffernan and Tawn method is also required to handle temporal dependence. We illustrate the benefits of the procedure with a simulation study and by assessing spatial dependence over four fluvial sites in Scotland. [source] Modelling concurrency of events in on-line auctions via spatiotemporal semiparametric modelsJOURNAL OF THE ROYAL STATISTICAL SOCIETY: SERIES C (APPLIED STATISTICS), Issue 1 2007Wolfgang Jank Summary., We introduce a semiparametric approach for modelling the effect of concurrent events on an outcome of interest. Concurrency manifests itself as temporal and spatial dependences. By temporal dependence we mean the effect of an event in the past. Modelling this effect is challenging since events arrive at irregularly spaced time intervals. For the spatial part we use an abstract notion of ,feature space' to conceptualize distances among a set of item features. We motivate our model in the context of on-line auctions by modelling the effect of concurrent auctions on an auction's price. Our concurrency model consists of three components: a transaction-related component that accounts for auction design and bidding competition, a spatial component that takes into account similarity between item features and a temporal component that accounts for recently closed auctions. To construct each of these we borrow ideas from spatial and mixed model methodology. The power of this model is illustrated on a large and diverse set of laptop auctions on eBay.com. We show that our model results in superior predictive performance compared with a set of competitor models. The model also allows for new insight into the factors that drive price in on-line auctions and their relationship to bidding competition, auction design, product variety and temporal learning effects. [source] Hopping photoconductivity and its long-time relaxation in two-dimensional array of Ge/Si quantum dotsPHYSICA STATUS SOLIDI (C) - CURRENT TOPICS IN SOLID STATE PHYSICS, Issue 8 2005N. P. Stepina Abstract Photoconductivity excitation kinetics has been studied in a two-dimensional array of Ge/Si quantum dots under illumination with different light wavelength. Both negative and positive photoeffects depending on dot occupations with holes were observed. Long-time conductivity dynamics (typically, 102,104 sec at T = 4.2 K) has been revealed as well as after switch on and switch off the illumination, displaying a sluggish temporal dependence. The observed effects were not suppressed by decreasing of the excitation energy below the silicon band-gap. For electronic glasses it was discovered that the more time under excitation the faster relaxation rate. Our results are explained by the different capture rate of electrons and holes by quantum dots, due to the presence of potential barriers created by positively charged Ge quantum dots. (© 2005 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim) [source] | |||||||||||||