N. Limnios  M. Mesbah  A. Sadek 《Environmetrics》2004,15(5):483-490

In this work, a new index for longitudinal quality of life is proposed and statistically analyzed through discrete and continuous time Markov process models. Copyright © 2004 John Wiley & Sons, Ltd.  相似文献   

    

Richard M. Engeman  N. Paige Groninger  Daniel S. Vice 《Environmetrics》2003,14(3):295-305

The inadvertent introduction of the brown tree snake (Boiga irregularis) to Guam has resulted in the extirpation of most of the island's native terrestrial vertebrates, has presented a health hazard to small children, and also has produced economic problems. Trapping around ports and other cargo staging areas is central to a program designed to deter dispersal of the species. Sequential trapping of smaller plots is also being used to clear larger areas of snakes in preparation for endangered species reintroductions. Traps and trapping personnel are limited resources, which places a premium on the ability to plan the deployment of trapping efforts. In a series of previous trapping studies, data on brown tree snake removal from forested plots was found to be well modeled by exponential decay functions. For the present article, we considered a variety of model forms and estimation procedures, and used capture data from individual plots as random subjects to produce a general random coefficients model for making predictions of brown tree snake capture rates. The best model was an exponential decay with positive asymptote produced using nonlinear mixed model estimation where variability among plots was introduced through the scale and asymptote parameters. Practical predictive abilities were used in model evaluation so that a manager could project capture rates in a plot after a period of time, or project the amount of time required for trapping to reduce capture rates to a desired level. The model should provide managers with a tool for optimizing the allocation of limited trapping resources. Copyright © 2003 John Wiley & Sons, Ltd.  相似文献   

    

T. P. Hutchinson 《Environmetrics》2000,11(3):305-314

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Renata Romanowicz  Helen Higson  Ian Teasdale 《Environmetrics》2000,11(3):351-371

The aim of the study is an uncertainty analysis of an air dispersion model. The model used is described in NRPB‐R91 (Clarke, 1979), a model for short and medium range dispersion of radionuclides released into the atmosphere. Uncertainties in the model predictions arise both from the uncertainty of the input variables and the model simplifications, resulting in parameter uncertainty. The uncertainty of the predictions is well described by the credibility intervals of the predictions (prediction limits), which in turn are derived from the distribution of the predictions. The methodology for estimating this distribution consists of running multiple simulations of the model for discrete values of input parameters following some assumed random distributions. The value of the prediction limits lies in their objectivity. However, they depend on the assumed input distributions and their ranges (as do the model results). Hence the choice of distributions is very important for the reliability of the uncertainty analysis. In this work, the choice of input distributions is analysed from the point of view of the reliability of the predictive uncertainty of the model. An analysis of the influence of different assumptions regarding model input parameters is performed. Of the parameters investigated (i.e. roughness length, release height, wind fluctuation coefficient and wind speed), the model showed the greatest sensitivity to wind speed values. A major influence on the results of the stability condition specification is also demonstrated. Copyright © 2000 John Wiley & Sons, Ltd.  相似文献   

    

J. Gani 《Environmetrics》1999,10(6):677-683

This note considers the spread of HIV in a single prison where there is a constant rate of departure and replacement of prisoners. Some of the incoming prisoners will be HIV+, and homogeneous mixing within the prison is assumed. HIV is thus spread sexually or by the sharing of intravenous drug users' needles. A deterministic continuous time prison model is examined, and the number of HIV+ infective prisoners at time t derived. A stochastic analogue of this model is constructed, in the form of a continuous Markov chain, and its embedded chain studied. Finally, a control procedure involving the screening of a proportion of the incoming prisoners, and the quarantining of the HIV+ individuals is proposed. Its consequences are derived for the deterministic model. The proportion to be screened, given a total expenditure for the screening procedure and the medical costs of quarantined and non‐quarantined infectives, can be calculated. Copyright © 1999 John Wiley & Sons, Ltd.  相似文献   

    

Resat Kasap 《Environmetrics》1999,10(5):625-631

In the study of multivariate processes, a framework is needed for describing not only the properties of individual series, but also the possible cross‐relationship among the series. For this purpose, the method of canonical correlation analysis is used for treatment of multivariate time series which results in scalar component models (SCMs) already given by Tiao and Tsay (1989, Journal of Business and Economic Statistics, 1 , 43–56). For the application of this methodology, temperature data are used which led to some useful empirical results. Copyright © 1999 John Wiley & Sons, Ltd.  相似文献   

    

N. H. Augustin  M. A. Mugglestone  S. T. Buckland 《Environmetrics》1998,9(2):175-196

Three approaches to modelling spatial data in which simulation plays a vital role are described and illustrated with examples. The first approach uses flexible regression models, such as generalized additive models, together with locational covariates to fit a surface to spatial data. We show how the bootstrap can be used to quantify the effects of model selection uncertainty and to avoid oversmoothing. The second approach, which is appropriate for binary data, allows for local spatial correlation by the inclusion in a logistic regression model of a covariate derived from neighbouring values of the response variable. The resulting autologistic model can be fitted to survey data obtained from a random sample of sites by incorporating the Gibbs sampler into the modelling procedure. We show how this modelling strategy can be used not only to fit the autologistic model to sites included in the survey, but also to estimate the probability that a certain species is present in the unsurveyed sites. Our third approach relates to the analysis of spatio-temporal data. Here we model the distribution of a plant or animal species as a function of the distribution at an earlier time point. The bootstrap is used to estimate parameters and quantify their precision. © 1998 John Wiley & Sons, Ltd.  相似文献   

    

Don Mackay  Eva Webster 《Environmetrics》1998,9(5):541-553

The role of mass balance models for estimating the fate and concentration of chemicals in a multimedia environment on a local scale within typically 10 to 20 km of the contaminant source is described and discussed. An approach is suggested for estimating these concentrations as a function of emission rate, chemical properties, and meteorological conditions. It is hoped that models of the type described may assist in assessing the impact of a municipal or industrial source on the surrounding community and specifically assist in the epidemiological evaluation of the incidence of diseases such as cancer in which environmental exposure may be a contributing factor. © 1998 John Wiley & Sons, Ltd.  相似文献   

    

Kristina Rasmusson  Chin‐Fu Tsang  Yvonne Tsang  Maria Rasmusson  Lehua Pan  Fritjof Fagerlund  Jacob Bensabat  Auli Niemi 《Greenhouse Gases: Science and Technology》2015,5(4):419-436

Geological storage in sedimentary basins is considered a viable technology in mitigating atmospheric CO₂ emissions. Alternating high and low permeability strata are common in these basins. The distribution of injected CO₂ among such layers affects e.g. CO₂ storage efficiency, capacity and plume footprint. A numerical study on the distribution of injected CO₂ into a multi‐layered reservoir, accounting for coupled wellbore‐reservoir flow, was carried out using the T2Well/ECO2N code. A site‐specific case as well as a more general case were considered. Properties and processes governing the distribution of sequestrated CO₂ were identified and the potential to operationally modify the distribution was investigated. The distribution of CO₂ was seen to differ from that of injected water, i.e. it was not proportional to the transmissivity of the layers. The results indicate that caution should be taken when performing numerical simulations of CO₂ injection into layered formations. Ignoring coupled wellbore‐reservoir flow and instead adopting a simple boundary condition at the injection well, such as an inflow rate proportional to the transmissivity of each layer, may result in significant underestimation of the proportion of CO₂ ending up in the shallower layers, as not all relevant processes are accounted for. This discrepancy has been thoroughly investigated and quantified for several CO₂ sequestration scenarios.  相似文献   

    

S. Baran  A. Mller 《Environmetrics》2015,26(2):120-132

Ensembles of forecasts are typically employed to account for the forecast uncertainties inherent in predictions of future weather states. However, biases and dispersion errors often present in forecast ensembles require statistical post‐processing. Univariate post‐processing models such as Bayesian model averaging (BMA) have been successfully applied for various weather quantities. Nonetheless, BMA and many other standard post‐processing procedures are designed for a single weather variable, thus ignoring possible dependencies among weather quantities. In line with recently upcoming research to develop multivariate post‐processing procedures, for example, BMA for bivariate wind vectors, or flexible procedures applicable for multiple weather quantities of different types, a bivariate BMA model for joint calibration of wind speed and temperature forecasts is proposed on the basis of the bivariate truncated normal distribution. It extends the univariate truncated normal BMA model designed for post‐processing ensemble forecast of wind speed by adding a normally distributed temperature component with a covariance structure representing the dependency among the two weather quantities. The method is applied to wind speed and temperature forecasts of the eight‐member University of Washington mesoscale ensemble and of the 11‐member Aire Limitée Adaptation dynamique Développement International‐Hungary Ensemble Prediction System (ALADIN‐HUNEPS) ensemble of the Hungarian Meteorological Service, and its predictive performance is compared to that of the independent BMA calibration of these weather quantities and the general Gaussian copula method. The results indicate improved calibration of probability and accuracy of point forecasts in comparison to the raw ensemble and the independent BMA approach, and the overall performance of this bivariate model is able to keep up with that of the Gaussian copula method. Copyright © 2014 John Wiley & Sons, Ltd.  相似文献