bluuebunny/crossref_metadata_2025_split huggingface dataset:
Space‐Time Stochastic Modelling in Human Exposure
Authors: Christakos George 
Published: January 2013

Abstract
Perceptions regarding the meaning of the term stochastic modeling (SM) are not as uniform as one might think. This should not come as a surprise, in view of the multidisciplinary nature of environmental health science. Depending on the application considered, one may refer to stochastic models as environmental, ecologic, genetic, epidemiologic, medical, etc. A common factor in all these cases is that SM is concerned with the mathematically rigorous and scientifically meaningful representation, explanation, and prediction of natural phenomena (physical, biological, etc.) in uncertain environments. Uncertainty may be due to measurement errors, heterogeneous databases, erratic biologic fluctuations in space/time, insufficient knowledge, etc. Within such a framework, SM seeks to provide a realistic environmental situation with spatio‐temporal continuity and internal consistency.
Sustainability
Authors: Southam Colette , Southam Gordon 
Published: January 2013

Abstract
A relatively stable environment was vital for the advancement of human civilization over the past 12,000 years (the Holocene). During this time period, humans became experts in exploiting natural resources, allowing for an enormous population expansion as a technologically advanced society. Recognition that our very success is causing widespread damage to Earth's ecosystems is the current basis of sustainability initiatives. Life on this planet is endlessly interconnected. Scientists cannot approach sustainability issues in isolation and sustainable development management needs to reconcile social, economic, and environmental demands – the “three pillars” of sustainability. Collaborative and multidisciplinary academic research is required to understand, predict, and manage the effects humans are having on Earth in order to become sustainable.
Toxicology, Environmental
Authors: Bailer A. John , Oris James T. 
Published: January 2013

AbstractEnvironmental toxicology addresses the potential adverse impacts of toxicants on the function of organisms in the environment. This impact could be evaluated ranging from the molecular level to species interactions at an ecosystem function level. A historic context for environmental toxicology is introduced with connections between toxicity tests and environmental regulations being drawn. Statistical dimensions of risk assessment components are presented. An illustration from toxicant impacts in receiving waters is used to describe hypothesis‐testing approaches for evaluating toxicity and is contrasted with potency estimates based on inverting regression relationships. The entry concludes with a consideration of other regulatory endpoints and future directions in methods development.
Trend Detecting
Authors: Woodward Wayne A. 
Published: January 2013

Abstract
This article discusses the problem of testing for trend in time series data, which is a difficult problem because, among other things, there is not a unified definition of trend. A variety of trend definitions are given and the distinction between deterministic and random trends is discussed. Simulated realizations with random trends are shown along with the global temperature data, and the issues related to deciding whether an apparent trend is deterministic or random are discussed. We examine classical tests for linear trend and discuss the inflated observed significance levels associated with many of these tests. Several tests are presented that have been developed to better control the observed significance level. Also discussed is the problem of using nonparametric methods to test for more general types of trend, such as monotonic trends, that may have no known functional form.
Water Quality Assessment and European Water Framework Directive
Authors: Scott E. Marian , Gemmell J. Campbell 
Published: January 2013

AbstractWater quality assessment is carried out in a spatiotemporal framework, following guidelines and procedures described by regulations such as the EU Water Framework Directive (WFD) (2000) and the US Clean Water Act (1972, and those that follow). This assessment presents a number of statistical challenges, some of which are highlighted in this article.
Spatial and Space‐Time Threshold Exceedances
Authors: Angulo José M. , Madrid Ana E. 
Published: January 2013

AbstractThreshold exceedance sets, defined by the coordinates where a certain critical level is exceeded, are of interest in many application fields in relation to risk analysis including deophysics, environmental sciences, engineering, astrophysics, finance, and insurance, among many others. In particular, many risk indicators can be formulated based on certain structural properties of threshold exceedance sets.This article is structured in two parts. The first part reviews the two main approaches to describe the stochastic behavior of temporal threshold excesses, namely, the generalized Pareto distribution and nonhomogeneous Poisson processes, and collects references to some recent developments in the spatial and spatiotemporal contexts. The second part refers to some aspects of interest in relation to the structure of spatial threshold exceedance sets: on the one hand, geometrical measures such as the hypervolume and the Euler characteristic, which are related with certain probabilities of extremal occurrences; on the other hand, two different types of point processes, respectively based on centroids of connected components and on boundaryA‐exit points, which can be used depending on the specific structural properties of interest under study. The article concludes with a discussion and an illustration in the spatiotemporal context.
Wind Turbines, Birds, and Bats
Authors: Warren‐hicks William J. , Warren‐hicks W. Colin 
Published: January 2013

Abstract
Wind energy produced by wind turbines is a form of green energy. Wind turbines are generally thought to be a positive force for the environment, however, they bring their own controversies to the environmentally couscous community table. Where wind turbines are not thought to contribute to global warming or cause headline news stories of mass tragedy, the turbines' blades have been consistently correlated to bird and bat fatalities.
Hydrological Frequency Analysis
Authors: El Adlouni Salaheddine 
Published: January 2013

AbstractThis article presents a detailed review on developments related to hydrological frequency analysis (HFA). All the HFA steps for hypothesis testing, probability distribution tails, and parameter estimation are discussed. These developments on HFA concern nonstationary models in order to consider the effect of covariates on extreme quantile estimation. Such an approach allows one to reduce uncertainty when estimating return period events.
Hydrological Frequency Analysis, Regional
Authors: Ouarda Taha B. M. J. 
Published: January 2013

AbstractThe optimal design and operation of hydraulic structures relies on the availability of appropriate estimates of hydrological variables at the local and regional levels. Regional frequency analysis is commonly used for the estimation of hydrological or meteorological events (such as floods) at sites where little or no data are available. A number of methodologies have been developed for the regional analysis of hydrological events, with different target hydrological variables, assumptions, limitations, data needs, and outputs. This article presents a review and classification of recent developments in regional hydrological frequency analysis with a focus on the strengths and potentials of the various theories.
Kriging, Asymptotic Theory
Authors: Du Juan 
Published: January 2013

Abstract
The fixed‐domain asymptoic theory regarding the impact of misspecified covariance structure on the optimality of spatial interpolation is reviewed. Conditions in terms of equivalence of measures, similar tail behavior of spectral densities, and the distance of variances after orthogonalization are provided to ensure the pseudo‐BLP to be asymptotically optimal and the assessment of the mean squared error to be comparably accurate.
PredictiveScores
Authors: Gneiting Tilmann 
Published: January 2013

AbstractPredictive scores assess the quality of forecasts, by assigning a numerical score based on the forecast and on the event or value that materializes. Probabilistic forecasts take the form of a predictive probability distribution. Their evaluation calls for the use of proper scoring rules, such as the logarithmic score or the continuous ranked probability score. Effective point forecasting requires a directive in the form of a target functional, say a quantile or the mean of the predictive distribution. It is then critical for the scoring function to be decision theoretically consistent, so that the expected score is minimized when following the directive. For example, the squared error is consistent when the point forecast is desired to be a mean, and the absolute error is consistent when we seek a median.
Uncertainty Quantification, Physical Models
Authors: He Xian , Zhang Hao 
Published: January 2013

Abstract
A physical model refers to a deterministic mathematical model that is built partially based upon physical or biological principles. Because it is deterministic, it is vital to quantify the uncertainty of its output. The ensemble is a common method for a model whose output can be simulated efficiently. For those models that are more computationally demanding to simulate, statistical emulation and stochastic differential models are two useful approaches. This article briefly reviews these methods.
Z
ero‐
I
nflated
C
ount
T
ime
S
eries
Authors: Ray Bonnie K. , Thomas Sarah J. 
Published: January 2013

Abstract
This articles describes an observation‐driven approach to modeling univariate time series of counts that have an overabundance of zeros. A series of daily counts of excess pollution levels observed at air monitoring stations in and around Houston, TX is used to illustrate the ideas.
Bartlett Test
Authors: Hallin Marc 
Published: January 2013

Abstract

The standard test for homogeneity of covariance matrices, known as the
Bartlett test
, is notoriously sensitive to violations of Gaussian assumptions. Its asymptotic behavior under non‐Gaussian densities and its robustification (
validity‐robustness
and
efficiency‐robustness
) have been the subject of an abundant literature, which we briefly review.
A
symptotic
R
elative
E
fficiency (
ARE
)
Authors: Hallin Marc 
Published: January 2013

Abstract

The purpose of asymptotic relative efficiency is to compare two statistical procedures by comparing the sample sizes,
n
1
and
n
2
, say, at which those procedures achieve some given measure of performance; the ratio
n
2
/
n
1
is called the
relative efficiency
of procedure one with respect to procedure two. Finite‐sample evaluations being difficult or impossible, a sequence of measures of performances requiring that those sample sizes go to infinity is generally considered. If those measures of performance are indexed by
n
, say, so that
n
1
and
n
2
take the form
n
1
(
n
) and
n
2
(
n
), the limit lim

n
→∞

n
2
(
n
)/
n
1
(
n
), if it exists, is called the
asymptotic relative efficiency
of procedure one with respect to procedure two.
Independent Component Analysis
Authors: Oja Hannu , Nordhausen Klaus 
Published: January 2013

AbstractIndependent component modelshave gained increasing interest in various fields of applications in recent years. The basic independent component model is a semiparametric model assuming that ap‐variate observed random vector is a linear transformation of an unobserved vector ofpindependent latent variables. This linear transformation is given by an unknownmixing matrix, and one of the main objectives ofindependent component analysis(ICA) is to estimate anunmixing matrixby means of which the latent variables can be recovered. In this article, we discuss the basic independent component model in detail, define the concepts and analysis tools carefully, and consider two families of ICA estimates. The statistical properties (consistency, asymptotic normality, efficiency, robustness) of the estimates can be analyzed and compared via the so calledgain matrices. Some extensions of the basic independent component model, such as models with additive noise or models with dependent observations, are briefly discussed. The article ends with a short example.
Quantile RegresssionThis article has been prepared for the Statistical Theory and Methods section of the
Encyclopedia of Environmetrics
edited by Abdel El‐Shaarawi and Walter Piegorsch. The research was partially supported by NSF grant SES‐0850060.
Authors: Koenker Roger 
Published: January 2013

Abstract

Classical least squares regression may be viewed as a natural way of extending the idea of estimating an unconditional mean parameter to the problem of estimating conditional mean
functions
; the crucial link is the formulation of an optimization problem that encompasses both problems. Likewise, quantile regression offers an extension of univariate quantile estimation to estimation of conditional quantile functions via an optimization of a piecewise linear objective function in the residuals. Median regression minimizes the sum of absolute residuals, an idea introduced by Boscovich in the eighteenth century, and developed by Edgeworth in the nineteenth century.

The asymptotic theory of quantile regression closely parallels the theory of the univariate sample quantiles. Computation of quantile regression estimators may be formulated as a linear programming problem and efficiently solved by simplex or barrier methods. A close link to rank‐based inference has been forged from the theory of the dual regression quantile process, or regression rankscore process. Recent work has extended quantile regression into time‐series, spatial models, survival analysis, and nonparametric estimation.
Poisson Distribution
Authors: Hallin Marc 
Published: January 2013

Abstract

The random variable
X
taking values 0,1,2,…,
x
,… with probabilities
p
λ
(
x
) = e
−λ
λ

x

/
x
!, where is called a
Poisson variable
, and its distribution a
Poisson distribution
, with
parameter
λ. The Poisson distribution with parameter λ can be obtained as the limit, as
n
→ ∞ and
p
→ 0 in such a way that
np
→ λ, of the binomial distribution with exponent
n
and parameter
p
. The family of Poisson distributions indexed by is an exponential family, with natural parameter logλ and privileged sufficient and complete statistic
X
. Poisson distributions are often used in the modeling of count data for “rare events.” As such, they also play a fundamental role in the so‐called Poisson processes.
Nanotechnology: Environmental Applications
Authors: Pelaez Miguel , Han Changseok , Choi Hyeok , Sharma Virender , Byrne Anthony J. , Dunlop Patrick S.M. , Romanos George , Falaras Polycarpos , Dionysiou Dionysios D. 
Published: January 2013

Abstract
Nanomaterials are receiving particular interest due to their novel physical and chemical properties, which are important for a wide range of applications, including environmental remediation. This article presents an overview of the currentadvances on the most relevant nanomaterials and nanotechnologies employed for environmental remediation. Particular emphasis is given to nanostructured semiconductors for photocatalysis; the use of nanomaterials such as nano‐silver, single‐walled carbon nanotubes, fullerenes, and titania for disinfection purposes; reactive metal nanoparticles, in particular zero‐valent iron; ferrate and membrane nanotechnologies. These nanomaterials and nanotechnologies have been used for water and air purification or for the remediation of contaminated groundwater, soil, and sediments.
Water supply and treatment
Authors: Nfodzo Prince , Dionysiou Dionysios D. , Choi Hyeok 
Published: January 2013

AbstractHuman activities and freshwater pollution have impaired the supply of good quality water to majority of the world's population. It is anticipated that there will be a global water crisis by 2030 if definite measures are not taken to curtail the current trends. High population growth rate, increasing urban drift, economic growth, and climate changes are the key factors contributing to the water crisis. The development of sustainable water treatment systems with innovative approaches to planning, design, operation, and maintenance of water infrastructure is imperative, while an integrated management of water and energy can be a new paradigm shift toward sustainability. Going beyond removal of conventional contaminants using coagulation–flocculation–sedimentation–filtration processes, advanced treatment technologies including advanced oxidation, membrane separation, and activated carbon adsorption processes have been adopted to address emerging issues associated with the presence of toxic chemicals in water as well as aesthetic aspects (odor, color, and taste) of water quality. Recently, nanotechnological approaches have emerged as breakthrough technologies for improving water quality with less effort and materials. Meanwhile, more basic approaches employing the concept of water conservation, reclamation, recycle, and reuse might be a better solution to the ever increasing scarcity of good quality drinking water.
Covariance Matrix Estimation (High Dimensional)
Authors: Pourahmadi Mohsen , Biao Wu Wei 
Published: January 2013

AbstractThe article concerns estimation of high‐dimensional covariance matrices. In this case, the sample covariance matrix estimate is typically not consistent. For an improvement, we present various regularization procedures including shrinkage, penalized likelihood estimation, Cholesky decomposition, sparse principal component analysis, and elementwise shrinkage by banding, tapering, and thresholding.
Fish Habitat
Authors: Koops Marten A. , Chu Cindy 
Published: January 2013

Abstract
Fish habitat is composed of the physical, chemical, and biological features of the environment that allow fish to survive, grow, and reproduce. This may involve migration among different habitats as fishes complete portions of their life cycle. The destruction and degradation of fish habitat is one of the greatest threats to freshwater and marine fishes. Fish habitat stressors ultimately affect populations through processes acting on survival, growth, and reproduction. Fish habitat indicators and indices describe the suitability of an environment for fishes on the basis of physiological, behavioral, or ecological preferences. A number of modeling approaches have been used to determine the effects of habitat availability on fishes, including bioenergetic, matrix, individual‐based, trophodynamic, and ecosystem models. The geophysical and biological attributes of fish habitat, combined with both upstream and landscape effects, truly necessitates an ecosystem approach to the management of fish habitat.
Spatially‐Explicit Capture Recapture Methods
Authors: Gopalaswamy Arjun M. 
Published: January 2013

AbstractAnimal density is a parameter of basic interest to field biologists. But owing to logistical and analytical constraints, estimating animal density has been very challenging. Spatially explicit capture–recapture (SECR) models were developed to address this particular, long‐standing problem. In this article, some of the important “milestones” in the SECR literature are discussed. The basic idea in SECR models is to include information about locations of animal captures into the modeling so that density is estimated directly. The early SECR type of approach involved estimation of density via simulations and inverse prediction. The first direct SECR estimator was likelihood‐based, which was more flexible and allowed for inclusion of covariates. In parallel began the development of Bayesian versions of the SECR models. These allowed for greater flexibility and for extensions which could, in addition, also estimate population vital rates. SECR models have witnessed several applications, ranging from analysis of camera‐trap data on large cats to acoustic signal data from birds. The future of SECR models is expected to go far beyond density estimation. It has great potential to answer some long‐standing questions about how behavioral processes drive population dynamics in wild animals.
Dynamic Modeling
Authors: Dowd Michael 
Published: January 2013

Abstract
Dynamic modeling describes the quantitative representation of time‐dependent systems, usually as systems of differential equations or discrete versions thereof. Dynamic models may be nonlinear, high dimensional, spatially explicit, and can exhibit complex behavior. They are most commonly deterministic, but can be stochastic. They are key elements for many scientific disciplines, and the foundation for environmental prediction. Dynamic modeling in environmetrics considers uncertainty analysis, as well as inference on the state of the system and its parameters using available observations.
Variable Selection via Regularization
Authors: Li Runze , Cui Hengjian 
Published: January 2013

AbstractVariable selection has been an active research topic since the 1970s. There are hundreds of publications on variable selection. This entry describes regularization methods for variable selection developed in the recent literature. The regularization methods include classical variable selection criteria such as AIC and BIC and modern variable selection approaches such as LASSO, SCAD, and LARS.
Boycotts
Authors: Forno Francesca 
Published: January 2013

Abstract
In a boycott, one or more parties attempt to achieve certain goals by urging individuals to refrain from purchasing certain goods or using certain public services. Unlike other forms of action utilized by social movements, such as demonstrations and other unconventional activities, boycotts aim to activate the political agency embedded in consumption practices, by stimulating individuals to use marketplace means to achieve what may or may not be marketplace ends.
Claims‐Making
Authors: Lindekilde Lasse 
Published: January 2013

Abstract
Claims‐making refers to the process of performing or articulating claims that bear on someone else's interests. In its simplest form an instance of claims‐making includes two actors—a subject (claimant) and an object (addressee)—and a verbal or physical action (demanding, protesting, criticizing, blaming etc.). In the context of social movement studies and contentious politics, claims‐making has most often referred to the conscious articulation of political demands in the public sphere, thus leaving aside more private or hidden forms of political claims‐making such as voting and lobbyism.