Search results for "spatial dependence"
showing 10 items of 36 documents
Impact-parameter dependent nuclear parton distribution functions: EPS09s and EKS98s and their applications in nuclear hard processes
2012
We determine the spatial (impact parameter) dependence of nuclear parton distribution functions (nPDFs) using the $A$-dependence of the spatially independent (averaged) global fits EPS09 and EKS98. We work under the assumption that the spatial dependence can be formulated as a power series of the nuclear thickness functions $T_A$. To reproduce the $A$-dependence over the entire $x$ range we need terms up to $[T_A]^4$. As an outcome, we release two sets, EPS09s (LO, NLO, error sets) and EKS98s, of spatially dependent nPDFs for public use. We also discuss the implementation of these into the existing calculations. With our results, the centrality dependence of nuclear hard-process observables…
EPS09s and EKS98s: Impact parameter dependent nPDF sets
2013
In our recent study we have determined two new spatially dependent nuclear PDF (nPDF) sets, EPS09s and EKS98s. With these, the hard-process cross-sections can be calculated in different centrality classes consistently with the globally analyzed nPDFs for the first time. The sets were determined by exploiting the $A$-systematics of the globally fitted nPDF sets, EPS09 and EKS98. For the spatial dependence of the nPDFs we used a power series ansatz in the nuclear thickness function $T_A$. In this flash talk we introduce the framework, and present our NLO EPS09s-based predictions for the nuclear modification factor in four centrality classes for inclusive neutral pion production in p+Pb collis…
Modeling the Impact Parameter Dependence of the nPDFs With EKS98 and EPS09 Global Fits
2013
So far the nuclear PDFs (nPDFs) in the global DGLAP fits have been taken to be spatially independent. In this work, using the $A$-dependence of the globally fitted sets EPS09 and EKS98, we have determined the spatial dependence of the nPDFs in terms of powers of the nuclear thickness functions. New spatially dependent nPDF sets EPS09s (NLO, LO, error sets) and EKS98s (LO) are released. As an application, we consider the nuclear modification factor $R_{dAu}^{\pi^0}$ at midrapidity for neutral pion production in deuteron-gold collisions at RHIC in NLO. Comparison with the PHENIX data in different centrality classes is also shown. In addition, predictions for the corresponding nuclear modifica…
Spatial distribution of rainfall trends in Sicily (1921–2000)
2006
Abstract The feared global climate change could have important effects on various environmental variables including rainfall in many countries around the world. Changes in precipitation regime directly affect water resources management, agriculture, hydrology and ecosystems. For this reason it is important to investigate the changes in the spatial and temporal rainfall pattern in order to improve water management strategies. In this study a non-parametric statistical method (Mann–Kendall rank correlation method) is employed in order to verify the existence of trend in annual, seasonal and monthly rainfall and the distribution of the rainfall during the year. This test is applied to about 25…
A Spatial Econometric Analysis of Convergence Across European Regions, 1980–1995
2003
The convergence of European regions has been largely discussed in the macroeconomic and the regional science literature during the past decade. Two observations are often emphasized. First, the convergence rate among European regions appears to be very slow in the extensive samples considered (Barro and Sala-iMartin 1991, 1995; Armstrong 1995a; Sala-i-Martin 1996a, 1996b). Second, as shown in Ertur and Le Gallo (see Chap. 2), the geographical distribution of European per capita GDP is highly clustered.
Modeling accident risk at the road level through zero-inflated negative binomial models: A case study of multiple road networks
2021
Abstract This paper presents a case study carried out in multiple cities of the Valencian Community (Spain) to determine the effect of sociodemographic and road characteristics on traffic accident risk. The analyzes are performed at the road segment level, considering the linear network representing the road structure of each city as a spatial lattice. The number of accidents observed in each road segment from 2010 to 2019 is taken as the response variable, and a zero-inflated modeling approach is considered. Count overdispersion and spatial dependence are also accounted for. Despite the complexity and sparsity of the data, the fitted models performed considerably well, with few exceptions.…
A spatially filtered mixture of β-convergence regressions for EU regions, 1980–2002
2007
Assessing regional growth and convergence across Europe is a matter of primary relevance. Empirical models that do not account for structural heterogeneities and spatial effects may face serious misspecification problems. In this work, a mixture regression approach is applied to the beta-convergence model, in order to produce an endogenous selection of regional growth patterns. A priori choices, such as North-South or centre-periphery divisions, are avoided. In addition to this, we deal with the spatial dependence existing in the data, applying a local filter to the data. The results indicate that spatial effects matter, and either absolute, conditional, or club convergence, if extended to …
A spatial analysis of new business formation: Replicative vs innovative behaviour
2017
Abstract Using spatial econometric tools, the paper examines the spatial structure of new business formation of Italian regions during the period 2004–2007. In particular, the study empirically investigates whether new business formation in a given geographical area may be explained in terms of replicative and/or innovative entrepreneurial behaviour in each area as well as in the neighbouring areas. Additionally, the analysis focuses on the influence of urbanization on the birth of new firms. From the estimation of a Spatial Durbin Model, we find a significant degree of spatial dependence among Italian regions not only in new business formation but also in some of its determinants. We also …
Bayesian Mapping of Lichens Growing on Trees
2001
Suitability of trees as hosts for epiphytic lichens are studied in a forest stand of size 25 ha. Suitability is measured as occupation probabilites which are modelled using hierarchical Bayesian approach. These probabilities are useful for an ecologist. They give smoothed spatial distribution map of suitability for each of the species and can be used in detecting high- and low-probability areas. In addition, suitability is explained by tree-level covariates. Spatial dependence, which is due to unobserved spatially structured covariates, is modelled through an unobserved Markov random field. Markov chain Monte Carlo method has been applied in Bayesian computation. The extensive spatial data …
Gaussian component mixtures and CAR models in Bayesian disease mapping
2012
Hierarchical Bayesian models involving conditional autoregression (CAR) components are commonly used in disease mapping. An alternative model to the proper or improper CAR is the Gaussian component mixture (GCM) model. A review of CAR and GCM models is provided in univariate settings where only one disease is considered, and also in multivariate situations where in addition to the spatial dependence between regions, the dependence among multiple diseases is analyzed. A performance comparison between models using a set of simulated data to help illustrate their respective properties is reported. The results show that both in univariate and multivariate settings, both models perform in a comp…