1,721,018 research outputs found
Particulate matter and meteorological conditions: a multivariate spatio-temporal analysis
No full textA Geographic Information System for Outdoor Markets
No full textTrade management in public areas requires the availability of homogeneous and reliable data, as well as the use of advanced tools in order to store and process the large amount of information. In this context, the implementation of a Geographic Information System (GIS) and a Web-GIS for outdoor markets improves the levels of efficiency, effectiveness and quality of public services. In particular, the use of a GIS is advantageous to manage the available information, plan enhancement activities aimed at modifying the market areas and their services, support environmental, socio- economic and trade analyses
A new approach for assessing the probability of museum opening choices and its spatial continuity
Full text linkIn the literature, several approaches and methods were applied for studying the visitors' profile or the managerial performance and economic efficiency of the museums; however, none of them investigated the museums opening decisions. To this aim an innovative approach which combines multilevel multinomial ordered models and spatial correlation models, is introduced and some advances in logit data geostatistical modeling is proposed together with an extended form of regression kriging, called multilevel logit kriging. Thus, the variation of the probability of the museums opening decisions both at regional and provincial levels for some peculiar museums characteristics, as well as the effect of some specific regional/provincial key factors which might influence their regular/non regular opening are modeled, also with respect to different types of institution (private/public).
The ISTAT microdata concerning the Italian survey on the museums and cultural institutions, will be considered. The empirical findings will provide worthy advices for the development of suitable management policies
Computational advances for spatio-temporal multivariate environmental models
Full text linkIn multivariate Geostatistics, the linear coregionalization model (LCM) has been widely used over the last decades, in order to describe the spatial dependence which characterizes two or more variables of interest. However, in spatio-temporal multiple modeling, the identification of the main elements of a space–time linear coregionalization model (ST-LCM), as well as of the latent structures underlying the analyzed phenomenon, represents a tough task. In this paper, some computational advances which support the selection of an ST-LCM are described, gathering all the necessary steps which allow the analyst to easily and properly detect the basic space–time components for the phenomenon under study. The implemented algorithm is applied on space–time air quality data measured in Scotland in 2017
Computing non-separability for space-time covariancefunctions: a case study on PM10 data
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Multilevel modeling for investigating the probability of digital innovation in museums
Full text linkMuseums represent a fundamental asset for the Italian cultural and social background, and the use of digital technologies can be considered as a keystone for their attractiveness. Thus, assessing the specific determinants which stimulate to invest in new digital solutions and to provide a competitive museum offer is of crucial interest. For this reason, a performing multilevel approach for modeling the probability of including digital innovations in museums will be discussed and different modeling options will be compared. In particular, the imple- mentation of a multilevel binary logit model will be useful to detect the factors of adopting at least basic digital tools. Then, the development of an innovative and flexible multilevel multinomial ordered model will be suitable to further investigate on the probability for the museums to move towards medium/low or high levels of digitalization, on the basis of an increasing sorting criterion. This will be realized by considering the variation of such proba- bility both at regional and provincial levels for some key specific museums features, as well as by including some regional/provincial contextual factors
covatest: An R Package for Selecting a Class of Space-Time Covariance Functions
Full text linkAlthough a very rich list of classes of space-time covariance functions exists, specific tools for selecting the appropriate class for a given data set are needed. Thus, the main topic of this paper is to present the new R package, covatest, which can be used for testing some characteristics of a covariance function, such as symmetry, separability and type of non-separability, as well as for testing the adequacy of some classes of space-time covariance models. These last aspects can be relevant for choosing a suitable class of covariance models. The proposed results have been applied to an environmental case study
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