1,721,004 research outputs found
Esercizi di Statistica (2L) cod. 072900 Per gli allievi ING INF e TEL Anno accademico 2008-20091
No full textEserciziario di statistica per il corso di Statistica II livello per allievi INF-TE
Esercizi di Calcolo delle Probabilità cod. 061195 Per gli allievi ING AUT, ELN, INF e TEL Anno accademico 2008-2009
No full textEserciziario di Calcolo delle Probabilità per i corsi di primo livello ci calcolo delle probabilità tenuti per allievi ingegneria dell'Area dell'Informazion
Some considerations on a version of the law of the iterated logarithm due to F. P. Cantelli
No full textIstituto Lombardo. Accademia di Scienze e Lettere. Rendiconti. Scienze Matematiche e Applicazioni. A ISSN: 0021-250
On the population density distribution across space: a probabilistic approach.
No full textWorking within a Bayesian parametric framework, we develop a novel approach to studying the distribution of regional population density across space. By exploiting the Gamma distribution, we are able to introduce heterogeneity across space without incurring an a priori definition of territorial units. Our contribution also permits the inclusion of an approximation of individual preferences as a further driving force in location choices. We perform an empirical application to the case of Massachusetts. Our results demonstrate that a subjective measure of distance performs well in replicating the population distribution across Massachusetts
Population distribution over time: modelling local spatial dependence with a CAR process
Full text linkThe effectiveness of local spatial dependence in shaping the population density distribution is investigated. Individual location preferences are modelled by considering the status-related features of a given spatial unit and its neighbours as well as local random spatial dependence. The novelty is framing such a dependence through conditionally autoregressive (CAR) census random effects that are added to a spatially lagged explanatory variable X (SLX) setting. The results not only confirm that controlling for the spatial dimension is relevant but also indicate that local spatial dependence warrants consideration when determining the population distribution of recent decades. In this respect, the framework turns out to be useful for the analysis of microdata in which individual relationships (in a same spatial unit) enforce local spatial dependence
Case-deletion importance sampling estimators: central limit theorems and related results
No full textAbstract:
Case-deleted analysis is a popular method for evaluating the influence of a subset of cases on inference. The use of Monte Carlo estimation strategies in complicated Bayesian settings leads naturally to the use of importance sampling techniques to assess the divergence between full-data and case-deleted posteriors and to provide estimates under the case-deleted posteriors. However, the dependability of the importance sampling estimators depends critically on the variability of the case-deleted weights. We provide theoretical results concerning the assessment of the dependability of case-deleted importance sampling estimators in several Bayesian models. In particular, these results allow us to establish whether or not the estimators satisfy a central limit theorem. Because the conditions we derive are of a simple analytical nature, the assessment of the dependability of the estimators can be verified routinely before estimation is performed. We illustrate the use of the results in several examples
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