A Bayesian Factor Model for Spatial Panel Data with a Separable Covariance Approach

A hierarchical Bayesian factor model for multivariate spatially and temporally correlated data is proposed. This method searches factor scores incorporating a dependence within observations due to both a geographical and a temporal structure and it is an extension of a model proposed by Mezzetti (2012) using the results of a separable covariance matrix for the spatial panel data as in Leorato and Mezzetti (2016). A Gibbs sampling algorithm is implemented to sample from the posterior distributions. We illustrate the benefit and the performance of our model by analyzing death rates for different diseases together with some socio-economical and behavioural indicators and by analyzing simulated data

Evidence of a new low field cross-over in the vortex critical velocity of type-II superconducting thin films

We measure current-voltage characteristics as function of magnetic field and temperature in Nb strips of different thickness and width. The instability voltage of the flux flow state related to the vortex critical velocity v* is studied and compared with the Larkin-Ovchinnikov theory. Beside the usual power-law dependence v* ~ B^-1/2, in the low field range a new cross-over field, Bcr1, is observed below which v* decreases by further lowering the external magnetic field B. We ascribe this unexpected cross-over to vortex channeling due to a fan-like penetration of the applied magnetic field as confirmed by magneto-optic imaging. The observation of Bcr1 becomes a direct evidence of a general feature in type-II superconducting films at low fields, that is a channel-like vortex motion induced by the inhomogeneous magnetic state caused by the relatively strong pinning

Is a matrix exponential specification suitable for the modeling of spatial correlation structures?

This paper investigates the adequacy of the matrix exponential spatial specifications (MESS) as an alternative to the widely used spatial autoregressive models (SAR). To provide as complete a picture as possible, we extend the analysis to all the main spatial models governed by matrix exponentials comparing them with their spatial autoregressive counterparts. We propose a new implementation of Bayesian parameter estimation for the MESS model with vague prior distributions, which is shown to be precise and computationally efficient. Our implementations also account for spatially lagged regressors. We further allow for location-specific heterogeneity, which we model by including spatial splines. We conclude by comparing the performances of the different model specifications in applications to a real data set and by running simulations. Both the applications and the simulations suggest that the spatial splines are a flexible and efficient way to account for spatial heterogeneities governed by unknown mechanisms

Optical Luminosities and Mass-to-Light Ratios of Nearby Galaxy Clusters

We analyze a sample of 105 clusters having virial mass homogeneously estimated and for which galaxy magnitudes are available with a well defined high degree of completeness. In particular, we consider a subsample of 89 clusters with B_j band galaxy magnitudes taken from the COSMOS/UKST Southern Sky Object Catalogue. We compute cluster luminosities L_{B_j} within several clustercentric distances and within the virialization radius R_{vir}. In particular, we use the luminosity function and background counts estimated by Lumsden et al. (1997) on the Edinburgh/Durham Southern Galaxy Catalogue. We analyze the effect of several uncertainties connected to photometric data, fore/background removal, and extrapolation below the completeness limit of the photometry, in order to assess the robustness of our cluster luminosity estimates. We draw our results on the relations between luminosity and dynamical quantities from the COSMOS sample by considering mass and luminosities determined within the virialization radius. We find a very good correlation between cluster luminosity, L_{B_j}, and galaxy velocity dispersion, sigma_v, with L_{B_j} proportional to sigma_v^{2.1--2.3}. Our estimate of typical value for the mass-to-light ratio is M/L_{B_j} about 250 (in solar units). We do not find any correlation of M/L_{B_j} with cluster morphologies, i.e. Rood--Sastry and Bautz--Morgan types, and only a weak significant correlation with cluster richness. We find that mass has a slight, but significant, tendency to increase faster than the luminosity does, M proportional to L_{B_j}^{1.2--1.3}. We verify the robustness of this relation against a number of possible systematics

Spatial panel data model with error dependence: A Bayesian separable covariance approach

A hierarchical Bayesian model for spatial panel data is proposed. The idea behind the proposed method is to analyze spatially dependent panel data by means of a separable covariance matrix. Let us indicate the observations as yit, in i = 1,...,N regions and at t = 1,...,T times, and suppose the covariance matrix of y, given a set of regressors, is written as a Kronecker product of a purely spatial and a purely temporal covariance. On the one hand, the structure of separable covariances dramatically reduces the number of parameters, while on the other hand, the lack of a structured pattern for spatial and temporal covariances permits capturing possible unknown dependencies (both in time and space). The use of the Bayesian approach allows one to overcome some of the difficulties of the classical (MLE or GMM based) approach. We present two illustrative examples: the estimation of cigarette price elasticity and of the determinants of the house price in 120 municipalities in the Province of Rome

Advancing the science of cancer cost measurement: challenges and opportunities

Cancer accounts for a major proportion of national health expenditures, which are expected to increase in the future. This paper aims to identify major challenges with estimating cancer related costs, and discuss international comparisons, and recommendations for future research. Methods. It starts from the experience of an international workshop aimed at comparing cancer burden evaluation methods, improving results comparability, discussing strengths and criticisms of different approaches. Results. Three methodological themes necessary to inform the analysis are identified and discussed: data availability; costs definition; epidemiological measures. Conclusions. Cost evaluation is applied to cancer control interventions and is relevant for public health planners. Despite their complexity, international comparisons are fundamental to improve, generalize and extend cost evaluation to different contexts