Bimodal symmetric-asymmetric power-normal families

This article proposes new symmetric and asymmetric distributions applying methods analogous as the ones in Kim (2005 Kim, H.J. (2005). On a class of two-piece skew-normal distributions. Statist.: J. Theoret. Appl. Statist. 39:537–553.[Taylor &; Francis Online], [Web of Science ®] , [Google Scholar]) and Arnold et al. (2009 Arnold, B.C., H.W. Gómez, and H.S. Salinas. (2009). On multiple constraint skewed models. Statist. J. Theoret. Appl. Statist. 43: 279–293.[Taylor &; Francis Online], [Web of Science ®] , [Google Scholar]) to the exponentiated normal distribution studied in Durrans (1992 Durrans, S.R. (1992). Distributions of fractional order statistics in hydrology. Water Resour. Res. 28:1649–1655.[Crossref], [Web of Science ®] , [Google Scholar]), that we call the power-normal (PN) distribution. The proposed bimodal extension, the main focus of the paper, is called the bimodal power-normal model and is denoted by BPN(α) model, where α is the asymmetry parameter. The authors give some properties including moments and maximum likelihood estimation. Two important features of the model proposed is that its normalizing constant has closed and simple form and that the Fisher information matrix is nonsingular, guaranteeing large sample properties of the maximum likelihood estimators. Finally, simulation studies and real applications reveal that the proposed model can perform well in both situations.     

Random spectral measure for non Gaussian moving averages

We study the distribution of phases and amplitudes for the spectral representation of weighted moving averages of a general noise measure. The simple independent structure, known for the Gaussian case, and involving Rayleigh amplitude and uniform phase distributions, is lost for the non Gaussian noise case. We show that the amplitude/phase distributions exhibit a rich and more complex structure depending not just on the covariance of the process but specifically on the form of the kernel and the noise distribution. We present a theoretical tool for studying these distributions that follows from a proof of the spectral theorem that yields an explicit expression for the spectral measure. The main interest is in noise measures based on second-order Lévy motions since such measures are easily available through independent sampling. We approximate the spectral stochastic measure by independent noise increments which allows us to obtain amplitude/phase distributions that is of fundamental interest for analyzing processes in the frequency domain. For the purpose of approximating the moving average process through sums of trigonometric functions, we assess the mean square error of discretization of the spectral representation. For a specified accuracy, the approximation is explicitly given. We illustrate the method for the moving averages driven by the Laplace motion.     

Bayesian non-parametric modeling for integro-difference equations

Integro-difference equations (IDEs) provide a flexible framework for dynamic modeling of spatio-temporal data. The choice of kernel in an IDE model relates directly to the underlying physical process modeled, and it can affect model fit and predictive accuracy. We introduce Bayesian non-parametric methods to the IDE literature as a means to allow flexibility in modeling the kernel. We propose a mixture of normal distributions for the IDE kernel, built from a spatial Dirichlet process for the mixing distribution, which can model kernels with shapes that change with location. This allows the IDE model to capture non-stationarity with respect to location and to reflect a changing physical process across the domain. We address computational concerns for inference that leverage the use of Hermite polynomials as a basis for the representation of the process and the IDE kernel, and incorporate Hamiltonian Markov chain Monte Carlo steps in the posterior simulation method. An example with synthetic data demonstrates that the model can successfully capture location-dependent dynamics. Moreover, using a data set of ozone pressure, we show that the spatial Dirichlet process mixture model outperforms several alternative models for the IDE kernel, including the state of the art in the IDE literature, that is, a Gaussian kernel with location-dependent parameters.     

Automatic specification of piecewise linear additive models: application to forecasting natural gas demand

When facing any forecasting problem not only is accuracy on the predictions sought. Also, useful information about the underlying physics of the process and about the relevance of the forecasting variables is very much appreciated. In this paper, it is presented an automatic specification procedure for models that are based on additivity assumptions and piecewise linear regression. This procedure allows the analyst to gain insight about the problem by examining the automatically selected model, thus easily checking the validity of the forecast. Monte Carlo simulations have been run to ensure that the model selection procedure behaves correctly under weakly dependent data. Moreover, comparison over other well-known methodologies has been done to evaluate its accuracy performance, both in simulated data and in the context of short-term natural gas demand forecasting. Empirical results show that the accuracy of the proposed model is competitive against more complex methods such as neural networks.     

“Nothing goes as planned”: Practitioners reflect on matching children and foster families

Matching children with foster carers is an important step in every nonkinship family foster care placement. Although guidelines for matching are provided in several studies, the case‐specific context of the decision can influence the practitioners' ability to adhere to these guidelines. Therefore, this study answers the following question: “How does the case‐specific context influence the practitioners' decision‐making process regarding matching in family foster care?” Using a qualitative design, 20 semistructured interviews were conducted with practitioners matching children with foster families. Three themes emerged representing different layers of practitioners' everyday decision‐making: matching as planned, matching being tailored, and matching being compromised. The results show that exceptions are part of practitioners' daily work, either due to the belief that it might benefit those involved or because of obstacles presented during the decision‐making process. When the decision is compromised, matching practitioners lower their standards, while at the same time safeguarding the quality of the match. This proves that matching in practice is more than choosing a family, and guidelines are needed to determine what “good‐enough” matching should entail.     

Neoliberalism and Austerity in Spain,Portugal and South Africa: The Revolution of Older Persons

ABSTRACT

In Portugal, Spain, and South Africa, there has been a noted anti-neoliberal resistance, marked by the significant participation of the older generation in protest movements. Changing demographics, the global financial crisis, unemployment, poverty, and the reliance of the family nucleus on the pensioner, coupled with neoliberal and austerity-based reductions to welfare programs, pensions, health, and social care, has caused the “silver revolution.” As a population group that is often considered to be less politically active and robust members of society, such resistance is a noteworthy moment in society that needs to be considered and responded to.     

Estimating the expected value of fuzzy random variables in random samplings from finite populations

In this paper we consider the problem of estimating the expected value of a fuzzy-valued random element in random samplings from finite populations. To this purpose, we quantify the associated sampling error by means of a parameterized measure we have introduced in a previous paper. Keywords: Aumann's integral, expected value of a fuzzy random variable, fuzzy random variable, -mean squared dispersion, random samplings, random set.     

Composite measures of social,economic and demographic regional differentiation in Australia

This paper describes the application of the two-stage principal component method to analyse Australian aggretate/regional/ data. Statistical indicators of social standing, economic structure and demographic features are analysed separately in order to obtain composite measures of various complex characteristics of the regions in each of these domains. The method does not assume statistical independency of principal components, so the relations between them are examined. The index of regional socio-economic status as well as its relations to other characteristics are of the main interest.     

Types of Personal Social Networks of Older Adults in Portugal

This study presents and discusses a three-dimensional typology for personal social networks of Portuguese older adults. We used a K-means cluster analysis of structural, functional and relational-contextual variables of the networks of 612 participants aged 65?+?(M?=?76?±?7.6), mostly women (63%). Four types of networks emerged: family networks, friendship networks, neighbourhood networks and institutional networks. The most frequent are family networks (61.8%), constituted by 94.6% of family ties, on average, attesting the familistic nature of the older persons’ networks in Portugal, followed by friendship networks (23.5%) and neighbourhood networks (11.9%). The less frequent type is the institutional network (2.8%), dominated by formal ties (M?=?59.3%). Sociographic profiles reveal that family networks are more likely to be held by middle-old focal subjects, married or widowed, and with children. Friendship and neighbourhood networks are held by young-old subjects with different marital status, many of them living alone, with a higher proportion of men with friendship networks. Institutional networks are held by old–old, widowed or single with no children. The presented typology contributes to understand social support needs and social isolation. The conclusions allow to anticipate social services’ demand trajectories and to propose intervention plans and social policy measures to promote the wellbeing of the older population.