A new class of slash-elliptical distributions

In this paper, we consider a generalization of the modified slash distribution. We define the new family through the quotient between an elliptically distributed random variable and the power of an exponential random variable with parameter equals to 2, both independent. We use the same idea to extend the model for the multivariate case and study general important properties from the resultant family. We perform inference by the method of moments and maximum likelihood. We present a simulation study which indicates satisfactory parameter recovery by using the estimation approaches. Illustrations reveals that it has potential for doing well in real problems.     

A note on the EM algorithm for estimation in the destructive negative binomial cure rate model

In this note we present a modification in the EM algorithm for the destructive negative binomial cure rate model. This alteration enables us to obtain the estimates of the whole parameter vector from the complete log-likelihood function, avoiding the corresponding observed log-likelihood function, which is more involved. To achieve this goal, we resort to the mixture representation of the negative binomial distribution in terms of the Poisson and gamma distributions.     

Bayesian beta nonlinear models with constrained parameters to describe ruminal degradation kinetics

The models used to describe the kinetics of ruminal degradation are usually nonlinear models where the dependent variable is the proportion of degraded food. The method of least squares is the standard approach used to estimate the unknown parameters but this method can lead to unacceptable predictions. To solve this issue, a beta nonlinear model and the Bayesian perspective is proposed in this article. The application of standard methodologies to obtain prior distributions, such as the Jeffreys prior or the reference priors, involves serious difficulties here because this model is a nonlinear non-normal regression model, and the constrained parameters appear in the log-likelihood function through the Gamma function. This paper proposes an objective method to obtain the prior distribution, which can be applied to other models with similar complexity, can be easily implemented in OpenBUGS, and solves the problem of unacceptable predictions. The model is generalized to a larger class of models. The methodology was applied to real data with three models that were compared using the Deviance Information Criterion and the root mean square prediction error. A simulation study was performed to evaluate the coverage of the credible intervals.     

Modelling of socio-ecological connectivity. The rural-urban network in the surroundings of Madrid (Central Spain)

As most of Europe’s metropolitan landscapes grow, a change is occurring in their surrounding rural environment. The consequences thereof mainly involve losses of traditional land uses and changes in the socioecomic structures of the local population. The lack of coupling ‘urban society-countryside’ can be considered to constitute a driving force of this process. The present paper focuses upon the rural-urban network around the metropolis of Madrid (Central Spain). We developed a quantitative model to explain the socio-ecological rural-urban linkages, taking into account the influence of the metropolis in the network of neighbouring municipalities. The results show a rural landscape gradient ranging from silvo-pastoral to agricultural land uses and maintaining different interactions with the local socioeconomy. Urban-rural polarisation of the territory and accessibility to the metropolis are the main factors influencing the landscape dynamics. Territorial cohesion among municipalities and connectivity with the metropolis are factors determining the socio-ecological structure. The agricultural area presents good social cohesion, but a weak connection with the City. The silvo-pastoral landscape, on the contrary, maintains prominent links with the metropolis, but a non-significant interconnection between the small towns. The model tested constitutes a useful tool for analysing socio-ecological connectivity and for quantifying, designing and promoting territorial cohesion policies.     

Ethnic Origins and Religious Transformations in the Afro-Colombian Muslim Community of Buenaventura

The aim of this article is to analyse the origins and transformations of a Muslim community in western Colombia. The history of this small religious group of Afro-Colombians is presented over a period divided into four phases. This division is based on four dominant interpretations of Islamic doctrines adopted by the majority of the group over a period of time. These changes were not only due to religious motivations but also due to changes in the social milieu and the need for taking advantage of emerging opportunities. The religious conversion of Afro-Colombians to Islam took place within the complex socio-political context of the Colombian conflict which began in mid-1960s and is still ongoing. The adoption of this new religious perspective did not evolve in an isolated manner, rather, it transformed the identity of the community by strengthening the value of ethnic differences in a place of segregation. In this context, this paper analyses the role of religion as an important element in the construction of ethnic identity. It is also important to recognize that this cultural negotiation happens at the margins of the dominant society, which views Afro-Colombian minorities negatively or simply ignores their presence.     

Cognitive ergonomics: the use of mind mapping tool in maintaining productive sector of a Brazilian paper company

The use of mind maps as a method of building knowledge, planning, organizing activities and ideas can be seen in the literature related to ergonomics. The results of such use are relevant and its use in academic area found. However, regarding to its use in industrial environments, studies can't not be found. With this scenario, and based on the perception of the ergonomist about the importance of using methods such as mind maps in support of human cognition, it seems pertinent to its use in industry sectors whose cognitive demand requires. Given these assumptions, this study aimed to apply the method of Mind Maps in Productive Maintenance sector of a Brazilian paper. The Productive Maintenance sector in the Paper Industry has an important contribution to operational performance. With practical Predictive Maintenance, Preventive Maintenance and Corrective Maintenance, the industry advocates to make the machines to produce paper is not to stop producing when they are programmed to do so. Among the practices cited, the Preventive Maintenance is one that leads to pre-determined intervals in order to reduce the possibility of placing the equipment in a condition below the required level of acceptance. Therefore, this article aims to propose using the tool "mental maps" in order to collaborate in planning and implementation of preventive maintenance activities in the sector of mechanical maintenance of a pulp and paper industry in southern Brazil. The study investigated the maintenance sector through its employees, who went through training about the tool and then use it and ergonomists company.     

A new cure rate model based on the Yule–Simon distribution with application to a melanoma data set

In this paper, a new survival cure rate model is introduced considering the Yule–Simon distribution [12 H.A. Simon, On a class of skew distribution functions, Biometrika 42 (1955), pp. 425–440.[Crossref], [Web of Science ®] , [Google Scholar]] to model the number of concurrent causes. We study some properties of this distribution and the model arising when the distribution of the competing causes is the Weibull model. We call this distribution the Weibull–Yule–Simon distribution. Maximum likelihood estimation is conducted for model parameters. A small scale simulation study is conducted indicating satisfactory parameter recovery by the estimation approach. Results are applied to a real data set (melanoma) illustrating the fact that the model proposed can outperform traditional alternative models in terms of model fitting.     

A simplified estimation procedure based on the EM algorithm for the power series cure rate model

The family of power series cure rate models provides a flexible modeling framework for survival data of populations with a cure fraction. In this work, we present a simplified estimation procedure for the maximum likelihood (ML) approach. ML estimates are obtained via the expectation-maximization (EM) algorithm where the expectation step involves computation of the expected number of concurrent causes for each individual. It has the big advantage that the maximization step can be decomposed into separate maximizations of two lower-dimensional functions of the regression and survival distribution parameters, respectively. Two simulation studies are performed: the first to investigate the accuracy of the estimation procedure for different numbers of covariates and the second to compare our proposal with the direct maximization of the observed log-likelihood function. Finally, we illustrate the technique for parameter estimation on a dataset of survival times for patients with malignant melanoma.     

The Impact on Inequality of Raising the Minimum Wage: Gap‐narrowing and Reranking Effects

Raising the minimum wage may reduce inequality by increasing the wages of low‐skill workers, but it may also increase inequality due to negative impacts on employment that produce wage losses. Using previous estimates of the elasticities of wages and employment to changes in the minimum wage in Colombia and Brazil, we show that the net impact on inequality of increasing the minimum wage may depend on the distributional weights used for inequality measurement. The results are obtained by decomposing the Gini index into reranking and gap‐narrowing effects. Inequality‐increasing reranking effects, which are associated with job losses, may dominate inequality‐decreasing gap‐narrowing effects, which are associated with wage gains, when high weights are placed on workers with low earnings. For standard distributional weights, however, the likely net impact is a reduction in wage inequality.