A nonparametric test for serial independence of errors in linear regression

A test for serial independence of regression errors, consistent in the direction of first order alternatives, is proposed. The test statistic is a function of a Hoeffding-Blum-Kiefer-Rosenblatt type of empirical process, based on residuals. The resultant statistic converges, surprisingly, to the same limiting distribution as the corresponding statistic based on true errors

Nonparametric and semiparametric estimation with discrete regressors

This paper presents and discusses procedures for estimating regression curves when regressors are discrete and applies them to semiparametric inference problems. We show that pointwise root-n-consistency and global consistency of regression curve estimates are achieved without employing any smoothing, even for discrete regressors with unbounded support. These results still hold when smoothers are used, under much weaker conditions than those required with continuous regressors. Such estimates are useful in semiparametric inference problems. We discuss in detail the partially linear regression model and shape-invariant modelling. We also provide some guidance on estimation in semiparametric models where continuous and discrete regressors are present. The paper also includes a Monte Carlo study

Inference on semiparametric models with discrete regressors

We study statistical properties of coefficient estimates of the partially linear regression model when some or all regressors, in the unknown part of the model, are discrete. The method does not require smoothing in the discrete variables. Unlike when there are continuous regressors. when all regressors are discrete independence between regressors and regression errors is not required. We also give some guidance on how to implement the estimate when there are both continuous and discrete regressors in the unknown part of the model. Weights employed in this paper seem straightforwardly applicable to other semiparametric problems

- A NONPARAMETRIC TEST FOR SERIAL INDEPENDENCE OF REGRESSION ERRORS.

A test for serial independence of regression errors is proposed that is consistent in the direction ofserial dependence alternatives of first order. The test statistic is a function of aHoeffding-Blum-Kiefer-Rosenblatt type of empirical process, based on residuals. The resultantstatistic converges, surprisingly, to the same limiting distribution as the corresponding statisticbased on true errors.Empirical process based on residuals; Hoeffding-Blum-Kiefer-Rosenblatt statistic; Serial independence test

Heterogeneous data source integration for smart grid ecosystems based on metadata mining

The arrival of new technologies related to smart grids and the resulting ecosystem of applications andmanagement systems pose many new problems. The databases of the traditional grid and the variousinitiatives related to new technologies have given rise to many different management systems with several formats and different architectures. A heterogeneous data source integration system is necessary toupdate these systems for the new smart grid reality. Additionally, it is necessary to take advantage of theinformation smart grids provide. In this paper, the authors propose a heterogeneous data source integration based on IEC standards and metadata mining. Additionally, an automatic data mining framework isapplied to model the integrated information.Ministerio de Economía y Competitividad TEC2013-40767-

Household poultry production northern Tolima (Colombia)

Páginas 64-67Este artículo muestra los resultados obtenidos en un estudio transversal en cuatro municipios de la zona norte del departamento del Tolima (Colombia) con el fin de caracterizar la avicultura familiar en la comunidad. In formación sobre producción avícola, nivel tecnológico, sistemas de alimentación, consumo y contribución a la economía familiar fue recolectada mediante entrevistas a los granjeros. El principal fin de este componente productivo es el autoconsumo. En 2006 el 55, 62 y 78% de familias de cada grupos (C1, C2, C3, respectivamente) criaron aves. Las principales limitaciones identificadas son las deficiencias en la alimentación, la ausencia de asistencia técnica, la presencia de enfermedades. Los resultados sugieren que la avicultura familiar representa una oportunidad para contribuir al mejoramiento de las condiciones de vida de las familias campesinas, especialmente de las mujeres, para lo cual se requiere que la actividad ocupe un lugar relevante en la agenda de las instituciones de desarrollo de investigación.ABSTRACT. This article shows results of a research project related to household poultry production carried out in the peasant communities of four northern municipalities of Departamento del Tolima (Colombia), to characterize backyard poultry production and small poultry farms. Information on poultry production, technological level, feeding systems, and consumption and contribution to household income was collected through identified farmer in terviews. The main purpose of this production system is as food for the household. In 2006 55, 62 y 78 % of households of each group (C1,C2,C3, respectively) were raising poultry. Poultry feeding and nutrition practices, management, and presence of diseases were identified as the main limitations. Results suggest that backyard poultry and small poultry farms production systems contribute to the improvement of living standards of peasant households, especially those of women, and therefore should be included as a priority in the research agenda of institutions promoting research

Forecasting Recharging Demand to Integrate Electric Vehicle Fleets in Smart Grids

Electric vehicle fleets and smart grids are two growing technologies. These technologies provided new possibilities to reduce pollution and increase energy efficiency. In this sense, electric vehicles are used as mobile loads in the power grid. A distributed charging prioritization methodology is proposed in this paper. The solution is based on the concept of virtual power plants and the usage of evolutionary computation algorithms. Additionally, the comparison of several evolutionary algorithms, genetic algorithm, genetic algorithm with evolution control, particle swarm optimization, and hybrid solution are shown in order to evaluate the proposed architecture. The proposed solution is presented to prevent the overload of the power grid

Electricity clustering framework for automatic classification of customer loads

Clustering in energy markets is a top topic with high significance on expert and intelligent systems. The main impact of is paper is the proposal of a new clustering framework for the automatic classification of electricity customers’ loads. An automatic selection of the clustering classification algorithm is also highlighted. Finally, new customers can be assigned to a predefined set of clusters in the classificationphase. The computation time of the proposed framework is less than that of previous classification tech- niques, which enables the processing of a complete electric company sample in a matter of minutes on a personal computer. The high accuracy of the predicted classification results verifies the performance of the clustering technique. This classification phase is of significant assistance in interpreting the results, and the simplicity of the clustering phase is sufficient to demonstrate the quality of the complete mining framework.Ministerio de Economía y Competitividad TEC2013-40767-RMinisterio de Economía y Competitividad IDI- 2015004

Monitoring and Fault Location Sensor Network for Underground Distribution Lines

One of the fundamental tasks of electric distribution utilities is guaranteeing a continuous supply of electricity to their customers. The primary distribution network is a critical part of these facilities because a fault in it could affect thousands of customers. However, the complexity of this network has been increased with the irruption of distributed generation, typical in a Smart Grid and which has significantly complicated some of the analyses, making it impossible to apply traditional techniques. This problem is intensified in underground lines where access is limited. As a possible solution, this paper proposes to make a deployment of a distributed sensor network along the power lines. This network proposes taking advantage of its distributed character to support new approaches of these analyses. In this sense, this paper describes the aquiculture of the proposed network (adapted to the power grid) based on nodes that use power line communication and energy harvesting techniques. In this sense, it also describes the implementation of a real prototype that has been used in some experiments to validate this technological adaptation. Additionally, beyond a simple use for monitoring, this paper also proposes the use of this approach to solve two typical distribution system operator problems, such as: fault location and failure forecasting in power cables.Ministerio de Economía y Competitividad, Government of Spain project Sistema Inteligente Inalámbrico para Análisis y Monitorización de Líneas de Tensión Subterráneas en Smart Grids (SIIAM) TEC2013-40767-RMinisterio de Educación, Cultura y Deporte, Government of Spain, for the funding of the scholarship Formación de Profesorado Universitario 2016 (FPU 2016