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Pedro Macedo
Center for Research and Development in Mathematics and Applications, Department of Mathematics, Campus Universitário de Santiago, University of Aveiro, 3810-193 Aveiro, Portugal

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Journal article
Published: 13 June 2021 in Energies
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The maximum entropy bootstrap for time series is applied in this study to investigate the nexus between carbon emissions from electricity generation and the gross domestic product, using a bivariate framework for eight Middle Eastern countries between 1995 and 2017. The sample under study includes oil-producing countries such as Bahrain, Iran, Iraq, Kuwait, Oman, Qatar, Saudi Arabia, and United Arab Emirates. As the electricity generation in these economies relies mainly on oil and gas, finding out the existence and direction of the relationship between the two considered variables has remarkable implications for policymakers and governments in these countries to achieve both higher economic growth and environmental protection. As expected, this nexus is validated for all countries in the sample but not in all models, time periods, and lags. Therefore, policymakers can set appropriate electricity conservation policies based on these varied empirical findings to boost economic growth with minimum environmental degradation.

ACS Style

Zeinab Zanjani; Pedro Macedo; Isabel Soares. Investigating Carbon Emissions from Electricity Generation and GDP Nexus Using Maximum Entropy Bootstrap: Evidence from Oil-Producing Countries in the Middle East. Energies 2021, 14, 3518 .

AMA Style

Zeinab Zanjani, Pedro Macedo, Isabel Soares. Investigating Carbon Emissions from Electricity Generation and GDP Nexus Using Maximum Entropy Bootstrap: Evidence from Oil-Producing Countries in the Middle East. Energies. 2021; 14 (12):3518.

Chicago/Turabian Style

Zeinab Zanjani; Pedro Macedo; Isabel Soares. 2021. "Investigating Carbon Emissions from Electricity Generation and GDP Nexus Using Maximum Entropy Bootstrap: Evidence from Oil-Producing Countries in the Middle East." Energies 14, no. 12: 3518.

Journal article
Published: 19 May 2021 in Cuadernos de Gestión
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The objective of this paper is to analyse the retail banking behaviour in Portugal (2008–2010, 2011–2013 and 2014–2016), by taking into account the financial and economic assistance programme (FEAP) – monitored by the European Commission, the European Central Bank and the International Monetary Fund – that Portugal went through and that started in 2011. With competitive dynamics it is possible to understand the evolution of competitive strategies of the institutions of a strategic group within a given time horizon. Data were collected after consultation of reports and accounts of Banks from Banco de Portugal database. The results were analysed and discussed in light of the theory of strategic groups and their competitive dynamics allows us to conclude that: Banks implemented different competitive strategies; Strategic groups have dissimilar resources; and Strategic groups display different strategies. The 2008–2010 period can be considered as a ‘deregulated’ period, the 2011–2013 as a period of ‘imposed regulation’, and the 2014–2016 as a period of ‘strategic consolidation’ with strategic changes that have prompted strategic groupings of the various institutions as consequence of a low mobility barrier strategy.

ACS Style

Albérico Travassos Rosário; António Carrizo Moreira; Pedro Macedo. Competitive dynamics of strategic groups in the Portuguese banking industry. Cuadernos de Gestión 2021, 21, 119 -133.

AMA Style

Albérico Travassos Rosário, António Carrizo Moreira, Pedro Macedo. Competitive dynamics of strategic groups in the Portuguese banking industry. Cuadernos de Gestión. 2021; 21 (2):119-133.

Chicago/Turabian Style

Albérico Travassos Rosário; António Carrizo Moreira; Pedro Macedo. 2021. "Competitive dynamics of strategic groups in the Portuguese banking industry." Cuadernos de Gestión 21, no. 2: 119-133.

Conference paper
Published: 21 November 2020 in mODa 11 - Advances in Model-Oriented Design and Analysis
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In linear regression models where there are no relationships between the dependent variable and each of the potential explanatory variables-a usual scenario in real-world problems-some of them can be identified as relevant by standard statistical procedures. This incorrect identification is usually known as Freedman’s paradox. To avoid this disturbing effect in regression analysis, an info-metrics approach based on normalized entropy is discussed and illustrated in this work. As an alternative to traditional statistical methodologies currently used by practitioners, the simulation results suggest that normalized entropy is a powerful procedure to identify pure noise models.

ACS Style

Pedro Macedo. Freedman’s Paradox: A Solution Based on Normalized Entropy. mODa 11 - Advances in Model-Oriented Design and Analysis 2020, 239 -252.

AMA Style

Pedro Macedo. Freedman’s Paradox: A Solution Based on Normalized Entropy. mODa 11 - Advances in Model-Oriented Design and Analysis. 2020; ():239-252.

Chicago/Turabian Style

Pedro Macedo. 2020. "Freedman’s Paradox: A Solution Based on Normalized Entropy." mODa 11 - Advances in Model-Oriented Design and Analysis , no. : 239-252.

Journal article
Published: 20 April 2020 in Sustainable Cities and Society
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Cities and living standards contribute intensively to air pollution, an environmental risk factor which causes diseases. Recently, in developed countries, the majority of cities has grown rapidly and has experienced increasing environmental problems. In this article we analyze the effect of urban air pollution considering the available data for the years 2007, 2010 and 2013 in 24 German cities. Proposing a new model, we start the analysis using data envelopment analysis (DEA) and stochastic frontier analysis (SFA) to predict eco-efficiency scores for the 24 German cities. Afterwards, it is applied fractional regression to infer about the influencing factors of the eco-efficiency scores, at the city level. Results suggest a significant impact over eco-efficiency due to the excess of PM10, the average temperature, the average of NO2 concentration and rainfall. The findings in this study hold important implications for policymakers and urban planners in Germany, especially those that coordinate environmental protection and economic development in cities. Therefore, interventions to reduce urban air pollution can be accomplished on different regulatory levels, leading to synergistic effects as the decrease of climate change effects and noise.

ACS Style

Victor Moutinho; Mara Madaleno; Pedro Macedo. The effect of urban air pollutants in Germany: eco-efficiency analysis through fractional regression models applied after DEA and SFA efficiency predictions. Sustainable Cities and Society 2020, 59, 102204 .

AMA Style

Victor Moutinho, Mara Madaleno, Pedro Macedo. The effect of urban air pollutants in Germany: eco-efficiency analysis through fractional regression models applied after DEA and SFA efficiency predictions. Sustainable Cities and Society. 2020; 59 ():102204.

Chicago/Turabian Style

Victor Moutinho; Mara Madaleno; Pedro Macedo. 2020. "The effect of urban air pollutants in Germany: eco-efficiency analysis through fractional regression models applied after DEA and SFA efficiency predictions." Sustainable Cities and Society 59, no. : 102204.

Conference paper
Published: 19 October 2019 in mODa 11 - Advances in Model-Oriented Design and Analysis
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It was already in the fifties of the last century that the relationship between information theory, statistics and maximum entropy was established, following the works of Kullback, Leibler, Lindley and Jaynes. However, the applications were restricted to very specific domains and it was not until recently that the convergence between information processing, data analysis and inference demanded the foundation of a new scientific area, commonly referred to as Info-Metrics [1, 2]. As a huge amount of information and large-scale data have become available, the term “big data” has been used to refer to the many kinds of challenges presented in its analysis: many observations, many variables (or both), limited computational resources, different time regimes or multiple sources. In this work, we consider one particular aspect of big data analysis which is the presence of inhomogeneities, compromising the use of the classical framework in regression modelling. A new approach is proposed, based on the introduction of the concepts of info-metrics to the analysis of inhomogeneous large-scale data. The framework of information-theoretic estimation methods is presented, along with some information measures. In particular, the normalized entropy is tested in aggregation procedures and some simulation results are presented.

ACS Style

Maria Da Conceição Costa; Pedro Macedo. Normalized Entropy Aggregation for Inhomogeneous Large-Scale Data. mODa 11 - Advances in Model-Oriented Design and Analysis 2019, 19 -29.

AMA Style

Maria Da Conceição Costa, Pedro Macedo. Normalized Entropy Aggregation for Inhomogeneous Large-Scale Data. mODa 11 - Advances in Model-Oriented Design and Analysis. 2019; ():19-29.

Chicago/Turabian Style

Maria Da Conceição Costa; Pedro Macedo. 2019. "Normalized Entropy Aggregation for Inhomogeneous Large-Scale Data." mODa 11 - Advances in Model-Oriented Design and Analysis , no. : 19-29.

Original article
Published: 01 June 2019 in Journal of Regulatory Economics
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The literature on incentive-based regulation in the electricity sector indicates that the size of this sector in a country constrains the choice of frontier methods as well as the model specification itself to measure economic efficiency of regulated firms. The aim of this study is to propose a stochastic frontier approach with maximum entropy estimation, which is designed to extract information from limited and noisy data with minimal statements on the data generation process. Stochastic frontier analysis with generalized maximum entropy and data envelopment analysis—the latter one has been widely used by national regulators—are applied to a cross-section data on thirteen European electricity distribution companies. Technical efficiency scores and rankings of the distribution companies generated by both approaches are sensitive to model specification. Nevertheless, the stochastic frontier analysis with generalized maximum entropy results indicate that technical efficiency scores have similar distributional properties and these scores as well as the rankings of the companies are not very sensitive to the prior information. In general, the same electricity distribution companies are found to be in the highest and lowest efficient groups, reflecting weak sensitivity to the prior information considered in the estimation procedure.

ACS Style

Elvira Silva; Pedro Macedo; Isabel Soares. Maximum entropy: a stochastic frontier approach for electricity distribution regulation. Journal of Regulatory Economics 2019, 55, 237 -257.

AMA Style

Elvira Silva, Pedro Macedo, Isabel Soares. Maximum entropy: a stochastic frontier approach for electricity distribution regulation. Journal of Regulatory Economics. 2019; 55 (3):237-257.

Chicago/Turabian Style

Elvira Silva; Pedro Macedo; Isabel Soares. 2019. "Maximum entropy: a stochastic frontier approach for electricity distribution regulation." Journal of Regulatory Economics 55, no. 3: 237-257.

Research article
Published: 22 April 2018 in Environmental Science and Pollution Research
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This article intends to compute agriculture technical efficiency scores of 27 European countries during the period 2005–2012, using both data envelopment analysis (DEA) and stochastic frontier analysis (SFA) with a generalized cross-entropy (GCE) approach, for comparison purposes. Afterwards, by using the scores as dependent variable, we apply quantile regressions using a set of possible influencing variables within the agricultural sector able to explain technical efficiency scores. Results allow us to conclude that although DEA and SFA are quite distinguishable methodologies, and despite attained results are different in terms of technical efficiency scores, both are able to identify analogously the worst and better countries. They also suggest that it is important to include resources productivity and subsidies in determining technical efficiency due to its positive and significant exerted influence.

ACS Style

Victor Moutinho; Mara Madaleno; Pedro Macedo; Margarita Robaina; Carlos Marques. Efficiency in the European agricultural sector: environment and resources. Environmental Science and Pollution Research 2018, 25, 17927 -17941.

AMA Style

Victor Moutinho, Mara Madaleno, Pedro Macedo, Margarita Robaina, Carlos Marques. Efficiency in the European agricultural sector: environment and resources. Environmental Science and Pollution Research. 2018; 25 (18):17927-17941.

Chicago/Turabian Style

Victor Moutinho; Mara Madaleno; Pedro Macedo; Margarita Robaina; Carlos Marques. 2018. "Efficiency in the European agricultural sector: environment and resources." Environmental Science and Pollution Research 25, no. 18: 17927-17941.

Book chapter
Published: 01 January 2017 in Advances in Business Information Systems and Analytics
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Car safety is an essential feature of marketing strategies for automobile companies. In this work, a statistical analysis on crash tests is conducted based on data available from European New Car Assessment Programme (Euro NCAP). The research work developed in this chapter presents a statistical analysis of the information produced by Euro NCAP, using the SPSS and MATLAB software, and seeks to answer the following research questions: - are there statistically significant differences on adult occupant safety in the six years under study? - are there statistically significant differences among the best-selling car classes regarding safety in frontal collisions? - are electric and hybrid automobiles less secure than their traditional counterparts with respect to frontal collisions?

ACS Style

Antonio Moreira; Mónica Gouveia; Pedro Macêdo. Car Safety. Advances in Business Information Systems and Analytics 2017, 305 -331.

AMA Style

Antonio Moreira, Mónica Gouveia, Pedro Macêdo. Car Safety. Advances in Business Information Systems and Analytics. 2017; ():305-331.

Chicago/Turabian Style

Antonio Moreira; Mónica Gouveia; Pedro Macêdo. 2017. "Car Safety." Advances in Business Information Systems and Analytics , no. : 305-331.

Conference paper
Published: 01 June 2016 in 2016 13th International Conference on the European Energy Market (EEM)
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The main purpose of this study is to present an alternative benchmarking approach that can be used by national regulators of utilities. It is widely known that the lack of sizeable data sets limits the choice of the benchmarking method and the specification of the model to set price controls within incentive-based regulation. Ill-posed frontier models are the problem that some national regulators have been facing. Maximum entropy estimators are useful in the estimation of such ill-posed models, in particular in models exhibiting small sample sizes, collinearity and non-normal errors, as well as in models where the number of parameters to be estimated exceeds the number of observations available. The empirical study involves a sample data used by the Portuguese regulator of the electricity sector to set the parameters for the electricity distribution companies in the regulatory period of 2012-2014. DEA and maximum entropy methods are applied and the efficiency results are compared.

ACS Style

Elvira Silva; Pedro Macedo; Isabel Soares. An alternative benchmarking approach for electricity utility regulation using maximum entropy. 2016 13th International Conference on the European Energy Market (EEM) 2016, 1 -4.

AMA Style

Elvira Silva, Pedro Macedo, Isabel Soares. An alternative benchmarking approach for electricity utility regulation using maximum entropy. 2016 13th International Conference on the European Energy Market (EEM). 2016; ():1-4.

Chicago/Turabian Style

Elvira Silva; Pedro Macedo; Isabel Soares. 2016. "An alternative benchmarking approach for electricity utility regulation using maximum entropy." 2016 13th International Conference on the European Energy Market (EEM) , no. : 1-4.

Chapter
Published: 01 January 2016 in Advances in Marketing, Customer Relationship Management, and E-Services
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This study involves several theories, namely: the theory of reasoned action, the technology acceptance model, the theory of planned behavior and the internet banking acceptance model. It aims to understand the relationships between the virtual atmosphere and emotional states, how the individual characteristics (social identity, altruism and telepresence) and emotional states influence attitudes, and how attitudes, past experience and trust influence actual use of a site. To this end, the authors developed three conceptual models explaining the relationships among the above-mentioned variables. Methodologically, descriptive statistics, exploratory factor analysis and the generalized maximum entropy estimator are used to test the three models in a wedding site. Of the eight hypotheses proposed, one can only partially validate hypotheses h1, h2, h3 and h6, while hypothesis h7 is accepted and the remaining are rejected.

ACS Style

António C. Moreira; Mariana Mira Ferreira; Pedro Macedo. Virtual Atmosphere, Emotions, Attitudes and Real Use. Advances in Marketing, Customer Relationship Management, and E-Services 2016, 172 -206.

AMA Style

António C. Moreira, Mariana Mira Ferreira, Pedro Macedo. Virtual Atmosphere, Emotions, Attitudes and Real Use. Advances in Marketing, Customer Relationship Management, and E-Services. 2016; ():172-206.

Chicago/Turabian Style

António C. Moreira; Mariana Mira Ferreira; Pedro Macedo. 2016. "Virtual Atmosphere, Emotions, Attitudes and Real Use." Advances in Marketing, Customer Relationship Management, and E-Services , no. : 172-206.

Original articles
Published: 15 October 2015 in Communications in Statistics - Simulation and Computation
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In this article, the Ridge–GME parameter estimator, which combines Ridge Regression and Generalized Maximum Entropy, is improved in order to eliminate the subjectivity in the analysis of the ridge trace. A serious concern with the visual inspection of the ridge trace to define the supports for the parameters in the Ridge–GME parameter estimator is the misinterpretation of some ridge traces, in particular where some of them are very close to the axes. A simulation study and two empirical applications are used to illustrate the performance of the improved estimator. A MATLAB code is provided as supplementary material.

ACS Style

Pedro Macedo. Ridge Regression and Generalized Maximum Entropy: An Improved Version of the Ridge-GME Parameter Estimator. Communications in Statistics - Simulation and Computation 2015, 1 -13.

AMA Style

Pedro Macedo. Ridge Regression and Generalized Maximum Entropy: An Improved Version of the Ridge-GME Parameter Estimator. Communications in Statistics - Simulation and Computation. 2015; ():1-13.

Chicago/Turabian Style

Pedro Macedo. 2015. "Ridge Regression and Generalized Maximum Entropy: An Improved Version of the Ridge-GME Parameter Estimator." Communications in Statistics - Simulation and Computation , no. : 1-13.

Journal article
Published: 01 September 2015 in Journal of Cleaner Production
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This study aims to evaluate the resource and environment efficiency problem of European countries. We specify a new stochastic frontier model where Gross Domestic Product (GDP) is considered as the desirable output and Greenhouse Gases (GHG) emissions as the undesirable output. Capital, Labour, Fossil fuels and Renewable Energy consumption are regarded as inputs. GDP/GHG ratio is maximized given the values of the other four variables. The study is divided into two distinct periods: 2000-2004 and 2005-2011. This division is related to the implementation of the Kyoto Protocol in 2005, and will allow us to evaluate the difference between the levels of efficiency before and after the establishment of environmental targets. Since stochastic frontier models are typically ill-posed, a new maximum entropy approach to assess technical efficiency, which combines information from the data envelopment analysis and the structure of composed error from the stochastic frontier approach without requiring distributional assumptions, is presented in this work

ACS Style

Margarita Robaina-Alves; Victor Moutinho; Pedro Macedo. A new frontier approach to model the eco-efficiency in European countries. Journal of Cleaner Production 2015, 103, 562 -573.

AMA Style

Margarita Robaina-Alves, Victor Moutinho, Pedro Macedo. A new frontier approach to model the eco-efficiency in European countries. Journal of Cleaner Production. 2015; 103 ():562-573.

Chicago/Turabian Style

Margarita Robaina-Alves; Victor Moutinho; Pedro Macedo. 2015. "A new frontier approach to model the eco-efficiency in European countries." Journal of Cleaner Production 103, no. : 562-573.

Conference paper
Published: 01 May 2015 in 2015 12th International Conference on the European Energy Market (EEM)
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This study aims to evaluate the resource and environment efficiency problem of European countries. We specify a new stochastic frontier model where Gross Domestic Product (GDP) is considered as the desirable output and Greenhouse Gases (GHG) emissions as the undesirable output. Capital, Labour, Fossil fuels and Renewable Energy consumption are regarded as inputs. The study is divided into two distinct periods, 2000-2004 and 2005-2011, in order to evaluate the difference between efficiency levels before and after the establishment of environmental targets related with the implementation of the Kyoto Protocol in 2005. A maximum entropy approach to assess technical efficiency is discussed.

ACS Style

Margarita Robaina Alves; Victor Moutinho; Pedro Macedo; Alves Margarita Robaina. Economic and environmental efficiency in Europe: Evidence from a new stochastic frontier model. 2015 12th International Conference on the European Energy Market (EEM) 2015, 1 -4.

AMA Style

Margarita Robaina Alves, Victor Moutinho, Pedro Macedo, Alves Margarita Robaina. Economic and environmental efficiency in Europe: Evidence from a new stochastic frontier model. 2015 12th International Conference on the European Energy Market (EEM). 2015; ():1-4.

Chicago/Turabian Style

Margarita Robaina Alves; Victor Moutinho; Pedro Macedo; Alves Margarita Robaina. 2015. "Economic and environmental efficiency in Europe: Evidence from a new stochastic frontier model." 2015 12th International Conference on the European Energy Market (EEM) , no. : 1-4.

Journal article
Published: 01 October 2014 in Journal of Mathematical Economics
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ACS Style

Pedro Macedo; Manuel Scotto. Cross-entropy estimation in technical efficiency analysis. Journal of Mathematical Economics 2014, 54, 124 -130.

AMA Style

Pedro Macedo, Manuel Scotto. Cross-entropy estimation in technical efficiency analysis. Journal of Mathematical Economics. 2014; 54 ():124-130.

Chicago/Turabian Style

Pedro Macedo; Manuel Scotto. 2014. "Cross-entropy estimation in technical efficiency analysis." Journal of Mathematical Economics 54, no. : 124-130.

Original articles
Published: 11 September 2014 in Communications in Statistics - Simulation and Computation
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It is well-known that under fairly conditions linear regression becomes a powerful statistical tool. In practice, however, some of these conditions are usually not satisfied and regression models become ill-posed, implying that the application of traditional estimation methods may lead to non-unique or highly unstable solutions. Addressing this issue, in this paper a new class of maximum entropy estimators suitable for dealing with ill-posed models, namely for the estimation of regression models with small samples sizes affected by collinearity and outliers, is introduced. The performance of the new estimators is illustrated through several simulation studies.

ACS Style

Pedro Macedo; Manuel Scotto; Elvira Silva. Regularization With Maximum Entropy and Quantum Electrodynamics: The Merg(E) Estimators. Communications in Statistics - Simulation and Computation 2014, 45, 1143 -1157.

AMA Style

Pedro Macedo, Manuel Scotto, Elvira Silva. Regularization With Maximum Entropy and Quantum Electrodynamics: The Merg(E) Estimators. Communications in Statistics - Simulation and Computation. 2014; 45 (3):1143-1157.

Chicago/Turabian Style

Pedro Macedo; Manuel Scotto; Elvira Silva. 2014. "Regularization With Maximum Entropy and Quantum Electrodynamics: The Merg(E) Estimators." Communications in Statistics - Simulation and Computation 45, no. 3: 1143-1157.

Journal article
Published: 13 September 2012 in Journal of Productivity Analysis
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Although the theory of state-contingent production is well-established, the empirical implementation of this approach is still in an infancy stage. The possibility of finding a large number of states of nature, few observations per state and models affected by collinearity have led some researchers to claim the urgent need to develop robust estimation techniques. In this paper, we investigate the performance of some maximum entropy estimators to assess technical efficiency with state-contingent production frontiers. The methodological discussion and the simulation study provided in the paper reveal some of the potential of these estimators. Small mean squared error loss and small differences between the true and the estimated mean of technical efficiency show that the maximum entropy can be a powerful tool in the estimation of state-contingent production frontiers.

ACS Style

Pedro Macedo; Elvira Silva; Manuel Scotto. Technical efficiency with state-contingent production frontiers using maximum entropy estimators. Journal of Productivity Analysis 2012, 41, 131 -140.

AMA Style

Pedro Macedo, Elvira Silva, Manuel Scotto. Technical efficiency with state-contingent production frontiers using maximum entropy estimators. Journal of Productivity Analysis. 2012; 41 (1):131-140.

Chicago/Turabian Style

Pedro Macedo; Elvira Silva; Manuel Scotto. 2012. "Technical efficiency with state-contingent production frontiers using maximum entropy estimators." Journal of Productivity Analysis 41, no. 1: 131-140.

Original articles
Published: 27 August 2010 in Communications in Statistics - Simulation and Computation
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In this article, a new method to estimate the ridge parameter, based on the ridge trace and an analytical method borrowed from maximum entropy, is presented. The performance of the new estimator is illustrated through a Monte Carlo simulation study and an empirical application to the well-known Portland cement data set.

ACS Style

Pedro Macedo; Manuel Scotto; Elvira Silva. On the Choice of the Ridge Parameter: A Maximum Entropy Approach. Communications in Statistics - Simulation and Computation 2010, 39, 1628 -1638.

AMA Style

Pedro Macedo, Manuel Scotto, Elvira Silva. On the Choice of the Ridge Parameter: A Maximum Entropy Approach. Communications in Statistics - Simulation and Computation. 2010; 39 (8):1628-1638.

Chicago/Turabian Style

Pedro Macedo; Manuel Scotto; Elvira Silva. 2010. "On the Choice of the Ridge Parameter: A Maximum Entropy Approach." Communications in Statistics - Simulation and Computation 39, no. 8: 1628-1638.

Original articles
Published: 30 April 2010 in Communications in Statistics - Simulation and Computation
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In this article, a general class of estimators for the linear regression model affected by outliers and collinearity is introduced and studied in some detail. This class of estimators combines the theory of light, maximum entropy, and robust regression techniques. Our theoretical findings are illustrated through a Monte Carlo simulation study.

ACS Style

Pedro Macedo; Manuel Scotto; Elvira Silva. A General Class of Estimators for the Linear Regression Model Affected by Collinearity and Outliers. Communications in Statistics - Simulation and Computation 2010, 39, 981 -993.

AMA Style

Pedro Macedo, Manuel Scotto, Elvira Silva. A General Class of Estimators for the Linear Regression Model Affected by Collinearity and Outliers. Communications in Statistics - Simulation and Computation. 2010; 39 (5):981-993.

Chicago/Turabian Style

Pedro Macedo; Manuel Scotto; Elvira Silva. 2010. "A General Class of Estimators for the Linear Regression Model Affected by Collinearity and Outliers." Communications in Statistics - Simulation and Computation 39, no. 5: 981-993.