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Independence of error terms in a linear regression model, often not established. So a linear regression model with correlated error terms appears in many applications. According to the earlier studies, this kind of error terms, basically can affect the robustness of the linear regression model analysis. It is also shown that the robustness of the parameters estimators of a linear regression model can stay using the M-estimator. But considering that, it acquires this feature as the result of establishment of its efficiency. Whereas, it has been shown that the minimum Matusita distance estimators, has both features robustness and efficiency at the same time. On the other hand, because the Cochrane and Orcutt adjusted least squares estimators are not affected by the dependence of the error terms, so they are efficient estimators. Here we are using of a non-parametric kernel density estimation method, to give a new method of obtaining the minimum Matusita distance estimators for the linear regression model with correlated error terms in the presence of outliers. Also, simulation and real data study both are done for the introduced estimation method. In each case, the proposed method represents lower biases and mean squared errors than the other two methods.KEYWORDS: Robust estimation method, minimum Matusita distance estimation method, non-parametric kernel density estimation method, correlated error terms, outliers 相似文献
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AbstractInbound open innovation (IOI) has become a potentially valuable means of gaining competitive advantage and enhancing organizational performance. This article explores how knowledge infrastructure capability (KIC) affects IOI through the moderating role of absorptive capacity. This research conceptualizes and develops three dimensions of KIC (technological, structural and cultural), and tests the relationships between KIC, absorptive capacity and IOI. Data for the study were collected from 125 small and medium enterprises (SMEs) based in France, and the relationships proposed in the framework were tested using structural equation modeling (SEM). The results indicate that higher levels of KIC can lead to enhanced absorptive capacity and improved IOI. That is, KIC can have a direct, positive impact on absorptive capacity and IOI. Moreover, absorptive capacity partially mediates the linkage between KIC and IOI. The article contributes to the conceptualization of the impact of KIC on IOI, by emphasizing a firm’s absorptive capacity. It offers a validated instrument to measure KIC, and provides an empirical evidence of the impact of KIC on absorptive capacity and IOI. This article also extends the extant literature by focusing on KIC and absorptive capacity simultaneously in a model to understand the notion of IOI in the SMEs based in France. This study offers useful guidance for measuring and implementing KIC in a SME context and encourages further research in this area. 相似文献
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Sajjad Afraei Sayyed Hasan Madani 《Journal of Statistical Computation and Simulation》2017,87(17):3336-3376
Rock bursts are sudden and violent failures of surrounding rockmasses in underground mines and excavations. In this paper, a database consisting of 188 case histories was collected. Each case history contains some of the predictor variables ‘overburden thickness, maximum tangential stress, uniaxial compressive strength of rock, tensile strength of rock, stress ratio, brittleness ratio and elastic energy index’ and one of the four defined classes for the dependent variable ‘rock burst intensity’. A strategy, including ‘outlier detection and substitution, normality evaluation, deduction of distribution functions, estimation of mean and mean variation ranges, evaluation of mean-equality and distribution function-equality hypotheses, correlation analysis and factor analysis for in-review variables’, was implemented. The strategy led to conclude that some predictor variables with available case histories have no contributions for rock burst prediction. These inferences were in accordance with the results of regression techniques for qualitative dependent variables. Besides, many predictor variable arrangements were incompatible with factor analysis. In the case of compatible arrangements, the variation of the predictor variables cannot be considerably reflected. Application of nonlinear principal component analysis using auto-associative neural networks did not also lead to representative components. Therefore, the significant predictor variables can only be used to design new classifiers. 相似文献
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With adult smoking prevalence rates declining too slowly to reach national objectives, opinion leaders are considering policies to improve tobacco-related outcomes by regulating the composition of cigarettes to be (1) less harmful and/or (2) less addictive. Because harm reduction efforts may actually encourage higher cigarette consumption by promoting a safer image, and addictiveness reduction may increase the harmfulness of cigarettes by encouraging compensatory smoking behaviors, policymakers must consider the tradeoffs between these two approaches when proposing legislation to control cigarette content. To estimate health impacts, we developed a dynamic computer model simulating changes in the age- and gender-specific smoking behaviors of the U.S. population over time. Secondary data for model parameters were obtained from publicly available sources. Population health impacts were measured as change in smoking prevalence and the change in cumulative quality-adjusted life-years (QALYs) in the U.S. population over 75 years. According to the risk-use threshold matrix generated by the simulation, modifying cigarettes to reduce their harmfulness and/or addictiveness could result in important gains to the nation's health. Addictiveness reduction efforts producing a 60% improvement in smoking behavior change probabilities would produce a net gain in population health at every plausible level of increase of smoking-related harm that was modeled. A 40% reduction in smoking-related harm would produce a net QALY gain at every level of behavior change considered. This research should prove useful to policymakers as they contemplate giving the FDA the authority to regulate the composition of cigarettes. 相似文献
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Mohammad Sajjad 《Journal of Muslim Minority Affairs》2014,34(2):174-190
This essay attempts to explore mass-based movement (munazzam awami tehreek) of democratic politics of the protagonists of Urdu, in post-independence Bihar, India. This politics clinched relatively greater success in persuading the provincial government to offer incentives of public employment for the Urdu-speaking population/Muslims. Compared to the adjacent province of Uttar Pradesh, apparently, the status of Urdu in Bihar is much less discouraging. A probable reason for a more assertive political movement for Urdu in Bihar is that the Muslim League's separatist politics in late-colonial Bihar was much weaker. In the post-Partition/Independence period, when it became taboo for the Muslims to express their demands on the basis of religion, language movement emerged as a convenient tool of minority politics. Essentially speaking, the “popular politics” of Urdu in its first phase (1951–1971) functioned more as a “political society”, whereas in the second phase (1971–1989), as a “civil society”, when Urdu became the second official language. This movement maintained effective links with the relevant common population. Priority was more on seeking support and patronage of the government for the language to survive rather than making efforts to see that it thrives self-reliantly, except the Madrasas. 相似文献
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AbstractThe digital technologies such as Internet play a crucial role in the management of operations of organisations in both public and private sectors. Such technologies support the implementation of effective digital business strategies. By reviewing the extant literature, this paper aims to identify factors that influence the intention to use digital technologies in order to develop a theoretical model which is then tested empirically using the PLS-SEM approach. While many studies have focused solely on the importance of social influence, perceived usefulness, perceived ease of use, awareness, perceived trust in technology, perceived trust in government, perceived cost and perceived risk, this article brings them together to explain their linkage, and quantifies the relationship. This study is the first empirical attempt to explore the factors influence e-government services adoption in the UAE. Most specifically, this article emphasises the role of social influence, perceived ease to use and perceived trust in technology as the important determinants of the intention to digital technology adoption. The paper expands the traditional discussion by incorporating six variables in a model that acts as facilitator or barrier in the intention to use digital technologies. This article helps practitioners to understand of which factors should be given emphasis in enhancing the intention to use digital technologies. The model developed in this paper is not only a response to the need to understand what causes the variation in the intention to use digital technologies from the operation management perspective, it is also a response to practitioner needs to use an appropriate construct to ensure the effective operation and use of the digital technologies in e-government services. The paper will help to identify the key issues surrounding the digital technologies adoption that may lead the successful operations of e-government. 相似文献
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