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Some Likelihood Based Properties in Large Samples: Utility and Risk Aversion, Second Order Prior Selection and Posterior Density Stability
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作者 Michael Brimacombe 《Open Journal of Statistics》 2016年第6期1037-1049,共14页
The likelihood function plays a central role in statistical analysis in relation to information, from both frequentist and Bayesian perspectives. In large samples several new properties of the likelihood in relation t... The likelihood function plays a central role in statistical analysis in relation to information, from both frequentist and Bayesian perspectives. In large samples several new properties of the likelihood in relation to information are developed here. The Arrow-Pratt absolute risk aversion measure is shown to be related to the Cramer-Rao Information bound. The derivative of the log-likelihood function is seen to provide a measure of information related stability for the Bayesian posterior density. As well, information similar prior densities can be defined reflecting the central role of likelihood in the Bayes learning paradigm. 展开更多
关键词 Arrow-Pratt Theorem Expected Utility Information Similar Priors Likelihood Function Prior Stability Score Function Risk Aversion
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Analyzing the Potential Influence of Shanghai Stock Market Based on Link Prediction Method
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作者 Hongxing YAO Yunxia LU 《Journal of Systems Science and Information》 CSCD 2017年第5期446-461,共16页
In this paper, we analyze the 180 stocks which have the potential influence on the Shanghai Stock Exchange(SSE). First, we use the stock closing prices from January 1, 2005 to June 19, 2015 to calculate logarithmic th... In this paper, we analyze the 180 stocks which have the potential influence on the Shanghai Stock Exchange(SSE). First, we use the stock closing prices from January 1, 2005 to June 19, 2015 to calculate logarithmic the correlation coefficient and then build the stock market model by threshold method. Secondly, according to different networks under different thresholds, we find out the potential influence stocks on the basis of local structural centrality. Finally, by comparing the accuracy of similarity index of the local information and path in the link prediction method, we demonstrate that there are best similarity index to predict the probability for nodes connection in the different stock networks. 展开更多
关键词 correlation coefficient local structural centrality potentially influential stocks local information similarity index path similarity index
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