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Browsing Statistics by Title

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  • Sundar, Raghav Prashant; Becker, Mark W.; Bello, Nora M.; Bix, Laura (2012)
    Adverse drug events (ADEs) are a significant problem in health care. While effective warnings have the potential to reduce the prevalence of ADEs, little is known about how patients access and use prescription labeling. ...
  • Bai, Xiuqin; Yao, Weixin; Boyer, John E. (2012)
    The existing methods for tting mixture regression models assume a normal dis- tribution for error and then estimate the regression parameters by the maximum likelihood estimate (MLE). In this article, we demonstrate ...
  • Song, Weixing; Yao, Weixin; Xing, Yanru (2014)
    A robust estimation procedure for mixture linear regression models is proposed by assuming that the error terms follow a Laplace distribution. Using the fact that the Laplace distribution can be written as a scale mixture ...
  • Yao, Weixin; Wei, Yan; Yu, Chun (2014)
    The traditional estimation of mixture regression models is based on the normal assumption of component errors and thus is sensitive to outliers or heavy-tailed errors. A robust mixture regression model based on the ...
  • Yao, Weixin; Wang, Qin (2013)
    Dimension reduction and variable selection play important roles in high dimensional data analysis. The sparse MAVE, a model-free variable selection method, is a nice combination of shrinkage estimation, Lasso, and an ...
  • Cao, J.; Yao, Weixin (2012)
    Many historical datasets contain a large number of zeros, and cannot be modeled directly using a single distribution. Motivated by rain data from a global climate model, we study a semiparametric mixture of binomial ...
  • Anderson, Dean M.; Murray, Leigh W. (2013)
    Turning preferences among 309 white-faced ewes were individually evaluated in an enclosed, artificially lighted, T-maze, followed by each ewe choosing either a right or left return alley to return to peers. Data recorded ...
  • Wang, Haiyan; Zhang, Hongyan; Dai, Zhijun; Chen, Ming-Shun; Yuan, Zheming (2013)
    Background: One of the challenges in classification of cancer tissue samples based on gene expression data is to establish an effective method that can select a parsimonious set of informative genes. The Top Scoring Pair ...