Titlebook: Advances and Innovations in Statistics and Data Science; Wenqing He,Liqun Wang,Chunfang Devon Lin Book 2022 The Editor(s) (if applicable)

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https://doi.org/10.1007/978-3-031-08329-7Data Science; Biostatistics; statistical methods; high-dimensional data; high-dimensional statistics; sur

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Wenqing He,Liqun Wang,Chunfang Devon LinPromotes methodology development in data science, statistics, and biostatistics.Showcases the latest work as presented at the 4th ICSA-Canada Chapter Symposium.Includes applications to a variety of fi

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ICSA Book Series in Statisticshttp://image.papertrans.cn/a/image/146523.jpg

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Discovery and Development of Novel Drugs,thods have been developed in the literature, research gaps still exist. The existing methods usually make an implicit assumption that data are accurately measured. This requirement, however, is frequently violated in applications. In this chapter, we consider error-prone ultrahigh-dimensional surviv

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Vesna Erakovic Haber,Radan Spaventia analysis. . (LARS) is an efficient variable selection method, and it provides a solution path along which the entered predictors always have the same absolute correlation with the current residual. In this chapter, we propose a new method to control the FDR and sensitivity simultaneously for high-

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Al-Related Case Analysis (China),: the bag-of-word clusters model, i.e., grouping semantic-related words as clusters using pre-trained word2vec word embeddings and representing each comment as a distribution of word clusters. This method extracts both semantic and statistical information from texts. Next, we propose an unsupervised

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