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作者：Carvalho, Carlos M.; Chang, Jeffrey; Lucas, Joseph E.; Nevins, Joseph R.; Wang, Quanli; West, Mike
作者单位：University of Chicago; Duke University; Duke University; Duke University
摘要：We describe Studies in molecular profiling and biological pathway analysis that use sparse latent factor and regression models for microarray gene expression data. We discuss breast cancer applications and key aspects of the modeling and computational methodology. Our case Studies aim to investigate and characterize heterogeneity of structure related to specific oncogenic pathways, its well as links between aggregate patterns in gene expression profiles and clinical biomarkers. Based on the me...
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作者：Einmahl, John H. J.; Magnus, Jan R.
作者单位：Tilburg University; Tilburg University
摘要：We are interested in two questions on extremes relating to world records in athletics. The first question is: What is the ultimate world record in a specific athletic event (such as the 100-m race for men or the high jump for women), given today's state of the art? Our second question is: How good is a current athletic world record? An answer to the second question also enables us to compare the quality of world records in different athletic events. We consider these questions for each of 28 e...
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作者：Bae, Kyounghwa; Mallick, Bani K.; Elsik, Christine G.
作者单位：American College of Radiology; Texas A&M University System; Texas A&M University College Station; Georgetown University
摘要：Proteins have tow types of regions: linker regions that connect active domains and nonlinker regions, which include domains and terminal residues. It is important to try to distinguish these regions using information in the sequence of amino acids that, when folded, form the protein. In this article we develop a nonstationary hidden Markov model to infer region boundaries. The approach is based on a latent variable defined on the sequence, this variable is a continuous index of the region type...
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作者：Corkrey, Ross; Brooks, Steve; Lusseau, David; Parsons, Kim; Durban, John W.; Hammond, Philip S.; Thompson, Paul M.
作者单位：University of Cambridge; National Oceanic Atmospheric Admin (NOAA) - USA; University of St Andrews; University of Aberdeen
摘要：We develop a Bayesian capture-recapture model that provides estimates of abundance as well as time-varying and heterogeneous survival and capture probability distributions. The model uses a state-space approach by incorporating an underlying population model and an observation model, and here is applied to photo-identification data to estimate trends in the abundance and survival of a population of bottlenose dolphins (Tursiops truncatus) in northeast Scotland. Novel features fo the mdoel incl...
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作者：van Wieringen, Wessel N.; van de Wiel, Mark A.; van der Vaart, Aad W.
作者单位：Vrije Universiteit Amsterdam; Vrije Universiteit Amsterdam; Amsterdam University Medical Center
摘要：Even in a single-tissue type cancer is often a collection of different diseases, each with its own genetic mechanism. Consequently, a gene may be expressed in some but not all of the tissues in a sample. Differentially expressed genes are commonly detected by methods that test for a shift in location that ignore the possibility of heterogeneous expression. This article proposes a two-sample test statistic designed to detect shifts that occur in only a part of the sample (partial shifts). The s...
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作者：Wang, Xiao; Walker, Matthew; Pal, Jayanta; Woodroofe, Michael; Mateo, Mario
作者单位：University System of Maryland; University of Maryland Baltimore; University of Cambridge; University of Michigan System; University of Michigan; University of Michigan System; University of Michigan
摘要：A new nonparametric method is described to estimate the distribution of mass within spherical galaxies. The problem of estimating the mass, M(r), within radius r is converted into a problem of estimating a regression function nonparametrically, subject to shape restriction. We represent the restrictions by the interception of quadratic cones and use the second-order cone programming to estimate the unknown parameters. We establish asymptotic results that are used to construct confidence interv...
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作者：Zhou, Yong; Wan, Alan T. K.; Wang, Xiaojing
作者单位：Shanghai University of Finance & Economics; Chinese Academy of Sciences; Academy of Mathematics & System Sciences, CAS; City University of Hong Kong
摘要：There is a large and growing body of literature on estimating equation (EE) as an estimation approach. One basic property of EE that has been universely adopted in practice is that of unbiasedness, and there are deep conceptual reasons why unbiasedness is a desirable EE characteristic. This article deals with inference from EEs generally leads to EEs that are biased and thus, violates a basic assumption of the EE approach. The main contribution of this article is that it goes beyond existing i...
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作者：Froelich, Markus
作者单位：University of Mannheim
摘要：Choosing among a number of treatments the most suitable for a particular client is an issue of everyday concern. In this article two methodological advances for statistically assisted treatment choice are developed: First, it permits one to combine a dataset on previously treated clients with a dataset on new clients when the regressors available in these two datasets do not coincide. It thereby incorporates additional regressors on previously treated clients that are not available for the cur...
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作者：Gelman, Andrew; Huang, Zaiying
作者单位：Columbia University; Columbia University; New York Times
摘要：Incumbency advantage is one of the most widely studied features in American legislative elections. In this article we construct and implement an estimate that allows incumbency advantage to vary between individual incumbents. This model predicts that open-seat elections will be less variable than those with incumbents running, an observed empirical pattern that is not explained by previous models. We apply our method to the U.S. House of Representatives in the twentieth century. Our estimate o...
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作者：Wang, Hansheng; Xia, Yingcun
作者单位：Peking University; National University of Singapore
摘要：A new dimension-reduction method involving slicing the region of the response and applying local kernel regression to each slice is proposed. Compared with the traditional inverse regression methods [e.g., sliced inverse regression (SIR)], the new method is free of the linearity condition and has much better estimation accuracy. Compared with the direct estimation methods (e.g., MAVE), the new method is much more robust against extreme values and can capture the entire central subspace (CS) ex...
