9,291 research outputs found

    Reduction Techniques for Graph Isomorphism in the Context of Width Parameters

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    We study the parameterized complexity of the graph isomorphism problem when parameterized by width parameters related to tree decompositions. We apply the following technique to obtain fixed-parameter tractability for such parameters. We first compute an isomorphism invariant set of potential bags for a decomposition and then apply a restricted version of the Weisfeiler-Lehman algorithm to solve isomorphism. With this we show fixed-parameter tractability for several parameters and provide a unified explanation for various isomorphism results concerned with parameters related to tree decompositions. As a possibly first step towards intractability results for parameterized graph isomorphism we develop an fpt Turing-reduction from strong tree width to the a priori unrelated parameter maximum degree.Comment: 23 pages, 4 figure

    Associations of Cytokines Genetic Variants with Myomatous Knots Sizes

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    The article presents study of cytokines molecular genetic markers’ impact on nature of uterus affection with myomatous knot

    Analysis of Involvement of Cytokine Genetic Polymorphisms in Development of Genital Endometriosis

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    The article outlines the role of cytokines in development of genital endometriosis. There were detected associations between genetic polymorphisms and their combinations and development of genital endometriosis among women in the Central region of Russi

    Fixed Effect Estimation of Large T Panel Data Models

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    This article reviews recent advances in fixed effect estimation of panel data models for long panels, where the number of time periods is relatively large. We focus on semiparametric models with unobserved individual and time effects, where the distribution of the outcome variable conditional on covariates and unobserved effects is specified parametrically, while the distribution of the unobserved effects is left unrestricted. Compared to existing reviews on long panels (Arellano and Hahn 2007; a section in Arellano and Bonhomme 2011) we discuss models with both individual and time effects, split-panel Jackknife bias corrections, unbalanced panels, distribution and quantile effects, and other extensions. Understanding and correcting the incidental parameter bias caused by the estimation of many fixed effects is our main focus, and the unifying theme is that the order of this bias is given by the simple formula p/n for all models discussed, with p the number of estimated parameters and n the total sample size.Comment: 40 pages, 1 tabl
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