Mostrando recursos 1 - 6 de 6

  1. Sparse sampling: Spatial design for monitoring stream networks

    Dobbie,, Melissa J.; Henderson, Brent L.; Stevens, Jr, Don L.
    Spatial designs for monitoring stream networks, especially ephemeral systems, are typically non-standard, ‘sparse’ and can be very complex, reflecting the complexity of the ecosystem being monitored, the scale of the population, and the competing multiple monitoring objectives. The main purpose of this paper is to present a review of approaches to spatial design to enable informed decisions to be made about developing practical and optimal spatial designs for future monitoring of streams.

  2. Text Data Mining: Theory and Methods

    Solka, Jeffrey L.
    This paper provides the reader with a very brief introduction to some of the theory and methods of text data mining. The intent of this article is to introduce the reader to some of the current methodologies that are employed within this discipline area while at the same time making the reader aware of some of the interesting challenges that remain to be solved within the area. Finally, the articles serves as a very rudimentary tutorial on some of techniques while also providing the reader with a list of references for additional study.

  3. Statistical advances and challenges for analyzing correlated high dimensional SNP data in genomic study for complex diseases

    Liang, Yulan; Kelemen, Arpad
    Recent advances of information technology in biomedical sciences and other applied areas have created numerous large diverse data sets with a high dimensional feature space, which provide us a tremendous amount of information and new opportunities for improving the quality of human life. Meanwhile, great challenges are also created driven by the continuous arrival of new data that requires researchers to convert these raw data into scientific knowledge in order to benefit from it. Association studies of complex diseases using SNP data have become more and more popular in biomedical research in recent years. In this paper, we present a...

  4. Parametric and nonparametric models and methods in financial econometrics

    Zhao, Zhibiao
    Financial econometrics has become an increasingly popular research field. In this paper we review a few parametric and nonparametric models and methods used in this area. After introducing several widely used continuous-time and discrete-time models, we study in detail dependence structures of discrete samples, including Markovian property, hidden Markovian structure, contaminated observations, and random samples. We then discuss several popular parametric and nonparametric estimation methods. To avoid model mis-specification, model validation plays a key role in financial modeling. We discuss several model validation techniques, including pseudo-likelihood ratio test, nonparametric curve regression based test, residuals based test, generalized likelihood ratio test,...

  5. Wavelet methods in statistics: some recent developments and their applications

    Antoniadis, Anestis
    The development of wavelet theory has in recent years spawned applications in signal processing, in fast algorithms for integral transforms, and in image and function representation methods. This last application has stimulated interest in wavelet applications to statistics and to the analysis of experimental data, with many successes in the efficient analysis, processing, and compression of noisy signals and images. ¶ This is a selective review article that attempts to synthesize some recent work on “nonlinear” wavelet methods in nonparametric curve estimation and their role on a variety of applications. After a short introduction to wavelet theory, we discuss in detail several...

  6. 1953: An unrecognized summit in human genetic linkage analysis

    Thompson, E.A.
    This paper summarizes and discusses the methodological research in human genetic linkage analysis, leading up to and following from the paper of C. A. B. Smith presented as a Royal Statistical Society discussion paper in 1953. This paper was given as the Fisher XXVII Memorial Lecture, in Cambridge, December 4, 2006.

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