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Inverse Gaussian distribution

  • Statistical Modelling with Quantile Functionsby Warren Gilchrist

    CRC Press 2000; US$ 132.95

    INTRODUCTION An Overview Describing the Sample Describing the Population Statistical Foundations QUANTILE MODELS AND THEIR CONSTRUCTION Foundation Distributions Distributional Model Building THE STATISTICAL MODELLING PROCESS Identification Estimation Validation Application EXTENDING THE MODELS Regression Quantile Models Bivariate Quantile Models Postscript more...

  • Modern Applied U-Statisticsby Jeanne Kowalski; Xin M. Tu

    Wiley 2008; US$ 151.00

    A timely and applied approach to the newly discovered methods and applications of U-statistics Built on years of collaborative research and academic experience, Modern Applied U-Statistics successfully presents a thorough introduction to the theory of U-statistics using in-depth examples and applications that address contemporary areas of study... more...

  • Statistical Tolerance Regionsby Kalimuthu Krishnamoorthy; Thomas Mathew

    Wiley 2009; US$ 149.00

    K. Krishnamoorthy, PhD , is Professor in the Department of Mathematics at the University of Louisiana at Lafayette. He is Associate Editor of Communications in Statistics and has published numerous journal articles in his areas of research interest, which include tolerance regions, multivariate analysis, and statistical computing. Thomas Mathew,... more...

  • Dirichlet and Related Distributionsby Kai Wang Ng; Guo-Liang Tian; Man-Lai Tang

    Wiley 2011; US$ 117.00

    “The book is a treasure chest both for researchers in (mathematical and applied) statistics and for practitioners. Researchers will especially pro_t from the impressive survey of the literature and the many references, while practitioners will acknowledge the many real data examples and the S-PLUS code provided in the appendix.” ... more...

  • The Laws of Large Numbersby Pál Révész; Z. W. Birnbaum; E. Lukacs

    Elsevier Science 2014; US$ 31.95

    The Law of Large Numbers deals with three types of law of large numbers according to the following convergences: stochastic, mean, and convergence with probability 1. The book also investigates the rate of convergence and the laws of the iterated logarithm. It reviews measure theory, probability theory, stochastic processes, ergodic theory, orthogonal... more...

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