Mostrando recursos 1 - 9 de 9

  1. Higher Order Asymptotics

    Ghosh, Jayanta K.
    This monograph is based on my CBMS-NSF lectures in August, 1991 at Chapel Hill, North Carolina. The flow of the chapters mirrors the flow of the lectures. While I have rearranged the material I distributed during the lectures, I have not added or deleted very much, except for adding remarks or details by way of clarification or resolution of issues raised by my very lively audience at Chapel Hill. ¶Most of the material is taken from my own work done jointly with many students and friends. One of the pleasures of lecturing or writing about all this has been the reliving of that experience of working and discovering together....

  2. Analysis of Longitudinal and Cluster-Correlated Data

    Laird, Nan
    The analysis of data with outcomes measured repeatedly on each subject has experienced several transforming developments in the last twenty years. This monograph presents a unified treatment of modern methods for longitudinal and/or correlated data that have developed during this period. The basic approach that we take to modeling longitudinal data is to extend familiar univariate regression models to multivariate or correlated outcomes. We deal with linear models for measured data and generalized linear models for binary and count data. We show how methods can accommodate missing outcomes and/or unbalanced designs. Both likelihood and moment methods of estimation are covered, as are random effects approaches to data modeling and parameter...

  3. Generalized Linear Mixed Models

    McCulloch, Charles E.
    This monograph is written assuming familiarity with linear models and matrix algebra and some exposure to mixed models and logistic regression. References are given to more standard texts that cover some of the basic material in more depth. The monograph begins with an extended example that introduces all the main ideas. Chapters 2 and 3 briefly review linear mixed and generalized linear models and Chapter 4 defines and introduces GLMMs. Chapter 5 illustrates the breadth of inferential goals possible with GLMMs. One of my main attractions in conducting research on this class of models was the wide variety of practical applications. Chapters 6 through 9 contain the "meat"...

  4. Statistical Inference From Genetic Data on Pedigrees

    Thompson, Elizabeth A.
    This monograph is based primarily on material presented at the CBMS Summer Course on Inferences from genetic data on pedigrees given at Michigan Technical University, Houghton, Michigan, in July 1999.

  5. Mixture Models: Theory, Geometry and Applications

    Lindsay, Bruce G.
    The mixture model has long been a challenge to the statistician, whether beginner, practitioner or theoretician. Recent times have seen great advances in our understanding of the some basic mathematical features of this model, and these notes are meant to be a unification of the work I have carried out, jointly with many wonderful collaborators, in this area. Based on lectures given in 1993 at a regional conference of the Conference Board of the Mathematical Sciences, the notes are directed toward a mixed audience of advanced graduate students and research workers in this and related areas. For the sake of newcomers to the mixture model, I will attempt...

  6. Stochastic curve estimation

    Rosenblatt, Murray
    These notes are based on a regional set of lectures on curve estimation in the context of independent and dependent observations given at the University of California, Davis during June 1989. Much of these lectures is concerned with probability density or regression function estimation when observations are independent. The character of the asymptotic results (at least locally) is qualitatively the same if the observations are those of a dependent stationary sequence with short-range dependence. Research in the case of long-range dependence is recent and qualitatively of a different character. One should note that the spectral estimation (also discussed here) is of an older vintage and results there in part...

  7. Empirical Processes: Theory and Applications

    Pollard, David
    These notes grew from lectures I gave at the University of Iowa in July of 1988, as part of the NSF-CBMS Regional Conference Series. The conference was ably organized by Tim Robertson and Richard Dykstra. I am most grateful to them for giving me the opportunity to experiment on a live and receptive audience with material not entirely polished. I also appreciate the suggestions and comments of Richard Dudley. Much of the lecture material was repackaging of ideas originally due to him. ¶In reworking the lecture notes I have tried (not always successfully) to resist the urge to push the presentation to ever higher levels of generality. My...

  8. Group invariance in applications in statistics

    Easton, Morris L.
    These lecture notes are a result of the NSF ICBMS Regional Conference held at the University of Michigan, 15-19 June 1987. Topics in invariance with applications in statistics were discussed in a series of eighteen 45 minute lectures. Because of space and time limitations no material beyond that given in the lectures is presented here. Unfortunately, my original intention of including material on the invariance-sufficiency connection and on amenability had to be scrapped.

  9. Nonparametric Bayesian Inference

    Müller, Peter; Rodriguez, Abel
    These notes arose out of a short course at UC Santa Cruz in summer 2010. Like the course, the notes provide an overview of some popular Bayesian nonparametric (BNP) probability models. The discussion follows a logical development of many commonly used nonparametric Bayesian models as generalizations of the Dirichlet process (DP) in different directions, including Pólya tree (PT) models, species sampling models (SSM), dependent DP (DDP) models and product partition models (PPM). The selection of topics is subjective, simply driven by what the authors are familiar with. As a result, some useful and elegant classes of models such as normalized...

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