books about: semiparametric     books:     Semiparametric      Efficient and Adaptive Estimation for Semiparametric Models Peter J. Bickel, Chris A.J. Klaassen, ... Springer, 1998 This book is about estimation in situations where we believe we have enough knowledge to model some features of the data parametrically, but are unwilling to assume anything for other features. Such models have arisen in a wide variety of contexts in recent years, particularly in economics, epidemiology, and astronomy. The complicated structure of ...             Semiparametric Regression for the Social Sciences Luke John Keele Wiley, 2008 An introductory guide to smoothing techniques, semiparametric estimators, and their related methods, this book describes the methodology via a selection of carefully explained examples and data sets. It also demonstrates the potential of these techniques using detailed empirical examples drawn from the social and political sciences. Each chapter ...             Introduction to Empirical Processes and Semiparametric Inference (Springer Series in Statistics) Michael R. Kosorok Springer, 2008 This book provides a self-contained, linear, and unified introduction to empirical processes and semiparametric inference. These powerful research techniques are surprisingly useful for developing methods of statistical inference for complex models and in understanding the properties of such methods. The targeted audience includes statisticians, ...             Semiparametric Theory and Missing Data (Springer Series in Statistics) Anastasios A. Tsiatis Springer, 2006 missing data and statistical models Tsiatis is a top researcher in biostatistics amd a good writer. Missing data is a very important issue in clinical trials and many models have been devised to handle them including multiple imputation (Rubin), pattern mixture models (Little) and mixed effects linear ...             Practical Nonparametric and Semiparametric Bayesian Statistics (Lecture Notes in Statistics) Springer, 1998 A Great Book In The Field Of Statistics Practical Nonparametric and Semiparametric Bayesian Statistics is an extrodinary edited volume. This is the ideal book for graduate level teaching that focuses on biostatistics. This book contains state of the art computational methods with paper submissions from ...             Life Distributions: Structure of Nonparametric, Semiparametric, and Parametric Families (Springer Series in ... Albert W. Marshall, Ingram Olkin Springer, 2007 Olkin and Marshall team up again Ingram Olkin and Albert Marshall have collaborated on research on statistical distributions including a bivariate exponential distribution. They have also studied the properties of various distributions with respect to orderings such as majorization, total positivity ...             Semiparametric Modeling of Implied Volatility (Springer Finance) Matthias R. Fengler Springer, 2005 The implied volatility surface is a key financial variable for the pricing and the risk management of plain vanilla and exotic options portfolios alike. Consequently, statistical models of the implied volatility surface are of immediate importance in practice: they may appear as estimates of the current surface or as fully specified dynamic models ...             Statistical Methods for Environmental Epidemiology with R: A Case Study in Air Pollution and Health (Use R) Roger D. Peng, Francesca Dominici Springer, 2008 Advances in statistical methodology and computing have played an important role in allowing researchers to more accurately assess the health effects of ambient air pollution. The methods and software developed in this area are applicable to a wide array of problems in environmental epidemiology. This book provides an overview of the methods used ...             Semiparametric Methods in Econometrics (Lecture Notes in Statistics) Joel L. Horowitz Springer, 1998 Semiparametric methods This book has an excellent command on semiparametric methods. These methods are frequently used in econometrics. As a tradition many economists used to estimate parametric models. But estimating parametric models requires many assumptions. First of all while ...             Semiparametric Regression (Cambridge Series in Statistical and Probabilistic Mathematics) David Ruppert, M. P. Wand, ... Cambridge University Press, 2003 another great text by the team if Ruppert and Carroll David Ruppert and Ray Carroll have been a research team for over 25 years. They have published many articles and books on regression analysis. These articles are always very clearly written and are great at showing the big picture and not just the nitty gritty ...             Lectures on Probability Theory and Statistics Erwin Bolthausen, Edwin Perkins, ... Springer, 2002 This new volume of the long-established St. Flour Summer School of Probability includes the notes of the three major lecture courses by Erwin Bolthausen on "Large Deviations and Iterating Random Walks", by Edwin Perkins on "Dawson-Watanabe Superprocesses and Measure-Valued Diffusions", and by Aad van der Vaart on "Semiparametric Statistics".             Semi-parametric specification tests for discrete probability models.: An article from: Journal of Risk and ... Yue Fang American Risk and Insurance Association, Inc., 2003 This digital document is an article from Journal of Risk and Insurance, published by American Risk and Insurance Association, Inc. on March 1, 2003. The length of the article is 5894 words. The page length shown above is based on a typical 300-word page. The article is delivered in HTML format and is available in your Amazon.com Digital Locker ...             Parametric and Semiparametric Models with Applications to Reliability, Survival Analysis, and Quality of Life ... Birkhäuser Boston, 2004 Parametric and semiparametric models are tools with a wide range of applications to reliability, survival analysis, and quality of life. This self-contained volume examines these tools in survey articles written by experts currently working on the development and evaluation of models and methods. While a number of chapters deal with general ...             Nonparametric and Semiparametric Models Wolfgang Härdle, Marlene Müller, ... Springer, 2004   The concept of nonparametric smoothing is a central idea in statistics that aims to simultaneously estimate and modes the underlying structure. The book considers high dimensional objects, as density functions and regression. The semiparametric modeling technique compromises the two aims, flexibility and simplicity of statistical procedures, ...             Semiparametric Regression for the Applied Econometrician (Themes in Modern Econometrics) Adonis Yatchew Cambridge University Press, 2003 Adonis Yatchew provides simple and flexible (nonparametric) techniques for analyzing regression data. He includes a series of empirical examples with the estimation of Engel curves and equivalence scales, scale economies, household gasoline consumption, housing prices, option prices and state price density estimation. The book is of interest to a ...          products you might be interested in search for books distributions, econometrician, probabilistic, semi-parametric, semiparametric, specification      toavi.com    web we recommend missing data and statistical models randomly chosen book: The Modern Middle East: Revised Edition