Download or read book Statistical Inference in Random Coefficient Regression Models written by P.A.V.B. Swamy and published by Springer Science & Business Media. This book was released on 2012-12-06 with total page 219 pages. Available in PDF, EPUB and Kindle. Book excerpt: This short monograph which presents a unified treatment of the theory of estimating an economic relationship from a time series of cross-sections, is based on my Ph. D. dissertation submitted to the University of Wisconsin, Madison. To the material developed for that purpose, I have added the substance of two subsequent papers: "Efficient methods of estimating a regression equation with equi-correlated disturbances", and "The exact finite sample properties of estimators of coefficients in error components regression models" (with Arora) which form the basis for Chapters 11 and III respectively. One way of increasing the amount of statistical information is to assemble the cross-sections of successive years. To analyze such a body of data the traditional linear regression model is not appropriate and we have to introduce some additional complications and assumptions due to the hetero geneity of behavior among individuals. These complications have been discussed in this monograph. Limitations of economic data, particularly their non-experimental nature, do not permit us to know a priori the correct specification of a model. I have considered several different sets of assumptionR about the stability of coeffi cients and error variances across individuals and developed appropriate inference procedures. I have considered only those sets of assumptions which lead to opera tional procedures. Following the suggestions of Kuh, Klein and Zellner, I have adopted the linear regression models with some or all of their coefficients varying randomly across individuals.

Download or read book Asymptotic Inference in Random Coefficient Regression Models written by Søren Johansen and published by . This book was released on 1981 with total page 15 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Efficient inference in random coefficient models with multicollinearity in the time series regressions written by Robert K. Rayner, Roger L. Wright and published by . This book was released on 1980 with total page 26 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Ols based Asymptotic Inference in Linear Regression Models with Trending Regressiors and AR P disturbances written by Walter Krämer and published by . This book was released on 1999 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Functional Relations Random Coefficients and Nonlinear Regression with Application to Kinetic Data written by S. Johansen and published by Springer Science & Business Media. This book was released on 2012-12-06 with total page 135 pages. Available in PDF, EPUB and Kindle. Book excerpt: These notes on regression give an introduction to some of the techniques that I have found useful when working with various data sets in collaboration with Dr. S. Keiding (Copenhagen) and Dr. J.W.L. Robinson (Lausanne). The notes are based on some lectures given at the Institute of Mathematical Statistics, University of Copenhigen, 1978-81, for graduate students, and assumes a familiarity with statistical theory corresponding to the book by C.R. Rao: "Linear Statistical Inference and its Applications". Wiley, New York (1973) . The mathematical tools needed for the algebraic treatment of the models are some knowledge of finite dimensional vector spaces with an inner product and the notion of orthogonal projection. For the analytic treatment I need characteristic functions and weak convergence as the main tools. The most important statistical concepts are the general linear model for Gaussian variables and the general methods of maximum likelihood estimation as well as the likelihood ratio test. All these topics are presented in the above mentioned book by Rao and the reader is referred to that for details. For convenience a short appendix is added where the fundamental concepts from linear algebra are discussed.

Download or read book Testing for Random Walk Coefficients in Regression and State Space Models written by Martin Moryson and published by Springer Science & Business Media. This book was released on 2012-12-06 with total page 326 pages. Available in PDF, EPUB and Kindle. Book excerpt: Regression and state space models with time varying coefficients are treated in a thorough manner. State space models are introduced as a means to model time varying regression coefficients. The Kalman filter and smoother recursions are explained in an easy to understand fashion. The main part of the book deals with testing the null hypothesis of constant regression coefficients against the alternative that they follow a random walk. Different exact and large sample tests are presented and extensively compared based on Monte Carlo studies, so that the reader is guided in the question which test to choose in a particular situation. Moreover, different new tests are proposed which are suitable in situations with autocorrelated or heteroskedastic errors. Additionally, methods are developed to test for the constancy of regression coefficients in situations where one knows already that some coefficients follow a random walk, thereby one is enabled to find out which of the coefficients varies over time.

Download or read book Ols based Asymptotic Inference in Linear Regression Models with Trending Regressors and Ar p disturbances written by Walter Krämer and published by . This book was released on 1999 with total page 10 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Regression written by Ludwig Fahrmeir and published by Springer Science & Business Media. This book was released on 2013-05-09 with total page 768 pages. Available in PDF, EPUB and Kindle. Book excerpt: The aim of this book is an applied and unified introduction into parametric, non- and semiparametric regression that closes the gap between theory and application. The most important models and methods in regression are presented on a solid formal basis, and their appropriate application is shown through many real data examples and case studies. Availability of (user-friendly) software has been a major criterion for the methods selected and presented. Thus, the book primarily targets an audience that includes students, teachers and practitioners in social, economic, and life sciences, as well as students and teachers in statistics programs, and mathematicians and computer scientists with interests in statistical modeling and data analysis. It is written on an intermediate mathematical level and assumes only knowledge of basic probability, calculus, and statistics. The most important definitions and statements are concisely summarized in boxes. Two appendices describe required matrix algebra, as well as elements of probability calculus and statistical inference.

Download or read book Statistical Inference for Randomly Censored Linear Regression Model written by Wei-Hong Wang and published by . This book was released on 1983 with total page 124 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Estimation of a Random Coefficient Regression Model written by B. Robert Froehlich and published by . This book was released on 1971 with total page 256 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Asymptotic Inference in Censored Regression Models Revisited written by Chihwa Kao and published by . This book was released on 2011 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: This paper establishes that regressors in the models with censored dependent variables need not be bounded for the standard asymptotic results to apply. Thus regressors which grow monotonically with the observation index may be acceptable. It also purports to provide an upper bound on the rate at which regressors may grow.

Download or read book Transformation and Weighting in Regression written by Raymond J. Carroll and published by Routledge. This book was released on 2017-10-19 with total page 264 pages. Available in PDF, EPUB and Kindle. Book excerpt: This monograph provides a careful review of the major statistical techniques used to analyze regression data with nonconstant variability and skewness. The authors have developed statistical techniques--such as formal fitting methods and less formal graphical techniques-- that can be applied to many problems across a range of disciplines, including pharmacokinetics, econometrics, biochemical assays, and fisheries research. While the main focus of the book in on data transformation and weighting, it also draws upon ideas from diverse fields such as influence diagnostics, robustness, bootstrapping, nonparametric data smoothing, quasi-likelihood methods, errors-in-variables, and random coefficients. The authors discuss the computation of estimates and give numerous examples using real data. The book also includes an extensive treatment of estimating variance functions in regression.

Download or read book OLS based Asymptotic Inference in Linear Regression Models with Trending Regressors and AR p disturbances written by Walter Krämer and published by . This book was released on 1998 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Asymptotic Inference in Regression Models with Autoregressive Errors Having Roots on the Unit Circle written by Juha Ahtola and published by . This book was released on 1986 with total page 12 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Inference on Multivariate Heteroscedastic Time Varying Random Coefficient Models written by Liudas Giraitis and published by . This book was released on 2018 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: In this article, we introduce the general setting of a multivariate time series autoregressive model with stochastic time-varying coefficients and time-varying conditional variance of the error process. This allows modelling VAR dynamics for non-stationary time series and estimation of time-varying parameter processes by the well-known rolling regression estimation techniques. We establish consistency, convergence rates, and asymptotic normality for kernel estimators of the paths of coefficient processes and provide pointwise valid standard errors. The method is applied to a popular seven-variable dataset to analyse evidence of time variation in empirical objects of interest for the DSGE (dynamic stochastic general equilibrium) literature.

Download or read book Asymptotic Distributions of Estimators of the Mean Response Vector in the Random Coefficients Regression Model written by Baldev Raj and published by . This book was released on 1975* with total page 18 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Asymptotic Theory of Statistical Inference for Time Series written by Masanobu Taniguchi and published by Springer Science & Business Media. This book was released on 2012-12-06 with total page 671 pages. Available in PDF, EPUB and Kindle. Book excerpt: The primary aim of this book is to provide modern statistical techniques and theory for stochastic processes. The stochastic processes mentioned here are not restricted to the usual AR, MA, and ARMA processes. A wide variety of stochastic processes, including non-Gaussian linear processes, long-memory processes, nonlinear processes, non-ergodic processes and diffusion processes are described. The authors discuss estimation and testing theory and many other relevant statistical methods and techniques.