Download or read book Efficient Use of Higher Lag Autocorrelations for Estimating Autoregressive Processes written by Laurence Broze and published by . This book was released on 2004 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: The Yule-Walker estimator is commonly used in time-series analysis, as a simple way to estimate the coefficients of an autoregressive process. Under strong assumptions on the noise process, this estimator possesses the same asymptotic properties as the Gaussian maximum likelihood estimator. However, when the noise is a weak one, other estimators based on higher-order empirical autocorrelations can provide substantial efficiency gains. This is illustrated by means of a first-order autoregressive process with a Markov-switching white noise. We show how to optimally choose a linear combination of a set of estimators based on empirical autocorrelations. The asymptotic variance of the optimal estimator is derived. Empirical experiments based on simulations show that the new estimator performs well on the illustrative model.
Download or read book Efficient Use of High Order Autocorrelations for Estimating Autoregressive Processes written by Laurence Broze and published by . This book was released on 1999 with total page 24 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Automatic Autocorrelation and Spectral Analysis written by Petrus M.T. Broersen and published by Springer Science & Business Media. This book was released on 2006-08-02 with total page 301 pages. Available in PDF, EPUB and Kindle. Book excerpt: Spectral analysis requires subjective decisions which influence the final estimate and mean that different analysts can obtain different results from the same stationary stochastic observations. Statistical signal processing can overcome this difficulty, producing a unique solution for any set of observations but that is only acceptable if it is close to the best attainable accuracy for most types of stationary data. This book describes a method which fulfils the above near-optimal-solution criterion, taking advantage of greater computing power and robust algorithms to produce enough candidate models to be sure of providing a suitable candidate for given data.
Download or read book Statistical Modeling and Analysis for Complex Data Problems written by Pierre Duchesne and published by Springer Science & Business Media. This book was released on 2005-12-05 with total page 330 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book reviews some of today’s more complex problems, and reflects some of the important research directions in the field. Twenty-nine authors – largely from Montreal’s GERAD Multi-University Research Center and who work in areas of theoretical statistics, applied statistics, probability theory, and stochastic processes – present survey chapters on various theoretical and applied problems of importance and interest to researchers and students across a number of academic domains.
Download or read book Estimating Autocorrelations in Fixed effects Models written by Gary Solon and published by . This book was released on 1984 with total page 68 pages. Available in PDF, EPUB and Kindle. Book excerpt: This paper discusses the estimation of serial correlation in fixed effects models for longitudinal data. Like time series data, longitudinal data often contain serially correlated error terms, but the autocorrelation estimators commonly used for time series, which are consistent as the length of the time series goes to infinity, are not consistent for a short time series as the size of the cross-section goes to infinity. This form of inconsistency is of particular concern because a short time series of a large cross-section is the typical case in longitudinal data. This paper extends Nickell's method of correcting for the inconsistency of autocorrelation estimators by generalizing to higher than first-order autocorrelations and to error processes other than first-order autoregressions. The paper also presents statistical tables that facilitate the identification and estimation of autocorrelation processes in both the generalized Nickell method and an alternative method due to MaCurdy. Finally, the paper uses Monte Carlo methods to explore the finite-sample properties of both methods.
Download or read book On the Strong Consistency of Estimators for Certain Distributed Lag Models with Autocorrelated Errors and Applications to Nonlinear Estimation for Models with Autoregressive Error Processes written by Phoebus J. Dhrymes and published by . This book was released on 1971 with total page 56 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Applied Linear Statistical Models written by Michael H. Kutner and published by McGraw-Hill/Irwin. This book was released on 2005 with total page 1396 pages. Available in PDF, EPUB and Kindle. Book excerpt: Linear regression with one predictor variable; Inferences in regression and correlation analysis; Diagnosticis and remedial measures; Simultaneous inferences and other topics in regression analysis; Matrix approach to simple linear regression analysis; Multiple linear regression; Nonlinear regression; Design and analysis of single-factor studies; Multi-factor studies; Specialized study designs.
Download or read book Mathematical Reviews written by and published by . This book was released on 2003-05 with total page 870 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Automatic Autocorrelation and Spectral Analysis written by Piet M. T. Broersen and published by Springer Science & Business Media. This book was released on 2006-04-20 with total page 301 pages. Available in PDF, EPUB and Kindle. Book excerpt: Spectral analysis requires subjective decisions which influence the final estimate and mean that different analysts can obtain different results from the same stationary stochastic observations. Statistical signal processing can overcome this difficulty, producing a unique solution for any set of observations but that is only acceptable if it is close to the best attainable accuracy for most types of stationary data. This book describes a method which fulfils the above near-optimal-solution criterion, taking advantage of greater computing power and robust algorithms to produce enough candidate models to be sure of providing a suitable candidate for given data.
Download or read book Journal of the American Statistical Association written by and published by . This book was released on 2009 with total page 896 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Statistical Inference in Autoregressive Models written by B. Ramanjineyulu and published by LAP Lambert Academic Publishing. This book was released on 2013 with total page 260 pages. Available in PDF, EPUB and Kindle. Book excerpt: In this book, an attempt has been made by developing some inferential methods for autoregressive models by using Internally studentized residuals.In the Applied regression analysis, the autoregressive models, moving average models and combined autoregressive and moving average models have a wide number applications. The study on autoregressive process/models is considered to be essential to both the theoretical and applied statisticians.The first order and higher order autoregressive models for regressed variable and errors have been described by giving auto covariance functions.Further, an autoregressive dynamic model without constant term has been specified and in the presence of lagged dependent variable, a modified durbin's h-statistic for testing the hypthesis of no auto correlation has been developed for first order autoregressive error process, Instrumental variable method of estimation has been proposed to estimate the parameters of first order autoregressive errors model with lagged dependent variable as regressor and hence obtained estimates for autocorrelation co-efficients based an Internally studentized residual
Download or read book General Technical Report SE written by and published by . This book was released on 1991 with total page 440 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book The Theory and Practice of Econometrics written by George G. Judge and published by John Wiley & Sons. This book was released on 1991-01-16 with total page 1062 pages. Available in PDF, EPUB and Kindle. Book excerpt: This broadly based graduate-level textbook covers the major models and statistical tools currently used in the practice of econometrics. It examines the classical, the decision theory, and the Bayesian approaches, and contains material on single equation and simultaneous equation econometric models. Includes an extensive reference list for each topic.
Download or read book Applied Regression Modeling written by Iain Pardoe and published by John Wiley & Sons. This book was released on 2013-01-07 with total page 319 pages. Available in PDF, EPUB and Kindle. Book excerpt: Praise for the First Edition "The attention to detail is impressive. The book is very well written and the author is extremely careful with his descriptions . . . the examples are wonderful." —The American Statistician Fully revised to reflect the latest methodologies and emerging applications, Applied Regression Modeling, Second Edition continues to highlight the benefits of statistical methods, specifically regression analysis and modeling, for understanding, analyzing, and interpreting multivariate data in business, science, and social science applications. The author utilizes a bounty of real-life examples, case studies, illustrations, and graphics to introduce readers to the world of regression analysis using various software packages, including R, SPSS, Minitab, SAS, JMP, and S-PLUS. In a clear and careful writing style, the book introduces modeling extensions that illustrate more advanced regression techniques, including logistic regression, Poisson regression, discrete choice models, multilevel models, and Bayesian modeling. In addition, the Second Edition features clarification and expansion of challenging topics, such as: Transformations, indicator variables, and interaction Testing model assumptions Nonconstant variance Autocorrelation Variable selection methods Model building and graphical interpretation Throughout the book, datasets and examples have been updated and additional problems are included at the end of each chapter, allowing readers to test their comprehension of the presented material. In addition, a related website features the book's datasets, presentation slides, detailed statistical software instructions, and learning resources including additional problems and instructional videos. With an intuitive approach that is not heavy on mathematical detail, Applied Regression Modeling, Second Edition is an excellent book for courses on statistical regression analysis at the upper-undergraduate and graduate level. The book also serves as a valuable resource for professionals and researchers who utilize statistical methods for decision-making in their everyday work.
Download or read book Water Resources Systems Planning and Management written by Sharad K. Jain and published by Elsevier. This book was released on 2003-09-12 with total page 883 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book is divided into four parts. The first part, Preliminaries, begins by introducing the basic theme of the book. It provides an overview of the current status of water resources utilization, the likely scenario of future demands, and advantages and disadvantages of systems techniques. An understanding of how the hydrological data are measured and processed is important before undertaking any analysis. The discussion is extended to emerging techniques, such as Remote Sensing, GIS, Artificial Neural Networks, and Expert Systems. The statistical tools for data analysis including commonly used probability distributions, parameter estimation, regression and correlation, frequency analysis, and time-series analysis are discussed in a separate chapter. Part 2 Decision Making, is a bouquet of techniques organized in 4 chapters. After discussing optimization and simulation, the techniques of economic analysis are covered. Recently, environmental and social aspects, and rehabilitation and resettlement of project-affected people have come to occupy a central stage in water resources management and any good book is incomplete unless these topics are adequately covered. The concept of rational decision making along with risk, reliability, and uncertainty aspects form subject matter of a chapter. With these analytical tools, the practitioner is well equipped to take a rational decision for water resources utilization. Part 3 deals with Water Resources Planning and Development. This part discusses the concepts of planning, the planning process, integrated planning, public involvement, and reservoir sizing. The last part focuses on Systems Operation and Management. After a resource is developed, it is essential to manage it in the best possible way. Many dams around the world are losing some storage capacity every year due to sedimentation and therefore, the assessment and management of reservoir sedimentation is described in details. No analysis of water resources systems is complete without consideration of water quality. A river basin is the natural unit in which water occurs. The final chapter discusses various issues related to holistic management of a river basin.
Download or read book Proceedings of the 1991 Symposium on Systems Analysis in Forest Resources written by and published by . This book was released on 1991 with total page 440 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Topics in Autoregression microform written by Ying Zhang and published by National Library of Canada = Bibliothèque nationale du Canada. This book was released on 2002 with total page 292 pages. Available in PDF, EPUB and Kindle. Book excerpt: An overview of the thesis is given in Chapter 1. Chapter 2 discusses a symbolic form for the exact maximum likelihood estimator in the stationary normal AR(1) process. We derive the finite sample inference properties of the exact maximum likelihood estimator. We establish its consistency and its empirical cumulative distribution for a random walk case. The power of our one-tail unit root test overall outperforms that of previous proposals in the unknown mean AR(1) model. Chapter 3 provides a general technique to describe the shape of the admissible region of AR(p). As applications, we have visualized the admissible regions for AR(3) and AR(4). For the AR(4) process, all possible subset admissible regions for the model re-parametrized in terms of partial autocorrelations are obtained and it is demonstrated that these regions are quite complex and hence this re-parameterization is not so useful in the subset case. Chapter 4 develops an algorithm for computing the expectations of time series products given the autocovariance function. Using it as our tool, we evaluate the bias and variance of the Burg estimate to order n-1 in the first order autoregressive model and find that Burg estimate and the least-squares estimate have the same bias and variance to order n-1 in that case. We also obtain explicit formulae for the large sample bias of Burg estimates in the second order cases. Both simulations and theory indicates that Burg estimates have biases similar to the least-squares estimates in the second order cases. The advantages of the Burg estimates over the least-squares estimates are briefly indicated. Chapter 5 is an extension of Chapter 3. A new more computationally efficient general purpose algorithm for computing the exact maximum likelihood estimates in an AR(p) model is developed. Then this algorithm is used to develop a new approach to subset autoregression modelling in which the subsets are obtained by containing some of the zeta parameters to zero. After the exact maximum likelihood estimation algorithm for the subset models is presented, it is shown how a tentative identification of possible subset AR models can be accomplished using the AIC or BIC criterion and the partial autocorrelation function. The distribution of the residual autocorrelations for subset AR models is also derived and appropriate diagnostic checks for model adequacy are discussed. Several illustrative examples are presented.
