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Author : Douglas Gardiner Steigerwald
Publisher :
ISBN 13 :
Total Pages : 180 pages
Book Rating : 4.:/5 (7 download)
Download or read book Adaptive Estimation in Time Series Regression Models written by Douglas Gardiner Steigerwald and published by . This book was released on 1989 with total page 180 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Author : Charles F. Manski
Publisher :
ISBN 13 :
Total Pages : 51 pages
Book Rating : 4.:/5 (137 download)
Download or read book Adaptive Estimation of Non-linear Regression Models written by Charles F. Manski and published by . This book was released on 1983 with total page 51 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Author : Whitney K. Newey
Publisher :
ISBN 13 :
Total Pages : 50 pages
Book Rating : 4.:/5 (178 download)
Download or read book Adaptive Estimation of Regression Models Via Moment Restrictions written by Whitney K. Newey and published by . This book was released on 1987 with total page 50 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Author : Guangrui Zhu
Publisher :
ISBN 13 :
Total Pages : 196 pages
Book Rating : 4.F/5 ( download)
Download or read book Least Squares Estimation and Adaptive Prediction in Non-linear Stochastic Regression Models with Applications to Time Series and Stochastic Systems written by Guangrui Zhu and published by . This book was released on 1992 with total page 196 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Author : Peter C. Young
Publisher : Springer Science & Business Media
ISBN 13 : 3642219810
Total Pages : 505 pages
Book Rating : 4.6/5 (422 download)
Download or read book Recursive Estimation and Time-Series Analysis written by Peter C. Young and published by Springer Science & Business Media. This book was released on 2011-08-04 with total page 505 pages. Available in PDF, EPUB and Kindle. Book excerpt: This is a revised version of the 1984 book of the same name but considerably modified and enlarged to accommodate the developments in recursive estimation and time series analysis that have occurred over the last quarter century. Also over this time, the CAPTAIN Toolbox for recursive estimation and time series analysis has been developed at Lancaster, for use in the MatlabTM software environment (see Appendix G). Consequently, the present version of the book is able to exploit the many computational routines that are contained in this widely available Toolbox, as well as some of the other routines in MatlabTM and its other toolboxes. The book is an introductory one on the topic of recursive estimation and it demonstrates how this approach to estimation, in its various forms, can be an impressive aid to the modelling of stochastic, dynamic systems. It is intended for undergraduate or Masters students who wish to obtain a grounding in this subject; or for practitioners in industry who may have heard of topics dealt with in this book and, while they want to know more about them, may have been deterred by the rather esoteric nature of some books in this challenging area of study.
Author : Yadolah Dodge
Publisher : Springer Science & Business Media
ISBN 13 : 1441987665
Total Pages : 188 pages
Book Rating : 4.4/5 (419 download)
Download or read book Adaptive Regression written by Yadolah Dodge and published by Springer Science & Business Media. This book was released on 2012-10-01 with total page 188 pages. Available in PDF, EPUB and Kindle. Book excerpt: While there have been a large number of estimation methods proposed and developed for linear regression, none has proved good for all purposes. This text focuses on the construction of an adaptive combination of two estimation methods so as to help users make an objective choice and combine the desirable properties of two estimators.
Author : Feike C. Drost
Publisher :
ISBN 13 :
Total Pages : 48 pages
Book Rating : 4.:/5 (322 download)
Download or read book Adaptive Estimation in Time-series Models written by Feike C. Drost and published by . This book was released on 1994 with total page 48 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Author : Kiseok Lee
Publisher :
ISBN 13 :
Total Pages : 142 pages
Book Rating : 4.:/5 (224 download)
Download or read book Adaptive Estimation of Random Parameter Regression Models by State Space Representation Methods written by Kiseok Lee and published by . This book was released on 1990 with total page 142 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Author : Yanquin Fan
Publisher :
ISBN 13 :
Total Pages : 17 pages
Book Rating : 4.:/5 (27 download)
Download or read book Adaptive Estimation in Semiparametric Regression Models with Conditionally Heteroskedastic Disturbances written by Yanquin Fan and published by . This book was released on 1993 with total page 17 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Author : Ibrahim Dulger
Publisher :
ISBN 13 : 9781423529293
Total Pages : 153 pages
Book Rating : 4.5/5 (292 download)
Download or read book Multiple Model Adaptive Estimation for Time Series Analysis written by Ibrahim Dulger and published by . This book was released on 2001-03 with total page 153 pages. Available in PDF, EPUB and Kindle. Book excerpt: Multiple Model Adaptive Estimation (MMAE) is a Bayesian technique that applies a bank of Kalman filters to predict future observations. Each Kalman filter is based on a different set of parameters and hence produces different residuals. The likelihood of each Kalman filter's prediction is determined by a magnitude of the residuals. Since some researchers have obtained good forecasts using a single Kalman filter, we tested MMAE's ability to make time series predictions. Our Kalman filters have a dynamics model based on a Box-Jenkins Auto-Regressive Moving Average (ARMA) model and a measure model with additive noise. The time-series prediction is based on the probabilistic weighted Kalman filter predictions. We make a probability interval about that estimate also based on the filter probabilities. In a Monte Carlo analysis, we test this MMAE approach and report the results based on many different criteria. Our analysis tests the robustness of the approach by testing its ability to make predictions when the Kalman filter dynamics models did not match the data generation time-series model. Our analysis indicates benefits in applying multiple model adaptive estimation for time series analysis.
Author : Pavel Čižek
Publisher :
ISBN 13 :
Total Pages : pages
Book Rating : 4.:/5 (15 download)
Download or read book Robust and Efficient Adaptive Estimation of Binary-choice Regression Models written by Pavel Čižek and published by . This book was released on 2007 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt:
Author : Kevin Hanslow
Publisher :
ISBN 13 :
Total Pages : 108 pages
Book Rating : 4.:/5 (219 download)
Download or read book Adaptive Estimation in Multiple Linear Regression written by Kevin Hanslow and published by . This book was released on 1985 with total page 108 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Author : Cory Terrell
Publisher : Scientific e-Resources
ISBN 13 : 1839473290
Total Pages : 300 pages
Book Rating : 4.8/5 (394 download)
Download or read book Predictions in Time Series Using Regression Models written by Cory Terrell and published by Scientific e-Resources. This book was released on 2019-09-02 with total page 300 pages. Available in PDF, EPUB and Kindle. Book excerpt: Regression methods have been a necessary piece of time arrangement investigation for over a century. As of late, new advancements have made real walks in such territories as non-constant information where a direct model isn't fitting. This book acquaints the peruser with fresher improvements and more assorted regression models and methods for time arrangement examination. Open to any individual who knows about the fundamental present day ideas of factual deduction, Regression Models for Time Series Analysis gives a truly necessary examination of late measurable advancements. Essential among them is the imperative class of models known as summed up straight models (GLM) which gives, under a few conditions, a bound together regression hypothesis reasonable for constant, all out, and check information. The creators stretch out GLM methodology deliberately to time arrangement where the essential and covariate information are both arbitrary and stochastically reliant. They acquaint readers with different regression models created amid the most recent thirty years or somewhere in the vicinity and condense traditional and later outcomes concerning state space models.
Author : Ke-Li Xu
Publisher :
ISBN 13 :
Total Pages : 31 pages
Book Rating : 4.:/5 (129 download)
Download or read book Adaptive Estimation of Autoregression Models with Time-Varying Variances written by Ke-Li Xu and published by . This book was released on 2006 with total page 31 pages. Available in PDF, EPUB and Kindle. Book excerpt: Stable autoregressive models of known finite order are considered with martingale differences errors scaled by an unknown nonparametric time-varying function generating heterogeneity. An important special case involves structural change in the error variance, but in most practical cases the pattern of variance change over time is unknown and may involve shifts at unknown discrete points in time, continuous evolution or combinations of the two. This paper develops kernel-based estimators of the residual variances and associated adaptive least squares (ALS) estimators of the autoregressive coefficients. These are shown to be asymptotically efficient, having the same limit distribution as the infeasible generalized least squares (GLS). Comparisons of the efficient procedure and the ordinary least squares (OLS) reveal that least squares can be extremely inefficient in some cases while nearly optimal in others. Simulations show that, when least squares work well, the adaptive estimators perform comparably well, whereas when least squares work poorly, major efficiency gains are achieved by the new estimators.
Author : Douglas Steigerwald
Publisher :
ISBN 13 :
Total Pages : 54 pages
Book Rating : 4.:/5 (318 download)
Download or read book Generalized Adaptive Estimation for Econometric and Financial Models written by Douglas Steigerwald and published by . This book was released on 1990 with total page 54 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Deciding on the Best (in this Case) Approach to Time-series Forecasting written by and published by . This book was released on 1980 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: This paper was motivated by a Decision Sciences article (v. 10, no. 2, 232-244(April 1979)) that presented comparisons of the adaptive estimation procedure (AEP), adaptive filtering, the Box-Jenkins (BJ) methodology, and multiple regression analysis as they apply to time-series forecasting with single-series models. While such comparisons are to be applauded in general, it is demonstrated that the empirical comparisons of the above paper are quite misleading with respect to choosing between the AEP and BJ approaches. This demonstration is followed by a somewhat philosophical discussion on comparison-of-methods techniques.
Author : Lyle D. Broemeling
Publisher : CRC Press
ISBN 13 : 0429948913
Total Pages : 211 pages
Book Rating : 4.4/5 (299 download)
Download or read book Bayesian Analysis of Time Series written by Lyle D. Broemeling and published by CRC Press. This book was released on 2019-04-16 with total page 211 pages. Available in PDF, EPUB and Kindle. Book excerpt: In many branches of science relevant observations are taken sequentially over time. Bayesian Analysis of Time Series discusses how to use models that explain the probabilistic characteristics of these time series and then utilizes the Bayesian approach to make inferences about their parameters. This is done by taking the prior information and via Bayes theorem implementing Bayesian inferences of estimation, testing hypotheses, and prediction. The methods are demonstrated using both R and WinBUGS. The R package is primarily used to generate observations from a given time series model, while the WinBUGS packages allows one to perform a posterior analysis that provides a way to determine the characteristic of the posterior distribution of the unknown parameters. Features Presents a comprehensive introduction to the Bayesian analysis of time series. Gives many examples over a wide variety of fields including biology, agriculture, business, economics, sociology, and astronomy. Contains numerous exercises at the end of each chapter many of which use R and WinBUGS. Can be used in graduate courses in statistics and biostatistics, but is also appropriate for researchers, practitioners and consulting statisticians. About the author Lyle D. Broemeling, Ph.D., is Director of Broemeling and Associates Inc., and is a consulting biostatistician. He has been involved with academic health science centers for about 20 years and has taught and been a consultant at the University of Texas Medical Branch in Galveston, The University of Texas MD Anderson Cancer Center and the University of Texas School of Public Health. His main interest is in developing Bayesian methods for use in medical and biological problems and in authoring textbooks in statistics. His previous books for Chapman & Hall/CRC include Bayesian Biostatistics and Diagnostic Medicine, and Bayesian Methods for Agreement.
