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 Mathematical Reviews written by and published by . This book was released on 2003 with total page 1448 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Distributed Lags written by Phoebus J. Dhrymes and published by . This book was released on 1971 with total page 446 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Handbook of Applied Economic Statistics written by Aman Ullah and published by CRC Press. This book was released on 1998-02-03 with total page 646 pages. Available in PDF, EPUB and Kindle. Book excerpt: This work examines theoretical issues, as well as practical developments in statistical inference related to econometric models and analysis. This work offers discussions on such areas as the function of statistics in aggregation, income inequality, poverty, health, spatial econometrics, panel and survey data, bootstrapping and time series.
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 Quarterly Publication of the American Statistical Association written by and published by . This book was released on 2005 with total page 376 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Statistics Subject Indexes from Mathematical Reviews written by American Mathematical Society and published by . This book was released on 1987 with total page 540 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Asymptotic Distribution of the Bias Corrected Least Squares Estimators in Measurement Error Linear Regression Models Under Long Memory written by Hira Koul and published by . This book was released on 2020 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: This article derives the consistency and asymptotic distribution of the bias corrected least squares estimators (LSEs) of the regression parameters in linear regression models when covariates have measurement error (ME) and errors and covariates form mutually independent long memory moving average processes. In the structural ME linear regression model, the nature of the asymptotic distribution of suitably standardized bias corrected LSEs depends on the range of the values of where ,, and are the LM parameters of the covariate, ME and regression error processes respectively. This limiting distribution is Gaussian when and non-Gaussian in the case . In the former case some consistent estimators of the asymptotic variances of these estimators and a log()-consistent estimator of an underlying LM parameter are also provided. They are useful in the construction of the large sample confidence intervals for regression parameters. The article also discusses the asymptotic distribution of these estimators in some functional ME linear regression models, where the unobservable covariate is non-random. In these models, the limiting distribution of the bias corrected LSEs is always a Gaussian distribution determined by the range of the values of )-)
Download or read book Error Estimation for Pattern Recognition written by Ulisses M. Braga Neto and published by John Wiley & Sons. This book was released on 2015-06-22 with total page 336 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book is the first of its kind to discuss error estimation with a model-based approach. From the basics of classifiers and error estimators to distributional and Bayesian theory, it covers important topics and essential issues pertaining to the scientific validity of pattern classification. Error Estimation for Pattern Recognition focuses on error estimation, which is a broad and poorly understood topic that reaches all research areas using pattern classification. It includes model-based approaches and discussions of newer error estimators such as bolstered and Bayesian estimators. This book was motivated by the application of pattern recognition to high-throughput data with limited replicates, which is a basic problem now appearing in many areas. The first two chapters cover basic issues in classification error estimation, such as definitions, test-set error estimation, and training-set error estimation. The remaining chapters in this book cover results on the performance and representation of training-set error estimators for various pattern classifiers. Additional features of the book include: • The latest results on the accuracy of error estimation • Performance analysis of re-substitution, cross-validation, and bootstrap error estimators using analytical and simulation approaches • Highly interactive computer-based exercises and end-of-chapter problems This is the first book exclusively about error estimation for pattern recognition. Ulisses M. Braga Neto is an Associate Professor in the Department of Electrical and Computer Engineering at Texas A&M University, USA. He received his PhD in Electrical and Computer Engineering from The Johns Hopkins University. Dr. Braga Neto received an NSF CAREER Award for his work on error estimation for pattern recognition with applications in genomic signal processing. He is an IEEE Senior Member. Edward R. Dougherty is a Distinguished Professor, Robert F. Kennedy ’26 Chair, and Scientific Director at the Center for Bioinformatics and Genomic Systems Engineering at Texas A&M University, USA. He is a fellow of both the IEEE and SPIE, and he has received the SPIE Presidents Award. Dr. Dougherty has authored several books including Epistemology of the Cell: A Systems Perspective on Biological Knowledge and Random Processes for Image and Signal Processing (Wiley-IEEE Press).
Download or read book Current Index to Statistics Applications Methods and Theory written by and published by . This book was released on 1990 with total page 760 pages. Available in PDF, EPUB and Kindle. Book excerpt: The Current Index to Statistics (CIS) is a bibliographic index of publications in statistics, probability, and related fields.
Download or read book Asymptotic Distributions of Some Scale Estimators in Nonlinear Models With Long Memory Errors Having Infinite Variance written by and published by . This book was released on 2017 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Minimum Distance Estimation of Dynamic Models with Errors in Variables written by Nikolay Gospodinov and published by . This book was released on 2015 with total page 37 pages. Available in PDF, EPUB and Kindle. Book excerpt: Empirical analysis often involves using inexact measures of desired predictors. The bias created by the correlation between the problematic regressors and the error term motivates the need for instrumental variables estimation. This paper considers a class of estimators that can be used when external instruments may not be available or are weak. The idea is to exploit the relation between the parameters of the model and the least squares biases. In cases when this mapping is not analytically tractable, a special algorithm is designed to simulate the latent predictors without completely specifying the processes that induce the biases. The estimators perform well in simulations of the autoregressive distributed lag model and the dynamic panel model. The methodology is used to re-examine the Phillips curve, in which the real activity gap is latent.
Download or read book Ridge Estimators for Distributed Lag Models written by G. S. Maddala and published by . This book was released on 1974 with total page 17 pages. Available in PDF, EPUB and Kindle. Book excerpt: The paper explains how the Almon polynominal lag specification can be made stochastic in two different ways - one suggested by Shiller and another following the lines of Lindley and Smith. It is shown that both the estimators can be considered as modified ridge estimators. The paper then compares these modified ridge estimators with the ridge estimator suggested by Hoerl and Kennard. It is shown that for the estimation of distributed lag models the ridge estimator suggested by Hoerl and Kennard is not useful but that the modified ridge estimators corresponding to the stochastic versions of the Almon lag are promising. The paper has two empirical illustrations
Download or read book Nonlinear Estimation written by SHOVAN. DATE BHAUMIK (PARESH.) and published by CRC Press. This book was released on 2019-08-09 with total page 280 pages. Available in PDF, EPUB and Kindle. Book excerpt: Nonlinear Estimation: Methods and Applications with Deterministic Sample Points focusses on a comprehensive treatment of deterministic sample point filters (also called Gaussian filters) and their variants for nonlinear estimation problems, for which no closed-form solution is available in general. Gaussian filters are becoming popular with the designers due to their ease of implementation and real time execution even on inexpensive or legacy hardware. The main purpose of the book is to educate the reader about a variety of available nonlinear estimation methods so that the reader can choose the right method for a real life problem, adapt or modify it where necessary and implement it. The book can also serve as a core graduate text for a course on state estimation. The book starts from the basic conceptual solution of a nonlinear estimation problem and provides an in depth coverage of (i) various Gaussian filters such as the unscented Kalman filter, cubature and quadrature based filters, Gauss-Hermite filter and their variants and (ii) Gaussian sum filter, in both discrete and continuous-discrete domain. Further, a brief description of filters for randomly delayed measurement and two case-studies are also included. Features: The book covers all the important Gaussian filters, including filters with randomly delayed measurements. Numerical simulation examples with detailed matlab code are provided for most algorithms so that beginners can verify their understanding. Two real world case studies are included: (i) underwater passive target tracking, (ii) ballistic target tracking. The style of writing is suitable for engineers and scientists. The material of the book is presented with the emphasis on key ideas, underlying assumptions, algorithms, and properties. The book combines rigorous mathematical treatment with matlab code, algorithm listings, flow charts and detailed case studies to deepen understanding.
Download or read book Estimating Deterministic Trends in the Presence of Serially Correlated Errors written by Eugene Canjels and published by . This book was released on 1994 with total page 54 pages. Available in PDF, EPUB and Kindle. Book excerpt: This paper studies the problems of estimation and inference in the linear trend model: yt=̉+þt+ut, where ut follows an autoregressive process with largest root þ, and þ is the parameter of interest. We contrast asymptotic results for the cases þþþ
Download or read book The Small Sample Problem of Truncation Remainders in the Estimation of Distributed Lag Models with Autocorrelated Errors written by M. H. Pesaran and published by . This book was released on 1973 with total page 13 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Estimating Distributed Lag Coefficients when There are Errors in the Observed Time Series written by Melvin J. Hinich and published by . This book was released on 1982 with total page 23 pages. Available in PDF, EPUB and Kindle. Book excerpt: Estimating the distributed lag coefficients (h(mTAU)) from a sample of the two processes when (x(NTAU)) and (y(nTAU)) are measured with error is a statistical problem that is frequently encountered in physical science, engineering, and social science applications. In the engineering and science literature the distributed lags are called the impulse response weights of a causal linear filter. A least squares fit of the model gives biased estimates of the coefficients for this time series version of the errors-in-variables problem. This paper presents approximately unbiased estimators of a scalar multiple of the coefficients. (Author).
