Download or read book Maximum Likelihood Estimation of the Parameters of Non minimum Phase Non causal and Non linear ARMA models written by Klaus Bolding Rasmussen and published by . This book was released on 1991 with total page 18 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Maximum Likehood Estimation of the Parameters of Non minimum Phase Non causal and Non linear ARMA Models written by K. Bolding Rasmussen and published by . This book was released on 1991 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book On estimating non causal non minimum phase arma models of non gaussian processes written by Georgios B. Giannakis and published by . This book was released on 1988 with total page 66 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Semi Parametric Estimation for Non Gaussian Non Minimum Phase ARMA Models written by Richard A. Davis and published by . This book was released on 2018 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: We consider inference for the parameters of general autoregressive moving average (ARMA) models which are possibly non-causal/non-invertible (also referred to as non-minimum phase) and driven by a non-Gaussian distribution. For non-minimum phase models, the observations can depend on both the past and future shocks in the system. The non-Gaussianity constraint is necessary to distinguish between causal-invertible and non-causal/non-invertible models. Many of the existing estimation procedures adopt quasi-likelihood methods by assuming a non-Gaussian density function for the noise distribution that is fully known up to a scalar parameter. To relax such distributional restrictions, we borrow ideas from non-parametric density estimation and propose a semi-parametric maximum likelihood estimation procedure, in which the noise distribution is projected onto the space of log-concave measures. We show the maximum likelihood estimators (MLEs) in this semi-parametric setting are consistent. In fact, the MLE is robust to the misspecification of log-concavity in cases where the true distribution of the noise is close to its log-concave projection (Cule and Samworth, 2010; Dümbgen, 2011). We derive a lower bound for the best asymptotic variance of regular estimators at rate for autoregressive (AR) models and construct a semi-parametric efficient one-step estimator. The estimation procedure is illustrated a simulation study and an empirical example illustrating the methodology is also provided.

Download or read book Gaussian and Non Gaussian Linear Time Series and Random Fields written by Murray Rosenblatt and published by Springer Science & Business Media. This book was released on 2012-12-06 with total page 252 pages. Available in PDF, EPUB and Kindle. Book excerpt: The principal focus here is on autoregressive moving average models and analogous random fields, with probabilistic and statistical questions also being discussed. The book contrasts Gaussian models with noncausal or noninvertible (nonminimum phase) non-Gaussian models and deals with problems of prediction and estimation. New results for nonminimum phase non-Gaussian processes are exposited and open questions are noted. Intended as a text for gradutes in statistics, mathematics, engineering, the natural sciences and economics, the only recommendation is an initial background in probability theory and statistics. Notes on background, history and open problems are given at the end of the book.

Download or read book Prediction and Estimation in ARMA Models written by Helgi Tómasson and published by Coronet Books. This book was released on 1986 with total page 138 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Maximum Likelihood Estimation of Restricted Parameters written by H. D. Brunk and published by . This book was released on 1956 with total page 68 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Semiparametric Maximum Likelihood Estimation of Nonlinear Regression Models and Monte Carlo Evidence written by Jian Yang and published by London : Department of Economics, University of Western Ontario. This book was released on 1997 with total page 68 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Cumulant and polyspectral measures for non Gaussian signal classification and estimation written by Georgios B. Giannakis and published by . This book was released on 1989 with total page 72 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Maximum likelihood parameter estimation for general non linear dynamic systems written by and published by . This book was released on 1987 with total page 6 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book A Maximum Likelihood Parameter Estimation Progam for General Non linear Systems written by J Blackwell and published by . This book was released on 1988 with total page 28 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Signal Processing Workshop on Higher Order Statistics June 7 9 1993 Stanford Sierra Group South Lake Tahoe CA USA written by and published by . This book was released on 1993 with total page 498 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Proceedings of the IEEE Signal Processing Workshop on Higher Order Statistics July 21 23 1997 Banff Alberta Canada written by and published by Institute of Electrical & Electronics Engineers(IEEE). This book was released on 1997 with total page 496 pages. Available in PDF, EPUB and Kindle. Book excerpt: This text covering the 1997 IEEE Signal Processing Workshop on High-Order Statistics is designed for researchers, professors, practitioners, students and other computing professionals.

Download or read book A Maximum Likelihood Parameter Estimation Program for General Non linear Systems U written by Jeremy Blackwell and published by . This book was released on 1987 with total page 28 pages. Available in PDF, EPUB and Kindle. Book excerpt: A computer program has been developed for the Maximum Likelihood estimation of parameters in general non-linear systems. Sensitivity matrix elements are calculated numerically, overcoming the need for explicit sensitivity equations. Parameters such as break points and time shifts are successfully determined using both simulated and actual test data. Keywords: Non linear systems, Time lag, Drop tests, Parameter estimation, Maximum likelihood, Landing gear.

Download or read book Index to IEEE Publications written by Institute of Electrical and Electronics Engineers and published by . This book was released on 1990 with total page 848 pages. Available in PDF, EPUB and Kindle. Book excerpt: Issues for 1973- cover the entire IEEE technical literature.

Download or read book Computational Approaches for Maximum Likelihood Estimation for Nonlinearmixed Models written by and published by . This book was released on 2000 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: The nonlinear mixed model is an important tool for analyzingpharmacokinetic and other repeated-measures data. In particular, these models are used when the measured response for anindividual, has a nonlinear relationship with unknown, random, individual-specificparameters, . Ideally, the method of maximum likelihood is used to find estimates forthe parameters ofthe model after integrating out the random effects in the conditionallikelihood. However, closed form solutions tothe integral are generally not available. As a result, methods have beenpreviously developed to find approximatemaximum likelihood estimates for the parameters in the nonlinear mixedmodel. These approximate methods include FirstOrder linearization, Laplace's approximation, importance sampling, andGaussian quadrature. The methods are availabletoday in several software packages for models of limited sophistication;constant conditional error variance is requiredfor proper utilization of most software. In addition, distributionalassumptions are needed. This work investigates howrobust two of these methods, First Order linearization and Laplace'sapproximation, are to these assumptions. The findingis that Laplace's approximation performs well, resulting in betterestimation than first order linearization when bothmodels converge to a solution. A method must provide good estimates of the likelihood at points inthe parameter space near the solution. This workcompares this ability among the numerical integration techniques, Gaussian quadrature, importance sampling, and Laplace'sapproximation. A new "scaled" and "centered" version of Gaussianquadrature is found to be the most accurate technique. In addition, the technique requires evaluation of the integrand at onlya few abscissas. Laplace's method also performs well; it is more accurate than importance sampling with even 100importance samples over two dimensions. Even so, Laplace's method still does not perform as well as Gaussian quadrature. Overall, Laplace's a.

Download or read book ARMA Model Identification written by ByoungSeon Choi and published by Springer Science & Business Media. This book was released on 2012-12-06 with total page 211 pages. Available in PDF, EPUB and Kindle. Book excerpt: During the last two decades, considerable progress has been made in statistical time series analysis. The aim of this book is to present a survey of one of the most active areas in this field: the identification of autoregressive moving-average models, i.e., determining their orders. Readers are assumed to have already taken one course on time series analysis as might be offered in a graduate course, but otherwise this account is self-contained. The main topics covered include: Box-Jenkins' method, inverse autocorrelation functions, penalty function identification such as AIC, BIC techniques and Hannan and Quinn's method, instrumental regression, and a range of pattern identification methods. Rather than cover all the methods in detail, the emphasis is on exploring the fundamental ideas underlying them. Extensive references are given to the research literature and as a result, all those engaged in research in this subject will find this an invaluable aid to their work.