Download or read book Asymptotics for the Conditional Sum Of Squares Estimator in Multivariate Fractional Time Series Models written by Morten Ørregaard Nielsen and published by . This book was released on 2015 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: This article proves consistency and asymptotic normality for the conditional-sum-of-squares estimator, which is equivalent to the conditional maximum likelihood estimator, in multivariate fractional time-series models. The model is parametric and quite general and, in particular, encompasses the multivariate non-cointegrated fractional autoregressive integrated moving average (ARIMA) model. The novelty of the consistency result, in particular, is that it applies to a multivariate model and to an arbitrarily large set of admissible parameter values, for which the objective function does not converge uniformly in probability, thus making the proof much more challenging than usual. The neighbourhood around the critical point where uniform convergence fails is handled using a truncation argument.

Download or read book Asymptotics for the Conditional sum of squares Estimator in Fractional Time Series Models written by Morten Ørregaard Nielsen and published by . This book was released on 2011 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: This paper proves consistency and asymptotic normality for the conditional-sum-of-squares (CSS) estimator in fractional time series models. The models are parametric and quite general. The novelty of the consistency result is that it applies to an arbitrarily large set of admissible parameter values, for which the objective function does not converge uniformly in probablity thus making the proof much more challenging than usual. The neighborhood around the critical point where uniform convergence fails is handled using a truncation argument. The only other consistency proof for such models that applies to an arbitrarily large set of admissible parameter values appears to be Hualde and Robinson (2010), who require all moments of the innovation process to exist. In contrast, the present proof requires only a few moments of the innovation process to be finite (four in the simplest case). Finally, all arguments, assumptions, and proofs in this paper are stated entirely in the time domain, which is somewhat remarkable for this literature. -- Asymptotic normality ; conditional-sum-of-squares estimator ; consistency ; fractional integration ; fractional time series ; likelihood inference ; long memory ; nonstationary ; uniform convergence

Download or read book Truncated Sum of Squares Estimation of Fractional Time Series Models with Deterministic Trends written by Javier Hualde and published by . This book was released on 2017 with total page 58 pages. Available in PDF, EPUB and Kindle. Book excerpt: We consider truncated (or conditional) sum of squares estimation of a parametric model composed of a fractional time series and an additive generalized polynomial trend. Both the memory parameter, which characterizes the behaviour of the stochastic component of the model, and the exponent parameter, which drives the shape of the deterministic component, are considered not only unknown real numbers, but also lying in arbitrarily large (but nite) intervals. Thus, our model captures dierent forms of nonstationarity and noninvertibility. As in related settings, the proof of con- sistency (which is a prerequisite for proving asymptotic normality) is challenging due to non-uniform convergence of the objective function over a large admissible parameter space, but, in addition, our framework is substantially more involved due to the com- petition between stochastic and deterministic components. We establish consistency and asymptotic normality under quite general circumstances, nding that results dif- fer crucially depending on the relative strength of the deterministic and stochastic components.

Download or read book Asymptotic Properties of Conditional Least squares Estimators for Array Time Series written by Rajae Azral and published by . This book was released on 2020 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Self Similar Processes in Telecommunications written by Oleg Sheluhin and published by John Wiley & Sons. This book was released on 2007-03-13 with total page 334 pages. Available in PDF, EPUB and Kindle. Book excerpt: For the first time the problems of voice services self-similarity are discussed systematically and in detail with specific examples and illustrations. Self-Similar Processes in Telecommunications considers the self-similar (fractal and multifractal) models of telecommunication traffic and efficiency based on the assumption that its traffic has fractal or multifractal properties (is self-similar). The theoretical aspects of the most well-known traffic models demonstrating self-similar properties are discussed in detail and the comparative analysis of the different models’ efficiency for self-similar traffic is presented. This book demonstrates how to use self-similar processes for designing new telecommunications systems and optimizing existing networks so as to achieve maximum efficiency and serviceability. The approach is rooted in theory, describing the algorithms (the logical arithmetical or computational procedures that define how a task is performed) for modeling these self-similar processes. However, the language and ideas are essentially accessible for those who have a general knowledge of the subject area and the advice is highly practical: all models, problems and solutions are illustrated throughout using numerous real-world examples. Adopts a detailed, theoretical, yet broad-based and practical mathematical approach for designing and operating numerous types of telecommunications systems and networks so as to achieve maximum efficiency Places the subject in context, describing the current algorithms that make up the fractal or self-similar processes while pointing to the future development of the technology Offers a comparative analysis of the different types of self-similar process usage within the context of local area networks, wide area networks and in the modeling of video traffic and mobile communications networks Describes how mathematical models are used as a basis for building numerous types of network, including voice, audio, data, video, multimedia services and IP (Internet Protocol) telephony The book will appeal to the wide range of specialists dealing with the design and exploitation of telecommunication systems. It will be useful for the post-graduate students, lecturers and researchers connected with communication networks disciplines.

Download or read book Asymptotic Filtering Theory for Multivariate ARCH Models written by Daniel B. Nelson and published by . This book was released on 1994 with total page 55 pages. Available in PDF, EPUB and Kindle. Book excerpt: ARCH models are widely used to estimate conditional variances and covariances in financial time series models. How successfully can ARCH models carry out this estimation when they are misspecified? How can ARCH models be optimally constructed? Nelson and Foster (1994) employed continuous record asymptotics to answer these questions in the univariate case. This paper considers the general multivariate case. Our results allow us, for example, to construct an asymptotically optimal ARCH model for estimating the conditional variance or conditional beta of a stock return given lagged returns on the stock, volume, market returns, implicit volatility from options contracts, and other relevant data. We also allow for time-varying shapes of conditional densities (e.g., heteroskewticityànd heterokurticity'). Examples are provided

Download or read book Time Series and Related Topics written by Ching-Zong Wei and published by IMS. This book was released on 2006 with total page 314 pages. Available in PDF, EPUB and Kindle. Book excerpt:

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:

Download or read book Asymptotic Bias of the Least Squares Estimator for Multivariate Autoregressive Models written by Stanford University. Institute for Mathematical Studies in the Social Sciences and published by . This book was released on 1982 with total page 15 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Asymptotic Theory for M estimators in General Autoregressive Conditional Heteroscedastic Time Series Models written by Fabian Tinkl and published by . This book was released on 2013 with total page 184 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Journal of Econometrics written by and published by . This book was released on 1998 with total page 830 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Asymptotics of Multivariate Regression with Consecutively Added Dependent Variables written by Vera Maria Raats and published by . This book was released on 2004 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Asymptotic Properties of Sample Autocorrelations Least Squares Estimators and Predictors of Non stationary Multivariate Time Series written by Vanniarachchige Amarasiri Samaranayake and published by . This book was released on 1983 with total page 100 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Estimation in Conditionally Heteroscedastic Time Series Models written by Daniel Straumann and published by . This book was released on 2004 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Asymptotic Properties of Nonlinear Least Squares Estimators in a Replicated Time Series Model written by Jeremy Sin-hing Wu and published by . This book was released on 1982 with total page 246 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book On the asymptotic estimation theory of vector linear time series models with stationary residuals written by Australian National University. Faculty of Economics and Research School of Social Sciences and published by . This book was released on 1978 with total page 63 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Time Series Analysis written by James D. Hamilton and published by Princeton University Press. This book was released on 2020-09-01 with total page 820 pages. Available in PDF, EPUB and Kindle. Book excerpt: An authoritative, self-contained overview of time series analysis for students and researchers The past decade has brought dramatic changes in the way that researchers analyze economic and financial time series. This textbook synthesizes these advances and makes them accessible to first-year graduate students. James Hamilton provides comprehensive treatments of important innovations such as vector autoregressions, generalized method of moments, the economic and statistical consequences of unit roots, time-varying variances, and nonlinear time series models. In addition, he presents basic tools for analyzing dynamic systems—including linear representations, autocovariance generating functions, spectral analysis, and the Kalman filter—in a way that integrates economic theory with the practical difficulties of analyzing and interpreting real-world data. Time Series Analysis fills an important need for a textbook that integrates economic theory, econometrics, and new results. This invaluable book starts from first principles and should be readily accessible to any beginning graduate student, while it is also intended to serve as a reference book for researchers.