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Book Pseudo variance Quasi maximum Likelihood Estimation of Semiparametric Time Series Models

Download or read book Pseudo variance Quasi maximum Likelihood Estimation of Semiparametric Time Series Models written by Mirko Armillotta and published by . This book was released on 2023 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: We propose a novel estimation approach for a general class of semi-parametric time series models where the conditional expectation is modeled through a parametric function. The proposed class of estimators is based on a Gaussian quasi-likelihood function and it relies on the specification of a parametric pseudo-variance that can contain parametric restrictions with respect to the conditional expectation. The specification of the pseudo-variance and the parametric restrictions follow naturally in observation-driven models with bounds in the support of the observable process, such as count processes and double-bounded time series. We derive the asymptotic properties of the estimators and a validity test for the parameter restrictions. We show that the results remain valid irrespective of the correct specification of the pseudo-variance. The key advantage of the restricted estimators is that they can achieve higher efficiency compared to alternative quasi-likelihood methods that are available in the literature. Furthermore, the testing approach can be used to build specification tests for parametric time series models. We illustrate the practical use of the methodology in a simulation study and two empirical applications featuring integer-valued autoregressive processes, where assumptions on the dispersion of the thinning operator are formally tested, and autoregressions for double-bounded data with application to a realized correlation time series.

Book Quasi maximum Likelihood Estimation of Heteroskedastic Fractional Time Series Models

Download or read book Quasi maximum Likelihood Estimation of Heteroskedastic Fractional Time Series Models written by Giuseppe Cavaliere and published by . This book was released on 2014 with total page 41 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Book Semiparametric Maximum Likelihood Estimation of GARCH Models

Download or read book Semiparametric Maximum Likelihood Estimation of GARCH Models written by Jian Yang and published by London : Department of Economics, University of Western Ontario. This book was released on 1998 with total page 38 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Book Quasi maximum Likelihood Estimation of Dynamic Models with Time Varying Covariances

Download or read book Quasi maximum Likelihood Estimation of Dynamic Models with Time Varying Covariances written by Tim Bollerslev and published by . This book was released on 1988 with total page 50 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Book Advances and Challenges in Parametric and Semi parametric Analysis for Correlated Data

Download or read book Advances and Challenges in Parametric and Semi parametric Analysis for Correlated Data written by Brajendra C. Sutradhar and published by Springer. This book was released on 2016-06-15 with total page 267 pages. Available in PDF, EPUB and Kindle. Book excerpt: This proceedings volume contains eight selected papers that were presented in the International Symposium in Statistics (ISS) 2015 On Advances in Parametric and Semi-parametric Analysis of Multivariate, Time Series, Spatial-temporal, and Familial-longitudinal Data, held in St. John’s, Canada from July 6 to 8, 2015. The main objective of the ISS-2015 was the discussion on advances and challenges in parametric and semi-parametric analysis for correlated data in both continuous and discrete setups. Thus, as a reflection of the theme of the symposium, the eight papers of this proceedings volume are presented in four parts. Part I is comprised of papers examining Elliptical t Distribution Theory. In Part II, the papers cover spatial and temporal data analysis. Part III is focused on longitudinal multinomial models in parametric and semi-parametric setups. Finally Part IV concludes with a paper on the inferences for longitudinal data subject to a challenge of important covariates selection from a set of large number of covariates available for the individuals in the study.

Book Econometric Analysis of Count Data

Download or read book Econometric Analysis of Count Data written by Rainer Winkelmann and published by Springer Science & Business Media. This book was released on 2013-06-29 with total page 291 pages. Available in PDF, EPUB and Kindle. Book excerpt: The primary objective of this book is to provide an introduction to the econometric modeling of count data for graduate students and researchers. It should serve anyone whose interest lies either in developing the field fur ther, or in applying existing methods to empirical questions. Much of the material included in this book is not specific to economics, or to quantita tive social sciences more generally, but rather extends to disciplines such as biometrics and technometrics. Applications are as diverse as the number of congressional budget vetoes, the number of children in a household, and the number of mechanical defects in a production line. The unifying theme is a focus on regression models in which a dependent count variable is modeled as a function of independent variables which mayor may not be counts as well. The modeling of count data has come of age. Inclusion of some of the fundamental models in basic textbooks, and implementation on standard computer software programs bear witness to that. Based on the standard Poisson regression model, numerous extensions and alternatives have been developed to address the common challenges faced in empirical modeling (unobserved heterogeneity, selectivity, endogeneity, measurement error, and dependent observations in the context of panel data or multivariate data, to name but a few) as well as the challenges that are specific to count data (e. g. , over dispersion and underdispersion).

Book Further Results on Pseudo Maximum Likelihood Estimation and Testing in the Constant Elasticity of Variance Continuous Time Model

Download or read book Further Results on Pseudo Maximum Likelihood Estimation and Testing in the Constant Elasticity of Variance Continuous Time Model written by Emma Iglesias and published by . This book was released on 2020 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Book QUASI MAXIMUM LIKELIHOOD ESTIMATION OF DYNAMIC MODELS WITH TIME VARYNG COVARIANCES

Download or read book QUASI MAXIMUM LIKELIHOOD ESTIMATION OF DYNAMIC MODELS WITH TIME VARYNG COVARIANCES written by Tim BOLLERSLEV and published by . This book was released on 1988 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt:

Book Quasi maximum likelihood Estimation in Heteroscedastic Time Series

Download or read book Quasi maximum likelihood Estimation in Heteroscedastic Time Series written by Daniel Straumann and published by . This book was released on 2003 with total page 36 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Book Negative Binomial Quasi Likelihood Inference for General Integer Valued Time Series Models

Download or read book Negative Binomial Quasi Likelihood Inference for General Integer Valued Time Series Models written by Abdelhakim Aknouche and published by . This book was released on 2018 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: Two negative binomial quasi-maximum likelihood estimates (NB-QMLEs) for a general class of count time series models are proposed. The first one is the profile NB-QMLE calculated while arbitrarily fixing the dispersion parameter of the negative binomial likelihood. The second one, termed two-stage NB-QMLE, consists of four stages estimating both conditional mean and dispersion parameters. It is shown that the two estimates are consistent and asymptotically Gaussian under mild conditions. Moreover, the two-stage NB-QMLE enjoys a certain asymptotic efficiency property provided that a negative binomial link function relating the conditional mean and conditional variance is specified. The proposed NB-QMLEs are compared with the Poisson QMLE asymptotically and in finite samples for various well-known particular classes of count time series models such as the Poisson and negative binomial integer-valued GARCH model and the INAR(1) model. Application to a real dataset is given.

Book Poisson QMLE of Count Time Series Models

Download or read book Poisson QMLE of Count Time Series Models written by Ali Ahmad and published by . This book was released on 2016 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: Regularity conditions are given for the consistency of the Poisson quasi-maximum likelihood estimator of the conditional mean parameter of a count time series model. The asymptotic distribution of the estimator is studied when the parameter belongs to the interior of the parameter space and when it lies at the boundary. Tests for the significance of the parameters and for constant conditional mean are deduced. Applications to specific integer-valued autoregressive (INAR) and integer-valued generalized autoregressive conditional heteroscedasticity (INGARCH) models are considered. Numerical illustrations, Monte Carlo simulations and real data series are provided.

Book Handbook of Financial Time Series

Download or read book Handbook of Financial Time Series written by Torben Gustav Andersen and published by Springer Science & Business Media. This book was released on 2009-04-21 with total page 1045 pages. Available in PDF, EPUB and Kindle. Book excerpt: The Handbook of Financial Time Series gives an up-to-date overview of the field and covers all relevant topics both from a statistical and an econometrical point of view. There are many fine contributions, and a preamble by Nobel Prize winner Robert F. Engle.