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Estimation In Semiparametric Time Series Models
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Book Synopsis Estimation in Semiparametric Time Series Models by : Jiti Gao
Download or read book Estimation in Semiparametric Time Series Models written by Jiti Gao and published by . This book was released on 2010 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: In this paper, we consider a semiparametric time series regression model and establish a set of identification conditions such that the model under discussion is both identifiable and estimable. We then discuss how to estimate a sequence of local alternative functions nonparametrically when the null hypothesis does not hold. An asymptotic theory is established in each case. An empirical application is also included.
Book Synopsis Parametric and Semiparametric Models with Applications to Reliability, Survival Analysis, and Quality of Life by : M.S. Nikulin
Download or read book Parametric and Semiparametric Models with Applications to Reliability, Survival Analysis, and Quality of Life written by M.S. Nikulin and published by Springer Science & Business Media. This book was released on 2013-11-11 with total page 566 pages. Available in PDF, EPUB and Kindle. Book excerpt: Parametric and semiparametric models are tools with a wide range of applications to reliability, survival analysis, and quality of life. This self-contained volume examines these tools in survey articles written by experts currently working on the development and evaluation of models and methods. While a number of chapters deal with general theory, several explore more specific connections and recent results in "real-world" reliability theory, survival analysis, and related fields. Specific topics covered include: * cancer prognosis using survival forests * short-term health problems related to air pollution: analysis using semiparametric generalized additive models * semiparametric models in the studies of aging and longevity This book will be of use as a reference text for general statisticians, theoreticians, graduate students, reliability engineers, health researchers, and biostatisticians working in applied probability and statistics.
Download or read book Nonlinear Time Series written by Jiti Gao and published by CRC Press. This book was released on 2007-03-22 with total page 249 pages. Available in PDF, EPUB and Kindle. Book excerpt: Useful in the theoretical and empirical analysis of nonlinear time series data, semiparametric methods have received extensive attention in the economics and statistics communities over the past twenty years. Recent studies show that semiparametric methods and models may be applied to solve dimensionality reduction problems arising from using fully
Book Synopsis Nonparametric and Semiparametric Methods in Econometrics and Statistics by : William A. Barnett
Download or read book Nonparametric and Semiparametric Methods in Econometrics and Statistics written by William A. Barnett and published by Cambridge University Press. This book was released on 1991-06-28 with total page 512 pages. Available in PDF, EPUB and Kindle. Book excerpt: Papers from a 1988 symposium on the estimation and testing of models that impose relatively weak restrictions on the stochastic behaviour of data.
Book Synopsis Efficient and Adaptive Estimation for Semiparametric Models by : Peter J. Bickel
Download or read book Efficient and Adaptive Estimation for Semiparametric Models written by Peter J. Bickel and published by Springer. This book was released on 1998-06-01 with total page 588 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book deals with estimation in situations in which there is believed to be enough information to model parametrically some, but not all of the features of a data set. Such models have arisen in a wide context in recent years, and involve new nonlinear estimation procedures. Statistical models of this type are directly applicable to fields such as economics, epidemiology, and astronomy.
Book Synopsis Semiparametric Estimation in Time Series Regression with Long Range Dependence by : M. Ørregaard Nielsen
Download or read book Semiparametric Estimation in Time Series Regression with Long Range Dependence written by M. Ørregaard Nielsen and published by . This book was released on 2004 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Semiparametric Regression by : David Ruppert
Download or read book Semiparametric Regression written by David Ruppert and published by Cambridge University Press. This book was released on 2003-07-14 with total page 408 pages. Available in PDF, EPUB and Kindle. Book excerpt: Even experts on semiparametric regression should find something new here.
Book Synopsis Estimation in Semiparametric Models by : Johann Pfanzagl
Download or read book Estimation in Semiparametric Models written by Johann Pfanzagl and published by Springer Science & Business Media. This book was released on 2012-12-06 with total page 116 pages. Available in PDF, EPUB and Kindle. Book excerpt: Assume one has to estimate the mean J x P( dx) (or the median of P, or any other functional t;;(P)) on the basis ofi.i.d. observations from P. Ifnothing is known about P, then the sample mean is certainly the best estimator one can think of. If P is known to be the member of a certain parametric family, say {Po: {) E e}, one can usually do better by estimating {) first, say by {)(n)(.~.), and using J XPo(n)(;r.) (dx) as an estimate for J xPo(dx). There is an "intermediate" range, where we know something about the unknown probability measure P, but less than parametric theory takes for granted. Practical problems have always led statisticians to invent estimators for such intermediate models, but it usually remained open whether these estimators are nearly optimal or not. There was one exception: The case of "adaptivity", where a "nonparametric" estimate exists which is asymptotically optimal for any parametric submodel. The standard (and for a long time only) example of such a fortunate situation was the estimation of the center of symmetry for a distribution of unknown shape.
Book Synopsis Semiparametric Methods in Econometrics by : Joel L. Horowitz
Download or read book Semiparametric Methods in Econometrics written by Joel L. Horowitz 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: Many econometric models contain unknown functions as well as finite- dimensional parameters. Examples of such unknown functions are the distribution function of an unobserved random variable or a transformation of an observed variable. Econometric methods for estimating population parameters in the presence of unknown functions are called "semiparametric." During the past 15 years, much research has been carried out on semiparametric econometric models that are relevant to empirical economics. This book synthesizes the results that have been achieved for five important classes of models. The book is aimed at graduate students in econometrics and statistics as well as professionals who are not experts in semiparametic methods. The usefulness of the methods will be illustrated with applications that use real data.
Book Synopsis Semiparametric Estimation in Time Series Regression with Long Range Dependence by :
Download or read book Semiparametric Estimation in Time Series Regression with Long Range Dependence written by and published by . This book was released on 2002 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Semiparametric Regression Estimation in Null Recurrent Nonlinear Time Series by : Jia Chen
Download or read book Semiparametric Regression Estimation in Null Recurrent Nonlinear Time Series written by Jia Chen and published by . This book was released on 2009 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: Estimation theory in a nonstationary environment has been very popular in recent years. Existing studies focus on nonstationarity in parametric linear, parametric nonlinear and nonparametric nonlinear models. In this paper, we consider a partially linear model of the form Yt = X t +g(Vt)+ t, t = 1, · · ·, n, where {Vt} is a sequence of -null recurrent Markov chains, {Xt} is a sequence of either strictly stationary or nonstationary regressors and { t} is a stationary sequence. We propose to estimate both a and g(·) semiparametrically. We then show that the proposed estimator of is still asymptotically normal with the same rate as for the case of stationary time series. We also establish the asymptotic normality for the nonparametric estimator of the function g(·) and the uniform consistency of the nonparametric estimator. The simulated example is given to show that our theory and method work well in practice.
Author :Torben Gustav Andersen Publisher :Springer Science & Business Media ISBN 13 :3540712976 Total Pages :1045 pages Book Rating :4.5/5 (47 download)
Book Synopsis Handbook of Financial Time Series by : Torben Gustav Andersen
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.
Book Synopsis Microeconometrics by : Steven Durlauf
Download or read book Microeconometrics written by Steven Durlauf and published by Springer. This book was released on 2016-06-07 with total page 365 pages. Available in PDF, EPUB and Kindle. Book excerpt: Specially selected from The New Palgrave Dictionary of Economics 2nd edition, each article within this compendium covers the fundamental themes within the discipline and is written by a leading practitioner in the field. A handy reference tool.
Book Synopsis Semiparametric and Nonparametric Estimation for Dynamic Quantile Regression Models by : Xiaoping Xu
Download or read book Semiparametric and Nonparametric Estimation for Dynamic Quantile Regression Models written by Xiaoping Xu and published by . This book was released on 2005 with total page 210 pages. Available in PDF, EPUB and Kindle. Book excerpt: Since quantile regression was proposed by Koenker and Bassett (1978), recently, it has been successfully applied to various applied fields such as finance and economics as well as biology. In this dissertation, I consider two classes of quantile regression models for dynamic time series data: nonparametric and semiparametric quantile regression models with a functional or partially functional coefficient structure. Firstly, I develop an estimate procedure to estimate functional coefficients by using local linear approximations under dynamic time series data. I derive the local Bahadur representation of the local linear estimator under a-mixing conditions and establish the consistency and the asymptotic normality of the estimator. Secondly, I derive the [the square root of]n-consistency estimator for parameters in semi-parametric model by using average method for [beta]-mixing time series. Also, I establish the consistency and the asymptotic normality of the proposed estimator. The programming involved in the proposed estimation procedures is relatively simple and it can be modified with few efforts from the existing programs for the linear quantile model. A comparison of the local linear quantile estimator with other methods is presented. Simulation studies are carried out to illustrate the performance of the estimates. An empirical application of the model to the exchange rate time series data and the well-known Boston house price data further demonstrates the potential of the proposed modeling procedures.
Book Synopsis Broadband Semi-Parametric Estimation of Long-Memory Time Series by Fractional Exponential Models by : Masaki Narukawa
Download or read book Broadband Semi-Parametric Estimation of Long-Memory Time Series by Fractional Exponential Models written by Masaki Narukawa and published by . This book was released on 2011 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: This article proposes broadband semi-parametric estimation of a long-memory parameter by fractional exponential (FEXP) models. We construct the truncated Whittle likelihood based on FEXP models in a semi-parametric setting to estimate the parameter and show that the proposed estimator is more efficient than the FEXP estimator by Moulines and Soulier (1999) in linear processes. A Monte Carlo simulation suggests that the proposed estimation is more preferable than the existing broadband semi-parametric estimation.
Book Synopsis Shrinkage Estimation of Semiparametric Multiplicative Error Models by : Christian T. Brownlees
Download or read book Shrinkage Estimation of Semiparametric Multiplicative Error Models written by Christian T. Brownlees and published by . This book was released on 2009 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: Within models for nonnegative time series, it is common to encounter deterministic components (trends, seasonalities) which can be specified in a flexible form. This work proposes the use of shrinkage type estimation for the parameters of such components. The amount of smoothing to be imposed on the estimates can be chosen using different methodologies: Cross-Validation for dependent data and the recently proposed Focused Information Criterion. We illustrate such a methodology using a simple semiparametric autoregressive conditional duration model that decomposes the conditional expectations of durations into dynamic (parametric) and diurnal (flexible) components. We use a shrinkage estimator that jointly estimates the parameters of the two components and controls the smoothness of the estimated flexible component. The results show that from a forecasting perspective such a procedure outperforms other estimation procedures.
Book Synopsis Essays in Nonlinear Time Series Econometrics by : Niels Haldrup
Download or read book Essays in Nonlinear Time Series Econometrics written by Niels Haldrup and published by OUP Oxford. This book was released on 2014-06-26 with total page 393 pages. Available in PDF, EPUB and Kindle. Book excerpt: This edited collection concerns nonlinear economic relations that involve time. It is divided into four broad themes that all reflect the work and methodology of Professor Timo Teräsvirta, one of the leading scholars in the field of nonlinear time series econometrics. The themes are: Testing for linearity and functional form, specification testing and estimation of nonlinear time series models in the form of smooth transition models, model selection and econometric methodology, and finally applications within the area of financial econometrics. All these research fields include contributions that represent state of the art in econometrics such as testing for neglected nonlinearity in neural network models, time-varying GARCH and smooth transition models, STAR models and common factors in volatility modeling, semi-automatic general to specific model selection for nonlinear dynamic models, high-dimensional data analysis for parametric and semi-parametric regression models with dependent data, commodity price modeling, financial analysts earnings forecasts based on asymmetric loss function, local Gaussian correlation and dependence for asymmetric return dependence, and the use of bootstrap aggregation to improve forecast accuracy. Each chapter represents original scholarly work, and reflects the intellectual impact that Timo Teräsvirta has had and will continue to have, on the profession.
