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Design Adaptive Pointwise Nonparametric Regression Estimation For Recurrent Markov Time Series
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Book Synopsis Design-adaptive Pointwise Nonparametric Regression Estimation for Recurrent Markov Time Series by : Emmanuel Guerre
Download or read book Design-adaptive Pointwise Nonparametric Regression Estimation for Recurrent Markov Time Series written by Emmanuel Guerre and published by . This book was released on 2004 with total page 38 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Handbook of Financial Econometrics by : Yacine Ait-Sahalia
Download or read book Handbook of Financial Econometrics written by Yacine Ait-Sahalia and published by Elsevier. This book was released on 2009-10-19 with total page 809 pages. Available in PDF, EPUB and Kindle. Book excerpt: This collection of original articles—8 years in the making—shines a bright light on recent advances in financial econometrics. From a survey of mathematical and statistical tools for understanding nonlinear Markov processes to an exploration of the time-series evolution of the risk-return tradeoff for stock market investment, noted scholars Yacine Aït-Sahalia and Lars Peter Hansen benchmark the current state of knowledge while contributors build a framework for its growth. Whether in the presence of statistical uncertainty or the proven advantages and limitations of value at risk models, readers will discover that they can set few constraints on the value of this long-awaited volume. Presents a broad survey of current research—from local characterizations of the Markov process dynamics to financial market trading activity Contributors include Nobel Laureate Robert Engle and leading econometricians Offers a clarity of method and explanation unavailable in other financial econometrics collections
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.
Book Synopsis Uniform Consistency for Nonparametric Estimators in Null Recurrent Time Series by : Jiti Gao
Download or read book Uniform Consistency for Nonparametric Estimators in Null Recurrent Time Series written by Jiti Gao and published by . This book was released on 2009 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: This paper establishes several results for uniform convergence of nonparametric kernel density and regression estimates for the case where the time series regressors concerned are nonstationary null- recurrent Markov chains. Under suitable conditions, certain rates of convergence are also established for these estimates. Our results can be viewed as an extension of some well-known uniform consistency results for the stationary time series to the nonstationary time series case.
Book Synopsis Nonparametric Curve Estimation by : Sam Efromovich
Download or read book Nonparametric Curve Estimation written by Sam Efromovich and published by Springer Science & Business Media. This book was released on 1999-08-05 with total page 423 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book gives a systematic, comprehensive, and unified account of modern nonparametric statistics of density estimation, nonparametric regression, filtering signals, and time series analysis. The companion software package, available over the Internet, brings all of the discussed topics into the realm of interactive research. Virtually every claim and development mentioned in the book is illustrated with graphs which are available for the reader to reproduce and modify, making the material fully transparent and allowing for complete interactivity.
Book Synopsis Hidden Markov Models for Time Series by : Walter Zucchini
Download or read book Hidden Markov Models for Time Series written by Walter Zucchini and published by CRC Press. This book was released on 2017-12-19 with total page 370 pages. Available in PDF, EPUB and Kindle. Book excerpt: Hidden Markov Models for Time Series: An Introduction Using R, Second Edition illustrates the great flexibility of hidden Markov models (HMMs) as general-purpose models for time series data. The book provides a broad understanding of the models and their uses. After presenting the basic model formulation, the book covers estimation, forecasting, decoding, prediction, model selection, and Bayesian inference for HMMs. Through examples and applications, the authors describe how to extend and generalize the basic model so that it can be applied in a rich variety of situations. The book demonstrates how HMMs can be applied to a wide range of types of time series: continuous-valued, circular, multivariate, binary, bounded and unbounded counts, and categorical observations. It also discusses how to employ the freely available computing environment R to carry out the computations. Features Presents an accessible overview of HMMs Explores a variety of applications in ecology, finance, epidemiology, climatology, and sociology Includes numerous theoretical and programming exercises Provides most of the analysed data sets online New to the second edition A total of five chapters on extensions, including HMMs for longitudinal data, hidden semi-Markov models and models with continuous-valued state process New case studies on animal movement, rainfall occurrence and capture-recapture data
Book Synopsis Design-adaptive Nonparametric Regression by : Jianqing Fan
Download or read book Design-adaptive Nonparametric Regression written by Jianqing Fan and published by . This book was released on 1991 with total page 19 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Nonparametric Estimation in Null Recurrent Time Series by : Hans Arnfinn Karlsen
Download or read book Nonparametric Estimation in Null Recurrent Time Series written by Hans Arnfinn Karlsen and published by . This book was released on 1998 with total page 58 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Adaptive Estimation in Time Series Regression Models by : Douglas Gardiner Steigerwald
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:
Book Synopsis Local Composite Quantile Regression Smoothing for Harris Recurrent Markov Processes by : Degui Li
Download or read book Local Composite Quantile Regression Smoothing for Harris Recurrent Markov Processes written by Degui Li and published by . This book was released on 2015 with total page 37 pages. Available in PDF, EPUB and Kindle. Book excerpt: In this paper, we study the local polynomial composite quantile regression (CQR) smoothing method for the nonlinear and nonparametric models under the Harris recurrent Markov chain framework. The local polynomial CQR regression method is a robust alternative to the widely-used local polynomial method, and has been well studied in stationary time series. In this paper, we relax the stationarity restriction on the model, and allow that the regressors are generated by a general Harris recurrent Markov process which includes both the stationary (positive recurrent) and nonstationary (null recurrent) cases. Under some mild conditions, we establish the asymptotic theory for the proposed local polynomial CQR estimator of the mean regression function, and show that the convergence rate for the estimator in nonstationary case is slower than that in stationary case. Furthermore, a weighted type local polynomial CQR estimator is provided to improve the estimation efficiency, and a data-driven bandwidth selection is introduced to choose the optimal bandwidth involved in the nonparametric estimators. Finally, we give some numerical studies to examine the finite sample performance of the methodology and theory.
Book Synopsis Adaptive Pointwise Estimation in Time-inhomogeneous Time-series Models by : P. Čižek
Download or read book Adaptive Pointwise Estimation in Time-inhomogeneous Time-series Models written by P. Čižek and published by . This book was released on 2007 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Nonparametric Curve Estimation from Time Series by : Lazlo Gyorfi
Download or read book Nonparametric Curve Estimation from Time Series written by Lazlo Gyorfi and published by . This book was released on 2014-09-01 with total page 168 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Least Squares Estimation and Adaptive Prediction in Non-linear Stochastic Regression Models with Applications to Time Series and Stochastic Systems by : Guangrui Zhu
Download or read book Least Squares Estimation and Adaptive Prediction in Non-linear Stochastic Regression Models with Applications to Time Series and Stochastic Systems written by Guangrui Zhu and published by . This book was released on 1992 with total page 196 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Optimal Pointwise Adaptive Methods in Nonparametric Estimation by : Oleg V. Lepskij
Download or read book Optimal Pointwise Adaptive Methods in Nonparametric Estimation written by Oleg V. Lepskij and published by . This book was released on 1996 with total page 33 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Optimal Designs for Series Estimation in Nonparametric Regression with Correlated Data by : Holger Dette
Download or read book Optimal Designs for Series Estimation in Nonparametric Regression with Correlated Data written by Holger Dette and published by . This book was released on 2018 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Current Index to Statistics, Applications, Methods and Theory by :
Download or read book Current Index to Statistics, Applications, Methods and Theory written by and published by . This book was released on 1999 with total page 948 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.
Book Synopsis Image Processing and Jump Regression Analysis by : Peihua Qiu
Download or read book Image Processing and Jump Regression Analysis written by Peihua Qiu and published by John Wiley & Sons. This book was released on 2005-05-20 with total page 344 pages. Available in PDF, EPUB and Kindle. Book excerpt: The first text to bridge the gap between image processing andjump regression analysis Recent statistical tools developed to estimate jump curves andsurfaces have broad applications, specifically in the area of imageprocessing. Often, significant differences in technicalterminologies make communication between the disciplines of imageprocessing and jump regression analysis difficult. Ineasy-to-understand language, Image Processing and JumpRegression Analysis builds a bridge between the worlds ofcomputer graphics and statistics by addressing both the connectionsand the differences between these two disciplines. The authorprovides a systematic analysis of the methodology behindnonparametric jump regression analysis by outlining procedures thatare easy to use, simple to compute, and have proven statisticaltheory behind them. Key topics include: Conventional smoothing procedures Estimation of jump regression curves Estimation of jump location curves of regression surfaces Jump-preserving surface reconstruction based on localsmoothing Edge detection in image processing Edge-preserving image restoration With mathematical proofs kept to a minimum, this book isuniquely accessible to a broad readership. It may be used as aprimary text in nonparametric regression analysis and imageprocessing as well as a reference guide for academicians andindustry professionals focused on image processing or curve/surfaceestimation.
