Download or read book Kernel Estimation for the Mode and Quantiles of Time Series written by Raid Salha and published by LAP Lambert Academic Publishing. This book was released on 2011-12 with total page 168 pages. Available in PDF, EPUB and Kindle. Book excerpt: In this book, we are interested in the area of nonparametric prediction of time series. Therefore, the relationship between a current observation and past observations is considered, where the conditional density function plays an important role. Two aspects of the conditional probability density function, the mode and the quantiles are studied. Firstly, in the case of the mode, we state some sufficient conditions under which the joint kernel estimator of the conditional mode taken jointly at a finite number of distinct points is asymptotically normally distributed. Secondly, a new multivariate estimator for a multivariate conditional quantile is proposed, based on the reweighted Nadaraya-Watson estimator for the conditional cumulative distribution function. The efficiency of the proposed estimator is tested by giving two applications. The book also, involves a review which covers in sufficient details the up to date literature on kernel estimation for conditional mode and quantiles.
Download or read book Time Series Model Identification by Estimating Information Memory and Quantiles written by Emanuel Parzen and published by . This book was released on 1983 with total page 72 pages. Available in PDF, EPUB and Kindle. Book excerpt: This paper applies techniques of Quantile Data Analysis to non-parametrically analyze time series functions such as the sample spectral density, sample correlations, and sample partial correlations. The aim is to identify the memory type of an observed time series, and thus to identify parametric time domain models that fit an observed time series. Time series models are usually tested for adequacy by testing if their residuals are white noise. It is proposed that an additional criterion of fit for a parametric model is that it have the non-parametrically estimated memory characteristics. An important diagnostic of memory is the index delta of regular variation of a spectral density; estimators are proposed for delta. Interpretations of the new quantile criteria are developed through cataloging their values for representation time series. The model identification procedures proposed are illustrated by analysis of long memory series simulated by Granger and Joyeux, and the airline model of Box and Jenkins. (Author).
Download or read book Functional Estimation For Density Regression Models And Processes Second Edition written by Odile Pons and published by World Scientific. This book was released on 2023-09-22 with total page 259 pages. Available in PDF, EPUB and Kindle. Book excerpt: Nonparametric kernel estimators apply to the statistical analysis of independent or dependent sequences of random variables and for samples of continuous or discrete processes. The optimization of these procedures is based on the choice of a bandwidth that minimizes an estimation error and the weak convergence of the estimators is proved. This book introduces new mathematical results on statistical methods for the density and regression functions presented in the mathematical literature and for functions defining more complex models such as the models for the intensity of point processes, for the drift and variance of auto-regressive diffusions and the single-index regression models.This second edition presents minimax properties with Lp risks, for a real p larger than one, and optimal convergence results for new kernel estimators of function defining processes: models for multidimensional variables, periodic intensities, estimators of the distribution functions of censored and truncated variables, estimation in frailty models, estimators for time dependent diffusions, for spatial diffusions and for diffusions with stochastic volatility.
Download or read book Empirical Likelihood and Quantile Methods for Time Series written by Yan Liu and published by . This book was released on 2018 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: This book integrates the fundamentals of asymptotic theory of statistical inference for time series under nonstandard settings, e.g., infinite variance processes, not only from the point of view of efficiency but also from that of robustness and optimality by minimizing prediction error. This is the first book to consider the generalized empirical likelihood applied to time series models in frequency domain and also the estimation motivated by minimizing quantile prediction error without assumption of true model. It provides the reader with a new horizon for understanding the prediction problem that occurs in time series modeling and a contemporary approach of hypothesis testing by the generalized empirical likelihood method. Nonparametric aspects of the methods proposed in this book also satisfactorily address economic and financial problems without imposing redundantly strong restrictions on the model, which has been true until now. Dealing with infinite variance processes makes analysis of economic and financial data more accurate under the existing results from the demonstrative research. The scope of applications, however, is expected to apply to much broader academic fields. The methods are also sufficiently flexible in that they represent an advanced and unified development of prediction form including multiple-point extrapolation, interpolation, and other incomplete past forecastings. Consequently, they lead readers to a good combination of efficient and robust estimate and test, and discriminate pivotal quantities contained in realistic time series models.
Download or read book Recent Advances and Trends in Nonparametric Statistics written by M.G. Akritas and published by Elsevier. This book was released on 2003-10-31 with total page 524 pages. Available in PDF, EPUB and Kindle. Book excerpt: The advent of high-speed, affordable computers in the last two decades has given a new boost to the nonparametric way of thinking. Classical nonparametric procedures, such as function smoothing, suddenly lost their abstract flavour as they became practically implementable. In addition, many previously unthinkable possibilities became mainstream; prime examples include the bootstrap and resampling methods, wavelets and nonlinear smoothers, graphical methods, data mining, bioinformatics, as well as the more recent algorithmic approaches such as bagging and boosting. This volume is a collection of short articles - most of which having a review component - describing the state-of-the art of Nonparametric Statistics at the beginning of a new millennium. Key features: . algorithic approaches . wavelets and nonlinear smoothers . graphical methods and data mining . biostatistics and bioinformatics . bagging and boosting . support vector machines . resampling methods
Download or read book On the Estimation of Time series Quantiles Using Smoothed Order Statistics written by Gélinas, R. (René) and published by Québec : Faculté des sciences de l'administration, Université Laval. This book was released on 1991 with total page 25 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Time Series Analysis Methods and Applications written by Tata Subba Rao and published by Elsevier. This book was released on 2012-06-26 with total page 778 pages. Available in PDF, EPUB and Kindle. Book excerpt: 'Handbook of Statistics' is a series of self-contained reference books. Each volume is devoted to a particular topic in statistics, with volume 30 dealing with time series.
Download or read book Time Series Analysis Methods and Applications written by and published by Elsevier. This book was released on 2012-05-18 with total page 777 pages. Available in PDF, EPUB and Kindle. Book excerpt: The field of statistics not only affects all areas of scientific activity, but also many other matters such as public policy. It is branching rapidly into so many different subjects that a series of handbooks is the only way of comprehensively presenting the various aspects of statistical methodology, applications, and recent developments.The Handbook of Statistics is a series of self-contained reference books. Each volume is devoted to a particular topic in statistics, with Volume 30 dealing with time series. The series is addressed to the entire community of statisticians and scientists in various disciplines who use statistical methodology in their work. At the same time, special emphasis is placed on applications-oriented techniques, with the applied statistician in mind as the primary audience. - Comprehensively presents the various aspects of statistical methodology - Discusses a wide variety of diverse applications and recent developments - Contributors are internationally renowened experts in their respective areas
Download or read book Multivariate Nonparametric Regression and Visualization written by Jussi Sakari Klemelä and published by John Wiley & Sons. This book was released on 2014-05-05 with total page 317 pages. Available in PDF, EPUB and Kindle. Book excerpt: A modern approach to statistical learning and its applications through visualization methods With a unique and innovative presentation, Multivariate Nonparametric Regression and Visualization provides readers with the core statistical concepts to obtain complete and accurate predictions when given a set of data. Focusing on nonparametric methods to adapt to the multiple types of data generating mechanisms, the book begins with an overview of classification and regression. The book then introduces and examines various tested and proven visualization techniques for learning samples and functions. Multivariate Nonparametric Regression and Visualization identifies risk management, portfolio selection, and option pricing as the main areas in which statistical methods may be implemented in quantitative finance. The book provides coverage of key statistical areas including linear methods, kernel methods, additive models and trees, boosting, support vector machines, and nearest neighbor methods. Exploring the additional applications of nonparametric and semiparametric methods, Multivariate Nonparametric Regression and Visualization features: An extensive appendix with R-package training material to encourage duplication and modification of the presented computations and research Multiple examples to demonstrate the applications in the field of finance Sections with formal definitions of the various applied methods for readers to utilize throughout the book Multivariate Nonparametric Regression and Visualization is an ideal textbook for upper-undergraduate and graduate-level courses on nonparametric function estimation, advanced topics in statistics, and quantitative finance. The book is also an excellent reference for practitioners who apply statistical methods in quantitative finance.
Download or read book Handbook of Multilevel Analysis written by Jan Deleeuw and published by Springer Science & Business Media. This book was released on 2007-12-26 with total page 498 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book presents the state of the art in multilevel analysis, with an emphasis on more advanced topics. These topics are discussed conceptually, analyzed mathematically, and illustrated by empirical examples. Multilevel analysis is the statistical analysis of hierarchically and non-hierarchically nested data. The simplest example is clustered data, such as a sample of students clustered within schools. Multilevel data are especially prevalent in the social and behavioral sciences and in the biomedical sciences. The chapter authors are all leading experts in the field. Given the omnipresence of multilevel data in the social, behavioral, and biomedical sciences, this book is essential for empirical researchers in these fields.
Download or read book Nonparametric Functional Data Analysis written by Frédéric Ferraty and published by Springer Science & Business Media. This book was released on 2006-11-22 with total page 260 pages. Available in PDF, EPUB and Kindle. Book excerpt: Modern apparatuses allow us to collect samples of functional data, mainly curves but also images. On the other hand, nonparametric statistics produces useful tools for standard data exploration. This book links these two fields of modern statistics by explaining how functional data can be studied through parameter-free statistical ideas. At the same time it shows how functional data can be studied through parameter-free statistical ideas, and offers an original presentation of new nonparametric statistical methods for functional data analysis.
Download or read book Forecast Verification written by Ian T. Jolliffe and published by John Wiley & Sons. This book was released on 2003-08-01 with total page 257 pages. Available in PDF, EPUB and Kindle. Book excerpt: This handy reference introduces the subject of forecastverification and provides a review of the basic concepts,discussing different types of data that may be forecast. Each chapter covers a different type of predicted quantity(predictand), then looks at some of the relationships betweeneconomic value and skill scores, before moving on to review the keyconcepts and summarise aspects of forecast verification thatreceive the most attention in other disciplines. The book concludes with a discussion on the most importanttopics in the field that are the subject of current research orthat would benefit from future research. An easy to read guide of current techniques with real life casestudies An up-to-date and practical introduction to the differenttechniques and an examination of their strengths andweaknesses Practical advice given by some of the world?s leadingforecasting experts Case studies and illustrations of actual verification and itsinterpretation Comprehensive glossary and consistent statistical andmathematical definition of commonly used terms
Download or read book Bayesian Methods Applied to Time Series Data written by Thomas B. Fomby and published by JAI Press(NY). This book was released on 1996 with total page 302 pages. Available in PDF, EPUB and Kindle. Book excerpt: This 11th volume in the series discusses a variety of topics in the field of advances in econometrics.
Download or read book Quantile Processes with Statistical Applications written by Miklos Csorgo and published by SIAM. This book was released on 1983-01-01 with total page 169 pages. Available in PDF, EPUB and Kindle. Book excerpt: Provides a comprehensive theory of the approximations of quantile processes in light of recent advances, as well as some of their statistical applications.
Download or read book Asymptotics in Statistics and Probability written by Madan L. Puri and published by Walter de Gruyter GmbH & Co KG. This book was released on 2018-11-05 with total page 456 pages. Available in PDF, EPUB and Kindle. Book excerpt: No detailed description available for "Asymptotics in Statistics and Probability".
Download or read book Conference Proceedings of the 2023 3rd International Joint Conference on Energy Electrical and Power Engineering written by Cungang Hu and published by Springer Nature. This book was released on with total page 822 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Nonparametric Estimation of Conditional Quantile Function written by Ashis Kumar Gangopadhyay and published by . This book was released on 1987 with total page 152 pages. Available in PDF, EPUB and Kindle. Book excerpt:
