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Book Asymptotic Properties of the Autoregressive Spectral Estimator

Download or read book Asymptotic Properties of the Autoregressive Spectral Estimator written by Ralph Eugene Kromer and published by Scholarly Press. This book was released on 1969 with total page 408 pages. Available in PDF, EPUB and Kindle. Book excerpt: The thesis is concerned with the theory of autoregressive spectral estimators for the spectrum of a normal, stationary, zero-mean time series with a 'sufficiently smooth, ' strictly positive and bounded spectral density. (Author).

Book Asymptotic Statistics for Spectral Estimation Problems

Download or read book Asymptotic Statistics for Spectral Estimation Problems written by Donald Francis Gingras and published by . This book was released on 1986 with total page 172 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Book Asymptotic Properties of Some Estimators in Moving Average Models

Download or read book Asymptotic Properties of Some Estimators in Moving Average Models written by Stanford University. Department of Statistics and published by . This book was released on 1975 with total page 318 pages. Available in PDF, EPUB and Kindle. Book excerpt: The author considers estimation procedures for the moving average model of order q. Walker's method uses k sample autocovariances (k> or = q). Assume that k depends on T in such a way that k nears infinity as T nears infinity. The estimates are consistent, asymptotically normal and asymptotically efficient if k = k (T) dominates log T and is dominated by (T sub 1/2). The approach in proving these theorems involves obtaining an explicit form for the components of the inverse of a symmetric matrix with equal elements along its five central diagonals, and zeroes elsewhere. The asymptotic normality follows from a central limit theorem for normalized sums of random variables that are dependent of order k, where k tends to infinity with T. An alternative form of the estimator facilitates the calculations and the analysis of the role of k, without changing the asymptotic properties.

Book On a Spectral Estimate Obtained by an Autoregressive Model Fitting

Download or read book On a Spectral Estimate Obtained by an Autoregressive Model Fitting written by STANFORD UNIV CALIF DEPT OF STATISTICS. and published by . This book was released on 1976 with total page 38 pages. Available in PDF, EPUB and Kindle. Book excerpt: A stationary Gaussian process X(t) is considered which is expressed as an autoregressive process of infinite order. An autoregressive model of finite order K is fitted for this process and an estimate for the spectral density is obtained. The consistency and the asymptotic normality of this estimate under some conditions are shown. This estimate has an asymptotically efficient property in a sense under some conditions which are stronger than Berk's conditions.

Book Parameter Estimation and Hypothesis Testing in Spectral Analysis of Stationary Time Series

Download or read book Parameter Estimation and Hypothesis Testing in Spectral Analysis of Stationary Time Series written by K. Dzhaparidze and published by Springer Science & Business Media. This book was released on 2012-12-06 with total page 331 pages. Available in PDF, EPUB and Kindle. Book excerpt: . . ) (under the assumption that the spectral density exists). For this reason, a vast amount of periodical and monographic literature is devoted to the nonparametric statistical problem of estimating the function tJ( T) and especially that of leA) (see, for example, the books [4,21,22,26,56,77,137,139,140,]). However, the empirical value t;; of the spectral density I obtained by applying a certain statistical procedure to the observed values of the variables Xl' . . . , X , usually depends in n a complicated manner on the cyclic frequency). . This fact often presents difficulties in applying the obtained estimate t;; of the function I to the solution of specific problems rela ted to the process X . Theref ore, in practice, the t obtained values of the estimator t;; (or an estimator of the covariance function tJ~( T» are almost always "smoothed," i. e. , are approximated by values of a certain sufficiently simple function 1 = 1

Book Higher Order Asymptotic Theory for Time Series Analysis

Download or read book Higher Order Asymptotic Theory for Time Series Analysis written by Masanobu Taniguchi and published by Springer Science & Business Media. This book was released on 2012-12-06 with total page 169 pages. Available in PDF, EPUB and Kindle. Book excerpt: The initial basis of this book was a series of my research papers, that I listed in References. I have many people to thank for the book's existence. Regarding higher order asymptotic efficiency I thank Professors Kei Takeuchi and M. Akahira for their many comments. I used their concept of efficiency for time series analysis. During the summer of 1983, I had an opportunity to visit The Australian National University, and could elucidate the third-order asymptotics of some estimators. I express my sincere thanks to Professor E.J. Hannan for his warmest encouragement and kindness. Multivariate time series analysis seems an important topic. In 1986 I visited Center for Mul tivariate Analysis, University of Pittsburgh. I received a lot of impact from multivariate analysis, and applied many multivariate methods to the higher order asymptotic theory of vector time series. I am very grateful to the late Professor P.R. Krishnaiah for his cooperation and kindness. In Japan my research was mainly performed in Hiroshima University. There is a research group of statisticians who are interested in the asymptotic expansions in statistics. Throughout this book I often used the asymptotic expansion techniques. I thank all the members of this group, especially Professors Y. Fujikoshi and K. Maekawa foItheir helpful discussion. When I was a student of Osaka University I learned multivariate analysis and time series analysis from Professors Masashi Okamoto and T. Nagai, respectively. It is a pleasure to thank them for giving me much of research background.

Book Spectral Analysis for Physical Applications

Download or read book Spectral Analysis for Physical Applications written by Donald B. Percival and published by Cambridge University Press. This book was released on 1993-06-03 with total page 616 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book is an up-to-date introduction to univariate spectral analysis at the graduate level, which reflects a new scientific awareness of spectral complexity, as well as the widespread use of spectral analysis on digital computers with considerable computational power. The text provides theoretical and computational guidance on the available techniques, emphasizing those that work in practice. Spectral analysis finds extensive application in the analysis of data arising in many of the physical sciences, ranging from electrical engineering and physics to geophysics and oceanography. A valuable feature of the text is that many examples are given showing the application of spectral analysis to real data sets. Special emphasis is placed on the multitaper technique, because of its practical success in handling spectra with intricate structure, and its power to handle data with or without spectral lines. The text contains a large number of exercises, together with an extensive bibliography.

Book Spectral Analysis for Univariate Time Series

Download or read book Spectral Analysis for Univariate Time Series written by Donald B. Percival and published by Cambridge University Press. This book was released on 2020-03-19 with total page 718 pages. Available in PDF, EPUB and Kindle. Book excerpt: Spectral analysis is widely used to interpret time series collected in diverse areas. This book covers the statistical theory behind spectral analysis and provides data analysts with the tools needed to transition theory into practice. Actual time series from oceanography, metrology, atmospheric science and other areas are used in running examples throughout, to allow clear comparison of how the various methods address questions of interest. All major nonparametric and parametric spectral analysis techniques are discussed, with emphasis on the multitaper method, both in its original formulation involving Slepian tapers and in a popular alternative using sinusoidal tapers. The authors take a unified approach to quantifying the bandwidth of different nonparametric spectral estimates. An extensive set of exercises allows readers to test their understanding of theory and practical analysis. The time series used as examples and R language code for recreating the analyses of the series are available from the book's website.

Book Asymptotic Properties of Extended Yule Walker Estimates of the AR Parameters of an ARMA Autoregressive Moving Average

Download or read book Asymptotic Properties of Extended Yule Walker Estimates of the AR Parameters of an ARMA Autoregressive Moving Average written by D. F. Gingras and published by . This book was released on 1983 with total page 30 pages. Available in PDF, EPUB and Kindle. Book excerpt: The extended Yule-Walker equations are used to estimate the autoregressive parameters of an autoregressive moving-average time series. The asymptotic statistical properties of these estimates are derived. It is shown that they are asymptotically unbiased and normal; the covariance matrix of the limit distribution is calculated. The special case of estimating the autoregressive parameters of a noise corrupted autoregressive series is also treated. (Author).

Book Statistical Analysis of Autoregressive Spectral Estimates for Noise Corrupted Autoregressive Series

Download or read book Statistical Analysis of Autoregressive Spectral Estimates for Noise Corrupted Autoregressive Series written by D. F. Gingras and published by . This book was released on 1984 with total page 30 pages. Available in PDF, EPUB and Kindle. Book excerpt: Estimation of the spectral density function for a gaussian distributed autoregressive series from observations of a noise corrupted version is considered when the order of the autoregressive series is assumed to be known. When the high-order Yule-Walker equation estimates of the autoregressive parameters are used to form the spectral density estimate, it is shown that the estimate is weakly consistent and asymptotically normal with zero mean and finite variance. A closed form expression for the asymptotic variance is developed and the expression is analyzed for the first-order AR series case. (Author).

Book Nonlinear Methods of Spectral Analysis

Download or read book Nonlinear Methods of Spectral Analysis written by S. Haykin and published by Springer Science & Business Media. This book was released on 2006-01-21 with total page 276 pages. Available in PDF, EPUB and Kindle. Book excerpt: With contributions by numerous experts