Download or read book Autoregressive Spectral Estimation and Functional Inference written by Emanuel Parzen and published by . This book was released on 1982 with total page 15 pages. Available in PDF, EPUB and Kindle. Book excerpt: Functions used to describe the probability distributions of time series (both Gaussian and non-Gaussian) are introduced. The concept of type of a time series is defined. Autoregressive spectral densities are defined. Order determining criteria are motivated. through the concept of model identification by estimating information. An approach to empirical spectral analysis is suggested. (Author).
Download or read book Scientific and Technical Aerospace Reports written by and published by . This book was released on 1994 with total page 1038 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Spectral analysis methods for noisy sampled data systems written by Steve F. Russell and published by Steve F. Russell. This book was released on 1978-08-15 with total page 500 pages. Available in PDF, EPUB and Kindle. Book excerpt: This dissertation covers both the theory and practice of estimating the spectrum of signals in noise using digital data. The theory of describing some of the signal processing concepts for digital data are given and various spectral estimation methods are given. The theory of MEM is described in detail using approaches from estimation theory, communication theory, and statistics. The work was intended to give researchers the theory and practice of practical means of spectral estimation using communications or scientific data. The Maximum Entropy Method by John Parker Burg is explained from what was known in 1974-75. KEY WORDS: Calculus-of-Variations, Data Systems, Noise , Spectrum Analysis, Time Series Analysis, Autocorrelation, Computer Programs, Data Windowing, Ergodic Process, Maximum Entropy Method (MEM, Fourier Transformation, Optimum Order of Estimation, Sampling, Spectral Resolution, Statistical Significance Test, Systems Analysis, Wiener-Khinchine Theorem. From The Smithsonian/NASA Astrophysics Data System -- The practical aspects of spectral analysis are contrasted with the mathematical theory. Treatment is limited to ergodic processes and emphasizes data window and noise effects. The Discrete Fourier Transform (DFT) and Maximum Entropy Method (MEM) are covered extensively both in theory and application with FORTRAN programs and many examples being provided. Several of the chapters are tutorial and discuss the important topics of sampling theory and system analysis. Topics on MEM include a complete calculus-of-variations solution, relationship between MEM and the Wiener-Khinchine relations, spectral resolution, and choosing the optimum order of the estimation. DFT leakage effects are modeled. A statistical significance test was developed to determine the realness of a spectral component. Keywords: Data Systems, Noise (Sound), Spectrum Analysis, Time Series Analysis, Autocorrelation, Computer Programs, Ergodic Process, Fourier Transformation, Sampling, Systems Analysis [less]
Download or read book The Spectral Analysis of Time Series written by L. H. Koopmans and published by Academic Press. This book was released on 2014-05-12 with total page 383 pages. Available in PDF, EPUB and Kindle. Book excerpt: The Spectral Analysis of Time Series describes the techniques and theory of the frequency domain analysis of time series. The book discusses the physical processes and the basic features of models of time series. The central feature of all models is the existence of a spectrum by which the time series is decomposed into a linear combination of sines and cosines. The investigator can used Fourier decompositions or other kinds of spectrals in time series analysis. The text explains the Wiener theory of spectral analysis, the spectral representation for weakly stationary stochastic processes, and the real spectral representation. The book also discusses sampling, aliasing, discrete-time models, linear filters that have general properties with applications to continuous-time processes, and the applications of multivariate spectral models. The text describes finite parameter models, the distribution theory of spectral estimates with applications to statistical inference, as well as sampling properties of spectral estimates, experimental design, and spectral computations. The book is intended either as a textbook or for individual reading for one-semester or two-quarter course for students of time series analysis users. It is also suitable for mathematicians or professors of calculus, statistics, and advanced mathematics.
Download or read book Modern Spectral Estimation written by Steven M. Kay and published by . This book was released on 1988 with total page 574 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Autoregressive Model Based Spectral Analysis with Application to EEG written by G. Florian and published by . This book was released on 1994 with total page 15 pages. Available in PDF, EPUB and Kindle. Book excerpt: Abstract: "A parametric approach to spectral analysis, bypassing numerical Fourier transformation, is presented. Based on fitting autoregressive models, the estimated power spectral density (power spectrum) is derived as a function of the estimated model parameters. In addition, a representation of the autocovariance function of an autoregressive process is developed. Its Fourier transformation is derived, giving a decomposition of the spectral density function in terms of additive components, each corresponding to a certain frequency. For parameter estimation the Durbin-Levinson algorithm is presented. The problem of order selection is discussed. In section 2 the methods are applied to EEG data. Results obtained using an automatic approach to order selection are compared to results based on subjective order selection."
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).
Download or read book Technical Abstract Bulletin written by and published by . This book was released on 1980 with total page 196 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Spectral Analysis by Discrete and Continuous Autoregressive Moving Average Models written by Appasaheb Ningappa Madiwale and published by . This book was released on 1978 with total page 376 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Autoregressive Model Inference in Finite Samples written by Hans Einar Wensink and published by . This book was released on 1996 with total page 148 pages. Available in PDF, EPUB and Kindle. Book excerpt:
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
Download or read book Spectral Analysis and Its Applications written by Gwilym M. Jenkins and published by Emerson Adams PressInc. This book was released on 1968 with total page 525 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Autoregressive Spectral Averaging Estimator written by Chu-An Liu and published by . This book was released on 2017 with total page 25 pages. Available in PDF, EPUB and Kindle. Book excerpt: This paper considers model averaging in spectral density estimation. We construct the spectral density function by averaging the autoregressive coefficients from all potential autoregressive models and investigate the autoregressive spectral averaging estimator using weights that minimize the Mallows and jackknife criteria. We extend the consistency of the autoregressive spectral estimator in Berk (1974) to the autoregressive spectral averaging estimator under a condition that imposes a restriction on the relationship between the model weights and autoregressive coefficients. Simulation studies show that the autoregressive spectral averaging estimator compares favorably with the AIC and BIC model selection estimators, and the bias of the averaging estimator approaches zero as the sample size increases.
Download or read book Automatic Autocorrelation and Spectral Analysis written by Piet M. T. Broersen and published by Springer Science & Business Media. This book was released on 2006-04-20 with total page 301 pages. Available in PDF, EPUB and Kindle. Book excerpt: Spectral analysis requires subjective decisions which influence the final estimate and mean that different analysts can obtain different results from the same stationary stochastic observations. Statistical signal processing can overcome this difficulty, producing a unique solution for any set of observations but that is only acceptable if it is close to the best attainable accuracy for most types of stationary data. This book describes a method which fulfils the above near-optimal-solution criterion, taking advantage of greater computing power and robust algorithms to produce enough candidate models to be sure of providing a suitable candidate for given data.
Download or read book Spectral Analysis of Time series Data written by Rebecca M. Warner and published by Guilford Press. This book was released on 1998-05-22 with total page 244 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book provides a thorough introduction to methods for detecting and describing cyclic patterns in time-series data. It is written both for researchers and students new to the area and for those who have already collected time-series data but wish to learn new ways of understanding and presenting them. Facilitating the interpretation of observations of behavior, physiology, mood, perceptual threshold, social indicator variables, and other responses, the book focuses on practical applications and requires much less mathematical background than most comparable texts. Using real data sets and currently available software (SPSS for Windows), the author employs extensive examples to clarify key concepts. Topics covered include research design issues, preliminary data screening, identification and description of cycles, summary of results across time series, and assessment of relations between time series. Also considered are theoretical questions, problems of interpretation, and potential sources of artifact.
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).
Download or read book The Spectral Analysis of Time Series written by Lambert Herman Koopmans and published by . This book was released on 1974 with total page 390 pages. Available in PDF, EPUB and Kindle. Book excerpt: The Spectral Analysis of Time Series ...
