Download or read book Estimation of the Parameters in Stationary Autoregressive Processes After Hard Limiting written by Benjamin Kedem and published by . This book was released on 1977 with total page 25 pages. Available in PDF, EPUB and Kindle. Book excerpt: The parameters of a stationary AR(p) process are estimated after clipping. This estimation is based in part on the number of certain runs in the binary series. Very little precision is lost due to this quantization but the expected number of arithmetical operations which are saved is at least (p+2)n where counting a run is considered as an operation and n is the series size. (Author).
Download or read book Journal of the American Statistical Association written by and published by . This book was released on 2006 with total page 916 pages. Available in PDF, EPUB and Kindle. Book excerpt: A scientific and educational journal not only for professional statisticians but also for economists, business executives, research directors, government officials, university professors, and others who are seriously interested in the application of statistical methods to practical problems, in the development of more useful methods, and in the improvement of basic statistical data.
Download or read book Parameter Estimation of Nearly Non stationary Autoregressive Processes written by Michiel J.L. de Hoon and published by . This book was released on 1995 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Scientific and Technical Aerospace Reports written by and published by . This book was released on 1994 with total page 892 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Statistical Theory and Method Abstracts written by and published by . This book was released on 2000 with total page 886 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Mathematical Reviews written by and published by . This book was released on 2006 with total page 784 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book TIME SERIES ANALYSIS OF BINARY DATA WORKING PAPER NO 277 written by DANIEL MCRAE KEENAN and published by . This book was released on 1981 with total page 29 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Binary Time Series written by Benjamin Kedem and published by . This book was released on 1980 with total page 282 pages. Available in PDF, EPUB and Kindle. Book excerpt: Basic concepts of stationary processes; Sufficient statistics for binary Markov chains; The distribution of the number of axis-crossing; Upcrossings of a high level by a stationary process; Clipping a gaussian process; Estimation in ar(1) after hard limiting; Estimation in ar(p); Runs and estimates of correlations; Spectral analysis after clipping; Extremes in stationary time series; A central limit (ACL); Prediction in binary data.
Download or read book Journal of the Meteorological Society of Japan written by Nihon Kishō Gakkai and published by . This book was released on 1982 with total page 1480 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Parameter Estimation for Noncausal and Heavy Tailed Autoregressive Processes written by Matthew Calder and published by . This book was released on 1998 with total page 240 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Statistics Subject Indexes from Mathematical Reviews written by American Mathematical Society and published by . This book was released on 1987 with total page 540 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Improving Efficiency and Effectiveness of Dynamic Time Warping in Large Time Series Databases written by Chotirat Ratanamahatana and published by . This book was released on 2005 with total page 378 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Proceedings of the American Control Conference written by and published by . This book was released on 2005 with total page 864 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Estimation of Parameters and Classification of Mixtures of Autoregressive Processes written by Christophe Couvreur and published by . This book was released on 1995 with total page 184 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Current Index to Statistics Applications Methods and Theory written by and published by . This book was released on 1995 with total page 676 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.
Download or read book MIXTURE AUTOREGRESSION W HEAVY written by Po-Ling Kam and published by Open Dissertation Press. This book was released on 2017-01-27 with total page 94 pages. Available in PDF, EPUB and Kindle. Book excerpt: This dissertation, "Mixture Autoregression With Heavy-tailed Conditional Distribution" by Po-ling, Kam, 甘寶玲, was obtained from The University of Hong Kong (Pokfulam, Hong Kong) and is being sold pursuant to Creative Commons: Attribution 3.0 Hong Kong License. The content of this dissertation has not been altered in any way. We have altered the formatting in order to facilitate the ease of printing and reading of the dissertation. All rights not granted by the above license are retained by the author. Abstract: Abstract of thesis entitled MIXTURE AUTOREGRESSION WITH HEAVY-TAILED CONDITIONAL DISTRIBUTION submitted by KAM, Po Ling for the degree of Master of Philosophy at the University of Hong Kong in August 2003 In this thesis, we consider two types of the mixture autoregressive model. The first one is Gaussian mixture autoregressive model (GMAR) which is introduced by Wong and Li (2000). The second one is Student t-type MAR (TMAR) model which is a new model proposed by us. For GMAR model, it consists of a mixture K Gaussian autoregressive compo- nents. There are several properties which make Gaussian MAR model potentially useful in non-linear time series modelling. Firstly, it can be shown that a mixture of a non-stationary AR component with a stationary AR component can result in an overall stationary process. Secondly, the Gaussian MAR model can capture the shape-changing feature in conditional distribution of the time series. Lastly, the Gaussian MAR model can also capture conditional heteroscedasticity (Engle, 1982) which is a common phenomenon in financial time series. Despite the advantages of Gaussian MAR models, there are some limitations iin some real life applications. If densities of some financial time series data are plotted, it can be noticed that the densities tend to be fatter tailed than the normal. Moreover, extreme data are observed more often than those implied by a Gaussian distribution. According to Peel and McLachlan (2000), heavy tails and outliers affect the estimation of means and variances in mixture type models. The applicability of the Gaussian MAR model to financial time series might be questionable. In order to illustrate the problem, we perform several simulation studies to study the estimation of Gaussian MAR model using data generated from heavy tailed distributions. On the other hand, we introduced a new model called Student t-type MAR model. We propose to replace the normal conditional distribution in each com- ponent of the Gaussian MAR model by the Student t distribution. There is a parameter called degree of freedom which can be used to adjust the degree of heavy-tailness of the conditional distributions according to our need. As the de- gree of freedom in a Student t distribution approaches infinity, the distribution approaches normal. Hence, the Gaussian MAR model is a limiting case of the proposed Student t-type MAR model. The parameter estimation of TMAR model can be carried out via the EM al- gorithm (Dempster et al., 1977). The standard errors of the parameter estimates can be computed by the Missing Information Principle (Louis, 1982). For model selection, corrected Bayesian information criteria (BIC ) is adopted. Several simulation studies are preformed to illustrate the importance of correct choice of model when the true data generating process is a Student t-type MAR model. iiWe compare the performance of Gaussian and Student t-type MAR model by some simulation studies and real life examples. Several financial time series are employed to illustrate the usefulness of the Student t-type MAR model. (460 words) iii DOI: 10.5353/th_b2961492 Subjects: Autoregression (Statistics) Distribution (Probability theory) Time-series analysis Gaussian processes Finance - Statistical methods
Download or read book Maximum Likelihood Estimation for Nearly Non Stationary Stable Autoregressive Processes written by Rong-Mao Zhang and published by . This book was released on 2012 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt:
