Identifying Cointegration by Eigenanalysis
نویسندگان
چکیده
منابع مشابه
Testing and Identifying Structural Change in a Cointegration Regression Testing and Identifying Structural Change in a Cointegration Regression
Testing and Identifying Structural Change in a Cointegration Regression Jae-Young Kim 1 Department of Economics SUNY-Albany Albany, NY 12222 January 1996 Abstract This paper studies how to detect structural change in a cointegrated system under the situation of the change period being unknown. A general type of structural change is considered that causes the failure of an initial cointegration ...
متن کاملEmploying Symmetry Constraints for Improved Frequency Estimation by Eigenanalysis Methods
The problem of extracting sinusoid signals from noisy observations made at equally spaced times is considered. Eigenanalysis methods, such as Pisarenko’s method and the extended Prony method, find the eigenvector with minimum eigenvalue of a suitably chosen matrix, and then obtain the complex sinusoids as the roots of the polynomial which has the components of the eigenvector as coefficients. F...
متن کاملGradient Eigenanalysis Onnested Finite
The eecient computation of the leftmost eigenpairs of the generalized symmetric eigenproblem Ax = Bx by a de-ation accelerated conjugate gradient (DACG) method may be enhanced by an improved estimate of the initial eigenvectors obtained with a multigrid (MG) type approach. The DACG algorithm essentially optimizes the Rayleigh quotient in subspaces of decreasing size B-orthogonal to the eigenvec...
متن کاملPopulation Structure and Eigenanalysis
Current methods for inferring population structure from genetic data do not provide formal significance tests for population differentiation. We discuss an approach to studying population structure (principal components analysis) that was first applied to genetic data by Cavalli-Sforza and colleagues. We place the method on a solid statistical footing, using results from modern statistics to de...
متن کاملIncremental Eigenanalysis for Classification
Eigenspace models are a convenient way to represent sets of observations with widespread applications, including classification. In this paper we describe a new constructive method for incrementally adding observations to an eigenspace model. Our contribution is to explicitly account for a change in origin as well as a change in the number of eigenvectors needed in the basis set. No other metho...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: Journal of the American Statistical Association
سال: 2018
ISSN: 0162-1459,1537-274X
DOI: 10.1080/01621459.2018.1458620