Cotrending: testing for common deterministic trends in varying means model
DOI10.1016/j.jmva.2021.104825zbMath1480.62107OpenAlexW3198398156MaRDI QIDQ2057835
Marie-Christine Düker, Vladas Pipiras, Raanju R. Sundararajan
Publication date: 7 December 2021
Published in: Journal of Multivariate Analysis (Search for Journal in Brave)
Full work available at URL: https://doi.org/10.1016/j.jmva.2021.104825
asymptotic normalityprincipal component analysistestingcointegrationcotrending dimension and spacematrix rank and nullityvarying means
Factor analysis and principal components; correspondence analysis (62H25) Nonparametric hypothesis testing (62G10) Time series, auto-correlation, regression, etc. in statistics (GARCH) (62M10) Asymptotic distribution theory in statistics (62E20) Hypothesis testing in multivariate analysis (62H15)
Uses Software
Cites Work
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Generalized reduced rank tests using the singular value decomposition
- Time series analysis: Methods and applications
- Factor modeling for high-dimensional time series: inference for the number of factors
- Statistical analysis of cointegration vectors
- Asymptotic inference for eigenvectors
- On Wielandt's inequality and its application to the asymptotic distribution of the eigenvalues of a random symmetric matrix
- Time series: theory and methods.
- Principal component analysis.
- Stationary subspace analysis of nonstationary covariance processes: eigenstructure description and testing
- Nonparametric quasi-maximum likelihood estimation for Gaussian locally stationary processes
- ON RANK ESTIMATION IN SYMMETRIC MATRICES: THE CASE OF INDEFINITE MATRIX ESTIMATORS
- Multiple Time Series Regression with Integrated Processes
- Testing the Rank and Definiteness of Estimated Matrices With Applications to Factor, State-Space and ARMA Models
- On the Asymptotic Properties of LDU-Based Tests of the Rank of a Matrix
- TESTS OF RANK
- Testing the rank of the Hankel covariance matrix: a statistical approach
- Stationary subspace analysis of nonstationary processes
- Co-Integration and Error Correction: Representation, Estimation, and Testing
- Unit Roots, Cointegration, and Structural Change
- A useful variant of the Davis–Kahan theorem for statisticians
- Asymptotic Normality of Sample Quantiles for $m$-Dependent Processes
- SLEX Analysis of Multivariate Nonstationary Time Series
- Estimating Linear Restrictions on Regression Coefficients for Multivariate Normal Distributions
- Estimation and Hypothesis Testing of Cointegration Vectors in Gaussian Vector Autoregressive Models
This page was built for publication: Cotrending: testing for common deterministic trends in varying means model