Moderate Deviation Principles for Empirical Covariance in the Neighbourhood of the Unit Root
From MaRDI portal
Publication:5177960
DOI10.1111/sjos.12104zbMath1376.60052OpenAlexW1574119158MaRDI QIDQ5177960
Guangyu Yang, Yu Miao, Yan-Ling Wang
Publication date: 9 March 2015
Published in: Scandinavian Journal of Statistics (Search for Journal in Brave)
Full work available at URL: https://doi.org/10.1111/sjos.12104
Time series, auto-correlation, regression, etc. in statistics (GARCH) (62M10) Large deviations (60F10)
Related Items
Limit theory for moderate deviations from a unit root with a break in variance, Asymptotic inference of least absolute deviation estimation for AR(1) processes, Deviation inequalities and Cramér-type moderate deviations for the explosive autoregressive process, Asymptotic properties of the M-estimation for an AR(1) process with a general autoregressive coefficient, Least absolute deviation estimation for AR(1) processes with roots close to unity, Consistency and asymptotic normality in a class of nearly unstable processes, Moderate deviations for the mildly stationary autoregressive model with dependent errors, Moderate deviation principle for \(m\)-dependent random variables, Moderate deviations in a class of stable but nearly unstable processes, Asymptotic distribution with random indices for linear processes, Almost sure central limit theorems for m-dependent random variables
Cites Work
- Unnamed Item
- Limit theory for moderate deviations from a unit root
- Moderate deviation principle for autoregressive processes
- A moderate deviation principle for \(m\)-dependent random variables with unbounded \(m\)
- Asymptotic inference for nearly nonstationary AR(1) processes
- Large deviations for stationary Gaussian processes
- Moderate deviations for stable Markov chains and regression models
- Large deviations for quadratic functionals of Gaussian processes
- Moderate deviations for \(m\)-dependent random variables with Banach space values
- Large and moderate deviations for infinite-dimensional autoregressive processes.
- Some laws of the iterated logarithm in Hilbertian autoregressive models
- Large deviations for quadratic forms of stationary Gaussian processes
- Moderate deviations of empirical periodogram and non-linear functionals of moving average processes
- The Discounted Large Deviation Principle for Autoregressive Processes
- Distribution of the Estimators for Autoregressive Time Series With a Unit Root
- Uniform Limit Theory for Stationary Autoregression
- Towards a unified asymptotic theory for autoregression
- Likelihood Ratio Statistics for Autoregressive Time Series with a Unit Root
- Large and moderate deviations upper bounds for the Gaussian autoregressive process
- On large deviations in the Gaussian autoregressive process: Stable, unstable and explosive cases