Quantile inference for nonstationary processes with infinite variance innovations
DOI10.1007/s11766-021-4187-6zbMath1488.62132OpenAlexW3199505411MaRDI QIDQ2057405
Gui Li Liao, Qi Meng Liu, Rong Mao Zhang
Publication date: 6 December 2021
Published in: Applied Mathematics. Series B (English Edition) (Search for Journal in Brave)
Full work available at URL: https://doi.org/10.1007/s11766-021-4187-6
Asymptotic properties of parametric estimators (62F12) Applications of statistics to economics (62P20) Asymptotic distribution theory in statistics (62E20) Parametric hypothesis testing (62F03) Non-Markovian processes: hypothesis testing (62M07) Asymptotic properties of parametric tests (62F05)
Cites Work
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Testing the null hypothesis of stationarity against the alternative of a unit root. How sure are we that economic time series have a unit root?
- Quantile inference for near-integrated autoregressive time series under infinite variance and strong dependence
- Maximum likelihood type estimation for nearly nonstationary autoregressive time series
- Distribution estimates for functionals of the two-parameter Wiener process
- Rank tests for unit roots
- Limiting distributions for \(L_1\) regression estimators under general conditions
- Time series with unit roots and infinite-variance disturbances
- Regression quantiles for unstable autoregressive models
- Point process and partial sum convergence for weakly dependent random variables with infinite variance
- Unit root quantile autoregression testing using covariates
- Distribution of the Estimators for Autoregressive Time Series With a Unit Root
- A Note on Unit Root Tests with Infinite Variance Noise
- Limit theory for autoregressive-parameter estimates in an infinite-variance random walk
- Point processes, regular variation and weak convergence
- Testing for a unit root in time series regression
- Likelihood Ratio Statistics for Autoregressive Time Series with a Unit Root
- ESTIMATION OF A DENSITY FUNCTION USING ORDER STATISTICS1
- Robust Rank Tests of the Unit Root Hypothesis
- Extreme Values in Finance, Telecommunications, and the Environment
- Unit Root Tests and Heavy‐Tailed Innovations
- Unit Root Quantile Autoregression Inference
- Testing for a unit root in a nonlinear quantile autoregression framework
This page was built for publication: Quantile inference for nonstationary processes with infinite variance innovations
