Robust test for structural instability in dynamic factor models
DOI10.1007/s10463-020-00773-0zbMath1469.62341OpenAlexW3118283230MaRDI QIDQ2042290
Changryong Baek, Byungsoo Kim, Junmo Song
Publication date: 28 July 2021
Published in: Annals of the Institute of Statistical Mathematics (Search for Journal in Brave)
Full work available at URL: https://doi.org/10.1007/s10463-020-00773-0
outliersdynamic factor modelshigh-dimensional time seriesparameter change testminimum density power divergence
Nonparametric hypothesis testing (62G10) Time series, auto-correlation, regression, etc. in statistics (GARCH) (62M10) Nonparametric robustness (62G35) Applications of statistics to biology and medical sciences; meta analysis (62P10) Image analysis in multivariate analysis (62H35)
Related Items
Cites Work
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Change-point detection in multinomial data using phi-divergence test statistics
- Detecting big structural breaks in large factor models
- Minimum density power divergence estimator for GARCH models
- Testing for structural breaks in dynamic factor models
- Two sample tests for high-dimensional autocovariances
- A data-based method for selecting tuning parameters in minimum distance estimators
- Detecting shocks: Outliers and breaks in time series
- Periodic dynamic factor models: estimation approaches and applications
- Detecting structural breaks in realized volatility
- Testing statistical hypotheses based on the density power divergence
- Robust test for dispersion parameter change in discretely observed diffusion processes
- The minimum \(S\)-divergence estimator under continuous models: the Basu-Lindsay approach
- Robust estimation in the normal mixture model
- On distinguishing multiple changes in mean and long-range dependence using local Whittle estimation
- Outliers in multivariate time series
- TESTS FOR PARAMETER INSTABILITY IN DYNAMIC FACTOR MODELS
- Robust and efficient estimation by minimising a density power divergence
- Forecasting Using Principal Components From a Large Number of Predictors
- Tests for Volatility Shifts in Garch Against Long‐Range Dependence
- Inferential Theory for Factor Models of Large Dimensions
- Determining the Number of Factors in Approximate Factor Models
- Mean shift testing in correlated data
- Generalized Wald-type tests based on minimum density power divergence estimators
This page was built for publication: Robust test for structural instability in dynamic factor models
