Sequential testing with uniformly distributed size
From MaRDI portal
Publication:1669696
DOI10.1515/jtse-2017-0002zbMath1499.62280OpenAlexW1479753836MaRDI QIDQ1669696
Grigory Kosenok, Stanislav Anatolyev
Publication date: 4 September 2018
Published in: Journal of Time Series Econometrics (Search for Journal in Brave)
Full work available at URL: https://doi.org/10.1515/jtse-2017-0002
Applications of statistics to economics (62P20) Time series, auto-correlation, regression, etc. in statistics (GARCH) (62M10) Linear regression; mixed models (62J05) Sequential statistical analysis (62L10)
Related Items (5)
Sequential change point detection in high dimensional time series ⋮ BACKWARD CUSUM FOR TESTING AND MONITORING STRUCTURAL CHANGE WITH AN APPLICATION TO COVID-19 PANDEMIC DATA ⋮ Nonparametric sequential change-point detection for multivariate time series based on empirical distribution functions ⋮ Monitoring parameter changes in models with a trend ⋮ A new approach for open‐end sequential change point monitoring
Cites Work
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Monitoring disruptions in financial markets
- A new test for structural stability in the linear regression model
- Predictive tests for structural change with unknown breakpoint
- Alternative boundaries for CUSUM tests
- MONITORING STRUCTURAL CHANGES WITH THE GENERALIZED FLUCTUATION TEST
- Tests for Parameter Instability and Structural Change With Unknown Change Point
- ANOTHER NUMERICAL METHOD OF FINDING CRITICAL VALUES FOR THE ANDREWS STABILITY TEST
- Change‐point monitoring in linear models
- THE LIMIT DISTRIBUTION OF THE CUSUM OF SQUARES TEST UNDER GENERAL MIXING CONDITIONS
- Testing for Structural Change in Dynamic Models
- The Cusum Test with Ols Residuals
- Use of Cumulative Sums of Squares for Retrospective Detection of Changes of Variance
- Estimating and Testing Linear Models with Multiple Structural Changes
- The generalized fluctuation test: A unifying view
- Monitoring Structural Change
- Monitoring Parameter Constancy with Endogenous Regressors
- Boundary-crossing probabilities for the Brownian motion and Poisson processes and techniques for computing the power of the Kolmogorov-Smirnov test
- Boundary Crossing Probabilities for the Wiener Process and Sample Sums
This page was built for publication: Sequential testing with uniformly distributed size