Weak convergence of some marked empirical processes: Application to testing heteroscedasticity
From MaRDI portal
Publication:4805926
DOI10.1080/10485250212377zbMath1012.62051OpenAlexW2034274691MaRDI QIDQ4805926
Publication date: 24 June 2003
Published in: Journal of Nonparametric Statistics (Search for Journal in Brave)
Full work available at URL: https://doi.org/10.1080/10485250212377
Nonparametric hypothesis testing (62G10) Time series, auto-correlation, regression, etc. in statistics (GARCH) (62M10) Asymptotic properties of nonparametric inference (62G20) Point estimation (62F10) Inference from stochastic processes (62M99) Functional limit theorems; invariance principles (60F17)
Related Items (8)
Joint parametric specification checking of conditional mean and volatility in time series models with martingale difference innovations ⋮ The marked empirical process to test nonlinear time series against a large class of alternatives when the random vectors are nonstationary and absolutely regular ⋮ A nonparametric model check for time series when the random vectors are nonstationary and absolutely regular ⋮ Estimation in a class of nonlinear heteroscedastic time series models ⋮ The marked empirical process to test a general AR-ARCH against an other general AR-ARCH when the random vectors are nonstationary and absolutely regular ⋮ A simultaneous test for conditional mean and conditional variance functions in time series models with martingale difference innovations ⋮ Checking nonlinear heteroscedastic time series models ⋮ Testing nonstationary and absolutely regular nonlinear time series models
Cites Work
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Testing the functions defining a nonlinear autoregressive time series
- The asymptotic behavior of the empirical process based on a linear process under some contiguous alternatives
- Identification of nonlinear time series from first order cumulative characteristics
- A Kolmogorov-Smirnov type test for conditional heteroskedasticity in time series
- Model checks for regression: an innovation process approach
- Nonparametric model checks for time series
- A Kolmogorov-Smirnov Type Statistic with Application to Test for Nonlinearity in Time Series
This page was built for publication: Weak convergence of some marked empirical processes: Application to testing heteroscedasticity
