Estimation of slowly time-varying trend function in long memory regression models
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Publication:4960653
DOI10.1080/00949655.2018.1466141OpenAlexW2803018509WikidataQ129902716 ScholiaQ129902716MaRDI QIDQ4960653
Emilio Porcu, Nicolas Piña, Guillermo P. Ferreira
Publication date: 23 April 2020
Published in: Journal of Statistical Computation and Simulation (Search for Journal in Brave)
Full work available at URL: https://doi.org/10.1080/00949655.2018.1466141
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- Kalman filter estimation for a regression model with locally stationary errors
- Empirical spectral processes for locally stationary time series
- An efficient estimator for locally stationary Gaussian long-memory processes
- Asymptotic properties of the LSE in a regression model with long-memory stationary errors
- Efficient parameter estimation for self-similar processes
- On the sample mean of locally stationary long-memory processes
- On parameter estimation for locally stationary long-memory processes
- Large-sample properties of parameter estimates for strongly dependent stationary Gaussian time series
- On estimation of a regression model with long-memory stationary errors
- Time series: theory and methods.
- Fitting time series models to nonstationary processes
- A multivariate test against spurious long memory
- A likelihood approximation for locally stationary processes
- Efficient location and regression estimation for long range dependent regression models
- Asymptotic distributions of the sample mean, autocovariances, and autocorrelations of long-memory time series
- Estimation of the dependence parameter in linear regression with long-range-dependent errors
- Nonparametric quasi-maximum likelihood estimation for Gaussian locally stationary processes
- Statistical inference for time-varying ARCH processes
- An Efficient Taper for Potentially Overdifferenced Long-memory Time Series
- Long‐Memory Time Series
- ESTIMATION OF THE MEMORY PARAMETER FOR NONSTATIONARY OR NONINVERTIBLE FRACTIONALLY INTEGRATED PROCESSES
- Discrimination of Locally Stationary Time Series Based on the Excess Mass Functional
- Long memory and regime switching
