6 papers
Recursive Multiple Change Point Detection of Nonstationary Time Series: Instability Tests, Estimation and Confidence Intervals
Leheng Cai, Zhou Zhou
We develop bootstrap-assisted robust binary segmentation (BARBS), a recursive binary segmentation method for multiple change point detection under general nonstationary temporal dy…
Simultaneous Inference for Nonlinear Time Series, a Sieve M-regression Approach
Tianpai Luo, Zhou Zhou
This paper studies simultaneous inference of conditional distributions in nonlinear time series from a sieve M-regression perspective. Existing literature on sieve M-regression has…
Simultaneous Sieve Estimation and Inference for Time-Varying Nonlinear Time Series Regression
Xiucai Ding, Zhou Zhou
In this paper, we investigate time-varying nonlinear time series regression for a broad class of locally stationary time series. First, we propose sieve nonparametric estimators fo…
Uncertainty quantification of synchrosqueezing transform under complicated nonstationary noise
Hau-Tieng Wu, Zhou Zhou
We propose a bootstrapping framework to quantify uncertainty in time-frequency representations (TFRs) generated by the short-time Fourier transform (STFT) and the STFT-based synchr…
Inference for non-stationary time series quantile regression with inequality constraints
Yuan Sun, Zhou Zhou
We consider parameter inference for linear quantile regression with non-stationary predictors and errors, where the regression parameters are subject to inequality constraints. We…
On the partial autocorrelation function for locally stationary time series: characterization, estimation and inference
Xiucai Ding, Zhou Zhou
For stationary time series, it is common to use the plots of partial autocorrelation function (PACF) or PACF-based tests to explore the temporal dependence structure of such proces…