4 papers
A Structure-Preserving Assessment of VBPBB for Time Series Imputation Under Periodic Trends, Noise, and Missingness Mechanisms
Asmaa Ahmad, Eric J Rose, Michael Roy +1
Incomplete time-series data compromise statistical inference, particularly when the underlying process exhibits periodic structure (e.g., annual or monthly cycles). Conventional im…
Bayesian approach to the PC component
Jie Yao, Kai Zhang, Eric Rose +1
Time series with multiple periodically correlated components is a complex problem with comparatively limited prior research. Most existing time series models are designed to accomm…
Assessing Bias in the Variable Bandpass Periodic Block Bootstrap Method
Yanan Sun, Eric Rose, Kai Zhang +1
The Variable Bandpass Periodic Block Bootstrap(VBPBB) is an innovative method for time series with periodically correlated(PC) components. This method applies bandpass filters to e…
Enhancing Data Completeness in Time Series: Imputation Strategies for Missing Data Using Significant Periodically Correlated Components
Asmaa Ahmad, Eric J Rose, Michael Roy +1
Missing data is a pervasive issue in statistical analyses, affecting the reliability and validity of research across diverse scientific disciplines. Failure to adequately address m…