Autoregressive random matrix theory based on the q-Dependent detrended cross-correlation coefficient

Key Points

• The proposed model shows significant advancements in understanding data dependencies, with enhanced accuracy in coefficient estimates.
• Using q-dependent cross-correlation coefficients, the analysis reveals intricate relationships between variables across diverse datasets.
• This framework provides a robust method for assessing statistical correlations, making it applicable to various fields and scenarios.
• Improved statistical insights from this model may lead to better interpretations of complex datasets, highlighting the need for advanced analysis techniques.