Principal Component Analysis for Dependent FunctionalData: Incorporating Spatial and Temporal Structures

Key Points

• This analysis demonstrates enhanced dimensionality reduction using principal component analysis techniques.
• The method effectively incorporates spatial and temporal structures, allowing for richer data insights.
• Observational analysis considers various functional data applications, improving interpretation of complex datasets.
• This approach highlights the potential for better modeling of dependent functional data, bridging gaps in current methodologies.