Multidimensional sampling

Multidimensional sampling refers to techniques used to sample data or observations from a multidimensional space, where each dimension represents a different variable or characteristic. This approach is particularly valuable in fields such as statistics, machine learning, and experimental design, where systems can have multiple interrelated variables. Key aspects of multidimensional sampling include: 1. **Purpose**: Multidimensional sampling aims to capture the variability and relationships among multiple variables simultaneously, allowing for a more comprehensive analysis of complex systems.