Parsimonious reduction

Parsimonious reduction is a concept often discussed in the context of model selection, data analysis, and statistical modeling. The term "parsimonious" refers to the principle of simplicity or minimalism, suggesting that when choosing between competing models, one should prefer the simplest model that adequately explains the data. In statistical modeling, parsimonious reduction involves: 1. **Model Simplification**: Reducing the complexity of a model by eliminating unnecessary variables or parameters.