Selected New Yorkers are interspersed to show where they might rank, using publicly available sources for compensation.
Most interestingly, it is possible for Belgium to be the highest ranked nation: Rank using scores of matches Type weights:.1, 2.5, 5,.1, 2.5, 5 Years: 3.2 Weighting: logistic PSO value:.5 95% age:.6 50% age: 2 Max winning margin: 1 This produces: Belgium, Spain, Argentina, Germany, Brazil.
It is also possible to put England in the top five: Rank using scores of matches Type weights: 1, 1.5, 4.5, 3.5, 3, 5 Number of years: 2 Weighting type: logistic PSO value:.5 Logistic parameters:.25 for 95%; 1 for 50% Max winning margin: 4 This produces: Brazil, Germany, Chile, England, France.
The low and high embodied groups were then asked to rank, using 1 through 7, the games they "most enjoyed".
SD&ML has described the use of SRL through different use cases, such as defining component rank using an importance measurement score, and strategic decision making using an optimized resource algorithm [6, 7].
The number of pure components can also be estimated using Principal Component Analysis (PCA) which provides the number of components needed to explain the variance in the data in a satisfactory way [19, 30] or by determining the data matrix rank using singular value decomposition (SVD) [31].
