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Table 1 Parameter values for two Logistic and two Poisson simulated models

From: Particle swarm based algorithms for finding locally and Bayesian D-optimal designs

Model

θ0,θ1,⋯,θ15

8-1 (Logistic)

[0.72, -0.25, 0.11, 0.91, 0.47, 0.63, -0.80, 0.86

 

0.22, 0.19, -0.82, -0.31, 0.33, -0.12, 0.10, 0.41]

8-2 (Logistic)

[-0.50, -0.10, -0.18, -0.48, 0.74, -0.63, -0.96, 0.90

 

0.36, -0.03, -0.93, -0.21, -0.84, -0.30, -0.67, 0.97]

9-1 (Poisson)

[0.54, -2.70, 0.37, 1.60, 2.47, -2.44, 2.42, -0.23

 

-0.29, 3.00, -2.03, 1.26, -2.04, -1.86, -2.79, 0.21]

9-2 (Poisson)

[0.17, -1.01, -0.88, -2.53, 0.34, -2.01, -1.23, 2.04

 

-0.82, -0.96, 1.26, -2.81, -0.17, 1.39, 1.64, -1.55]

  1. Parameters for Logistic models were generated randomly from uniform[-1, 1] and parameters for Poisson models were generated randomly from uniform [-3, 3]