saemix version used for fitting: Dummy 0.0 for testing mkin version used for pre-fitting: Dummy 0.0 for testing R version used for fitting: Dummy R version for testing Date of fit: Dummy date for testing Date of summary: Dummy date for testing Equations: d_parent/dt = - ((k1 * g * exp(-k1 * time) + k2 * (1 - g) * exp(-k2 * time)) / (g * exp(-k1 * time) + (1 - g) * exp(-k2 * time))) * parent d_m1/dt = + f_parent_to_m1 * ((k1 * g * exp(-k1 * time) + k2 * (1 - g) * exp(-k2 * time)) / (g * exp(-k1 * time) + (1 - g) * exp(-k2 * time))) * parent - k_m1 * m1 Data: 507 observations of 2 variable(s) grouped in 15 datasets Model predictions using solution type analytical Fitted in test time 0 s Using 300, 100 iterations and 4 chains Variance model: Two-component variance function Mean of starting values for individual parameters: parent_0 k_m1 f_parent_to_m1 k1 k2 1e+02 5e-03 5e-01 6e-02 1e-02 g 5e-01 Fixed degradation parameter values: None Results: Likelihood computed by importance sampling AIC BIC logLik 2369 2379 -1170 Optimised parameters: est. lower upper parent_0 1e+02 1e+02 1e+02 k_m1 5e-03 4e-03 6e-03 f_parent_to_m1 5e-01 4e-01 5e-01 k1 6e-02 5e-02 7e-02 k2 1e-02 9e-03 1e-02 g 5e-01 4e-01 5e-01 Correlation: pr_0 k_m1 f___ k1 k2 k_m1 -0.3 f_parent_to_m1 -0.3 0.3 k1 0.1 -0.1 -0.1 k2 0.0 0.0 0.0 0.1 g 0.1 -0.1 0.0 -0.3 -0.3 Random effects: est. lower upper SD.parent_0 0.02 -89.53 89.6 SD.k_m1 0.20 0.07 0.3 SD.f_parent_to_m1 0.32 0.20 0.4 SD.k1 0.38 0.23 0.5 SD.k2 0.33 0.20 0.5 SD.g 0.26 0.06 0.5 Variance model: est. lower upper a.1 0.90 0.76 1.03 b.1 0.05 0.05 0.06 Resulting formation fractions: ff parent_m1 0.5 parent_sink 0.5 Estimated disappearance times: DT50 DT90 DT50back DT50_k1 DT50_k2 parent 26 146 44 12 60 m1 144 478 NA NA NA