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-Kinetic nonlinear mixed-effects model fit by SAEM
-Structural model:
-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:
-509 observations of 2 variable(s) grouped in 15 datasets
-
-Likelihood computed by importance sampling
- AIC BIC logLik
- 2692 2702 -1333
-
-Fitted parameters:
- estimate lower upper
-parent_0 1e+02 99.303 1e+02
-k_m1 2e-03 0.002 3e-03
-f_parent_to_m1 5e-01 0.448 5e-01
-k1 4e-02 0.024 6e-02
-k2 2e-02 0.009 2e-02
-g 5e-01 0.381 6e-01
-Var.parent_0 2e+00 -0.551 4e+00
-Var.k_m1 2e-02 -0.151 2e-01
-Var.f_parent_to_m1 8e-02 0.018 1e-01
-Var.k1 5e-01 0.095 9e-01
-Var.k2 6e-01 0.125 1e+00
-Var.g 7e-02 -0.245 4e-01
-a.1 3e+00 2.569 3e+00
-SD.parent_0 1e+00 0.390 2e+00
-SD.k_m1 1e-01 -0.478 8e-01
-SD.f_parent_to_m1 3e-01 0.175 4e-01
-SD.k1 7e-01 0.422 1e+00
-SD.k2 8e-01 0.471 1e+00
-SD.g 3e-01 -0.326 9e-01

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