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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
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