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Of course, depending on the simulated case, the initial steady-state conditions were set according to the measurements.
Times are again well estimated until a threshold depending on the simulated ρ.
Gains in accuracy ranged from close to zero to 37.14%, depending on the simulated scenario.
Using the true model, we find that times are well estimated until a threshold depending on the simulated ρ.
Simulated phenotypes were exported to the SAS® software and analyses of variance were performed as previously described to determine which inheritance pattern was detected depending on the simulated parameters, applying either the IGF2pat or the IGF2mat models.
Depending on the simulated condition, this was either directly followed by fitting the linear regression model using the CC method, or by first creating multiple imputations and then following with regression analyses.
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Breakdown of litter depends on the simulated action of soil microbes, which is highly temperature dependent.
Changes in daily simulated runoff + drainage and measured stream flow depended on the simulated volumetric soil water content (θv).
Finally, as a general conclusion, the CUSUM algorithm performance considerably depends on the simulated scenario and the parameters applied to it, such as learning time and number of attackers.
The quality of the time's estimation depends on the simulated ρ since the loss times depend on ρ.
The simulated value of is defined as LRT* = K0 - K. Note that up to a constant which depends on the simulated data but not on the model, K0 = -2ℒ(H0, ) while K = -2ℒ(H1, ).
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