Thus, we searched for parameter values that minimize the deviation of results from experimental data, based on the least-squares criterion defined above.
We have previously described the dynamics of SF disassembly with a deterministic model using first-order reaction kinetics in which the rate parameter for disassembly depended on the deviation of SF stretch from the prestretch value [13].
In the simultaneous approach, we search for the optimal parameter combination that minimizes the deviation of simulated concentration predictions from the experimental concentration data.
where Pi is the estimated parameter value for individual i, Ppop represents the typical population estimate for the parameter, and η i is the deviation of Pi from Ppop.
Therefore, the deviation from the real model represents a very important parameter for the selection of the appropriate parameterized model.
Using the first ten runs of converged parameters, we calculated standard deviations for the 11 parameters, and used them to set the upper- and lower-boundary of each parameter for the prior distribution of the subsequent runs.
These histograms follow chi-square distributions with 2 degrees of freedom (Eq. (6a)) for the estimated non-centrality parameter and standard deviation of the measured linear intensity.
Since V includes random parameters, the standard deviation of those parameters should be accounted for [ 8, 23].
This is slightly higher than the value for the standard deviation of these parameters determined in simulations by Binsl et al. [ 8].
For each model parameter, the median and the standard deviation of the parameters' distributions from the bootstrap runs were computed and reported.
