1 |
data |
Data input containing a time series of observations in longitudinal matrix form |
parms0 |
Optional. Starting parameter vector. Default = Zero vector |
ftol |
Minimum change in the value of the objective function (sum of squared residuals) between two consecutive steps before stopping iterative optimization |
ptol |
Minimum change in the value of parameters being estimated between two consecutive steps before stopping iterative optimization |
maxiter |
Maximal number of iterations allowed before breaking the optimization algorithm |
lowerbound |
Numerical vector of equal length as parameter vector describing lower bound for constrained parameter search |
upperbound |
Numerical vector of equal length as parameter vector describing upper bound for constrained parameter search |
method |
Method used for optimization of the objective function. Default is "Marq" for Leverberg-Marquandt |
Parms |
Estimated parameter matrix |
SSR |
The value of the sum of squared residuals of the found solution |
residual_SD |
The estimated standard deviation of the data stochasticity in respect to the solution found |
SE |
A matrix contatining the standard errors of each estimated parameter |
residuals_t.test |
The result of a t test with the null hypothesis of the residuals from the model solution being normally distributed with standard error 'residual_SD' |
message |
A text message related to the reason why the optimization algorithm stopped |
obs |
A matrix with the calculated abundances on each timestep according to the estimated parameters |
Fit |
The object returned by the optimization algorithm. It is a list containing further details of the optimization algorithm run |
df |
The degrees of freedom |
quantitative |
Only when validating against in Silico data: The ratio of estimated parameters that contain the original value within the 95% confidence interval given by their standard error (displayed in 'SE') |
qualitative1 |
Only when validating against in Silico data: The ratio of correctly retrieved edges from the original interaction network |
qualititative2 |
Only when validating against in Silico data: The ratio of correctly retrieved edges from the original interaction network after setting estimated parameters that are not significantly different from zero to zero (i.e. parameters that contain the zero in their 95% confidence interval as given by their standard error) |
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