A time-series model consists of one or more StressModels which together with a Constant and a NoiseModel form the simulation. Most StressModels use a response-function from the rfunc-module that transforms the stress into its contribution in the simulation. Examples of response-functions are Gamma, Exponential or One (which is used for the Constant). Each StressModel has a number of parameters, which are optimized by the Solver. During optimization the noise (or the residuals, the difference between the simulation and the observations, when no NoiseModel is used) are minimized.
Warning
This section is unfortunately slightly outdated and needs to be updated. Check the code on GitHub for the current implementations.