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There exists a few papers that systematically compare various model checkers on a common case study. The comparison usually discusses the modelling tradeoffs faced when using the input languages of each model checker, as well as the comparison of performances of the tools when verifying correctness properties. One can mention:
The original model uses an iterative three-stage modeling approach: Model identification and model selection: making sure that the variables are stationary, identifying seasonality in the dependent series (seasonally differencing it if necessary), and using plots of the autocorrelation (ACF) and partial autocorrelation (PACF) functions of the dependent time series to decide which (if any ...
In the context of nonlinear system identification Jin et al. [9] describe grey-box modeling by assuming a model structure a priori and then estimating the model parameters. Parameter estimation is relatively easy if the model form is known but this is rarely the case.
Identifiability of the model in the sense of invertibility of the map is equivalent to being able to learn the model's true parameter if the model can be observed indefinitely long. Indeed, if { X t } ⊆ S is the sequence of observations from the model, then by the strong law of large numbers ,
AFCAA REVIC is a set of programs for use in estimating the cost of software development projects. [1] The Revised Enhanced Version of Intermediate COCOMO (REVIC) model is a copyrighted program available for public distribution under agreement with the REVIC developer, Ray Kile, and the U.S. Air Force Cost Analysis Agency (AFCAA).
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