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LIMDEP is an econometric and statistical software package with a variety of estimation tools. In addition to the core econometric tools for analysis of cross sections and time series, LIMDEP supports methods for panel data analysis, frontier and efficiency estimation and discrete choice modeling.
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.
Includes tools for optimization/parameter estimation, sensitivity analysis, and statistical analysis and presentation of results from multiple simulations of stochastic models. Based on the InsightMaker-engine, stock and flow models are constructed in a click-and-draw manner.
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 ...
The Toolkit for Conceptual Modeling (TCM) is a collection of software tools to present specifications of software systems in the form of diagrams, tables, trees, and the like. TCM offers editors for techniques used in Structured Analysis as well as editors for object-oriented (UML) techniques.
In mathematics, specifically in control theory, subspace identification (SID) aims at identifying linear time invariant (LTI) state space models from input-output data. SID does not require that the user parametrizes the system matrices before solving a parametric optimization problem and, as a consequence, SID methods do not suffer from problems related to local minima that often lead to ...
MCL: Model Checking Language; Alternation-Free Modal μ-calculus extended with user-friendly regular expressions and value-passing constructs; subsumes CTL and LTL. mCRL2 mu-calculus: Kozen's propositional modal μ-calculus (excluding atomic propositions), extended with: data-depended processes, quantification over data types, multi-actions ...
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 ,