Overview of structural model objects

Structural models are systems of dynamic simultaneous (interdependent) equations with lags and leads (expectations). Iris supports nonlinear nonstationary (balanced growth path) structural models.

Categorical list of functions

Constructing model objects

Function	Description
`Model.fromFile`	Create new Model object from model source file(s)
`Model.fromSnippet`	Create new Model object from snippet of code within m-file
`Model.fromString`	Create new Model object from string array

Getting information about models

Function	Description
`access`	Access properties of Model objects
`beenSolved`	True if first-order solution has been successfully calculated
`byAttributes`	Look up model quantities and equation by attributes
`findEquation`	Find equations whose input strings pass one or more tests
`getBounds`	Get lower and upper bounds imposed on model quantities
`isLinear`	True if the model has been declared as linear
`isLinkActive`	True if dynamic link is active
`isLog`	True for variables declared as log-variables
`print`	Print model object
`solutionMatrices`	Access first-order state-space (solution) matrices
`subsref`	Subscripted reference for Model objects
`table`	Create table based on selected indicators from Model object
`isnan`	Check for NaNs in model object.
`isempty`	True for empty model object

Assigning values within models

Function	Description
`assign`	Assign parameters, steady states, std deviations or cross-correlations
`assignFromModel`	Assign model quantities from another model
`replaceNames`	Replace model names with some other names
`reset`	Reset specific values within model object
`resetBounds`	Reset lower and upper bounds imposed on model quantities
`setBounds`	Set bounds for model quantities
`rescaleStd`	Rescale all std deviations by the same factor

Analytical properties of models

Function	Description
`analyticGradients`	Evaluate analytic/symbolic derivatives of model equations
`blazer`	Analyze sequential block structure of steady equations
`eig`	Eigenvalues of model transition matrix
`systemMatrices`	First-order system matrices describing the unsolved model
`isstationary`	True if the model or a linear combination of its variables is stationary

Stochastic properties of models

Function	Description
`acf`	Autocovariance and autocorrelation function for model variables
`fevd`	Forecast error variance decomposition for model variables.
`ffrf`	Filter frequency response function of transition variables to measurement variables
`fisher`	Approximate Fisher information matrix in frequency domain
`fmse`	Forecast mean square error matrices.

Solving and simulating models

Function	Description
`checkSteady`	Check if equations hold for currently assigned steady-state values
`checkInitials`	Check if databank contains all initial conditions for simulation
`expand`	Compute forward expansion of model solution for anticipated shocks
`simulate`	Run a model simulation
`solve`	Calculate first-order solution matrices
`steady`	Compute steady state or balance-growth path of the model
`system`	System matrices for the unsolved model
`lhsmrhs`	Discrepancy between the LHS and RHS of each model equation for given data

Estimating and filtering model quantities

Function	Description
`beveridgeNelson`	Beveridge-Nelson trends
`estimate.md`	Estimate model parameters by maximizing posterior-based objective function
`kalmanFilter`	Kalman smoother and estimator of out-of-likelihood parameters

Manipulating the structure of models

Function	Description
`activeLink`	Activate dynamic links for selected LHS names
`deactiveLink`	Deactivate dynamic links for selected LHS names
`alter`	Expand or reduce number of parameter variants in model object
`changeGrowthStatus`	Change growth status of the model
`changeLinearStatus`	Change linear status of model
`changeLogStatus`	Change log status of model variables
`horzcat`	Merge two or more compatible model objects into multiple parameterizations