Model objects are created by loading a model file. Once a model object exists, you can use model functions and standard Matlab functions to write your own m-files to perform the desired tasks, such calibrate or estimate the model, find its steady state, solve and simulate it, produce forecasts, analyse its properties, and so on.
Model methods:
model
- Create new model object based on model file.addparam
- Add model parameters to a database (struct).autocaption
- Create captions for graphs of model variables or parameters.autoexogenise
- Get or set variable/shock pairs for use in autoexogenised simulation plans.comment
- Get or set user comments in an IRIS object.eig
- Eigenvalues of the transition matrix.findeqtn
- Find equations by the labels.findname
- Find names of variables, shocks, or parameters by their descriptors.get
- Query model object properties.iscompatible
- True if two models can occur together on the LHS and RHS in an assignment.islinear
- True for models declared as linear.islog
- True for log-linearised variables.ismissing
- True if some initical conditions are missing from input database.isnan
- Check for NaNs in model object.isname
- True for valid names of variables, parameters, or shocks in model object.issolved
- True if a model solution exists.isstationary
- True if model or specified combination of variables is stationary.length
- Number of alternative parameterisations.omega
- Get or set the covariance matrix of shocks.sspace
- State-space matrices describing the model solution.system
- System matrices for unsolved model.userdata
- Get or set user data in an IRIS object.subsasgn
- Subscripted assignment for model and systemfit objects.subsref
- Subscripted reference for model and systemfit objects.alter
- Expand or reduce number of alternative parameterisations.assign
- Assign parameters, steady states, std deviations or cross-correlations.export
- Save carry-around files to disk file.horzcat
- Combine two compatible model objects in one object with multiple parameterisations.refresh
- Refresh dynamic links.reset
- Reset specific values within model object.stdscale
- Rescale all std deviations by the same factor.set
- Change modifiable model object property.single
- Convert solution matrices to single precision.blazer
- Reorder steady-state equations into block-recursive structure.chksstate
- Check if equations hold for currently assigned steady-state values.sstate
- Compute steady state or balance-growth path of the model.sstatefile
- Create a steady-state file based on the model object's steady-state equations.chkmissing
- Check for missing initial values in simulation database.diffsrf
- Differentiate shock response functions w.r.t. specified parameters.expand
- Compute forward expansion of model solution for anticipated shocks.jforecast
- Forecast with judgmental adjustments (conditional forecasts).icrf
- Initial-condition response functions.lhsmrhs
- Evaluate the discrepancy between the LHS and RHS for each model equation and given data.resample
- Resample from the model implied distribution.reporting
- Evaluate reporting equations from within model object.shockplot
- Short-cut for running and plotting plain shock simulation.simulate
- Simulate model.solve
- Calculate first-order accurate solution of the model.srf
- Shock response functions, first-order solution only.data4lhsmrhs
- Prepare data array for running lhsmrhs
.emptydb
- Create model-specific database with empty tseries for all variables and shocks.rollback
- Prepare database for a rollback run of Kalman filter.sstatedb
- Create model-specific steady-state or balanced-growth-path database.zerodb
- Create model-specific zero-deviation database.acf
- Autocovariance and autocorrelation functions for model variables.ifrf
- Frequency response function to shocks.fevd
- Forecast error variance decomposition for model variables.ffrf
- Filter frequency response function of transition variables to measurement variables.fmse
- Forecast mean square error matrices.vma
- Vector moving average representation of the model.xsf
- Power spectrum and spectral density of model variables.bn
- Beveridge-Nelson trends.diffloglik
- Approximate gradient and hessian of log-likelihood function.estimate
- Estimate model parameters by optimising selected objective function.evalsystempriors
- Evaluate minus log of system prior density.filter
- Kalman smoother and estimator of out-of-likelihood parameters.fisher
- Approximate Fisher information matrix in frequency domain.lognormal
- Characteristics of log-normal distributions returned by filter of forecast.loglik
- Evaluate minus the log-likelihood function in time or frequency domain.neighbourhood
- Evaluate the local behaviour of the objective function around the estimated parameter values.regress
- Centred population regression for selected model variables.VAR
- Population VAR for selected model variables.help model
help model/function_name