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