IRIS Toolbox Reference Manual

prior

Add new prior to system priors object

Syntax

S = prior(S,Expr,PriorFunc,...)
S = prior(S,Expr,[],...)

Input arguments

Output arguments

Options

Description

System properties that can be used in Expr

If a variable is declared as a log variable, it must be referred to as log(VarName) in the above expressions, and the log of that variables is returned, e.g. srf[log(VarName),ShockName,T]. or ffrf[log(TVarName),MVarName,T].

Expressions involving combinations or functions of parameters

Model parameter names can be referred to in Expr preceded by a dot (period), e.g. .alpha^2 + .beta^2 defines a prior on the sum of squares of the two parameters (alpha and beta).

Example

Create a new empty systemprios object based on an existing model.

s = systempriors(m);

Add a prior on minus the shock response function of variable ygap to shock eps_pie in period 4. The prior density is lognormal with mean 0.3 and std deviation 0.05;

s = prior(s,'-srf[ygap,eps_pie,4]',logdist.lognormal(0.3,0.05));

Add a prior on the gain of the frequency response function of transition variable ygap to measurement variable 'y' at frequency 2*pi/40. The prior density is normal with mean 0.5 and std deviation 0.01. This prior says that we wish to keep the cut-off periodicity for trend-cycle decomposition close to 40 periods.

s = prior(s,'abs(ffrf[ygap,y,2*pi/40])',logdist.normal(0.5,0.01));

Add a prior on the sum of parameters alpha1 and alpha2. The prior is normal with mean 0.9 and std deviation 0.1, but the sum is forced to be between 0 and 1 by imposing lower and upper bounds.

s = prior(s,'alpha1+alpha2',logdist.normal(0.9,0.1), ...
    'lowerBound=',0,'upperBound=',1);