Inspecting the solution

The output of most solution methods is a decision rule for the controls as a function of the exogenous and endogenous states: dr. This decision rule can be called using one of the following methods:

• dr.eval_s(s: array): function of endogenous state. Works only if exgogenous process is i.i.d.
• dr.eval_ms(m: array,s: array): function of exogenous and endogenous values. Works only if exogenous process is continuous.
• dr.eval_is(i: int,s: array): function of exognous index and endogenous values. Works only if some indexed discrete values are associated with exogenous process.

There is also a __call__ function, which tries to make the sensible call based on argument types. Hence dr(0, s) will behave as the third example.

Tabulating a decision rule

Dolo provides a convenience function to plot the values of a decision rule against different values of a state:

Stochastic simulations

Given a model object and a corresponding decision rule, one can get a N stochastic simulation for T periods, using the simulate function. The resulting object is an 3-dimensional DataArray, with the following labelled axes:

• T: date of the simulation (range(0,T))
• N: index of the simulation (range(0,N))
• V: variables of the model (model.variables)

Impulse response functions

For continuously valued exogenous shocks, one can perform an impulse response function:

Graphing nonstochastic simulations

Given one or many nonstochstic simulations of a model, obtained with response, or deterministic_solve it is possible to quickly create an irf for multiple variables.