utilities

Utility routines for the game_theory submodule

class quantecon.game_theory.utilities.NashResult[source]

Bases: dict

Contain the information about the result of Nash equilibrium computation.

Notes

This is sourced from sicpy.optimize.OptimizeResult.

There may be additional attributes not listed above depending of the routine.

Attributes:
NE : tuple(ndarray(float, ndim=1))

Computed Nash equilibrium.

converged : bool

Whether the routine has converged.

num_iter : int

Number of iterations.

max_iter : int

Maximum number of iterations.

init : scalar or array_like

Initial condition used.

Methods

clear()
copy()
fromkeys($type, iterable[, value]) Returns a new dict with keys from iterable and values equal to value.
get(k[,d])
items()
keys()
pop(k[,d]) If key is not found, d is returned if given, otherwise KeyError is raised
popitem() 2-tuple; but raise KeyError if D is empty.
setdefault(k[,d])
update([E, ]**F) If E is present and has a .keys() method, then does: for k in E: D[k] = E[k] If E is present and lacks a .keys() method, then does: for k, v in E: D[k] = v In either case, this is followed by: for k in F: D[k] = F[k]
values()