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animate_capped_rne_history()
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Use ggplotly to show an animation of the payoff sets of a capped RNE going from t=T to t=1 |
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animate_eq_li()
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Use ggplotly to show an animation of the payoff sets of a list of equilibria |
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compare_eq()
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Helper function to find differences between two equilibria |
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diagnose_transitions()
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Take a look at the computed transitions for each state
using separate data frames |
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eq_combine_xgroup()
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Aggregate equilibrium behavior in games with random active player |
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eq_diagram()
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Draws a diagram of equilibrium state transition |
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eq_diagram_xgroup()
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Draws a diagram of equilibrium state transition |
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get_eq()
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Get the last computed equilibrium of game g |
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get_repgames_results()
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Get the results of all solved repeated games assuming the state is fixed |
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get_rne()
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Get the last computed RNE of game g |
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get_rne_details()
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Retrieve more details about the last computed RNE |
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get_spe()
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Get the last computed SPE of game g |
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get_T_rne_history()
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Get the intermediate steps in from t = T to t = 1 for
a T-RNE or capped RNE that has been solved with
save.history = TRUE |
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irv()
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Helper functions to specify state transitions |
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irv_joint_dist()
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Helper function to specify state transitions |
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irv_val()
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Helper functions to specify state transitions |
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plot_eq_payoff_set()
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Show a base R plot of equilibrium payoff set |
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rel_after_cap_actions()
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Fix action profiles for the equilibrium path (ae) and during punishment (a1.hat and a2.hat) that are assumed to be played after the cap in period T onwards. The punishment profile a1.hat is the profile in which player 1 already plays a best-reply (in a1 he might play a non-best reply). From the specified action profiles in all states, we can compute the relevant after-cap payoffs U(x), v1(x) and v2(x) assuming that state transitions would continue. |
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rel_after_cap_payoffs()
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Specify the SPE payoff set(s) of the truncated game(s) after a cap in period T. While we could specify a complete repeated game that is played after the cap, it also suffices to specify just an SPE payoff set of the truncated game of the after-cap state. |
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rel_capped_rne()
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Solve an RNE for a capped version of a game |
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rel_change_param()
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Add parameters to a relational contracting game |
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rel_compile()
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Compiles a relational contracting game |
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rel_eq_as_discounted_sums()
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Translate equilibrium payoffs as discounted sum
of payoffs |
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rel_first_best()
|
Compute first-best. |
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rel_game()
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Creates a new relational contracting game |
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rel_is_eq_rne()
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Checks if an equilibrium eq with negotiation payoffs is an RNE |
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rel_mpe()
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Tries to find a MPE by computing iteratively best replies |
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rel_options()
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Set some game options |
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rel_param()
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Add parameters to a relational contracting game |
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rel_rne()
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Find an RNE for a (weakly) directional game |
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rel_scale_eq_payoffs()
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Scale equilibrium payoffs |
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rel_solve_repgames()
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Solves for all specified states the repeated game assuming the state is fixed |
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rel_spe()
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Finds an optimal simple subgame perfect equilibrium of g. From this the whole SPE payoff set can be deduced. |
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rel_states() rel_state()
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Add one or multiple states. Allows to specify action spaces, payoffs and state transitions via functions |
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rel_state_probs()
|
Compute the long run probability distribution over states if an
equilibrium is played for many periods. |
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rel_transition()
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Add a state transition from one state to one or several states. For more complex games, it may be preferable to use the arguments trans.fun of link{rel_states} instead. |
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rel_T_rne()
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Compute a T-RNE |