Model	Parameter	Population Parameters
Exponential	$k\sim Gamma(A,B)$	$A\sim Norma{l}_{+}(0,1)$	$B\sim Norma{l}_{+}(0,1)$
	$\sigma \sim Gamma(A,B)$	$A\sim Norma{l}_{+}(0,1)$	$B\sim Norma{l}_{+}(0,1)$
Hyperbolic	$k\sim Gamma(A,B)$	$A\sim Norma{l}_{+}(0,1)$	$B\sim Norma{l}_{+}(0,1)$
	$\sigma \sim Gamma(A,B)$	$A\sim Norma{l}_{+}(0,1)$	$B\sim Norma{l}_{+}(0,1)$
Double	$\omega \sim Beta(A,B)$	$L\sim Uniform(0,1)$	$S\sim Gamma(1,20)$
Exponential	$\mathrm{\Theta }\sim Gamma(A,B)$	$A\sim Norma{l}_{+}(0,1)$	$B\sim Norma{l}_{+}(0,1)$
	$\delta \sim Gamma(A,B)$	$A\sim Norma{l}_{+}(0,1)$	$B\sim Norma{l}_{+}(0,1)$
	$\sigma \sim Gamma(A,B)$	$A\sim Norma{l}_{+}(0,1)$	$B\sim Norma{l}_{+}(0,1)$
Generalized	$k\sim Gamma(A,B)$	$A\sim Norma{l}_{+}(0,1)$	$B\sim Norma{l}_{+}(0,1)$
Hyperbolic	$s\sim Gamma(A,B)$	$A\sim Norma{l}_{+}(0,1)$	$B\sim Norma{l}_{+}(0,1)$
	$\sigma \sim Gamma(A,B)$	$A\sim Norma{l}_{+}(0,1)$	$B\sim Norma{l}_{+}(0,1)$
Hyperboloid	$k\sim Gamma(A,B)$	$A\sim Norma{l}_{+}(0,1)$	$B\sim Norma{l}_{+}(0,1)$
	$s\sim Gamma(A,B)$	$A\sim Norma{l}_{+}(0,1)$	$B\sim Norma{l}_{+}(0,1)$
	$\sigma \sim Gamma(A,B)$	$A\sim Norma{l}_{+}(0,1)$	$B\sim Norma{l}_{+}(0,1)$
Generalized	$\alpha \sim Gamma(A,B)$	$A\sim Norma{l}_{+}(0,1)$	$B\sim Norma{l}_{+}(0,1)$
Hyperbola	$\mathrm{\Theta }\sim Gamma(A,B)$	$A\sim Norma{l}_{+}(0,1)$	$B\sim Norma{l}_{+}(0,1)$
	$\sigma \sim Gamma(A,B)$	$A\sim Norma{l}_{+}(0,1)$	$B\sim Norma{l}_{+}(0,1)$
Constant	$\alpha \sim Gamma(A,B)$	$A\sim Norma{l}_{+}(0,1)$	$B\sim Norma{l}_{+}(0,1)$
Sensitivity	$\beta \sim Gamma(A,B)$	$A\sim Norma{l}_{+}(0,1)$	$B\sim Norma{l}_{+}(0,1)$
	$\sigma \sim Gamma(A,B)$	$A\sim Norma{l}_{+}(0,1)$	$B\sim Norma{l}_{+}(0,1)$
Additive	$\alpha \sim Beta(A,B)$	$L\sim Uniform(0,1)$	$S\sim Gamma(1,20)$
Utility	$\beta \sim Beta(A,B)$	$L\sim Uniform(0,1)$	$S\sim Gamma(1,20)$
	$\lambda \sim Gamma(A,B)$	$A\sim Norma{l}_{+}(0,1)$	$B\sim Norma{l}_{+}(0,1)$
	$\sigma \sim Gamma(A,B)$	$A\sim Norma{l}_{+}(0,1)$	$B\sim Norma{l}_{+}(0,1)$
Proportional	$\delta \sim Normal(L,S)$	$L\sim Normal(0,1)$	$S\sim Norma{l}_{+}(0,1)$
Difference	$\sigma \sim Gamma(A,B)$	$A\sim Norma{l}_{+}(0,1)$	$B\sim Norma{l}_{+}(0,1)$
ITCH	${\beta }_1\sim Normal(L,S)$	$L\sim Normal(0,1)$	$S\sim Norma{l}_{+}(0,1)$
	${\beta }_{xA}\sim Norma{l}_{+}(L,S)$	$L\sim Norma{l}_{+}(0,1)$	$S\sim Norma{l}_{+}(0,1)$
	${\beta }_{xR}\sim Norma{l}_{+}(L,S)$	$L\sim Norma{l}_{+}(0,1)$	$S\sim Norma{l}_{+}(0,1)$
	${\beta }_{tA}\sim Norma{l}_{-}(L,S)$	$L\sim Norma{l}_{-}(0,1)$	$S\sim Norma{l}_{+}(0,1)$
	${\beta }_{tR}\sim Norma{l}_{-}(L,S)$	$L\sim Norma{l}_{-}(0,1)$	$S\sim Norma{l}_{+}(0,1)$
Tradeoff	$\gamma \sim Gamma(A,B)$	$A\sim Norma{l}_{+}(0,1)$	$B\sim Norma{l}_{+}(0,1)$
	$\tau \sim Gamma(A,B)$	$A\sim Norma{l}_{+}(0,1)$	$B\sim Norma{l}_{+}(0,1)$
	$\mathrm{\Theta }\sim Gamma(A,B)$	$A\sim Norma{l}_{+}(0,1)$	$B\sim Norma{l}_{+}(0,1)$
	$\kappa \sim Gamma(A,B)$	$A\sim Norma{l}_{+}(0,1)$	$B\sim Norma{l}_{+}(0,1)$
	$\alpha \sim Gamma(A,B)$	$A\sim Norma{l}_{+}(0,1)$	$B\sim Norma{l}_{+}(0,1)$
	$𝜖\sim Gamma(A,B)$	$A\sim Norma{l}_{+}(0,1)$	$B\sim Norma{l}_{+}(0,1)$

Note: Normal₊(L,S) represents a truncated normal distribution with mean L, standard deviation S, a lower bound of 0, and no upper bound. Normal₋ represents a truncated normal distribution with an upper bound of 0 and no lower bound. Gamma(A,B) represents a gamma distribution with shape A and scale B. Certain models were reparameterized for efficiency reasons and/or in order to enforce parameter constraints. In the double exponential model, β = Θ + δ. In the generalized hyperbola model, the parameter β = Θ × α. For the additive utility and double exponential models, A = L × S and B = (1 − L) × S. For the tradeoff model, 𝜃 = Θ + 1