SAVF_preferred_rho: Identify preferred rho

In koalaverse/KraljicMatrix: A Quantified Implementation of the Kraljic Matrix

Description

SAVF_preferred_rho computes the preferred rho that minimizes the squared error between subject matter input desired values and exponentially fitted scores

Usage

SAVF_preferred_rho(desired_x, desired_v, x_low, x_high, rho_low = 0,
  rho_high = 1)

Arguments

desired_x	Elicited input x value(s)
desired_v	Elicited value score related to elicited input value(s)
x_low	Lower bound anchor point (can be different than min(x))
x_high	Upper bound anchor point (can be different than max(x))
rho_low	Lower bound of the exponential constant search space for a best fit value function
rho_high	Upper bound of the exponential constant search space for a best fit value function

Value

A single element vector that represents the rho value that best fits the exponential utility function to the desired inputs

See Also

SAVF_plot_rho_error for plotting the rho squared error terms

SAVF_score for computing the exponential single attribute value score

Examples

# Given the single attribute x is bounded between 1 and 5 and the subject matter experts
# prefer x values of 3, 4, & 5 provide a utility score of .75, .90 & 1.0 respectively, we
# can search for a rho value between 0-1 that provides the best fit utility function:

SAVF_preferred_rho(desired_x = c(3, 4, 5),
                   desired_v = c(.75, .9, 1),
                   x_low = 1,
                   x_high = 5,
                   rho_low = 0,
                   rho_high = 1)

koalaverse/KraljicMatrix documentation built on May 25, 2019, 9:30 p.m.