Given a set of smooth and continuous functions, computes predefined and user-defined measures.
compute_measures_aux(
x_grids,
coeffs,
ids,
ndx = 20,
deg = 6,
measures = c("risk-arrow-pratt", "crainich-eeckhoudt", "denuit-eeckhoudt"),
...
)
a dataframe of vectors of x-values for a smooth and continuous function.
a dataframe of coefficients for a smooth and continuous function for each participant.
a list containing the IDs of the participants. If not given, a list with IDs from 1 to n_observations will be created.
number of intervals to partition the distance between the lowest and highest x-values of the utility points.
degree of the B-spline basis. Determines the degree of the function to be estimated. If deg = 2, the estimated utility function will consist of quadratic functions.
a vector of measures to be computed.
additional parameters for user-defined measures.
A set of measurements.