compute_higher_order_risk_preferences: Computes a continuous and smooth function according to the...

In utilityFunctionTools: P-Spline Regression for Utility Functions and Derived Measures

Description

Computes a continuous and smooth function according to the given utility points

Usage

compute_higher_order_risk_preferences(
  x,
  y,
  ids = NULL,
  mode = 1,
  penalty_orders = c(4),
  ndx = 20,
  deg = 6,
  measures = c("risk-arrow-pratt", "crainich-eeckhoudt", "denuit-eeckhoudt"),
  ...,
  root_filename = NULL,
  verbose = 0
)

Arguments

x	a matrix or dataframe containing the certainty equivalents (x-values of utility points) for a given participant in each use case.
y	can be a vector or a matrix representing the corresponding utility values (y-values of utility points).
ids	a list containing the IDs of the participants. If not given, a list with IDs from 1 to n_observations will be created.
mode	an integer between 0, 1, 2 representing the three possible modes: multiple imputation, optimal classification or 'weak' classification. Default is optimal classification (1).
penalty_orders	vector or constant that contains the derivates that will be smoothened. The values in this vector should not be larger than 4.
ndx	number of intervals to partition the distance between the lowest and highest x-values of the utility points.
deg	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.
measures	the utility based (intensity) measures to be computed.
...	additional parameters for user-defined measures.
root_filename	filename containing the location of where the output files are going to be saved.
verbose	shows some information while the program is running.

Value

A smooth and continuous function.

Examples

x <- matrix(c(24.60938,34.76074,78.75,81.86035,128.5156, 
              7.109375,80.4248,113.75,115.083,135.0781, 
              3.828125,7.211914,8.75,124.1064,131.7969, 
              1.640625,2.084961,8.75,36.94824,98.98438), nrow = 4, ncol = 5, byrow = TRUE)
y <- c(0.25, 0.375, 0.5, 0.625, 0.75)
compute_higher_order_risk_preferences(x, y, mode = 1)

# could be used with root_filename argument: 
# Linux
# outfile <- paste(dirname(getwd()), "/out", sep="")
# Win
# outfile <- paste(dirname(getwd()), "\out", sep="")
compute_higher_order_risk_preferences(x, y, mode = 2, verbose = 1)

utilityFunctionTools documentation built on March 29, 2021, 5:06 p.m.