evaluate_solution

0th

Percentile

Evaluate MSE Equation

The function computes the mean squared error for a given treatment assignment. More precisely: it computes the mean squared error of the treatment effect estimator resulting from the treatment groups as specified by the argument, the treatment assignment vector. The function uses matrix multiplication and the Moore-Penrose generalized inverse.

Keywords
treatment, optim, Assignment, MSE
Usage
evaluate_solution(par, data)
Arguments
par

a treatment assignment. The treatment and the data must have the same number of observations (rows).

data

a dataframe containing the covariate vectors for each attribute.

Value

Returns the mean squared error value for the current treatment assignment.

References

Schneider and Schlather (2017),

See Also

ginv

Aliases
  • evaluate_solution
Examples
# NOT RUN {
input <- data.frame(c(10, 20, 30, 40, 130, 40, 120, 5, 10, 80),
                    c(2, 6, 2, 8, 1, 10, 9, 8, 7, 5),
                    c(1, 0, 2, 1, 0, 1, 0, 2, 1, 0))
colnames(input) <- c("IQ", "grade_maths", "both_parents")

evaluate_solution(par = c(0, 1, 1, 1, 1, 0, 0, 0, 0, 0),
                  input)
# }
Documentation reproduced from package minMSE, version 0.1.1, License: GNU General Public License

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