minMSE (version 0.5.1)

evaluate_solution: Evaluate MSE Equation

Description

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.

Usage

evaluate_solution(treatment, data, mse_weights = NULL)

Arguments

treatment

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

data

a matrix containing the covariate vectors for each attribute.

mse_weights

not used, needed for compatibility.

Value

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

References

Schneider and Schlather (2017),

See Also

ginv

Examples

Run this code
# NOT RUN {
input <- matrix(1:30, nrow = 10, ncol = 3)

evaluate_solution(treatment = c(0, 1, 1, 1, 1, 0, 0, 0, 0, 0),
                  input)
# }

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