evaluate_solution_vector: Evaluate MSE Equation

In minMSE: Implementation of the minMSE Treatment Assignment Method for One or Multiple Treatment Groups

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_vector(treatment, data, mse_weights)

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	a vector containing the mse_weights for each treatment.

Value

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

Author(s)

Sebastian Schneider [e-mail]; [e-mail], Giulia Baldini [e-mail]

References

Schneider and Schlather (2017),

See Also

ginv

Examples

input <- matrix(1:30, nrow = 10, ncol = 3)

evaluate_solution_vector(treatment = c(0, 1, 1, 1, 1, 0, 0, 0, 0, 0),
                         input,
                         mse_weights = c(1, 2))

minMSE documentation built on March 18, 2022, 8:05 p.m.