qvirus (version 0.0.5)

mse: Mean Squared Errors for Interaction Classification

Description

Mean squared errors (MSE) for viral load differences and CD4 count differences by comparing the actual values with the group means from the classification.

Computes the mean squared error (MSE) between observed CD4 and viral load differences and their corresponding predicted payoff values within each interaction classification.

Usage

mse(object, ...)
mse(object, ...)

Value

A data.frame containing the MSE for CD4 count differences (mse_cds_diff) and (mse_vlogs_diff) for viral load differences.

Arguments

object

An object of class payoffs.

...

Additional arguments passed to other methods (currently not used).

Examples

set.seed(42)
data(cd_3)
cd_data <- cd_3[,-1]
cd_result <- cds_diff(cd_data)
data(vl_3)
vl_data <- vl_3[,-1]
vl_result <- vlogs_diff(vl_data)
result <- InteractionClassification(cd_result = cd_result, vl_result = vl_result)
mse(result)

set.seed(42)
data(cd_3)
cd_data <- cd_3[,-1]
cd_result <- cds_diff(cd_data)
data(vl_3)
vl_data <- vl_3[,-1]
vl_result <- vlogs_diff(vl_data)
result <- InteractionClassification(cd_result = cd_result, vl_result = vl_result)
data(preds)
payoffs_results <- estimate_payoffs(result, preds)
mse(payoffs_results)