calculate_errors: Calculate error metrics

In andreaskapou/mpgex: Methylation Profiles predict Gene Expression

Description

calculate_errors calculates error metrics so as to assess the performance of a model, e.g. linear regression.

Usage

calculate_errors(x, y, summary = FALSE)

Arguments

x	Actual values.
y	Predicted values.
summary	Logical, indicating if the erorr metrics should be printed.

Value

A list containing the following components:

• mae mean absolute error.

• mse mean squared error (the variance).

• rmse root mean squared error (std dev).

• mape mean absolute percentage error.

• rstd relative standard deviation.

Examples

# Example data
actual <- c(4, 6, 9, 10, 4, 6, 4, 7, 8, 7)
predicted <- c(5, 6, 8, 10, 4, 8, 4, 9, 8, 9)

calculate_errors(actual, predicted, summary = TRUE)

andreaskapou/mpgex documentation built on May 12, 2019, 3:33 a.m.