Computes a confidence interval for a population mean absolute prediction error (MAPE) in a general linear model. The MAPE is a more robust alternative to the residual standard deviation. This function requires a vector of estimated residuals from a general linear model. This confidence interval does not assume zero excess kurtosis but does assume symmetry of the population prediction errors.
ci.mape(alpha, res, s)alpha level for 1-alpha confidence
vector of residuals
number of predictor variables in model
Returns a 1-row matrix. The columns are:
Estimate - estimated mean absolute prediction error
SE - standard error
LL - lower limit of the confidence interval
UL - upper limit of the confidence interval
res <- c(-2.70, -2.69, -1.32, 1.02, 1.23, -1.46, 2.21, -2.10, 2.56,
-3.02, -1.55, 1.46, 4.02, 2.34)
ci.mape(.05, res, 1)
#> Estimate SE LL UL
#> 2.3744 0.3314752 1.806022 3.121654
# Should return:
# Estimate SE LL UL
# 2.3744 0.3314752 1.751678 3.218499