ci.mape2 | R Documentation |
Computes a confidence interval for a ratio of population mean absolute prediction errors (MAPEs) from in a general linear model in two independent groups. The number of predictor variables can differ across groups and the two models can be non-nested. This function requires a vector of estimated residuals from each group. This function does not assume zero excess kurtosis but does assume symmetry in the population prediction errors.
ci.mape2(alpha, res1, res2, s1, s2)
alpha |
alpha level for 1-alpha confidence |
res1 |
vector of residuals from group 1 |
res2 |
vector of residuals from group 2 |
s1 |
number of predictor variables used in group 1 |
s2 |
number of predictor variables used in group 2 |
Returns a 1-row matrix. The columns are:
MAPE1 - bias adjusted mean absolute prediction error for group 1
MAPE2 - bias adjusted mean absolute prediction error for group 2
MAPE1/MAPE2 - ratio of bias adjusted mean absolute prediction errors
LL - lower limit of the confidence interval
UL - upper limit of the confidence interval
res1 <- 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)
res2 <- c(-0.71, -0.89, 0.72, -0.35, 0.33 -0.92, 2.37, 0.51, 0.68, -0.85,
-0.15, 0.77, -1.52, 0.89, -0.29, -0.23, -0.94, 0.93, -0.31 -0.04)
ci.mape2(.05, res1, res2, 1, 1)
# Should return:
# MAPE1 MAPE2 MAPE1/MAPE2 LL UL
# [1,] 2.58087 0.8327273 3.099298 1.917003 5.010761
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