KIC {ICglm} | R Documentation |
Kullback–Leibler Information Criterion
Description
Calculates Kullback–Leibler Information Criterion (KIC) and its corrected form (KICC) for "lm" and "glm" objects.
Usage
KIC(model)
KICC(model)
Arguments
model |
a "lm" or "glm" object |
Details
KIC (Seghouane, 2006) is calculated as
-2LL(theta) + 3k
and KICC (Seghouane, 2006) is calculated as
-2LL(theta) + ((k + 1)(3n - k - 2)) + (k/(n-k))
Value
KIC measurement of the model
References
Seghouane, A. K. (2006). A note on overfitting properties of KIC and KICC. Signal Processing, 86(10), 3055-3060.
Examples
x1 <- rnorm(100, 3, 2)
x2 <- rnorm(100, 5, 3)
x3 <- rnorm(100, 67, 5)
err <- rnorm(100, 0, 4)
## round so we can use it for Poisson regression
y <- round(3 + 2*x1 - 5*x2 + 8*x3 + err)
m1 <- lm(y~x1 + x2 + x3)
m2 <- glm(y~x1 + x2 + x3, family = "gaussian")
m3 <- glm(y~x1 + x2 + x3, family = "poisson")
KIC(m1)
KIC(m2)
KIC(m3)
KICC(m1)
KICC(m2)
KICC(m3)
[Package ICglm version 0.1.0 Index]