ICglm (version 0.1.0)

KIC: Kullback<U+2013>Leibler Information Criterion

Description

Calculates Kullback<U+2013>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

Value

KIC measurement of the model

Details

KIC (Seghouane, 2006) is calculated as

$$-2LL(theta) + 3k$$

and KICC (Seghouane, 2006) is calculated as

$$-2LL(theta) + ((k + 1)(3n - k - 2)) + (k/(n-k))$$

References

Seghouane, A. K. (2006). A note on overfitting properties of KIC and KICC. Signal Processing, 86(10), 3055-3060.

Examples

# NOT RUN {
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)

# }