IC {ICglm}

Information Criteria

Description

Calculates Various Information Criteria for "lm" and "glm" objects.

Usage

IC(
  model,
  criteria = c("AIC", "BIC", "CAIC", "KIC", "HQIC", "FIC", "ICOMP_IFIM_C1",
    "ICOMP_PEU_C1", "ICOMP_PEU_LN_C1", "CICOMP_C1"),
  ...
)

Arguments

model

a "lm" or "glm" object or object list

criteria

a vector of criteria names. Can be set to respective numbers. Possible criteria names at the moment are:
1 = "AIC"
2 = "AIC4"
3 = "BIC"
4 = "BICadj"
5 = "BICQ"
6 = "CAIC"
7 = "CAICF"
8 = "FIC"
9 = "GCV"
10 = "HBIV"
11 = "GQIC"
12 = "IBIC"
13 = "ICOMP_IFIM_CF"
14 = "ICOMP_IFIM_C1"
15 = "ICOMP_IFIM_C1F"
16 = "ICOMP_IFIM_C1R"
17 = "ICOMP_PEU_CF"
18 = "ICOMP_PEU_C1"
19 = "ICOMP_PEU_C1F"
20 = "ICOMP_PEU_C1R"
21 = "ICOMP_PEU_LN_CF"
22 = "ICOMP_PEU_LN_C1"
23 = "ICOMP_PEU_LN_C1F"
24 = "ICOMP_PEU_LN_C1R"
25 = "CICOMP_CF"
26 = "CICOMP_C1"
27 = "CICOMP_C1F"
28 = "CICOMP_C1R"
29 = "JIC"
30 = "KIC"
31 = "KICC"
32 = "SPBIC"

...

additional parameters. Currently none.

Details

Calculates Various Information Criteria for "lm" and "glm" objects. model can be a list. If it is a list, function returns a matrix of selected information criteria for all models.

Value

Information criteria of the model(s) for selected criteria

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")

IC(model = m1, criteria = 1:32)
IC(model = list(lm = m1,
               glm = m2,
               glm_pois = m3), criteria = 1:32)