nonadaptivefence {fence}

Nonadaptive Fence model selection

Description

Nonadaptive Fence model selection

Usage

nonadaptivefence(mf, f, ms, d, lf, pf, cn)

Arguments

mf

function for fitting the model

f

formula of full model

ms

list of formula of candidates models

d

data

lf

measure lack of fit (to minimize)

pf

model selection criteria, e.g., model dimension

cn

given a specific c value

Value

models

list all model candidates in the model space

lack_of_fit

list a vector of Qs for all model candidates

formula

list the model of the selected parsimonious model

sel_model

list the selected (parsimonious) model given the adaptive c value

Author(s)

Jiming Jiang Jianyang Zhao J. Sunil Rao Thuan Nguyen

References

• Jiang J., Rao J.S., Gu Z., Nguyen T. (2008), Fence Methods for Mixed Model Selection. The Annals of Statistics, 36(4): 1669-1692

• Jiang J., Nguyen T., Rao J.S. (2009), A Simplified Adaptive Fence Procedure. Statistics and Probability Letters, 79, 625-629

• Thuan Nguyen, Jie Peng, Jiming Jiang (2014), Fence Methods for Backcross Experiments. Statistical Computation and Simulation, 84(3), 644-662

Examples

## Not run: 
require(fence)

#### Example 1 #####
data(iris)
full = Sepal.Length ~ Sepal.Width + Petal.Length + Petal.Width + (1|Species)
test_naf = fence.lmer(full, iris, fence = "nonadaptive", cn = 12)
test_naf$sel_model

## End(Not run)