BiasCorrect: Corrects for bias in parameter estimates due to model...
In mcullan/ecic:

Description Usage Arguments Value Examples

Corrects for bias in parameter estimates due to model uncertainty.

1 2	BiasCorrect(n, true, parameters, models, N = 1000, ic = "AIC", genBest = TRUE)

`n:`	Sample size.
`true:`	A string giving the name of the model to generate data from.
`models:`	A string vector of model names for selecting between.
`param:`	A vector of parameters specifying a fitted true model.
`N:`	Number of bootstrap samples.
`ic:`	String giving which information criterion to use (e.g. 'AICc', 'BIC')

: The corrected model parameters.

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data = GenerateData(25, "norm", c(mu = 0.3, sd = 1.2))
models = c("norm0", "norm1", "norm")
ecic = ECIC(data, models, alpha = 0.05, N = 100, ic = "AIC", correct = T)