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Model Selection - Based on BIC or Log-Likelihood

Source: R/quackit.R
quackit.Rd

This function is for model interpretation.

Usage

quackit(
  model_out,
  summary_statistic = "BIC",
  mixtures = c("diploid", "triploid", "tetraploid", "hexaploid", "pentaploid")
)

Arguments

model_out

Data frame containing, at minimum, columns labeled LL, type, mixture, distribution, and BIC.

summary_statistic

May be equal to BIC or dLL.

mixtures

Defaults to c("diploid", "triploid", "tetraploid", "hexaploid", "pentaploid").

Value

Returns data frame with the most likely model for each set of mixtures. Includes the best and second best mixtures, as well as the difference between the two.