select_pred function

Selects a best subset of predictor variables.

Selects among a set of covariates the best set of npred

predictors for a given response trait resp based on AIC values.

select_pred(.data, resp, covariates = NULL, npred)

Arguments

• .data: A data frame with the response variable and covariates.
• resp: The response variable.
• covariates: The covariates. Defaults to NULL. In this case, all numeric traits in .data, except that in resp are selected. To select specific covariates from .data, use a list of unquoted comma-separated variable names (e.g. traits = c(var1, var2, var3)), an specific range of variables, (e.g. traits = c(var1:var3)), or even a select helper like starts_with("N").
• npred: An integer specifying the size of the subset of predictors to be selected

Returns

A list with the following elements:

• sel_mod An object of class lm that is the selected model.
• predictors The name of the selected predictors.
• AIC The Akaike's Information Criterion for the selected model.
• pred_models The Akaike's Information Criterion and the predictors selected in each step.
• predicted The predicted values considering the model in sel_mod.

Examples

library(metan)
mod <- select_pred(data_ge2, resp = PH, npred = 10)
mod$predictors
mod$AIC

Author(s)

Tiago Olivoto tiagoolivoto@gmail.com