fit_models: Fit several models with different response variables

In manymodelr: Build and Tune Several Models

Description

Fit several models with different response variables

Usage

fit_models(
  df = NULL,
  yname = NULL,
  xname = NULL,
  modeltype = NULL,
  drop_non_numeric = FALSE,
  ...
)

Arguments

df	A data.frame object
yname	The outcome variable
xname	The predictor variable(s)
modeltype	A character specifying the model type e.g lm for linear model
drop_non_numeric	Should non numeric columns be dropped? Defaults to FALSE
...	Other arguments to specific model types.

Value

A list of model objects that can be used later.

Examples

data("yields", package="manymodelr")
fit_models(df=yields,yname=c("height","yield"),xname="weight",modeltype="lm")
#many model types
fit_models(df=yields,yname=c("height","yield"),xname="weight",
modeltype=c("lm", "glm"))

manymodelr documentation built on Nov. 15, 2021, 5:07 p.m.