run_model: run_model

In linea: Linear Regression Interface

run_model

Description

Run a linear regression model

Usage

run_model(
  data = NULL,
  dv = NULL,
  ivs = NULL,
  trans_df = NULL,
  id_var = NULL,
  pool_var = NULL,
  model_table = NULL,
  verbose = FALSE,
  normalise_by_pool = FALSE,
  save_all_raw_data = TRUE,
  decompose = TRUE,
  tail_window = NULL,
  categories = NULL
)

Arguments

data	data.frame containing variables included in the model specification
dv	string of the dependent variable name
ivs	character vector of the independent variables names
trans_df	data.frame defining the non-linear transformations to apply
id_var	string of id variable name (e.g. date)
pool_var	string specifying the pool variable name (e.g. 'country')
model_table	data.frame as created in the build_model_table function
verbose	A boolean to specify whether to print warnings
normalise_by_pool	A boolean to specify whether to apply the normalisation
save_all_raw_data	A boolean to specify whether to save whole input data to the model object
decompose	A boolean to specify whether to generate the model decomposition
tail_window	for time series, length of tail in decomposition
categories	data.frame mapping variables to groups

Details

Run a linear regression model that captures the transformations applied in the model_table and the normalisation based on the pool_var. A model can be run also by only supplying a dependent variable name dv, a vector of independent variable names dependent variable ivs, and the data that contains these.

Value

Model object

Examples

trans_df = data.frame(
    name = c('diminish', 'decay', 'hill', 'exp'),
    func = c(
      'linea::diminish(x,a)',
      'linea::decay(x,a)',
      "linea::hill_function(x,a,b,c)",
      '(x^a)'
    ),
    order = 1:4
)

data = read_xcsv("https://raw.githubusercontent.com/paladinic/data/main/ecomm_data.csv")
dv = 'ecommerce'
ivs = c('christmas','black.friday')

run_model(data = data,
          dv = dv,
          ivs = ivs,
          trans_df = trans_df)

run_model(data = mtcars,dv = 'mpg',ivs = c('disp','cyl'))

linea documentation built on Sept. 15, 2022, 9:06 a.m.