Constructor function for the class smimodelFit — new

Constructs an object of class smimodelFit using the information passed to arguments.

Usage

new_smimodelFit(
  data,
  yvar,
  neighbour = 0,
  family = gaussian(),
  index.vars,
  initialise = c("additive", "linear", "userInput"),
  index.ind = NULL,
  index.coefs = NULL,
  s.vars = NULL,
  linear.vars = NULL
)

Arguments

data: Training data set on which models will be trained. Must be a data set of class tsibble.(Make sure there are no additional date or time related variables except for the index of the tsibble).
yvar: Name of the response variable as a character string.
neighbour: neighbour argument passed from the outer function.
family: A description of the error distribution and link function to be used in the model (see glm and family).
index.vars: A character vector of names of the predictor variables for which indices should be estimated.
initialise: The model structure with which the estimation process should be initialised. The default is "additive", where the initial model will be a nonparametric additive model. The other options are "linear" - linear regression model (i.e. a special case single-index model, where the initial values of the index coefficients are obtained through a linear regression), and "userInput" - user specifies the initial model structure (i.e. the number of indices and the placement of index variables among indices) and the initial index coefficients through index.ind and index.coefs arguments respectively.
index.ind: If initialise = "userInput": an integer vector that assigns group index for each predictor in index.vars.
index.coefs: If initialise = "userInput": a numeric vector of index coefficients.
s.vars: A character vector of names of the predictor variables for which splines should be fitted individually (rather than considering as part of an index).
linear.vars: A character vector of names of the predictor variables that should be included linearly into the model.

Value

A list of initial model information. For descriptions of the list elements see make_smimodelFit).