twFSA {rFSA}

twFSA

Description

A function for termwise feasiblity

Usage

twFSA(
  formula,
  data,
  fitfunc = lm,
  fixvar = NULL,
  quad = FALSE,
  cores = 1,
  criterion = AIC,
  minmax = "min",
  checkfeas = NULL,
  var4int = NULL,
  min.nonmissing = 1,
  ...
)

Arguments

formula

an object of class "formula" (or one that can be coerced to that class): a symbolic description of the model to be fitted.

data

a data frame, list or environment (or object coercible by as.data.frame to a data frame) containing the variables in the model.

fitfunc

the method that should be used to fit the model. For Example: lm, glm, or other methods that rely on formula, data, and other inputs.

fixvar

variable(s) to fix in the model. Usually a covariate that should always be included (Example: Age, Sex). Will still consider it with interactions. Default is NULL.

quad

Include quadratic terms or not. Logical.

cores

number of cores to use while running. Note: Windows can only use 1 core. See mclapply for details. If function detects a Windows user it will automatically set cores=1.

criterion

which criterion function to either maximize or minimize. For linear models one can use: r.squared, adj.r.squared, cv5.lmFSA (5 Fold Cross Validation error), cv10.lmFSA (10 Fold Cross Validation error), apress (Allen's Press Statistic), int.p.val (Interaction P-value), AIC, BIC.

minmax

whether to minimize or maximize the criterion function

checkfeas

vector of variables that could be a feasible solution. These variables will be used as the last random start.

var4int

specification of which variables to check for marginal feasiblilty. Default is NULL

min.nonmissing

the combination of predictors will be ignored unless this many of observations are not missing

...

other arguments passed to fitfunc.

Value

matrix of results