LDA.fit: 'LDA.fit' Fits linear discriminant analysis models.
In Displayr/flipMultivariates: Multivariate models

LDA.fit

R Documentation

`LDA.fit` Fits linear discriminant analysis models.

Description

LDA.fit Fits linear discriminant analysis models.

Usage

LDA.fit(
  x,
  grouping,
  prior = proportions,
  tol = 1e-04,
  method = c("moment", "mle"),
  weights = NULL,
  CV = FALSE,
  nu = 5,
  labels = NULL,
  functions.output = FALSE,
  ...
)

Arguments

`x`	A matrix or data frame of explanatory variables.
`grouping`	A variable containg the group memberships (i.e., to be predicted or explained by x).
`prior`	The assumed probability of each value of y occurring in the population. By default this is set to "observed" and the value is computed based on the observed data. If set to "constant" the prior will be set to be equal for each group (this is the default in SPSS). Alternatively, a vector of probabilities can be provided.
`tol`	Tolerance to decide if a matrix is singular.
`method`	The method used to estimate the variance; either `"moment"` for the method of moments or `"mle"` for maximum likelihood estimaion.
`weights`	An optional vector of sampling weights.
`CV`	Not used.
`nu`	the number of left singular vectors to be computed.
`labels`	The labels of the predictor variables.
`functions.output`	Logical; whether the discriminant functions are the required output of `LDA`.
`...`	Additional arguments.