ssden2: Estimating joint density using smoothing splines

In haodongucsb/edgeSelection: Edge selection

Estimating joint density using smoothing splines

Description

Estimating joint density using smoothing splines

Usage

ssden2(
  formula,
  type = NULL,
  data = list(),
  alpha = 1.4,
  weights = NULL,
  subset,
  na.action = na.omit,
  id.basis = NULL,
  nbasis = NULL,
  seed = NULL,
  domain = as.list(NULL),
  quad = NULL,
  prec = 1e-07,
  maxiter = 30,
  theta2 = NULL,
  w = NULL
)

Arguments

formula	Symbolic description of the model to be fit.
type	List specifying the type of spline for each variable.
data	Optional data frame containing the variables in the model.
alpha	Parameter defining cross-validation score for smoothing parameter selection.
weights	Optional vector of bin-counts for histogram data.
subset	Optional vector specifying a subset of observations to be used in the fitting process.
na.action	Function which indicates what should happen when the data contain NAs.
id.basis	Index of observations to be used as "knots."
nbasis	Number of "knots" to be used.
seed	Seed to be used for the random generation of "knots."
domain	Data frame specifying marginal support of density.
quad	Quadrature for calculating integral. Mandatory if variables other than factors or numerical vectors are involved.
prec	Precision requirement for internal iterations.
maxiter	Maximum number of iterations allowed for internal iterations.
theta2	Parameters for two-way interactions.
w	Optional vector to specify weights for two-way interactions.

haodongucsb/edgeSelection documentation built on May 8, 2022, 4:40 p.m.