dlg_marginal_wrapper: Marginal estimates for multivariate data
In lg: Locally Gaussian Distributions: Estimation and Methods

Description Usage Arguments Details Value Examples

Estimates the marginal locally Gaussian parameters for a multivariate data set

1	dlg_marginal_wrapper(data_matrix, eval_matrix, bw_vector)

`data_matrix`	The matrix of data points. One column constitutes an observation vector.
`eval_matrix`	The matrix of evaluation points. One column constitutes a vector of grid points.
`bw_vector`	The vector of bandwidths, one element per component.

This function takes in a matrix of observations, a matrix of evaluation points and a vector of bandwidths, and does a locally Gaussian fit on each of the marginals using the dlg_bivariate-function. This function assumes that the data and evaluation points are organized column-wise in matrices, and that the bandwidth is found in the corresponding element in the bandwidth matrix. The primary use for this function is multivariate density estimation using the "5par_marginals_fixed"-method.

A list with marginal parameter and density estimates as provided by the dlg_bivariate-function. One element per column in the data.

  data_matrix <- cbind(rnorm(100), rnorm(100))
  eval_matrix <- cbind(seq(-4, 4, 1), seq(-4, 4, 1))
  bw <- c(1, 1)

  estimate <- dlg_marginal_wrapper(data_matrix, eval_matrix = eval_matrix, bw = bw)