lg (version 0.4.1)

dlg_marginal: Marginal density estimation

Description

Function that estimates a univariate density estimation by local Gaussian approximations, as described in Hufthammer and Tj<U+00F8>stheim (2009).

Usage

dlg_marginal(x, bw = 1, eval_points = seq(quantile(x, 0.01),
  quantile(x, 0.99), length.out = grid_size), grid_size = 15)

Arguments

x

The data vector.

bw

The bandwidth (a single number).

eval_points

The grid where we want to evaluate the density. Chosen suitably if not provided, with length equal to grid_size.

grid_size

Number of grid points if grid is not provided.

Value

A list including the data set $x, the grid $eval_points, the bandwidth $bw, as well as a matrix of the estimated parameter estimates $par_est and the estimated bivariate density $f_est.

Details

This function is mainly mean to be used as a tool in multivariate analysis as away to obtain the estimate of a univariate (marginal) density function, but it can of course be used in general to estimate univariate densities.

References

Hufthammer, Karl Ove, and Dag Tj<U+00F8>stheim. "Local Gaussian Likelihood and Local Gaussian Correlation" PhD Thesis of Karl Ove Hufthammer, University of Bergen, 2009.

Examples

# NOT RUN {
  x <- rnorm(100)
  estimate <- dlg_marginal(x, bw = 1, eval_points = -4:4)

# }