condLocal: Estimate conditional densities using the LGDE

In hotneim/lgde: Implements the Locally Gaussian Density Estimator

Description

Estimate conditional densities using the LGDE

Usage

condLocal(data, cond, bandwidths = NULL, gsize = 15,
  grid = apply(as.matrix(data[, 1:(dim(data)[2] - length(cond))]), 2,
  function(x) seq(quantile(x, 0.001), quantile(x, 0.999), length.out = gsize)))

Arguments

data	The data matrix, one row per observation.
cond	A vector of values to be conditioned on.
bandwidths	A matrix of bandwidths. Must be in the same format as is produced by the HLocal-function.
gsize	If grid is not provided, the density will be estimated at gsize points going diagonally through the data.
grid	The grid at which to estimate the density. Must be a matrix with the same number of columns as the data matrix.

Value

A list with 1 element: $f.est.cond is the estimated conditional density.

Examples

# Three dimensional example. The conditioning variables must be the last columns in the data matrix.
Estimating the density of X1|X2 = 0, X3 = 0:
data <- cbind(rt(100, df = 10), rt(100, df = 10), rt(100, df = 10))
condLocal(data, cond = c(0,0))

hotneim/lgde documentation built on May 17, 2019, 4:52 p.m.