summary.lpcde: Summary method for local polynomial density conditional estimation

Description

The summary method for local polynomial conditional density objects.

Usage

# S3 method for lpcde
summary(object, ...)

Value

Display output: A list of specified options and a matrix of grid points and estimates.

Arguments

object: Class "lpcde" object, obtained from calling lpcde.
...: Additional options, including (i)y_grid specifies a subset of grid points in y- directions to display results; (ii) gridIndex specifies the indices of grid points to display results; (iii) alpha specifies the significance level; (iv) CIuniform specifies whether displaying pointwise confidence intervals (FALSE, default) or the uniform confidence band (TRUE); (v) CIsimul specifies the number of simulations used to construct critical values (default is 2000).

Author

Matias D. Cattaneo, Princeton University. cattaneo@princeton.edu.

Rajita Chandak (maintainer), Princeton University. rchandak@princeton.edu

Michael Jansson, University of California Berkeley. mjansson@econ.berkeley.edu.

Xinwei Ma, University of California San Diego. x1ma@ucsd.edu.

Examples

Run this code

n=100
x_data = as.matrix(rnorm(n, mean=0, sd=1))
y_data = as.matrix(rnorm(n, mean=0, sd=1))
y_grid = stats::quantile(y_data, seq(from=0.1, to=0.9, by=0.1))
# density estimation
model1 = lpcde::lpcde(x_data=x_data, y_data=y_data, y_grid=y_grid, x=0, bw=0.5)
summary(model1)