summary.lpcde {lpcde}

Summary method for local polynomial density conditional estimation

Description

The summary method for local polynomial conditional density objects.

Usage

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

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).

Value

Display output

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

Author(s)

Matias D. Cattaneo, Princeton University. [e-mail].

Rajita Chandak (maintainer), Princeton University. [e-mail]

Michael Jansson, University of California Berkeley. [e-mail].

Xinwei Ma, University of California San Diego. [e-mail].

See Also

lpcde for local polynomial conditional density estimation. Supported methods: coef.lpcde, confint.lpcde, plot.lpcde, print.lpcde, summary.lpcde, vcov.lpcde

Examples

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)