confint.lpdensity: Confint Method for Local Polynomial Density Estimation and Inference

Description

The confint method for local polynomial density objects.

Usage

# S3 method for lpdensity
confint(object, parm = NULL, level = NULL, ...)

Value

A matrix containing grid points and confidence interval end points using p- and q-th order local polynomials.

Arguments

object: Class "lpdensity" object, obtained by calling lpdensity.
parm: Integer, indicating which parameters are to be given confidence intervals.
level: Numeric scalar between 0 and 1, the significance level for computing confidence intervals
...: Additional options, including (i) grid specifies a subset of grid points to display the bandwidth; (ii) gridIndex specifies the indices of grid points to display the bandwidth (this is the same as parm); (iii) alpha specifies the significance level (this is 1-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.

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

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

Examples

Run this code

# Generate a random sample
set.seed(42); X <- rnorm(2000)

# Estimate density and report 95% confidence intervals
est1 <- lpdensity(data = X, bwselect = "imse-dpi")
confint(est1)

# Report results for a subset of grid points
confint(est1, parm=est1$Estimate[4:10, "grid"])
confint(est1, grid=est1$Estimate[4:10, "grid"])
confint(est1, gridIndex=4:10)

# Report the 99% uniform confidence band
# Fix the seed for simulating critical values
set.seed(42); confint(est1, level=0.99, CIuniform=TRUE)
set.seed(42); confint(est1, alpha=0.01, CIuniform=TRUE)