sandwich (version 3.1-1)

kweights: Kernel Weights

Description

Kernel weights for kernel-based heteroscedasticity and autocorrelation consistent (HAC) covariance matrix estimators as introduced by Andrews (1991).

Usage

kweights(x, kernel = c("Truncated", "Bartlett", "Parzen",
  "Tukey-Hanning", "Quadratic Spectral"), normalize = FALSE)

Value

Value of the kernel function at x.

Arguments

x

numeric.

kernel

a character specifying the kernel used. All kernels used are described in Andrews (1991).

normalize

logical. If set to TRUE the kernels are normalized as described in Andrews (1991).

References

Andrews DWK (1991). “Heteroskedasticity and Autocorrelation Consistent Covariance Matrix Estimation.” Econometrica, 59, 817--858.

See Also

kernHAC, weightsAndrews

Examples

curve(kweights(x, kernel = "Quadratic", normalize = TRUE),
      from = 0, to = 3.2, xlab = "x", ylab = "k(x)")
curve(kweights(x, kernel = "Bartlett", normalize = TRUE),
      from = 0, to = 3.2, col = 2, add = TRUE)
curve(kweights(x, kernel = "Parzen", normalize = TRUE),
      from = 0, to = 3.2, col = 3, add = TRUE)
curve(kweights(x, kernel = "Tukey", normalize = TRUE),
      from = 0, to = 3.2, col = 4, add = TRUE)
curve(kweights(x, kernel = "Truncated", normalize = TRUE),
      from = 0, to = 3.2, col = 5, add = TRUE)