wdkll_cdf: Weighted Double Kernel Local Linear Estimation of Coditional...

In ygeunkim/ceshat: Nonparametric Estimation of Conditional Expected Shortfall

Description

This function estimates conditional CDF using WDKLL method.

Usage

wdkll_cdf(
  formula,
  data,
  wt,
  nw_kernel = c("Gaussian", "Epanechinikov", "Tricube", "Boxcar"),
  nw_h,
  pdf_kernel = c("Gaussian", "Epanechinikov", "Tricube", "Boxcar"),
  h0,
  init = 0,
  eps = 1e-05,
  iter = 1000
)

Arguments

formula	an object class formula.
data	an optional data to be used.
wt	weights for WNW. Computing in prediction step will help efficiency.
nw_kernel	Kernel for weighted nadaraya watson
nw_h	Bandwidth for WNW
pdf_kernel	Kernel for initial estimate of conditinal pdf
h0	Bandwidth for pdf kernel
init	initial value for finding lambda
eps	small value
iter	maximum iteration when finding lambda

Details

\hat{F}_c(y \mid x) = ∑_{t = 1}^n W_{c,t} G_{h_0} (y - Y_t)

Value

Conditional CDF function with argument y and x

References

Cai, Z., & Wang, X. (2008). Nonparametric estimation of conditional VaR and expected shortfall. Journal of Econometrics, 147(1), 120-130.

ygeunkim/ceshat documentation built on Dec. 16, 2019, 12:39 p.m.