wnw_cdf: Weighted Nadaraya Watson Estimator of Coditional CDF

In ygeunkim/ceshat: Nonparametric Estimation of Conditional Expected Shortfall

Description

This function estimates conditional CDF by WNW.

Usage

wnw_cdf(
  formula,
  data,
  wt,
  nw_kernel = c("Gaussian", "Epanechinikov", "Tricube", "Boxcar"),
  nw_h,
  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
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} I (Y_t ≤ y)

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.