Description Usage Arguments Details Value References
This function estimates conditional pdf using WDKLL method.
1 2 3 4 5 6 7 8 9 10 11 |
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 |
h0 |
Binwidth |
init |
initial value for finding lambda |
eps |
small value |
iter |
maximum iteration when finding lambda |
Since standalone LL or WNW does not fully satisfy the conditions of cdf, Cai et al (2008) proposed to use WNW in LL scheme.
\hat{f}_c(y \mid x) = ∑_{t = 1}^n W_{c,t}(w, h) K_{h_0}(y - Y_t)
Conditional pdf function of (y, x)
. y
can be a numeric vector.
Cai, Z., & Wang, X. (2008). Nonparametric estimation of conditional VaR and expected shortfall. Journal of Econometrics, 147(1), 120-130.
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