kader (version 0.0.8)

fnhat_SS2011: (Non-robust) Kernel Density Estimator of Srihera & Stute (2011)

Description

Implementation of eq. (1.6) in Srihera & Stute (2011) for given and fixed scalars \(\sigma\) and \(\theta\) (and, of course, for fixed and given location(s) in \(x\), data \((X_1, \ldots, X_n)\), a kernel function \(K\) and a bandwidth \(h\)).

Usage

fnhat_SS2011(x, data, K, h, theta, sigma)

Arguments

x

Numeric vector with the location(s) at which the density estimate is to be computed.

data

Numeric vector \((X_1, \ldots, X_n)\) of the data from which the estimate is to be computed. Missing or infinite values are not allowed and entail an error.

K

A kernel function to be used for the estimator.

h

Numeric scalar for bandwidth \(h\).

theta

Numeric scalar for value of location parameter \(\theta\).

sigma

Numeric scalar for value of scale parameter \(\sigma\).

Value

An object with class "density" whose underlying structure is a list containing the following components (as described in density), so that the print and plot methods for density-objects are immediately available):

x	the n coordinates of the points where the density is estimated.
y	the estimated density values from eq. (1.6) in Srihera & Stute (2011).
bw	the bandwidth used.
n	the sample size. (Recall: missing or infinite values are not allowed here.)
call	the call which produced the result.
data.name	the deparsed name of the x argument.
has.na	logical, for compatibility (always FALSE).
	Additionally:
	theta
as in Arguments.	sigma
as in Arguments.	x

Details

The formula upon which the computational version implemented here is based is given in eq. (15.3) of Eichner (2017). This function does mainly only a simple preparatory computation and then calls compute_fnhat which does the actual work.

References

Srihera & Stute (2011) and Eichner (2017): see kader.

See Also

fnhat_ES2013.

Examples

# NOT RUN {
require(stats);   require(grDevices);    require(datasets)

 # Simulated N(0,1)-data and one sigma-value
set.seed(2017);     n <- 100;     d <- rnorm(n)
xgrid <- seq(-4, 4, by = 0.1)
(fit <- fnhat_SS2011(x = xgrid, data = d, K = dnorm, h = n^(-1/5),
  theta = mean(d), sigma = 1))
# }
# NOT RUN {
plot(fit, ylim = range(0, dnorm(0), fit$y), col = "blue")
curve(dnorm, add = TRUE);   rug(d, col = "red")
legend("topleft", lty = 1, col = c("blue", "black", "red"),
  legend = expression(tilde(f)[n], phi, "data")) 
# }
# NOT RUN {
 # The same data, but several sigma-values
sigmas <- seq(1, 4, length = 4)
(fit <- lapply(sigmas, function(sig)
  fnhat_SS2011(x = xgrid, data = d, K = dnorm, h = n^(-1/5),
    theta = mean(d), sigma = sig)))

ymat <- sapply(fit, "[[", "y")
matplot(x = xgrid, y = ymat, type = "l", lty = 1, col = 3:6,
  ylim = range(0, dnorm(0), ymat), main = "", xlab = "", ylab = "Density")
curve(dnorm, add = TRUE);   rug(d, col = "red")
legend("topleft", lty = 1, col = c("black", "red", NA), bty = "n",
  legend = expression(phi, "data", tilde(f)[n]~"in other colors")) 
# }
# NOT RUN {
 # Old-Faithful-eruptions-data and several sigma-values
d <- faithful$eruptions;     n <- length(d);     er <- extendrange(d)
xgrid <- seq(er[1], er[2], by = 0.1);    sigmas <- seq(1, 4, length = 4)
(fit <- lapply(sigmas, function(sig)
   fnhat_SS2011(x = xgrid, data = d, K = dnorm, h = n^(-1/5),
     theta = mean(d), sigma = sig)))

ymat <- sapply(fit, "[[", "y");     dfit <- density(d, bw = "sj")
plot(dfit, ylim = range(0, dfit$y, ymat), main = "", xlab = "")
rug(d, col = "red")
matlines(x = xgrid, y = ymat, lty = 1, col = 3:6)
legend("top", lty = 1, col = c("black", "red", NA), bty = "n",
  legend = expression("R's est.", "data", tilde(f)[n]~"in other colors")) 
# }