density.circular {circular} | R Documentation |
The function density.circular
computes kernel density estimates
with the given kernel and bandwidth for circular data.
## S3 method for class 'circular': density(x, z, bw, adjust = 1, type = c("K", "L"), kernel = c("vonmises", "wrappednormal"), na.rm = FALSE, from = 0, to = 2 * pi, n = 512, K = 10, ...) ## S3 method for class 'density.circular': print(x, digits = NULL, ...)
x |
the data from which the estimate is to be computed. |
z |
the points where the density is estimated. If missing
equally spaced points are used according to the parameters
from , to and n . |
bw |
the smoothing bandwidth to be used. When the kernel
is vonmises the bandwidth is equal to the concentration
parameter. |
adjust |
the bandwidth used is actually adjust*bw . This
makes it easy to specify values like ``half the default bandwidth''. |
type |
Not Yet Used. |
kernel |
a character string giving the smoothing kernel to be
used. This must be one of "vonmises" or
"wrappednormal" , that are kernels of type "K" . |
na.rm |
logical; if TRUE , missing values are removed from
x . If FALSE any missing values cause an error. |
from, to |
the left and right-most points of the grid at which the density is to be estimated. |
n |
the number of equally spaced points at which the density is to be estimated. |
K |
number of terms to be used in approximating the density. |
digits |
integer indicating the precision to be used. |
... |
further arguments passed to or from other methods. |
an object with class "density.circular"
whose
underlying structure is a list containing the following components.
data |
original dataset. |
x |
the n coordinates of the points where the density is
estimated. |
y |
the estimated density values. |
bw |
the bandwidth used. |
N |
the sample size after elimination of missing values. |
call |
the call which produced the result. |
data.name |
the deparsed name of the x argument. |
has.na |
logical, for compatibility (always FALSE). |
Claudio Agostinelli
Z.D. Bai and C.R. Rao and L.C. Zhao (1988). Kernel Estimators of Density Function of Directional Data, Journal of Multivariate Analysis, 27, 24-39.
J. Klemel"a (2000). Estimation of densities and derivatives of densities with directioinal data, Journal of Multivariate Analysis, 73, 18-40.
V.R. Prayag and A.P. Gore (1990). Density Estimation for Randomly Distributed Circular Objects, Metrika, 1990, 37, 63-69.
P. Hall and G.S. Watson and J. Cabrera (1987). Kernel Density Estimation with Spherical Data, Biometrika, 74, 4, 751–762.
plot.density.circular
and lines.density.circular
x <- rvonmises(n=100, mu=pi, kappa=2) res25 <- density(x, bw=25) plot(res25, points.plot=TRUE, xlim=c(-1.5,1)) res50 <- density(x, bw=25, adjust=2) lines(res50, col=2)