| 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=NULL, bw, adjust = 1, type = c("K", "L"),
kernel = c("vonmises", "wrappednormal"), na.rm = FALSE, from = circular(0),
to = circular(2 * pi), n = 512, K = NULL, min.k=10, control.circular=list(), ...)
## S3 method for class 'density.circular':
print(x, digits = NULL, ...)
x |
the data from which the estimate is to be computed. The object is coerced to class circular. |
z |
the points where the density is estimated. If NULL
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. The objects are coerced to class circular. |
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. |
min.k |
minimum number of terms used in approximating the density. |
control.circular |
the attribute of the resulting objects (x component). |
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. It is a circular objects with coordinate system setting using control.circular. |
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=circular(pi), kappa=2) res25 <- density(x, bw=25, control.circular=list(units="degrees")) circularp(res25$x) plot(res25, points.plot=TRUE, xlim=c(-1.6,1)) res50 <- density(x, bw=25, adjust=2) lines(res50, col=2)