circular: density.circular – R documentation

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density.circular

Kernel Density Estimation for Circular Data

Description

The function density.circular computes kernel density estimates with the given kernel and bandwidth for circular data.

Usage

## 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, ...)

Arguments

`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.

Value

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).

Author(s)

Claudio Agostinelli

References

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.

Examples

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)
lines(res50, col=3, shrink=0.9) #shrink the plot wrt the function :-)
lines(res50, col=4, offset=0.5) #draw it with a reference circle of 0.5

circular

Circular Statistics

v0.4-93

GPL-2

Authors

Ulric Lund <ulund@calpoly.edu> [aut], Claudio Agostinelli <claudio.agostinelli@unitn.it> [aut, cre], Hiroyoshi Arai <h_arai@aoni.waseda.jp> [ctb], Alessando Gagliardi <gagliardi@stud.unive.it> [ctb], Eduardo Garcia Portugues <edgarcia@est-econ.uc3m.es> [ctb], Dimitri Giunchi <dimitri.giunchi@unipi.it> [ctb], Jean-Olivier Irisson <irisson@normalesup.org> [ctb], Matthew Pocernich <pocernic@ucar.edu> [ctb], Federico Rotolo [ctb]

Initial release

2017-06-26