Description Usage Arguments Value Author(s) References See Also Examples

View source: R/density.circular.R

The function `density.circular`

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

1 2 3 4 5 6 7 | ```
## 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 |

`z` |
the points where the density is estimated. If |

`bw` |
the smoothing bandwidth to be used. When the |

`adjust` |
the bandwidth used is actually |

`type` |
Not Yet Used. |

`kernel` |
a character string giving the smoothing kernel to be
used. This must be one of |

`na.rm` |
logical; if |

`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 |

`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 ( |

`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 |

`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 |

`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`

1 2 3 4 5 6 7 8 | ```
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
``` |

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