*! v1.0.0 IHSalgado-Ugarte 04July2012
help circkde

Title

circkde -- Performs kernel density estimation for circular data

Syntax

circkde varname [if] [in] [, kc(kernelcode) h(#) genpdf(pdfvar) gendeg(degvar) graph_options]

Description

circkde calculates kernel density estimation for circular variables with azimutal scale (0 to 360 degrees) by means of a discretized procedure (Cox, 1998) and draws the result.

It is possible to choose the kernel function and to specify the smoothing parameter (half-width). Additionally it provides modality (and anti-modality) information.

Options

kc(kernelcode) set kernel (weight) function according to the following numerical codes (default is 6, Gaussian):

1 = Uniform

2 = Triangle

3 = Epanechnikov

4 = Quartic (Biweight)

5 = Triweight

6 = Gaussian

7 = Cosine

h(#) is the smoothness parameter (half-width) in degrees. The default is 30.

numodes display the number of modes (maxima) in the density estimation.

modes lists the estimated values for each mode. The numodes option must
be included first.

nuamodes display the number of antimodes (minima) in the density estimation.

amodes lists the estimated values for each antimode. The nuamodes option must
be included first.

genpdf(pdfvar) specifies the name of a new variable in which probability density estimates are to be stored.

gendeg(degvar) specifies the name of a new variable in which equally spaced angles are to be stored.

graph_options are any of the options allowed with graph, twoway; see help for graph.

Examples

. use circdat

. circkde angles

. circbw angles, k(4)

. circkde angles, h(38) k(4) numodes modes

. circkde angles, h(14.5) nuamodes amodes genpdf(density) gendeg(deg)

Authors

Isaías H. Salgado-Ugarte,
Laboratorio de Biometría y Biología Pesquera, FES Zaragoza, UNAM;
Departamento de Biología UAM Iztapalapa

ihsalgadougarte@gmail.com

References

Cox, N.J. 1998. Circular statistics in Stata. 3rd UK User Group meeting. June 5, 1997. London.

Fisher, N.I. 1993. Statistical analysis of circular data. Cambridge University Press, Cambridge, 296p.

Salgado-Ugarte, I.H. & M.A. Pérez-Hernández, 2017. estimación de densidad por núcleo (kernel) para datos circulares. In: Rodríguez-Yam, G.A., F.J. Araiza-Hernández, B.R. Pérez-Salvador & F. Ulín-Montejo (eds.). Aportaciones Recientes a la Estadística en México. INEGI, Mexico: 518-526. ISBN: 978-607-530-067-2.

Also see

Online: [R] kdensity

Help: Help for circbw, circnpde