powered by
Density of some circular distributions.
dvm(x, m, k, rads = FALSE, logden = FALSE) dspml(x, mu, rads = FALSE, logden = FALSE) dwrapcauchy(x, m, rho, rads = FALSE, logden = FALSE) dcircpurka(x, m, a, rads = FALSE, logden = FALSE) dggvm(x, param, rads = FALSE, logden = FALSE) dcircbeta(x, m, a, b, rads = FALSE, logden = FALSE) dcardio(x, m, rho, rads = FALSE, logden = FALSE)
A vector with the (log) density values of x.
A vector with circular data.
The mean value of the von Mises distribution and of the cardioid, a scalar. This is the median for the circular Purkayastha distribution.
The mean vector, a vector with two values for the "spml" and with
The concentration parameter.
The \(rho\) parameter of the wrapped Cauchy distribution.
The \(alpha\) parameter of the circular Purkayastha distribution or the \(alpha\) parameter of the circular beta distribution.
The \(\beta\) parameter of the circular beta distribution.
The vector of parameters of the GGVM distribution as returned by the function ggvm.mle.
ggvm.mle
If the data are in rads, then this should be TRUE, otherwise FALSE.
If you the logarithm of the density values set this to TRUE.
Michail Tsagris
R implementation and documentation: Michail Tsagris mtsagris@uoc.gr
The density of the von Mises, bivariate projected normal, wrapped Cauchy or the circular Purkayastha distributions is computed.
Mardia, K. V. and Jupp, P. E. (2000). Directional statistics. Chicester: John Wiley & Sons.
dkent, rvonmises, desag
x <- rvonmises(500, m = 2.5, k = 10, rads = TRUE) mod <- circ.summary(x, rads = TRUE, plot = FALSE) den <- dvm(x, mod$mesos, mod$kappa, rads = TRUE, logden = TRUE ) mod$loglik sum(den)
Run the code above in your browser using DataLab