| mle.wrappedcauchy {circular} | R Documentation |
Computes the maximum likelihood estimates for the parameters of a Wrapped Cauchy distribution: mean and concentration parameter.
mle.wrappedcauchy(x, mu = NULL, rho = NULL, tol = 1e-15,
max.iter = 100, control.circular = list())
## S3 method for class 'mle.wrappedcauchy':
print(x, digits = max(3, getOption("digits") - 3), ...)
x |
a vector. The object is coerced to class
circular. |
mu |
if NULL the maximum likelihood estimate of the mean
direction is calculated otherwise it is coerced to an object of class circular. |
rho |
if NULL the maximum likelihood estimate of the
concentration parameter is calculated. |
tol |
precision of the estimation. |
max.iter |
maximum number of iterations. |
control.circular |
the attribute of the resulting objects (mu) |
digits |
integer indicating the precision to be used. |
... |
further arguments passed to or from other methods. |
Returns a list with the following components:
call |
the match.call(). |
mu |
the estimate of the mean direction or the value supplied as an object of class circular. |
rho |
the estimate of the concentration parameter or the value supplied |
convergence |
TRUE if convergence is achieved. |
Claudio Agostinelli and Ulric Lund
Jammalamadaka, S. Rao and SenGupta, A. (2001). Topics in Circular Statistics, Section 4.2.1, World Scientific Press, Singapore.
x <- rwrappedcauchy(n=50, mu=circular(0), rho=0.5) mle.wrappedcauchy(x) # estimation of mu and rho mle.wrappedcauchy(x, mu=circular(0)) # estimation of rho only