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Computes the maximum likelihood estimates for the parameters of a Wrapped Normal distribution: mean and concentration parameter.
mle.wrappednormal(x, mu = NULL, rho = NULL, sd = NULL, K = NULL, tol = 1e-05, min.sd = 1e-3, min.k = 10, max.iter = 100, verbose = FALSE, control.circular=list()) # S3 method for mle.wrappednormal print(x, digits = max(3, getOption("digits") - 3), ...)
Returns a list with the following components:
the match.call result.
match.call
the estimate of the mean direction or the value supplied as an object of class circular.
circular
the estimate of the concentration parameter or the value supplied
the estimate of the standard deviation or the value supplied.
TRUE if the estimator is reported.
TRUE if the convergence is achieved.
a vector. The object is coerced to class circular.
if NULL the maximum likelihood estimate of the mean direction is calculated, otherwise the value is coerced to an object of class circular.
NULL
if NULL the maximum likelihood estimate of the concentration parameter is calculated.
standard deviation of the (unwrapped) normal. Used as an alternative parametrization.
number of terms to be used in approximating the density.
precision of the estimation.
minimum value should be reached by the search procedure for the standard deviation parameter.
minimum number of terms used in approximating the density.
maximum number of iterations.
logical, if TRUE information on the convergence process are printed.
TRUE
the attribute of the resulting objects (mu)
mu
integer indicating the precision to be used.
further arguments passed to or from other methods.
Claudio Agostinelli with a bug fix by Ana Nodehi
Jammalamadaka, S. Rao and SenGupta, A. (2001). Topics in Circular Statistics, Section 4.2.1, World Scientific Press, Singapore.
mean.circular
x <- rwrappednormal(n=50, mu=circular(0), rho=0.5) mle.wrappednormal(x) # estimation of mu and rho (and sd) mle.wrappednormal(x, mu=circular(0)) # estimation of rho (and sd) only
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