circfit: Maximum-Likelihood Fitting of the von Mises Distribution.

In circmax: Circular Regression with Maximum Likelihood Estimation and Regression Trees

Description

The function circfit carries out maximum-likelihood estimation of parameters for the von Mises distribution.

Usage

  circfit(y, x = NULL, start = NULL, subset = NULL, na.action = NULL,
    weights = NULL, offset = NULL, ...,
    vcov = TRUE, estfun = TRUE, object = FALSE, fit_control = circfit_control())

Arguments

y	Numeric vector of the response.
x	Covariates not supported. Use circmax instead.
start	Starting values of distribution parameters used in the optimization. Currently, not supported.
subset	An optional vector specifying a subset of observations to be used for fitting. Currently, not supported.
na.action	A function which indicates what should happen when the data contain NAs. Currently, not supported.
weights	Optional numeric vector of case weights.
offset	Optional numeric vector with a priori known component to be included in the linear predictor for the location. Currently, not supported.
vcov	Logical. Specifies whether or not a variance-covariance matrix should be calculated and returned.
estfun	Logical. Should the matrix of observation-wise score contributions be returned?
object	Logical. If true, the fitted model is returned.
fit_control	A list of control parameters passed to optim in circfit. Default is circfit_control()
...	Further arguments passed to mob. Really?

Details

The function circfit fits a von Mises distribution to the data. The resulting object of class circfit comes with a set of standard methods to generic functions including coef, estfun, vcov, predict and logLik.

See Also

circtree, optim

circmax documentation built on May 2, 2019, 5:16 p.m.