View source: R/family.circular.R
| cardioid | R Documentation |
Estimates the two parameters of the cardioid distribution by maximum likelihood estimation.
cardioid(lmu = extlogitlink(min = 0, max = 2*pi),
lrho = extlogitlink(min = -0.5, max = 0.5),
imu = NULL, irho = 0.3, nsimEIM = 100, zero = NULL)
lmu, lrho |
Parameter link functions applied to the |
imu, irho |
Initial values.
A |
nsimEIM, zero |
See |
The two-parameter cardioid distribution has a density that can be written as
f(y;\mu,\rho) = \frac{1}{2\pi}
\left(1 + 2\, \rho \cos(y - \mu) \right)
where 0 < y < 2\pi,
0 < \mu < 2\pi, and
-0.5 < \rho < 0.5 is the concentration
parameter.
The default link functions enforce the range constraints of
the parameters.
For positive \rho the distribution is unimodal and
symmetric about \mu.
The mean of Y (which make up the fitted values) is
\pi + (\rho/\pi) ((2 \pi-\mu) \sin(2 \pi-\mu) +
\cos(2 \pi-\mu) - \mu \sin(\mu) - \cos(\mu)).
An object of class "vglmff" (see
vglmff-class). The object is used by modelling
functions such as vglm, rrvglm
and vgam.
Numerically, this distribution can be difficult to fit because
of a log-likelihood having multiple maximums. The user is
therefore encouraged to try different starting values, i.e.,
make use of imu and irho.
Fisher scoring using simulation is used.
T. W. Yee
Jammalamadaka, S. R. and SenGupta, A. (2001). Topics in Circular Statistics, Singapore: World Scientific.
rcard,
extlogitlink,
vonmises.
CircStats and circular currently have a lot more R functions for circular data than the VGAM package.
## Not run:
cdata <- data.frame(y = rcard(n = 1000, mu = 4, rho = 0.45))
fit <- vglm(y ~ 1, cardioid, data = cdata, trace = TRUE)
coef(fit, matrix=TRUE)
Coef(fit)
c(with(cdata, mean(y)), head(fitted(fit), 1))
summary(fit)
## End(Not run)
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