View source: R/family.aunivariate.R
riceff | R Documentation |
Estimates the two parameters of a Rice distribution by maximum likelihood estimation.
riceff(lsigma = "loglink", lvee = "loglink", isigma = NULL,
ivee = NULL, nsimEIM = 100, zero = NULL, nowarning = FALSE)
nowarning |
Logical. Suppress a warning? Ignored for VGAM 0.9-7 and higher. |
lvee , lsigma |
Link functions for the |
ivee , isigma |
Optional initial values for the parameters.
If convergence failure occurs (this VGAM family function
seems to require good initial values) try using these arguments.
See |
nsimEIM , zero |
See |
The Rician distribution has density function
f(y;v,\sigma) =
\frac{y}{\sigma^2} \, \exp(-(y^2+v^2) / (2\sigma^2)) \,
I_0(y v / \sigma^2)
where y > 0
,
v > 0
,
\sigma > 0
and I_0
is the
modified Bessel function of the
first kind with order zero.
When v = 0
the Rice distribution reduces to a Rayleigh
distribution.
The mean is
\sigma \sqrt{\pi/2} \exp(z/2)
((1-z) I_0(-z/2)-z I_1(-z/2))
(returned as the fitted values) where
z=-v^2/(2 \sigma^2)
.
Simulated Fisher scoring is implemented.
An object of class "vglmff"
(see
vglmff-class
). The object is used by modelling
functions such as vglm
and vgam
.
Convergence problems may occur for data where v=0
;
if so, use rayleigh
or possibly use an
identity
link.
When v
is large (greater than 3, say) then the mean is
approximately v
and the standard deviation
is approximately
\sigma
.
T. W. Yee
Rice, S. O. (1945). Mathematical Analysis of Random Noise. Bell System Technical Journal, 24, 46–156.
drice
,
rayleigh
,
besselI
,
simulate.vlm
.
## Not run: sigma <- exp(1); vee <- exp(2)
rdata <- data.frame(y = rrice(n <- 1000, sigma, vee = vee))
fit <- vglm(y ~ 1, riceff, data = rdata, trace = TRUE, crit = "c")
c(with(rdata, mean(y)), fitted(fit)[1])
coef(fit, matrix = TRUE)
Coef(fit)
summary(fit)
## End(Not run)
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