View source: R/family.univariate.R
maxwell | R Documentation |
Estimating the parameter of the Maxwell distribution by maximum likelihood estimation.
maxwell(link = "loglink", zero = NULL, parallel = FALSE,
type.fitted = c("mean", "percentiles", "Qlink"),
percentiles = 50)
link |
Parameter link function applied to |
zero , parallel |
See |
type.fitted , percentiles |
See |
The Maxwell distribution, which is used in the area of thermodynamics, has a probability density function that can be written
f(y;a) = \sqrt{2/\pi} a^{3/2} y^2 \exp(-0.5 a y^2)
for y>0
and a>0
.
The mean of Y
is
\sqrt{8 / (a \pi)}
(returned as the fitted values), and its variance is
(3\pi - 8)/(\pi a)
.
An object of class "vglmff"
(see vglmff-class
).
The object is used by modelling functions
such as vglm
,
rrvglm
and vgam
.
Fisher-scoring and Newton-Raphson are the same here.
A related distribution is the Rayleigh distribution.
This VGAM family function handles multiple responses.
This VGAM family function can be mimicked by
poisson.points(ostatistic = 1.5, dimension = 2)
.
T. W. Yee
von Seggern, D. H. (1993). CRC Standard Curves and Surfaces, Boca Raton, FL, USA: CRC Press.
Maxwell
,
rayleigh
,
poisson.points
.
mdata <- data.frame(y = rmaxwell(1000, rate = exp(2)))
fit <- vglm(y ~ 1, maxwell, mdata, trace = TRUE, crit = "coef")
coef(fit, matrix = TRUE)
Coef(fit)
Add the following code to your website.
For more information on customizing the embed code, read Embedding Snippets.