Description Usage Arguments Details Value Author(s) References See Also Examples
The function WA1()
defines the Waring distribution, a two parameter distribution, for a gamlss.family
object to be used in GAMLSS fitting using the function gamlss()
, with parameters mu
and sigma
. The functions dWA1
, pWA1
, qWA1
and rWA1
define the density, distribution function, quantile function and random generation for the WA1
parameterization of the Waring distribution.
1 2 3 4 5 |
mu.link |
Defines the |
sigma.link |
Defines the |
x, q |
vector of quantiles |
mu |
vector of location parameter values |
sigma |
vector of scale parameter values |
log, log.p |
logical; if TRUE, probabilities p are given as log(p) |
lower.tail |
logical; if TRUE (default), probabilities are P[X <= x], otherwise P[X > x] |
p |
vector of probabilities |
n |
number of observations. If |
max.value |
constant; generates a sequence of values for the cdf function |
The parameterization of the Pareto Type 2 distribution in the function WA1
is
f(y|mu, sigma) = Beta(sigma+y, mu+1)/Beta(sigma, mu)
for y>=0, mu>0 and sigma>0.
returns a gamlss.family object which can be used to fit a Waring distribution in the gamlss()
function.
Bob Rigby r.rigby@londonmet.ac.uk, Mikis Stasinopoulos d.stasinopoulos@londonmet.ac.uk, Fiona McElduff F.Mcelduff@londonmet.ac.uk and Kalliope Akantziliotou
Rigby, R. A. and Stasinopoulos D. M. (2005). Generalized additive models for location, scale and shape,(with discussion), Appl. Statist., 54, part 3, pp 507-554.
Stasinopoulos D. M., Rigby R.A. and Akantziliotou C. (2006) Instructions on how to use the GAMLSS package in R. Accompanying documentation in the current GAMLSS help files, (see also http://www.gamlss.com/).
Stasinopoulos D. M. Rigby R.A. (2007) Generalized additive models for location scale and shape (GAMLSS) in R. Journal of Statistical Software, Vol. 23, Issue 7, Dec 2007, http://www.jstatsoft.org/v23/i07.
1 2 3 4 5 6 7 8 9 10 |
Add the following code to your website.
For more information on customizing the embed code, read Embedding Snippets.