mixgamma {RBesT} | R Documentation |
The Gamma Mixture Distribution
Description
The gamma mixture density and auxiliary functions.
Usage
mixgamma(..., param = c("ab", "ms", "mn"), likelihood = c("poisson", "exp"))
ms2gamma(m, s, drop = TRUE)
mn2gamma(m, n, likelihood = c("poisson", "exp"), drop = TRUE)
## S3 method for class 'gammaMix'
print(x, ...)
## S3 method for class 'gammaPoissonMix'
print(x, ...)
## S3 method for class 'gammaExpMix'
print(x, ...)
## S3 method for class 'gammaMix'
summary(object, probs = c(0.025, 0.5, 0.975), ...)
## S3 method for class 'gammaPoissonMix'
summary(object, probs = c(0.025, 0.5, 0.975), ...)
Arguments
... |
List of mixture components. |
param |
Determines how the parameters in the list are interpreted. See details. |
likelihood |
Defines with what likelihood the Gamma density is used (Poisson or Exp). Defaults to |
m |
Vector of means of the Gamma mixture components |
s |
Vector of standard deviations of the gamma mixture components, |
drop |
Delete the dimensions of an array which have only one level. |
n |
Vector of sample sizes of the Gamma mixture components. |
x |
The mixture to print |
object |
Gamma mixture object. |
probs |
Quantiles reported by the |
Details
Each entry in the ...
argument list is expected to
be a triplet of numbers which defines the weight w_k
, first
and second parameter of the mixture component k
. A triplet
can optionally be named which will be used appropriately.
The first and second parameter can be given in different
parametrizations which is set by the param
option:
- ab
Natural parametrization of Gamma density (
a
=shape andb
=rate). Default.- ms
Mean and standard deviation,
m=a/b
ands=\sqrt{a}/b
.- mn
Mean and number of observations. Translation to natural parameter depends on the
likelihood
argument. For a Poisson likelihoodn=b
(anda=m \cdot n
), for an Exp likelihoodn=a
(andb=n/m
).
Value
mixgamma
returns a gamma mixture with the specified mixture components.
ms2gamma
and
mn2gamma
return the equivalent natural a
and b
parametrization given
parameters m
, s
, or n
.
See Also
Other mixdist:
mixbeta()
,
mixcombine()
,
mixmvnorm()
,
mixnorm()
,
mixplot
,
mix
Examples
# Gamma mixture with robust and informative component
gmix <- mixgamma(rob=c(0.3, 20, 4), inf=c(0.7, 50, 10))
# objects can be printed
gmix
# or explicitly
print(gmix)
# summaries are defined
summary(gmix)
# sub-components may be extracted
# by component number
gmix[[2]]
# or component name
gmix[["inf"]]
# alternative mean and standard deviation parametrization
gmsMix <- mixgamma(rob=c(0.5, 8, 0.5), inf=c(0.5, 9, 2), param="ms")
# or mean and number of observations parametrization
gmnMix <- mixgamma(rob=c(0.2, 2, 1), inf=c(0.8, 2, 5), param="mn")
# and mixed parametrizations are also possible
gfmix <- mixgamma(rob1=c(0.15, mn2gamma(2, 1)), rob2=c(0.15, ms2gamma(2, 5)), inf=c(0.7, 50, 10))