FlexMix Clustering of Univariate Distributions

These are drivers for flexmix implementing model-based clustering of univariate data using different distributions for the component-specific models.

FLXMCdist1(formula = . ~ ., dist, ...)

Arguments

formula

A formula which is interpreted relative to the formula specified in the call to flexmix using update.formula. Only the left-hand side (response) of the formula is used. Default is to use the original flexmix model formula.

dist

Character string indicating the component-specific univariate distribution.

...

Arguments for the specific model drivers.

Details

Currently drivers for the following distributions are available:

1. Lognormal ("lnorm")

2. inverse Gaussian ("invGauss" using dinvGauss)

3. gamma ("gamma")

4. exponential ("exp")

5. Weibull ("weibull")

6. Burr ("burr" using dburr)

7. Inverse Burr ("invburr" using dinvburr)

Value

FLXMCdist1 returns an object of class FLXMC.

Author

Friedrich Leisch and Bettina Gruen

References

Tatjana Miljkovic and Bettina Gruen. Modeling loss data using mixtures of distributions. Insurance: Mathematics and Economics, 70, 387-396, 2016. doi:10.1016/j.insmatheco.2016.06.019

See also

flexmix

Examples

if (require("actuar")) {
    set.seed(123)
    y <- c(rexp(100, 10), rexp(100, 1))
    ex <- flexmix(y ~ 1, cluster = rep(1:2, each = 100), model = FLXMCdist1(dist = "exp"))    
    parameters(ex)
}
#> Loading required package: actuar
#> 
#> Attaching package: ‘actuar’
#> The following objects are masked from ‘package:stats’:
#> 
#>     sd, var
#> The following object is masked from ‘package:grDevices’:
#> 
#>     cm
#> Comp.1.rate Comp.2.rate 
#>    9.907339    1.069040