step.ds.mixture: Stepwise selection of mixture components

In mmds: Mixture Model Distance Sampling (mmds)

Description

Uses AIC to select the number of mixture components.

Usage

  step.ds.mixture(ds.object, max.terms = 4)

Arguments

ds.object	ds.mixture object.
max.terms	Maximum number of mixture components to attempt to fit. Default 4.

Value

a ds.mixture model object of the best (AIC-wise) model.

Details

This routine is most useful during model building. Setting up a basic 1-point mixture model and then running this on the object returns a model with the lowest AIC.

Progress will be printed to the screen.

Author(s)

David L. Miller

Examples

library(mmds)
set.seed(0)
## simulate some line transect data from a 2 point mixture
sim.dat<-sim.mix(c(-0.223,-1.897,inv.reparam.pi(0.3)),2,100,1)
## fit the model
fit.sim.dat.1<-fitmix(sim.dat,1,1)
## find best AIC model
step.ds.mixture(fit.sim.dat.1)

mmds documentation built on May 2, 2019, 8:55 a.m.