mixalg.boot {CAMAN} | R Documentation |
This function may be used to estimate the number of components based on a
nonparametric bootstrap approach.A bootstrap sample is obtained from the
original sample with replacement. Corresponding to the bootstrap data set we
obtain an estimate of the number of components k
applying a combination
of the VEM- and EM algorithm.
The bootstrap algorithm involves drawing B
independent bootstrap samples
and estimating k
using the hybrid mixture algorithm. The result is
the bootstrap distribution of the number of components k
.
The mode of this distribution is taken as an estimate of the number of components.
mixalg.boot(mix, nboot=500, limit=0.01, acc=10^(-5), numiter=5000, startk=50, returnBootstrapRep=FALSE)
the parameters limit, acc, numiter
and startk
are used for the VEM algorithm in each bootstrap sample.
mix |
A CAMAN-object which quantifies a finite mixture model. |
nboot |
number of bootstrap replications |
limit |
parameter to control the limit of union several components. Default is 0.01. |
acc |
convergence criterion. VEM and EM loops stop when deltaLL<acc. Default is 10^(-7). |
numiter |
parameter to control the maximal number of iterations in the VEM and EM loops. Default is 5000. |
startk |
starting/maximal number of components for the VEM algorithm in each bootstrap sample. This number will be used to compute the grid in the VEM. Default is 50. |
returnBootstrapRep |
A Boolean that indicates whether the bootstrapped data should be returned or not |
The function returns a list, describing the bootstrap replications:
$dat.bootstrap |
(used) sampled data |
$LL |
Likelihood of the final solutions of each bootstrap replication |
$LL_k1 |
vector with LL for each bootstrap replication using a homogeneous model (k=1) |
$numk.boot |
number of components obtained in replications. |
mixalg.Boot
and mixboot
are deprecated names for the mixalg.boot
function.
Peter Schlattmann and Johannes Hoehne
### POISSON data with weights: thai_cohort data(thai_cohort) m.thai <- mixalg(obs="counts", weights="frequency", family="poisson", data=thai_cohort, acc = 0.00003) ## Not run: boot <- mixalg.boot(m.thai, nboot=1000) #may take a few minutes ### POISSON data with observed and expected data: hepab data(hepab) mix <- mixalg(obs="observations",pop.at.risk="expected",family= "poisson",data=hepab) ## Not run: boot <- mixalg.boot(mix, nboot=250) #may take some time table(boot$numk.boot) ## End(Not run)