mix {depmixS4} | R Documentation |
mix
creates an object of class mix
, an (independent)
mixture model (as a limit case of dependent mixture models in which all
observed time series are of length 1), otherwise known latent class or
mixture model. For a short description of the package see
depmixS4
.
mix(response, data=NULL, nstates, family=gaussian(), prior=~1, initdata=NULL, respstart=NULL, instart=NULL,...)
response |
The response to be modeled; either a formula or a list of formulae in the multivariate case; this interfaces to the glm distributions. See 'Details'. |
data |
An optional data.frame to interpret the variables in the response and transition arguments. |
nstates |
The number of states of the model. |
family |
A family argument for the response. This must be a list of family's if the response is multivariate. |
prior |
A one-sided formula specifying the density for the prior or initial state probabilities. |
initdata |
An optional data.frame to interpret the variables occuring in prior. The number of rows of this data.frame must be equal to the number of cases being modeled. See 'Details'. |
respstart |
Starting values for the parameters of the response models. |
instart |
Starting values for the parameters of the prior or initial state probability model. |
... |
Not used currently. |
The function mix
creates an S4 object of class mix
,
which needs to be fitted using fit
to optimize the
parameters.
The response model(s) are created by call(s) to response
providing the response formula and the family specifying the error
distribution. If response is a list of formulae, the response
's
are assumed to be independent conditional on the latent class.
The prior density is modeled as a multinomial logistic. This model is
created by a call to transInit
.
Starting values may be provided by the respective arguments. The order
in which parameters must be provided can be easily studied by using the
setpars
function.
Linear constraints on parameters can be provided as argument to the
fit
function.
The print function prints the formulae for the response and prior models along with their parameter values.
mix
returns an object of class mix
which has the
following slots:
response |
A list of a list of response models; the first index runs over states; the second index runs over the independent responses in case a multivariate response is provided. |
prior |
A multinomial logistic model for the initial state probabilities. |
dens,init |
See mix-class help for details. For
internal use. |
ntimes |
A vector made by rep(1,nrow(data)) ; for internal
use only. |
nstates |
The number of states of the model. |
nresp |
The number of independent responses. |
npars |
The total number of parameters of the model. Note: this is not the degrees of freedom because there are redundancies in the parameters, in particular in the multinomial models for the transitions and prior probabilities. |
Ingmar Visser
On latent class models: A. L. McCutcheon (1987). Latent class analysis. Sage Publications.
fit
, transInit
, response
,
depmix-methods
for accessor functions to depmix
objects.
# four binary items on the balance scale task data(balance) # define a latent class model instart=c(0.5,0.5) set.seed(1) respstart=runif(16) # note that ntimes argument is used to make this a mixture model mod <- mix(list(d1~1,d2~1,d3~1,d4~1), data=balance, nstates=2, family=list(multinomial(),multinomial(),multinomial(),multinomial()), respstart=respstart,instart=instart) # to see the model mod